diff --git a/.Rbuildignore b/.Rbuildignore index 4da35e99..64d6f461 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -11,3 +11,7 @@ compare_versions .github docs .idea +^_pkgdown\.yml$ +^docs$ +^pkgdown$ +^\.github$ diff --git a/.github/.gitignore b/.github/.gitignore new file mode 100644 index 00000000..2d19fc76 --- /dev/null +++ b/.github/.gitignore @@ -0,0 +1 @@ +*.html diff --git a/.github/workflows/R_CMD_check_Hades.yaml b/.github/workflows/R_CMD_check_Hades.yaml index 8d5a924c..f5cf2832 100644 --- a/.github/workflows/R_CMD_check_Hades.yaml +++ b/.github/workflows/R_CMD_check_Hades.yaml @@ -20,9 +20,6 @@ jobs: fail-fast: false matrix: config: - - {os: windows-latest, r: '4.2.3', rtools: '42', rspm: "https://cloud.r-project.org"} - #- {os: macOS-latest, r: '4.2.3', rtools: '42', rspm: "https://cloud.r-project.org"} - - {os: ubuntu-20.04, r: '4.2.3', rtools: '42', rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} - {os: windows-latest, r: 'release', rtools: '', rspm: "https://cloud.r-project.org"} - {os: macOS-latest, r: 'release', rtools: '', rspm: "https://cloud.r-project.org"} - {os: ubuntu-20.04, r: 'release', rtools: '', rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} @@ -61,7 +58,6 @@ jobs: - uses: r-lib/actions/setup-r@v2 with: r-version: ${{ matrix.config.r }} - rtools-version: ${{ matrix.config.rtools }} - uses: r-lib/actions/setup-tinytex@v2 @@ -70,11 +66,7 @@ jobs: - name: Install system requirements if: runner.os == 'Linux' run: | - sudo apt-get install -y make - sudo apt-get install -y default-jdk - sudo apt-get install -y libcurl4-openssl-dev - sudo apt-get install -y libssl-dev - sudo apt-get install -y libglpk-dev + sudo apt-get install -y libssh-dev while read -r cmd do eval sudo $cmd @@ -93,7 +85,7 @@ jobs: - name: Upload source package if: success() && runner.os == 'Windows' && github.event_name != 'pull_request' && github.ref == 'refs/heads/main' - uses: actions/upload-artifact@v2 + uses: actions/upload-artifact@v4 with: name: package_tarball path: check/*.tar.gz @@ -164,7 +156,7 @@ jobs: # # - name: Download package tarball # if: ${{ env.new_version != '' }} - # uses: actions/download-artifact@v2 + # uses: actions/download-artifact@v4 # with: # name: package_tarball # diff --git a/.github/workflows/pkgdown.yaml b/.github/workflows/pkgdown.yaml new file mode 100644 index 00000000..178b0de9 --- /dev/null +++ b/.github/workflows/pkgdown.yaml @@ -0,0 +1,104 @@ +# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples +# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help +on: + push: + branches: [main, master] + pull_request: + branches: [main, master] + release: + types: [published] + workflow_dispatch: + +name: pkgdown.yaml + +permissions: read-all + +jobs: + pkgdown: + runs-on: ubuntu-latest + # Only restrict concurrency for non-PR jobs + concurrency: + group: pkgdown-${{ github.event_name != 'pull_request' || github.run_id }} + env: + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + permissions: + contents: write + services: + postgres: + image: postgres:latest + env: + POSTGRES_DB: strategus + POSTGRES_USER: user + POSTGRES_PASSWORD: password + POSTGRES_HOST: postgres + POSTGRES_PORT: 5432 + ports: + - 5432:5432 + options: --name postgres --health-cmd pg_isready --health-interval 10s --health-timeout 5s --health-retries 5 + + steps: + - name: Checkout repository + uses: actions/checkout@v4 + + - name: Setup Pandoc + uses: r-lib/actions/setup-pandoc@v2 + + - name: Setup R + uses: r-lib/actions/setup-r@v2 + with: + use-public-rspm: true + + - name: Setup R Dependencies + uses: r-lib/actions/setup-r-dependencies@v2 + with: + extra-packages: any::pkgdown, local::. + needs: website + + - name: Build site + run: pkgdown::build_site_github_pages(new_process = FALSE, install = FALSE) + shell: Rscript {0} + + - name: Wait for PostgreSQL to be ready + run: | + until pg_isready -h 127.0.0.1 -p 5432 -U myuser; do + echo "Waiting for postgres..."; + sleep 3; + done + + - name: Run SQL Script + run: | + PGPASSWORD=password psql -h 127.0.0.1 -U user -d strategus -f extras/rdms/full_data_model_pg.sql + + - name: Configure SchemaSpy environment + run: | + sudo apt-get update + sudo apt-get install default-jdk -y + sudo apt-get install postgresql-client -y + + - name: Download PostgreSQL JDBC Driver + run: | + wget https://jdbc.postgresql.org/download/postgresql-42.2.24.jar -O $HOME/postgresql-jdbc.jar + + - name: Execute SchemaSpy + run: | + java -jar extras/rdms/schemaspy-6.2.4.jar -vizjs -dp $HOME -configFile extras/rdms/schemaspy-config.properties -meta extras/rdms/schema_meta.xml -debug -desc "Results data model" -noTablePaging -noimplied + + - name: Upload artifact + uses: actions/upload-artifact@v4 + with: + name: documentation-artifact + path: public + + - name: download documentation + uses: actions/download-artifact@v4 + with: + name: documentation-artifact + path: docs/results-schema + + - name: Deploy to GitHub pages 🚀 + if: github.event_name != 'pull_request' + uses: JamesIves/github-pages-deploy-action@v4.5.0 + with: + clean: false + branch: gh-pages + folder: docs diff --git a/.gitignore b/.gitignore index 6ed21cce..cd1b73a4 100644 --- a/.gitignore +++ b/.gitignore @@ -19,3 +19,7 @@ src/*.dll /Debug standalone/build/* _targets +docs + +extras/rdms/public +extras/rdms/*.class \ No newline at end of file diff --git a/DESCRIPTION b/DESCRIPTION index 1fa7e091..fa6fc893 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,55 +1,69 @@ Package: Strategus Type: Package -Title: Coordinating and Executing Analytics Using HADES Modules -Version: 0.3.0 -Date: 2023-06-04 +Title: Coordinate and Execute OHDSI HADES Modules +Version: 1.0.0 +Date: 2024-10-08 Authors@R: c( - person("Martijn", "Schuemie", email = "schuemie@ohdsi.org", role = c("aut")), person("Anthony", "Sena", email = "sena@ohdsi.org", role = c("aut", "cre")), + person("Martijn", "Schuemie", email = "schuemie@ohdsi.org", role = c("aut")), person("Jamie", "Gilbert", role = c("aut")), person("Observational Health Data Science and Informatics", role = c("cph")) ) Maintainer: Anthony Sena -Description: An R package for coordinating and executing analytics using HADES modules. -License: Apache License 2.0 -URL: https://ohdsi.github.io/Strategus, https://github.com/OHDSI/Strategus -BugReports: https://github.com/OHDSI/Strategus/issues +Description: Coordinate and execute large scale analytics using OHDSI Health + Analytics Data-to-Evidence Suite (HADES) () + modules. Depends: R (>= 4.2.0), - CohortGenerator (>= 0.8.0), - DatabaseConnector (>= 6.2.3) + CohortGenerator (>= 0.11.0), + DatabaseConnector (>= 6.2.3), + R6 Imports: - targets, - renv (>= 1.0.0), - ParallelLogger (>= 3.1.0), - dplyr, checkmate, - keyring, - rlang, - utils, - R.utils, + cli, digest, + dplyr, methods, - tibble, - ResultModelManager (>= 0.3.0), - SqlRender (>= 1.11.0), - semver, - httr2, - jsonlite + ParallelLogger (>= 3.1.0), + purrr, + readr, + ResultModelManager (>= 0.5.8), + rlang, + SqlRender (>= 1.18.0) Suggests: - testthat (>= 3.0.0), + Characterization, + CirceR, + CohortDiagnostics, + CohortIncidence, + CohortMethod, + Cyclops, + Eunomia, + EvidenceSynthesis, + FeatureExtraction, fs, knitr, + PatientLevelPrediction, rmarkdown, - Eunomia, + RSQLite, + SelfControlledCaseSeries, + testthat (>= 3.0.0), withr Remotes: + ohdsi/Characterization, + ohdsi/CohortDiagnostics, ohdsi/CohortGenerator, + ohdsi/CohortIncidence, + ohdsi/CohortMethod, + ohdsi/PatientLevelPrediction, ohdsi/ResultModelManager, - ohdsi/Eunomia + ohdsi/SelfControlledCaseSeries +License: Apache License 2.0 VignetteBuilder: knitr +URL: https://ohdsi.github.io/Strategus, https://github.com/OHDSI/Strategus +BugReports: https://github.com/OHDSI/Strategus/issues NeedsCompilation: no -RoxygenNote: 7.3.1 +RoxygenNote: 7.3.2 Roxygen: list(markdown = TRUE) Encoding: UTF-8 +Language: en-US Config/testthat/edition: 3 diff --git a/NAMESPACE b/NAMESPACE index 373b0586..d0f72139 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -1,25 +1,36 @@ # Generated by roxygen2: do not edit by hand +export(CharacterizationModule) +export(CohortDiagnosticsModule) +export(CohortGeneratorModule) +export(CohortIncidenceModule) +export(CohortMethodModule) +export(EvidenceSynthesisModule) +export(PatientLevelPredictionModule) +export(SelfControlledCaseSeriesModule) +export(StrategusModule) +export(addCharacterizationModuleSpecifications) +export(addCohortDiagnosticsModuleSpecifications) +export(addCohortGeneratorModuleSpecifications) +export(addCohortIncidenceModuleSpecifications) +export(addCohortMethodeModuleSpecifications) +export(addEvidenceSynthesisModuleSpecifications) export(addModuleSpecifications) +export(addPatientLevelPredictionModuleSpecifications) +export(addSelfControlledCaseSeriesModuleSpecifications) export(addSharedResources) -export(compareLockFiles) export(createCdmExecutionSettings) export(createEmptyAnalysisSpecificiations) -export(createResultDataModels) +export(createResultDataModel) +export(createResultsDataModelSettings) export(createResultsExecutionSettings) -export(ensureAllModulesInstantiated) export(execute) -export(getModuleList) -export(installLatestModule) -export(retrieveConnectionDetails) -export(storeConnectionDetails) -export(syncLockFile) -export(unlockKeyring) -export(validateLockFile) -export(verifyModuleInstallation) +export(getCdmDatabaseMetaData) +export(uploadResults) export(zipResults) import(CohortGenerator) import(DatabaseConnector) +import(R6) import(dplyr) importFrom(methods,is) importFrom(rlang,.data) diff --git a/NEWS.md b/NEWS.md index 44956b2f..1cad6228 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,3 +1,22 @@ +Strategus 1.0.0 +=============== + +- Eliminated the dependencies for `keyring`, `renv` and `targets` (#135) +- Centralized all modules into the Strategus package (#29, #45, #51, #140) +- Strategus execution provides a summary of the execution time (#4) and continues after an error (#64, #141) +- Modules provide functions for creating their results data model (#43) and to upload results. +- Allow modules to obtain the full set of OMOP CDM metadata collected (#20, #154) +- Adds the `cdm_holder` attribute to the database_id hash calculation (#48) +- Moves the `incremental` setting to the execution settings vs. the module settings (#155) +- Adds threading options via execution settings (#151) +- Select subset of modules to execute from analysis specification (#169) +- Ensure release of Strategus has Python dependencies (#22) and OHDSI Shiny App dependencies (#78). See [StrategusStudyRepoTemplate](https://github.com/ohdsi-studies/StrategusStudyRepoTemplate) for more details. +- Document the results data model for HADES modules (#143) + +## Bug Fixes +- Make negative control outcome shared resource optional (#153) +- Export results data model specification file for PatientLevelPrediction (#165) + Strategus 0.3.0 =============== - Provide option to skip modules (#87) @@ -27,7 +46,7 @@ Strategus 0.1.0 - Robust handling of connection details via keyring (#74) - Ensures uniqueness of all CDM tables when gathering database metadata (#82) - `tempEmulationSchema` added to execution settings and passed properly to modules (#82) -- Adding logging to module initalization to detect `renv` restore errors (#82) +- Adding logging to module initialization to detect `renv` restore errors (#82) - Adopt HADES-wide lock file in latest versions of all modules (#83) - Use renv >= v1.0.0 for all modules and Strategus (#83) - Add GitHub unit tests for HADES adopted version (currently v4.2.3) and the latest R versions for all modules and Strategus. (#83) @@ -60,7 +79,7 @@ Strategus 0.0.3 - Breaking change: removed function `createExecutionSettings()` and replaced with 2 new functions: `createCdmExecutionSettings()` and `createResultsExecutionSettings()`. (#19) - Added Vignettes (#23) - Provide better support for `keyring` to handle named/locked keyrings (#24) -- Add function to list Strategus modules (#30) +- Add function to list HADES modules (#30) - Fixes from testing (#36) - Enforce module structure for proper use with renv (#37) - Support CDM 5.4 source table format (#41) diff --git a/R/DatabaseMetaData.R b/R/DatabaseMetaData.R index b4105ade..155b044c 100644 --- a/R/DatabaseMetaData.R +++ b/R/DatabaseMetaData.R @@ -21,16 +21,40 @@ # carefully consider serialization and deserialization to JSON, which currently # uses custom functionality in ParallelLogger to maintain object attributes. -createDatabaseMetaData <- function(executionSettings, keyringName = NULL) { - databaseMetaDataFolder <- file.path(executionSettings$resultsFolder, "DatabaseMetaData") - if (!dir.exists(databaseMetaDataFolder)) { - dir.create(databaseMetaDataFolder, recursive = TRUE) - } +#' Provides the file path to the database identifier file created +#' by Strategus +#' +#' @description +#' This function is used to identify the location of the database identifier +#' created by Strategus when executing an analysis specification. This +#' location is important when uploading results since the database identifier +#' may be needed to purge old results for a given database identifier. +#' +#' @template resultsFolder +#' @noRd +#' @keywords internal +getDatabaseIdentifierFilePath <- function(resultsFolder) { + return(file.path(.getDatabaseMetaDataResultsFolder(resultsFolder), "database_meta_data.csv")) +} + +#' Gets the metadata for your OMOP CDM Database +#' +#' @description +#' This function is used to gather metadata about your OMOP CDM and inspect +#' for informational purposes. This information will be saved with your +#' results when executing an analysis specification. +#' +#' @param cdmExecutionSettings An object of type `CdmExecutionSettings` as +#' created [createCdmExecutionSettings()]. +#' @template connectionDetails +#' +#' @export +getCdmDatabaseMetaData <- function(cdmExecutionSettings, connectionDetails) { + errorMessages <- checkmate::makeAssertCollection() + checkmate::assertClass(connectionDetails, "ConnectionDetails", add = errorMessages) + checkmate::assertClass(cdmExecutionSettings, "CdmExecutionSettings", add = errorMessages) + checkmate::reportAssertions(collection = errorMessages) - connectionDetails <- retrieveConnectionDetails( - connectionDetailsReference = executionSettings$connectionDetailsReference, - keyringName = keyringName - ) connection <- DatabaseConnector::connect(connectionDetails) on.exit(DatabaseConnector::disconnect(connection)) @@ -40,7 +64,7 @@ createDatabaseMetaData <- function(executionSettings, keyringName = NULL) { requiredTables <- c("cdm_source", "vocabulary", "observation_period") cdmTableList <- DatabaseConnector::getTableNames( connection = connection, - databaseSchema = executionSettings$cdmDatabaseSchema + databaseSchema = cdmExecutionSettings$cdmDatabaseSchema ) cdmTableList <- unique(tolower(cdmTableList)) @@ -53,17 +77,14 @@ createDatabaseMetaData <- function(executionSettings, keyringName = NULL) { stop(sprintf("FATAL ERROR: Your OMOP CDM is missing the following required tables: %s", paste(missingCdmTables, collapse = ", "))) } - resultsDataModel <- CohortGenerator::readCsv( - file = system.file("databaseMetaDataRdms.csv", package = "Strategus"), - warnOnCaseMismatch = FALSE - ) + resultsDataModel <- .getDatabaseMetaDataRdms() sql <- "SELECT TOP 1 * FROM @cdm_database_schema.cdm_source;" cdmSource <- renderTranslateQuerySql( connection = connection, sql = sql, snakeCaseToCamelCase = TRUE, - cdm_database_schema = executionSettings$cdmDatabaseSchema + cdm_database_schema = cdmExecutionSettings$cdmDatabaseSchema ) # Verify that the cdmSource table has information @@ -88,7 +109,7 @@ createDatabaseMetaData <- function(executionSettings, keyringName = NULL) { connection = connection, sql = sql, snakeCaseToCamelCase = TRUE, - cdm_database_schema = executionSettings$cdmDatabaseSchema + cdm_database_schema = cdmExecutionSettings$cdmDatabaseSchema ) # Verify that the vocabulary_version is found @@ -103,7 +124,7 @@ createDatabaseMetaData <- function(executionSettings, keyringName = NULL) { connection = connection, sql = sql, snakeCaseToCamelCase = TRUE, - cdm_database_schema = executionSettings$cdmDatabaseSchema + cdm_database_schema = cdmExecutionSettings$cdmDatabaseSchema ) # Verify that the MAX(observation_period_end_date) is a valid date @@ -111,17 +132,28 @@ createDatabaseMetaData <- function(executionSettings, keyringName = NULL) { stop("FATAL ERROR: The OBSERVATION_PERIOD table in your OMOP CDM lacks a maximum observation_period_end_date. This may be a result of an error in the ETL as each person in the OMOP CDM must have an observation period with a valid start and end date.") } - databaseId <- digest::digest2int(paste(cdmSource$cdmSourceName, cdmSource$cdmReleaseDate)) - database <- cdmSource %>% + databaseId <- digest::digest2int(paste(cdmSource$cdmSourceName, cdmSource$cdmReleaseDate, cdmSource$cdmHolder)) + databaseMetaData <- cdmSource %>% mutate( vocabularyVersion = vocabVersion$vocabularyVersion, databaseId = !!databaseId ) %>% bind_cols(observationPeriodMax) + return(databaseMetaData) +} + +.writeDatabaseMetaData <- function(databaseMetaData, executionSettings) { + # Save the results + databaseMetaDataFolder <- .getDatabaseMetaDataResultsFolder(executionSettings$resultsFolder) + if (!dir.exists(databaseMetaDataFolder)) { + dir.create(databaseMetaDataFolder, recursive = TRUE) + } + + resultsDataModel <- .getDatabaseMetaDataRdms() # Export the csv files: CohortGenerator::writeCsv( - x = database, + x = databaseMetaData, file = file.path(databaseMetaDataFolder, "database_meta_data.csv") ) @@ -130,5 +162,64 @@ createDatabaseMetaData <- function(executionSettings, keyringName = NULL) { file = file.path(databaseMetaDataFolder, "resultsDataModelSpecification.csv"), warnOnFileNameCaseMismatch = FALSE ) - return(databaseId) +} + +.createDatabaseMetadataResultsDataModel <- function(resultsConnectionDetails, + resultsDataModelSettings) { + rdmsFile <- file.path(.getDatabaseMetaDataResultsFolder(resultsDataModelSettings$resultsFolder), "resultsDataModelSpecification.csv") + if (file.exists(rdmsFile)) { + rlang::inform("Creating results data model for database metadata") + connection <- DatabaseConnector::connect(resultsConnectionDetails) + on.exit(DatabaseConnector::disconnect(connection)) + + # Create the SQL from the resultsDataModelSpecification.csv + sql <- ResultModelManager::generateSqlSchema( + csvFilepath = rdmsFile + ) + sql <- SqlRender::render( + sql = sql, + database_schema = resultsDataModelSettings$resultsDatabaseSchema + ) + DatabaseConnector::executeSql(connection = connection, sql = sql) + } else { + warning("DatabaseMetaData not found - skipping table creation") + } +} + +.uploadDatabaseMetadata <- function(resultsConnectionDetails, + resultsDataModelSettings) { + databaseMetaDataResultsFolder <- .getDatabaseMetaDataResultsFolder(resultsDataModelSettings$resultsFolder) + rdmsFile <- file.path(.getDatabaseMetaDataResultsFolder(resultsDataModelSettings$resultsFolder), "resultsDataModelSpecification.csv") + if (file.exists(rdmsFile)) { + rlang::inform("Uploading database metadata") + connection <- DatabaseConnector::connect(resultsConnectionDetails) + on.exit(DatabaseConnector::disconnect(connection)) + + specification <- CohortGenerator::readCsv(file = rdmsFile) + ResultModelManager::uploadResults( + connection = connection, + schema = resultsDataModelSettings$resultsDatabaseSchema, + resultsFolder = databaseMetaDataResultsFolder, + purgeSiteDataBeforeUploading = TRUE, + databaseIdentifierFile = getDatabaseIdentifierFilePath(resultsDataModelSettings$resultsFolder), + specifications = specification + ) + } else { + warning("DatabaseMetaData not found - skipping table creation") + } +} + +.getDatabaseMetaDataResultsFolder <- function(resultsFolder) { + return(file.path(resultsFolder, "DatabaseMetaData")) +} + +.getDatabaseMetaDataRdms <- function() { + resultsDataModel <- CohortGenerator::readCsv( + file = system.file( + file.path("csv", "databaseMetaDataRdms.csv"), + package = "Strategus" + ), + warnOnCaseMismatch = FALSE + ) + invisible(resultsDataModel) } diff --git a/R/Execution.R b/R/Execution.R index 100d11b4..47e8bee5 100644 --- a/R/Execution.R +++ b/R/Execution.R @@ -14,52 +14,32 @@ # See the License for the specific language governing permissions and # limitations under the License. -# Note: Using S3 for consistency with settings objects in PLP, CohortMethod, and -# FeatureExtraction. If we want to use S4 or R6 we need to first adapt those -# packages. This will be difficult, since these settings objects are used throughout -# these packages, and are for example used in do.call() calls. We should also -# carefully consider serialization and deserialization to JSON, which currently -# uses custom functionality in ParallelLogger to maintain object attributes. - #' Execute analysis specifications. #' #' @template AnalysisSpecifications #' @template executionSettings -#' @param executionScriptFolder Optional: the path to use for storing the execution script. -#' when NULL, this function will use a temporary -#' file location to create the script to execute. -#' @template keyringName -#' @param restart Restart run? Requires `executionScriptFolder` to be specified, and be -#' the same as the `executionScriptFolder` used in the run to restart. -#' -#' @template enforceModuleDependencies +#' @template connectionDetails #' #' @return -#' Does not return anything. Is called for the side-effect of executing the specified -#' analyses. +#' Returns a list of lists that contains +#' - moduleName: The name of the module executed +#' - result: The result of the execution. See purrr::safely for details on +#' this result. +#' - executionTime: The time for the module to execute #' #' @export execute <- function(analysisSpecifications, executionSettings, - executionScriptFolder = NULL, - keyringName = NULL, - restart = FALSE, - enforceModuleDependencies = TRUE) { + connectionDetails) { errorMessages <- checkmate::makeAssertCollection() - keyringList <- keyring::keyring_list() checkmate::assertClass(analysisSpecifications, "AnalysisSpecifications", add = errorMessages) checkmate::assertClass(executionSettings, "ExecutionSettings", add = errorMessages) - checkmate::assertChoice(x = keyringName, choices = keyringList$keyring, null.ok = TRUE, add = errorMessages) checkmate::reportAssertions(collection = errorMessages) # Validate the execution settings if (is(executionSettings, "CdmExecutionSettings")) { # Assert that the temp emulation schema is set if required for the dbms # specified by the executionSettings - connectionDetails <- retrieveConnectionDetails( - connectionDetailsReference = executionSettings$connectionDetailsReference, - keyringName = keyringName - ) DatabaseConnector::assertTempEmulationSchemaSet( dbms = connectionDetails$dbms, tempEmulationSchema = executionSettings$tempEmulationSchema @@ -87,7 +67,6 @@ execute <- function(analysisSpecifications, return(TRUE) }, warning = function(w) { - warning(w) return(FALSE) } ) @@ -101,149 +80,159 @@ execute <- function(analysisSpecifications, } } - # Validate the modules - modules <- ensureAllModulesInstantiated( - analysisSpecifications = analysisSpecifications, - enforceModuleDependencies = enforceModuleDependencies - ) - if (isFALSE(modules$allModulesInstalled)) { - stop("Stopping execution due to module issues") - } + # Determine if the user has opted to subset to specific modules + # in the analysis specification. If so, validate that the + # modulesToExecute are present in the analysis specification + # before attempting to subset the analyses to run. + if (length(executionSettings$modulesToExecute) > 0) { + # Get the modules in the analysis specification with their + # index in the array + modulesWithIndex <- lapply( + X = seq_along(analysisSpecifications$moduleSpecifications), + FUN = function(i) { + list( + idx = i, + module = analysisSpecifications$moduleSpecifications[[i]]$module + ) + } + ) + modulesInAnalysisSpecification <- sapply( + X = modulesWithIndex, + FUN = function(x) { + x$module + } + ) - if (is.null(executionScriptFolder)) { - executionScriptFolder <- tempfile("strategusTempSettings") - dir.create(executionScriptFolder) - on.exit(unlink(executionScriptFolder, recursive = TRUE)) - } else if (!restart) { - if (dir.exists(executionScriptFolder)) { - unlink(executionScriptFolder, recursive = TRUE) + modulesToExecuteString <- paste(executionSettings$modulesToExecute, collapse = ", ") + modulesInAnalysisSpecificationString <- paste(modulesInAnalysisSpecification, collapse = ", ") + + # Stop if we cannot find all of the requested modules + # to execute in the overall analysis specification + if (!all(tolower(executionSettings$modulesToExecute) %in% tolower(modulesInAnalysisSpecification))) { + errorMsg <- paste0( + "The executionSettings specified to run only the modules: ", + modulesToExecuteString, + ".\n However the analysis specification includes the following modules: ", + modulesInAnalysisSpecificationString + ) + stop(errorMsg) } - dir.create(executionScriptFolder, recursive = TRUE) - } - # Normalize path to convert from relative to absolute path - executionScriptFolder <- normalizePath(executionScriptFolder, mustWork = F) - if (is(executionSettings, "CdmExecutionSettings")) { - executionSettings$databaseId <- createDatabaseMetaData( - executionSettings = executionSettings, - keyringName = keyringName + # Subset the analysis specifications to those modules + # specified by the user + cli::cli_alert_info(paste0("Runnning a subset of modules: ", modulesToExecuteString)) + moduleSubset <- unlist( + lapply( + X = modulesWithIndex, + FUN = function(x) { + if (tolower(x$module) %in% tolower(executionSettings$modulesToExecute)) { + return(x$idx) + } + } + ) ) + analysisSpecifications$moduleSpecifications <- analysisSpecifications$moduleSpecifications[moduleSubset] } - dependencies <- extractDependencies(modules$modules) - fileName <- generateTargetsScript( - analysisSpecifications = analysisSpecifications, - executionSettings = executionSettings, - dependencies = dependencies, - executionScriptFolder = executionScriptFolder, - restart = restart, - keyringName = keyringName + # Set up logging + if (!dir.exists(dirname(executionSettings$logFileName))) { + dir.create(dirname(executionSettings$logFileName), recursive = T) + } + ParallelLogger::addDefaultFileLogger( + name = "STRATEGUS_LOGGER", + fileName = executionSettings$logFileName ) - # targets::tar_manifest(script = fileName) - # targets::tar_glimpse(script = fileName) - targets::tar_make(script = fileName, store = file.path(executionScriptFolder, "_targets")) -} + on.exit(ParallelLogger::unregisterLogger("STRATEGUS_LOGGER")) -generateTargetsScript <- function(analysisSpecifications, executionSettings, dependencies, executionScriptFolder, keyringName, restart) { - fileName <- file.path(executionScriptFolder, "script.R") - if (restart) { - return(fileName) + if (is(executionSettings, "CdmExecutionSettings")) { + cdmDatabaseMetaData <- getCdmDatabaseMetaData( + cdmExecutionSettings = executionSettings, + connectionDetails = connectionDetails + ) + executionSettings$cdmDatabaseMetaData <- cdmDatabaseMetaData + .writeDatabaseMetaData(cdmDatabaseMetaData, executionSettings) } - ### Note anything inisde this block will be scoped inside the targets script file - targets::tar_script( - { - ## - # Generated by Strategus - not advisable to edit by hand - ## - analysisSpecificationsLoad <- readRDS(analysisSpecificationsFileName) - moduleToTargetNames <- readRDS(moduleToTargetNamesFileName) - dependencies <- readRDS(dependenciesFileName) - - targets::tar_option_set(packages = c("Strategus", "keyring"), imports = c("Strategus", "keyring")) - targetList <- list( - targets::tar_target(analysisSpecifications, readRDS(analysisSpecificationsFileName)), - # NOTE Execution settings could be mapped to many different cdms making re-execution across cdms much simpler - targets::tar_target(executionSettings, readRDS(executionSettingsFileName)), - targets::tar_target(keyringSettings, readRDS(keyringSettingsFileName)) + executionStatus <- list() + + # Execute the cohort generator module first if it exists + for (i in 1:length(analysisSpecifications$moduleSpecifications)) { + moduleName <- analysisSpecifications$moduleSpecifications[[i]]$module + if (tolower(moduleName) == "cohortgeneratormodule") { + moduleExecutionStatus <- .executeModule( + moduleName = moduleName, + connectionDetails = connectionDetails, + analysisSpecifications = analysisSpecifications, + executionSettings = executionSettings ) + executionStatus <- append( + executionStatus, + moduleExecutionStatus + ) + break + } + } - # factory for producing module targets based on their dependencies - # This could be inside Strategus as an exported function - # it would also be much cleaner to use a targets pattern = cross(analysisSpecifications$moduleSpecifications) - # however, working out how to handle dependencies wasn't obvious - # This approach could be modified to allow multiple executionSettings, but that would require a substantial re-write - for (i in 1:length(analysisSpecificationsLoad$moduleSpecifications)) { - moduleSpecification <- analysisSpecificationsLoad$moduleSpecifications[[i]] - targetName <- sprintf("%s_%d", moduleSpecification$module, i) - dependencyModules <- dependencies[dependencies$module == moduleSpecification$module, ]$dependsOn - dependencyTargetNames <- moduleToTargetNames[moduleToTargetNames$module %in% dependencyModules, ]$targetName - - # Use of tar_target_raw allows dynamic names - targetList[[length(targetList) + 1]] <- targets::tar_target_raw(targetName, - substitute(Strategus:::runModule(analysisSpecifications, keyringSettings, i, executionSettings), - env = list(i = i) - ), - deps = c("analysisSpecifications", "keyringSettings", "executionSettings", dependencyTargetNames) - ) + # Execute any other modules + for (i in 1:length(analysisSpecifications$moduleSpecifications)) { + moduleName <- analysisSpecifications$moduleSpecifications[[i]]$module + if (tolower(moduleName) != "cohortgeneratormodule") { + moduleExecutionStatus <- .executeModule( + moduleName = moduleName, + connectionDetails = connectionDetails, + analysisSpecifications = analysisSpecifications, + executionSettings = executionSettings + ) + executionStatus <- append( + executionStatus, + moduleExecutionStatus + ) + } + } - if (execResultsUpload) { - resultsTargetName <- paste0(targetName, "_results_upload") - targetList[[length(targetList) + 1]] <- targets::tar_target_raw(resultsTargetName, - substitute(Strategus:::runResultsUpload(analysisSpecifications, keyringSettings, i, executionSettings), - env = list(i = i) - ), - deps = c("analysisSpecifications", "keyringSettings", "executionSettings", targetName) - ) - } - } - targetList - }, - script = fileName - ) + # Print a summary + cli::cli_h1("EXECUTION SUMMARY") + for (i in 1:length(executionStatus)) { + status <- executionStatus[[i]] + errorMessage <- ifelse(!is.null(status$result$error), status$result$error, "") + statusMessage <- sprintf("%s %s (Execution Time: %s)", status$moduleName, errorMessage, status$executionTime) + if (!is.null(status$result$error)) { + cli::cli_alert_danger(statusMessage) + } else { + cli::cli_alert_success(statusMessage) + } + } - # Store settings objects in the temp folder so they are available in targets - analysisSpecificationsFileName <- .formatAndNormalizeFilePathForScript(file.path(executionScriptFolder, "analysisSpecifications.rds")) - saveRDS(analysisSpecifications, analysisSpecificationsFileName) - executionSettingsFileName <- .formatAndNormalizeFilePathForScript(file.path(executionScriptFolder, "executionSettings.rds")) - saveRDS(executionSettings, executionSettingsFileName) - keyringSettingsFileName <- .formatAndNormalizeFilePathForScript(file.path(executionScriptFolder, "keyringSettings.rds")) - saveRDS(list(keyringName = keyringName), keyringSettingsFileName) + invisible(executionStatus) +} - # Generate target names by module type - moduleToTargetNames <- list() - for (i in 1:length(analysisSpecifications$moduleSpecifications)) { - moduleSpecification <- analysisSpecifications$moduleSpecifications[[i]] - targetName <- sprintf("%s_%d", moduleSpecification$module, i) - moduleToTargetNames[[length(moduleToTargetNames) + 1]] <- tibble( - module = moduleSpecification$module, - targetName = targetName - ) +.executeModule <- function(moduleName, connectionDetails, analysisSpecifications, executionSettings) { + moduleObject <- get(moduleName)$new() + safeExec <- purrr::safely(moduleObject$execute) + startTime <- Sys.time() + executionResult <- safeExec( + connectionDetails = connectionDetails, + analysisSpecifications = analysisSpecifications, + executionSettings = executionSettings + ) + timeToExecute <- Sys.time() - startTime + # Emit any errors + if (!is.null(executionResult$error)) { + .printErrorMessage(executionResult$error$message) } - moduleToTargetNames <- bind_rows(moduleToTargetNames) - moduleToTargetNamesFileName <- .formatAndNormalizeFilePathForScript(file.path(executionScriptFolder, "moduleTargetNames.rds")) - saveRDS(moduleToTargetNames, moduleToTargetNamesFileName) - - dependenciesFileName <- .formatAndNormalizeFilePathForScript(file.path(executionScriptFolder, "dependencies.rds")) - saveRDS(dependencies, dependenciesFileName) - - execResultsUpload <- all(c( - is(executionSettings, "CdmExecutionSettings"), - !is.null(executionSettings$resultsConnectionDetailsReference), - !is.null(executionSettings$resultsDatabaseSchema) - )) - - # Settings required inside script. There is probably a much cleaner way of doing this - writeLines(c( - sprintf("analysisSpecificationsFileName <- '%s'", analysisSpecificationsFileName), - sprintf("executionSettingsFileName <- '%s'", executionSettingsFileName), - sprintf("keyringSettingsFileName <- '%s'", keyringSettingsFileName), - sprintf("moduleToTargetNamesFileName <- '%s'", moduleToTargetNamesFileName), - sprintf("dependenciesFileName <- '%s'", dependenciesFileName), - sprintf("execResultsUpload <- '%s'", execResultsUpload), - readLines(fileName) - ), fileName) - - return(fileName) + return( + list( + list( + moduleName = moduleName, + result = executionResult, + executionTime = paste0(signif(timeToExecute, 3), " ", attr(timeToExecute, "units")) + ) + ) + ) +} + +.printErrorMessage <- function(message) { + error <- cli::combine_ansi_styles("red") + cat(error(paste0("ERROR: ", message, "\n"))) } diff --git a/R/Module-Characterization.R b/R/Module-Characterization.R new file mode 100644 index 00000000..b2b05938 --- /dev/null +++ b/R/Module-Characterization.R @@ -0,0 +1,268 @@ +# CharacterizationModule ------------- +#' @title Characterize cohorts with the \href{https://ohdsi.github.io/Characterization/}{HADES Characterization Package} +#' @export +#' @description +#' Computes cohort characterization information against +#' the OMOP Common Data Model +CharacterizationModule <- R6::R6Class( + classname = "CharacterizationModule", + inherit = StrategusModule, + public = list( + #' @field tablePrefix The table prefix to append to the results tables + tablePrefix = "c_", + #' @description Initialize the module + initialize = function() { + super$initialize() + }, + #' @description Execute characterization + #' @template connectionDetails + #' @template analysisSpecifications + #' @template executionSettings + execute = function(connectionDetails, analysisSpecifications, executionSettings) { + super$.validateCdmExecutionSettings(executionSettings) + super$execute(connectionDetails, analysisSpecifications, executionSettings) + + jobContext <- private$jobContext + workFolder <- jobContext$moduleExecutionSettings$workSubFolder + resultsFolder <- jobContext$moduleExecutionSettings$resultsSubFolder + + Characterization::runCharacterizationAnalyses( + connectionDetails = connectionDetails, + targetDatabaseSchema = jobContext$moduleExecutionSettings$workDatabaseSchema, + targetTable = jobContext$moduleExecutionSettings$cohortTableNames$cohortTable, + outcomeDatabaseSchema = jobContext$moduleExecutionSettings$workDatabaseSchema, + outcomeTable = jobContext$moduleExecutionSettings$cohortTableNames$cohortTable, + cdmDatabaseSchema = jobContext$moduleExecutionSettings$cdmDatabaseSchema, + characterizationSettings = jobContext$settings$analysis, + databaseId = jobContext$moduleExecutionSettings$cdmDatabaseMetaData$databaseId, + outputDirectory = resultsFolder, + executionPath = workFolder, + csvFilePrefix = self$tablePrefix, + minCellCount = jobContext$moduleExecutionSettings$minCellCount, + minCharacterizationMean = jobContext$settings$minCharacterizationMean, + incremental = jobContext$moduleExecutionSettings$incremental, + threads = as.double(ifelse(Sys.getenv("CharacterizationThreads") == "", 1, Sys.getenv("CharacterizationThreads"))) + ) + + # Export the resultsDataModelSpecification.csv + resultsDataModelSpecification <- self$getResultsDataModelSpecification() + + CohortGenerator::writeCsv( + x = resultsDataModelSpecification, + file = file.path(resultsFolder, "resultsDataModelSpecification.csv"), + warnOnCaseMismatch = FALSE, + warnOnFileNameCaseMismatch = FALSE, + warnOnUploadRuleViolations = FALSE + ) + + private$.message(paste("Results available at:", resultsFolder)) + }, + #' @description Create the results data model for the module + #' @template resultsConnectionDetails + #' @template resultsDatabaseSchema + #' @template tablePrefix + createResultsDataModel = function(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix = self$tablePrefix) { + super$createResultsDataModel(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix) + + Characterization::createCharacterizationTables( + connectionDetails = resultsConnectionDetails, + resultSchema = resultsDatabaseSchema, + deleteExistingTables = T, + createTables = T, + tablePrefix = tablePrefix + ) + }, + #' @description Get the results data model specification for the module + #' @template tablePrefix + getResultsDataModelSpecification = function(tablePrefix = "") { + resultsDataModelSpecification <- CohortGenerator::readCsv( + file = system.file( + file.path("settings", "resultsDataModelSpecification.csv"), + package = "Characterization" + ), + warnOnCaseMismatch = FALSE + ) + + # add the prefix to the tableName column + resultsDataModelSpecification$tableName <- paste0(tablePrefix, self$tablePrefix, resultsDataModelSpecification$tableName) + return(resultsDataModelSpecification) + }, + #' @description Upload the results for the module + #' @template resultsConnectionDetails + #' @template analysisSpecifications + #' @template resultsDataModelSettings + uploadResults = function(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) { + super$uploadResults(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) + jobContext <- private$jobContext + resultsFolder <- jobContext$moduleExecutionSettings$resultsSubFolder + + specifications <- private$.getResultsDataModelSpecification() + + ResultModelManager::uploadResults( + connectionDetails = resultsConnectionDetails, + schema = resultsDataModelSettings$resultsDatabaseSchema, + resultsFolder = resultsFolder, + purgeSiteDataBeforeUploading = FALSE, + specifications = specifications + ) + }, + #' @description Creates the CharacterizationModule Specifications + #' @param targetIds A vector of cohort IDs to use as the target(s) for the characterization + #' @param outcomeIds A vector of cohort IDs to use as the outcome(s) for the characterization + #' @param outcomeWashoutDays A vector of integers specifying the washout days for each outcome (same length as the outcomeIds) + #' @param minPriorObservation The number of days of minimum observation a patient in the target populations must have + #' @param dechallengeStopInterval description + #' @param dechallengeEvaluationWindow description + #' @param riskWindowStart The number of days after start anchor to start the time-at-risk (can be a vector for multiple TARS) + #' @param startAnchor The TAR starts relative to this either cohort start or cohort end (can be a vector for multiple TARS) + #' @param riskWindowEnd The number of days after end anchor to end the time-at-risk (can be a vector for multiple TARS) + #' @param endAnchor The TAR ends relative to this either cohort start or cohort end (can be a vector for multiple TARS) + #' @param minCharacterizationMean The minimum fraction patients in the target have a covariate for it to be included + #' @param covariateSettings Covariates for the database, cohort and risk factor characterization + #' @param caseCovariateSettings Covariates for the case-series characterization + #' @param casePreTargetDuration The number of days before target start to use for case-series + #' @param casePostOutcomeDuration The number of days after outcome start to use for case-series + createModuleSpecifications = function(targetIds, + outcomeIds, # a vector of ids + outcomeWashoutDays = c(365), # same length as outcomeIds with the outcomeWashout + minPriorObservation = 365, + dechallengeStopInterval = 30, + dechallengeEvaluationWindow = 30, + riskWindowStart = c(1, 1), + startAnchor = c("cohort start", "cohort start"), + riskWindowEnd = c(0, 365), + endAnchor = c("cohort end", "cohort end"), + minCharacterizationMean = 0.01, + covariateSettings = FeatureExtraction::createCovariateSettings( + useDemographicsGender = T, + useDemographicsAge = T, + useDemographicsAgeGroup = T, + useDemographicsRace = T, + useDemographicsEthnicity = T, + useDemographicsIndexYear = T, + useDemographicsIndexMonth = T, + useDemographicsTimeInCohort = T, + useDemographicsPriorObservationTime = T, + useDemographicsPostObservationTime = T, + useConditionGroupEraLongTerm = T, + useDrugGroupEraOverlapping = T, + useDrugGroupEraLongTerm = T, + useProcedureOccurrenceLongTerm = T, + useMeasurementLongTerm = T, + useObservationLongTerm = T, + useDeviceExposureLongTerm = T, + useVisitConceptCountLongTerm = T, + useConditionGroupEraShortTerm = T, + useDrugGroupEraShortTerm = T, + useProcedureOccurrenceShortTerm = T, + useMeasurementShortTerm = T, + useObservationShortTerm = T, + useDeviceExposureShortTerm = T, + useVisitConceptCountShortTerm = T, + endDays = 0, + longTermStartDays = -365, + shortTermStartDays = -30 + ), + caseCovariateSettings = Characterization::createDuringCovariateSettings( + useConditionGroupEraDuring = T, + useDrugGroupEraDuring = T, + useProcedureOccurrenceDuring = T, + useDeviceExposureDuring = T, + useMeasurementDuring = T, + useObservationDuring = T, + useVisitConceptCountDuring = T + ), + casePreTargetDuration = 365, + casePostOutcomeDuration = 365) { + # input checks + if (!inherits(outcomeIds, "numeric")) { + stop("outcomeIds must be a numeric or a numeric vector") + } + + if (!inherits(outcomeWashoutDays, "numeric")) { + stop("outcomeWashoutDays must be a numeric or a numeric vector") + } + if (length(outcomeIds) != length(outcomeWashoutDays)) { + stop("outcomeWashoutDaysVector and outcomeIds must be same length") + } + if (length(minPriorObservation) != 1) { + stop("minPriorObservation needs to be length 1") + } + if (length(riskWindowStart) != length(startAnchor) | + length(riskWindowEnd) != length(startAnchor) | + length(endAnchor) != length(startAnchor)) { + stop("Time-at-risk settings must be same length") + } + + # group the outcomeIds with the same outcomeWashoutDays + outcomeWashoutDaysVector <- unique(outcomeWashoutDays) + outcomeIdsList <- lapply( + outcomeWashoutDaysVector, + function(x) { + ind <- which(outcomeWashoutDays == x) + unique(outcomeIds[ind]) + } + ) + + + timeToEventSettings <- Characterization::createTimeToEventSettings( + targetIds = targetIds, + outcomeIds = outcomeIds + ) + + dechallengeRechallengeSettings <- Characterization::createDechallengeRechallengeSettings( + targetIds = targetIds, + outcomeIds = outcomeIds, + dechallengeStopInterval = dechallengeStopInterval, + dechallengeEvaluationWindow = dechallengeEvaluationWindow + ) + + aggregateCovariateSettings <- list() + + for (i in 1:length(riskWindowStart)) { + for (j in 1:length(outcomeIdsList)) { + aggregateCovariateSettings[[length(aggregateCovariateSettings) + 1]] <- Characterization::createAggregateCovariateSettings( + targetIds = targetIds, + outcomeIds = outcomeIdsList[[j]], + minPriorObservation = minPriorObservation, + outcomeWashoutDays = outcomeWashoutDaysVector[j], + riskWindowStart = riskWindowStart[i], + startAnchor = startAnchor[i], + riskWindowEnd = riskWindowEnd[i], + endAnchor = endAnchor[i], + covariateSettings = covariateSettings, + caseCovariateSettings = caseCovariateSettings, + casePreTargetDuration = casePreTargetDuration, + casePostOutcomeDuration = casePostOutcomeDuration + ) + } + } + + analysis <- Characterization::createCharacterizationSettings( + timeToEventSettings = list(timeToEventSettings), + dechallengeRechallengeSettings = list(dechallengeRechallengeSettings), + aggregateCovariateSettings = aggregateCovariateSettings + ) + + specifications <- super$createModuleSpecifications( + moduleSpecifications = list( + analysis = analysis, + minCharacterizationMean = minCharacterizationMean + ) + ) + return(specifications) + } + ), + private = list( + .getResultsDataModelSpecification = function(tablePrefix = self$tablePrefix) { + rdms <- CohortGenerator::readCsv( + file = system.file( + "settings/resultsDataModelSpecification.csv", + package = "Characterization" + ) + ) + rdms$tableName <- paste0(tablePrefix, rdms$tableName) + return(rdms) + } + ) +) diff --git a/R/Module-CohortDiagnostics.R b/R/Module-CohortDiagnostics.R new file mode 100644 index 00000000..916f3369 --- /dev/null +++ b/R/Module-CohortDiagnostics.R @@ -0,0 +1,229 @@ +# CohortDiagnosticsModule ------------- +#' @title Evaluate phenotypes with the \href{https://ohdsi.github.io/CohortDiagnostics/}{HADES CohortDiagnostics Package} +#' @export +#' @description +#' Development and evaluation of phenotype algorithms +#' against the OMOP Common Data Model. +CohortDiagnosticsModule <- R6::R6Class( + classname = "CohortDiagnosticsModule", + inherit = StrategusModule, + public = list( + #' @field tablePrefix The table prefix to append to results tables + tablePrefix = "cd_", + #' @description Initialize the module + initialize = function() { + super$initialize() + }, + #' @description Executes the CohortDiagnostics package + #' @template connectionDetails + #' @template analysisSpecifications + #' @template executionSettings + execute = function(connectionDetails, analysisSpecifications, executionSettings) { + super$.validateCdmExecutionSettings(executionSettings) + super$execute(connectionDetails, analysisSpecifications, executionSettings) + + jobContext <- private$jobContext + cohortDefinitionSet <- super$.createCohortDefinitionSetFromJobContext() + + exportFolder <- jobContext$moduleExecutionSettings$resultsSubFolder + args <- jobContext$settings + args$cohortDefinitionSet <- cohortDefinitionSet + args$exportFolder <- exportFolder + args$databaseId <- jobContext$moduleExecutionSettings$cdmDatabaseMetaData$databaseId + args$connectionDetails <- connectionDetails + args$cdmDatabaseSchema <- jobContext$moduleExecutionSettings$cdmDatabaseSchema + args$cohortDatabaseSchema <- jobContext$moduleExecutionSettings$workDatabaseSchema + args$cohortTableNames <- jobContext$moduleExecutionSettings$cohortTableNames + args$incrementalFolder <- jobContext$moduleExecutionSettings$workSubFolder + args$minCellCount <- jobContext$moduleExecutionSettings$minCellCount + args$cohortIds <- jobContext$moduleExecutionSettings$cohortIds + do.call(CohortDiagnostics::executeDiagnostics, args) + + # TODO: Removing this to make the upload easier + # unlink(file.path(exportFolder, sprintf("Results_%s.zip", jobContext$moduleExecutionSettings$cdmDatabaseMetaData$databaseId))) + + # NOTE: CD exports data without the table prefix and this section + # will manipulate the files to include the table prefix + resultsDataModelSpecification <- private$.getResultsDataModelSpecification() + resultsDataModelSpecification <- resultsDataModelSpecification[file.exists(file.path(exportFolder, paste0(resultsDataModelSpecification$tableName, ".csv"))), ] + newTableNames <- paste0(self$tablePrefix, resultsDataModelSpecification$tableName) + file.rename( + file.path(exportFolder, paste0(unique(resultsDataModelSpecification$tableName), ".csv")), + file.path(exportFolder, paste0(unique(newTableNames), ".csv")) + ) + resultsDataModelSpecification$tableName <- newTableNames + CohortGenerator::writeCsv( + x = resultsDataModelSpecification, + file.path(exportFolder, "resultsDataModelSpecification.csv"), + warnOnFileNameCaseMismatch = FALSE + ) + + private$.message(paste("Results available at:", exportFolder)) + }, + #' @description Create the results data model for the module + #' @template resultsConnectionDetails + #' @template resultsDatabaseSchema + #' @template tablePrefix + createResultsDataModel = function(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix = self$tablePrefix) { + super$createResultsDataModel(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix) + CohortDiagnostics::createResultsDataModel( + connectionDetails = resultsConnectionDetails, + databaseSchema = resultsDatabaseSchema, + tablePrefix = tablePrefix + ) + }, + #' @description Get the results data model specification for the module + #' @template tablePrefix + getResultsDataModelSpecification = function(tablePrefix = "") { + resultsDataModelSpecification <- private$.getResultsDataModelSpecification() + # add the prefix to the tableName column + resultsDataModelSpecification$tableName <- paste0(tablePrefix, self$tablePrefix, resultsDataModelSpecification$tableName) + return(resultsDataModelSpecification) + }, + #' @description Upload the results for the module + #' @template resultsConnectionDetails + #' @template analysisSpecifications + #' @template resultsDataModelSettings + uploadResults = function(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) { + super$uploadResults(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) + + # TODO: This is something CD does differently. + # Find the results zip file in the results sub folder + resultsFolder <- private$jobContext$moduleExecutionSettings$resultsSubFolder + zipFiles <- list.files( + path = resultsFolder, + pattern = "\\.zip$", + full.names = TRUE + ) + + if (length(zipFiles) > 0) { + zipFileName <- zipFiles[1] + } else { + # Create a zip file from the results in the directory + DatabaseConnector::createZipFile( + zipFile = "results.zip", + files = list.files(resultsFolder, pattern = ".*\\.csv$"), + rootFolder = resultsFolder + ) + zipFileName <- file.path(resultsFolder, "results.zip") + } + + CohortDiagnostics::uploadResults( + connectionDetails = resultsConnectionDetails, + schema = resultsDataModelSettings$resultsDatabaseSchema, + tablePrefix = self$tablePrefix, + zipFileName = zipFileName, + purgeSiteDataBeforeUploading = FALSE + ) + }, + #' @description Creates the CohortDiagnostics Module Specifications + #' + #' + #' @param cohortIds A list of cohort IDs to use when running the CohortDiagnostics. + #' Default is NULL which will use all cohorts present in the cohort definition set + #' in the analysis specification + #' @param runInclusionStatistics Generate and export statistic on the cohort inclusion rules? + #' @param runIncludedSourceConcepts Generate and export the source concepts included in the cohorts? + #' @param runOrphanConcepts Generate and export potential orphan concepts? + #' @param runTimeSeries Generate and export the time series diagnostics? + #' @param runVisitContext Generate and export index-date visit context? + #' @param runBreakdownIndexEvents Generate and export the breakdown of index events? + #' @param runIncidenceRate Generate and export the cohort incidence rates? + #' @param runCohortRelationship Generate and export the cohort relationship? Cohort relationship checks the temporal + #' relationship between two or more cohorts. + #' @param runTemporalCohortCharacterization Generate and export the temporal cohort characterization? + #' Only records with values greater than 0.001 are returned. + #' @param temporalCovariateSettings Either an object of type \code{covariateSettings} as created using one of + #' the createTemporalCovariateSettings function in the FeatureExtraction package, or a list + #' of such objects. + #' @param minCharacterizationMean The minimum mean value for characterization output. Values below this will be cut off from output. This + #' will help reduce the file size of the characterization output, but will remove information + #' on covariates that have very low values. The default is 0.001 (i.e. 0.1 percent) + #' @param irWashoutPeriod Number of days washout to include in calculation of incidence rates - default is 0 + createModuleSpecifications = function(cohortIds = NULL, + runInclusionStatistics = TRUE, + runIncludedSourceConcepts = TRUE, + runOrphanConcepts = TRUE, + runTimeSeries = FALSE, + runVisitContext = TRUE, + runBreakdownIndexEvents = TRUE, + runIncidenceRate = TRUE, + runCohortRelationship = TRUE, + runTemporalCohortCharacterization = TRUE, + temporalCovariateSettings = private$.getDefaultCovariateSettings(), + minCharacterizationMean = 0.01, + irWashoutPeriod = 0) { + analysis <- list() + for (name in names(formals(self$createModuleSpecifications))) { + analysis[[name]] <- get(name) + } + + specifications <- super$createModuleSpecifications( + moduleSpecifications = analysis + ) + return(specifications) + }, + #' @description Validate the module specifications + #' @param moduleSpecifications The CohortIncidence module specifications + validateModuleSpecifications = function(moduleSpecifications) { + super$validateModuleSpecifications( + moduleSpecifications = moduleSpecifications + ) + } + ), + private = list( + .getDefaultCovariateSettings = function() { + covariateSettings <- ' + { + "temporal": true, + "temporalSequence": false, + "DemographicsGender": true, + "DemographicsAge": true, + "DemographicsAgeGroup": true, + "DemographicsRace": true, + "DemographicsEthnicity": true, + "DemographicsIndexYear": true, + "DemographicsIndexMonth": true, + "DemographicsPriorObservationTime": true, + "DemographicsPostObservationTime": true, + "DemographicsTimeInCohort": true, + "DemographicsIndexYearMonth": true, + "ConditionOccurrence": true, + "ConditionEraStart": true, + "ConditionEraOverlap": true, + "ConditionEraGroupOverlap": true, + "DrugEraStart": true, + "DrugEraGroupOverlap": true, + "ProcedureOccurrence": true, + "DeviceExposure": true, + "Measurement": true, + "Observation": true, + "CharlsonIndex": true, + "Dcsi": true, + "Chads2": true, + "Chads2Vasc": true, + "temporalStartDays": [-9999, -365, -180, -30, -365, -30, 0, 1, 31, -9999], + "temporalEndDays": [0, 0, 0, 0, -31, -1, 0, 30, 365, 9999], + "includedCovariateConceptIds": [], + "addDescendantsToInclude": false, + "excludedCovariateConceptIds": [], + "addDescendantsToExclude": false, + "includedCovariateIds": [], + "attr_class": "covariateSettings", + "attr_fun": "getDbDefaultCovariateData" + } + ' + ParallelLogger::convertJsonToSettings(covariateSettings) + }, + .getResultsDataModelSpecification = function() { + resultsDataModelSpecification <- CohortGenerator::readCsv( + file = system.file( + file.path("settings", "resultsDataModelSpecification.csv"), + package = "CohortDiagnostics" + ), + warnOnCaseMismatch = FALSE + ) + return(resultsDataModelSpecification) + } + ) +) diff --git a/R/Module-CohortGenerator.R b/R/Module-CohortGenerator.R new file mode 100644 index 00000000..a5373ee5 --- /dev/null +++ b/R/Module-CohortGenerator.R @@ -0,0 +1,224 @@ +# CohortGeneratorModule ------------- +#' @title Generate cohorts with the \href{https://ohdsi.github.io/CohortGenerator/}{HADES CohortGenerator Package} +#' @export +#' @description +#' Generates cohorts against the OMOP Common Data Model +CohortGeneratorModule <- R6::R6Class( + classname = "CohortGeneratorModule", + inherit = StrategusModule, + public = list( + #' @field cohortDefinitionSharedResourcesClassName A constant for the name + #' of the cohort definition shared resources section of the analysis + #' specification + cohortDefinitionSharedResourcesClassName = "CohortDefinitionSharedResources", + #' @field negativeControlOutcomeSharedResourcesClassName A constant for the + #' name of the negative control outcome shared resources section of the + #' analysis specification + negativeControlOutcomeSharedResourcesClassName = "NegativeControlOutcomeSharedResources", + #' @description Initialize the module + initialize = function() { + super$initialize() + }, + #' @description Generates the cohorts + #' @template connectionDetails + #' @template analysisSpecifications + #' @template executionSettings + execute = function(connectionDetails, analysisSpecifications, executionSettings) { + super$.validateCdmExecutionSettings(executionSettings) + super$execute(connectionDetails, analysisSpecifications, executionSettings) + + jobContext <- private$jobContext + cohortDefinitionSet <- super$.createCohortDefinitionSetFromJobContext( + generateStats = jobContext$settings$generateStats + ) + negativeControlOutcomeSettings <- private$.createNegativeControlOutcomeSettingsFromJobContext() + resultsFolder <- jobContext$moduleExecutionSettings$resultsSubFolder + if (!dir.exists(resultsFolder)) { + dir.create(resultsFolder, recursive = TRUE) + } + + CohortGenerator::runCohortGeneration( + connectionDetails = connectionDetails, + cdmDatabaseSchema = jobContext$moduleExecutionSettings$cdmDatabaseSchema, + cohortDatabaseSchema = jobContext$moduleExecutionSettings$workDatabaseSchema, + cohortTableNames = jobContext$moduleExecutionSettings$cohortTableNames, + cohortDefinitionSet = cohortDefinitionSet, + negativeControlOutcomeCohortSet = negativeControlOutcomeSettings$cohortSet, + occurrenceType = negativeControlOutcomeSettings$occurrenceType, + detectOnDescendants = negativeControlOutcomeSettings$detectOnDescendants, + outputFolder = resultsFolder, + databaseId = jobContext$moduleExecutionSettings$cdmDatabaseMetaData$databaseId, + minCellCount = jobContext$moduleExecutionSettings$minCellCount, + incremental = jobContext$moduleExecutionSettings$incremental, + incrementalFolder = jobContext$moduleExecutionSettings$workSubFolder + ) + + private$.message(paste("Results available at:", resultsFolder)) + }, + #' @description Create the results data model for the module + #' @template resultsConnectionDetails + #' @template resultsDatabaseSchema + #' @template tablePrefix + createResultsDataModel = function(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix = "") { + super$createResultsDataModel(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix) + CohortGenerator::createResultsDataModel( + connectionDetails = resultsConnectionDetails, + databaseSchema = resultsDatabaseSchema, + tablePrefix = tablePrefix + ) + }, + #' @description Get the results data model specification for the module + #' @template tablePrefix + getResultsDataModelSpecification = function(tablePrefix = "") { + resultsDataModelSpecification <- CohortGenerator::readCsv( + file = system.file( + file.path("csv", "resultsDataModelSpecification.csv"), + package = "CohortGenerator" + ), + warnOnCaseMismatch = FALSE + ) + + # add the prefix to the tableName column + resultsDataModelSpecification$tableName <- paste0(tablePrefix, resultsDataModelSpecification$tableName) + return(resultsDataModelSpecification) + }, + #' @description Upload the results for the module + #' @template resultsConnectionDetails + #' @template analysisSpecifications + #' @template resultsDataModelSettings + uploadResults = function(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) { + super$uploadResults(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) + + CohortGenerator::uploadResults( + connectionDetails = resultsConnectionDetails, + schema = resultsDataModelSettings$resultsDatabaseSchema, + resultsFolder = private$jobContext$moduleExecutionSettings$resultsSubFolder, + purgeSiteDataBeforeUploading = FALSE + ) + }, + #' @description Creates the CohortGenerator Module Specifications + #' @param generateStats When TRUE, the Circe cohort definition SQL will + #' include steps to compute inclusion rule statistics. + createModuleSpecifications = function(generateStats = TRUE) { + analysis <- list() + for (name in names(formals(self$createModuleSpecifications))) { + analysis[[name]] <- get(name) + } + + specifications <- super$createModuleSpecifications( + moduleSpecifications = analysis + ) + return(specifications) + }, + #' @description Create shared specifications for the cohort definition set + #' @param cohortDefinitionSet The cohort definition set to include in the + #' specification. See the CohortGenerator package for details on how to + #' build this object. + createCohortSharedResourceSpecifications = function(cohortDefinitionSet) { + if (!CohortGenerator::isCohortDefinitionSet(cohortDefinitionSet)) { + stop("cohortDefinitionSet is not properly defined") + } + + subsetDefinitions <- CohortGenerator::getSubsetDefinitions(cohortDefinitionSet) + if (length(subsetDefinitions) > 0) { + # Filter the cohort definition set to the "parent" cohorts. + parentCohortDefinitionSet <- cohortDefinitionSet[!cohortDefinitionSet$isSubset, ] + } else { + parentCohortDefinitionSet <- cohortDefinitionSet + } + + sharedResource <- list() + cohortDefinitionSetFiltered <- private$.listafy(parentCohortDefinitionSet) + sharedResource["cohortDefinitions"] <- list(cohortDefinitionSetFiltered) + + if (length(subsetDefinitions)) { + # Subset definitions + subsetDefinitionsJson <- lapply(subsetDefinitions, function(x) { + x$toJSON() + }) + sharedResource["subsetDefs"] <- list(subsetDefinitionsJson) + + # Filter to the subsets + subsetCohortDefinitionSet <- cohortDefinitionSet[cohortDefinitionSet$isSubset, ] + subsetIdMapping <- list() + for (i in 1:nrow(subsetCohortDefinitionSet)) { + idMapping <- list( + cohortId = subsetCohortDefinitionSet$cohortId[i], + subsetId = subsetCohortDefinitionSet$subsetDefinitionId[i], + targetCohortId = subsetCohortDefinitionSet$subsetParent[i] + ) + subsetIdMapping[[i]] <- idMapping + } + sharedResource["cohortSubsets"] <- list(subsetIdMapping) + } + + sharedResource <- super$createSharedResourcesSpecifications( + className = self$cohortDefinitionSharedResourcesClassName, + sharedResourcesSpecifications = sharedResource + ) + return(sharedResource) + }, + #' @description Create shared specifications for the negative control outcomes cohort set + #' @param negativeControlOutcomeCohortSet The negative control outcome cohort + #' definition set defines the concepts to use to construct negative control + #' outcome cohorts. See the CohortGenerator package for more details. + #' @param occurrenceType Either "first" or "all + #' @param detectOnDescendants When TRUE, the concept ID for the negative + #' control will use the `concept_ancestor` table and will detect + #' descendant concepts when constructing the cohort. + createNegativeControlOutcomeCohortSharedResourceSpecifications = function(negativeControlOutcomeCohortSet, + occurrenceType, + detectOnDescendants) { + negativeControlOutcomeCohortSet <- apply(negativeControlOutcomeCohortSet, 1, as.list) + sharedResource <- list( + negativeControlOutcomes = list( + negativeControlOutcomeCohortSet = negativeControlOutcomeCohortSet, + occurrenceType = occurrenceType, + detectOnDescendants = detectOnDescendants + ) + ) + sharedResource <- super$createSharedResourcesSpecifications( + className = self$negativeControlOutcomeSharedResourcesClassName, + sharedResourcesSpecifications = sharedResource + ) + return(sharedResource) + }, + #' @description Validate the module specifications + #' @param moduleSpecifications The CohortGenerator module specifications + validateModuleSpecifications = function(moduleSpecifications) { + super$validateModuleSpecifications( + moduleSpecifications = moduleSpecifications + ) + }, + #' @description Validate the cohort shared resource specifications + #' @param cohortSharedResourceSpecifications The cohort shared resource specifications + validateCohortSharedResourceSpecifications = function(cohortSharedResourceSpecifications) { + super$validateSharedResourcesSpecifications( + className = self$cohortDefinitionSharedResourcesClassName, + sharedResourcesSpecifications = cohortSharedResourceSpecifications + ) + }, + #' @description Validate the cohort shared resource specifications + #' @param negativeControlOutcomeCohortSharedResourceSpecifications The cohort shared resource specifications + validateNegativeControlOutcomeCohortSharedResourceSpecifications = function(negativeControlOutcomeCohortSharedResourceSpecifications) { + super$validateSharedResourcesSpecifications( + className = self$negativeControlOutcomeSharedResourcesClassName, + sharedResourcesSpecifications = negativeControlOutcomeCohortSharedResourceSpecifications + ) + } + ), + private = list( + .listafy = function(df) { + mylist <- list() + for (i in 1:nrow(df)) { + cohortData <- list( + cohortId = df$cohortId[i], + cohortName = df$cohortName[i], + cohortDefinition = df$json[i] + ) + mylist[[i]] <- cohortData + } + return(mylist) + } + ) +) diff --git a/R/Module-CohortIncidence.R b/R/Module-CohortIncidence.R new file mode 100644 index 00000000..a0b3fb0b --- /dev/null +++ b/R/Module-CohortIncidence.R @@ -0,0 +1,216 @@ +# CohortIncidenceModule ------------- +#' @title Compute incidence with the \href{https://ohdsi.github.io/CohortIncidence/}{HADES CohortIncidence Package} +#' @export +#' @description +#' Computes incidence rates for cohorts against the OMOP Common Data Model +CohortIncidenceModule <- R6::R6Class( + classname = "CohortIncidenceModule", + inherit = StrategusModule, + public = list( + #' @field tablePrefix The table prefix to append to results tables + tablePrefix = "ci_", + #' @description Initialize the module + initialize = function() { + super$initialize() + }, + #' @description Execute the CohortIncidence package + #' @template connectionDetails + #' @template analysisSpecifications + #' @template executionSettings + execute = function(connectionDetails, analysisSpecifications, executionSettings) { + super$.validateCdmExecutionSettings(executionSettings) + super$execute(connectionDetails, analysisSpecifications, executionSettings) + + refId <- 1 # this should be part of execution settings + resultsFolder <- private$jobContext$moduleExecutionSettings$resultsSubFolder + + # Establish the connection and ensure the cleanup is performed + connection <- DatabaseConnector::connect(connectionDetails) + on.exit(DatabaseConnector::disconnect(connection)) + + # extract CohortIncidence design from jobContext + irDesign <- CohortIncidence::IncidenceDesign$new(private$jobContext$settings$irDesign) + irDesignJSON <- as.character(irDesign$asJSON()) + + # construct buildOptions from executionSettings + # Questions: + # Will there be a subgroup cohort table? + # Are we pulling the source name from the right place? + + buildOptions <- CohortIncidence::buildOptions( + cohortTable = paste0(private$jobContext$moduleExecutionSettings$workDatabaseSchema, ".", private$jobContext$moduleExecutionSettings$cohortTableNames$cohortTable), + cdmDatabaseSchema = private$jobContext$moduleExecutionSettings$cdmDatabaseSchema, + sourceName = as.character(private$jobContext$moduleExecutionSettings$cdmDatabaseMetaData$databaseId), + refId = refId + ) + + executeResults <- CohortIncidence::executeAnalysis( + connection = connection, + incidenceDesign = irDesignJSON, + buildOptions = buildOptions + ) + + # Export the results + exportFolder <- private$jobContext$moduleExecutionSettings$resultsSubFolder + if (!dir.exists(exportFolder)) { + dir.create(exportFolder, recursive = TRUE) + } + + private$.message("Export data") + + # apply minCellCount to executeResults + minCellCount <- private$jobContext$moduleExecutionSettings$minCellCount + if (minCellCount > 0) { + executeResults$incidence_summary <- private$.enforceMinCellValue(executeResults$incidence_summary, "PERSONS_AT_RISK_PE", minCellCount) + executeResults$incidence_summary <- private$.enforceMinCellValue(executeResults$incidence_summary, "PERSONS_AT_RISK", minCellCount) + executeResults$incidence_summary <- private$.enforceMinCellValue(executeResults$incidence_summary, "PERSON_OUTCOMES_PE", minCellCount) + executeResults$incidence_summary <- private$.enforceMinCellValue(executeResults$incidence_summary, "PERSON_OUTCOMES", minCellCount) + executeResults$incidence_summary <- private$.enforceMinCellValue(executeResults$incidence_summary, "OUTCOMES_PE", minCellCount) + executeResults$incidence_summary <- private$.enforceMinCellValue(executeResults$incidence_summary, "OUTCOMES", minCellCount) + executeResults$incidence_summary <- private$.enforceMinCellStats(executeResults$incidence_summary) + } + + for (tableName in names(executeResults)) { + tableData <- executeResults[[tableName]] + if (tableName == "incidence_summary") { + if (nrow(tableData) > 0) { + tableData$database_id <- private$jobContext$moduleExecutionSettings$cdmDatabaseMetaData$databaseId + } else { + tableData$database_id <- character(0) + } + } + readr::write_csv(tableData, file.path(exportFolder, paste0(self$tablePrefix, tableName, ".csv"))) + } + + # in addition to the output of the module, we will produce a T-O lookup table that can be used to filter results + # to either 'Outcomes for T' or 'Targets for Outcomes' + + targetOutcomeDfList <- lapply(irDesign$analysisList, function(analysis) { + outcomeDefs <- Filter(function(o) o$id %in% analysis$outcomes, irDesign$outcomeDefs) + outcome_cohort_id <- sapply(outcomeDefs, function(o) o$cohortId) + as.data.frame(expand.grid(target_cohort_id = analysis$targets, outcome_cohort_id = outcome_cohort_id)) + }) + + target_outcome_ref <- unique(do.call(rbind, targetOutcomeDfList)) + target_outcome_ref$ref_id <- refId + readr::write_csv(target_outcome_ref, file.path(exportFolder, paste0(self$tablePrefix, "target_outcome_ref", ".csv"))) + + resultsDataModelSpecification <- self$getResultsDataModelSpecification() + CohortGenerator::writeCsv( + x = resultsDataModelSpecification, + file.path(exportFolder, "resultsDataModelSpecification.csv"), + warnOnFileNameCaseMismatch = FALSE + ) + + private$.message(paste("Results available at:", resultsFolder)) + }, + #' @description Create the results data model for the module + #' @template resultsConnectionDetails + #' @template resultsDatabaseSchema + #' @template tablePrefix + createResultsDataModel = function(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix = "") { + super$createResultsDataModel(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix) + if (resultsConnectionDetails$dbms == "sqlite" & resultsDatabaseSchema != "main") { + stop("Invalid schema for sqlite, use databaseSchema = 'main'") + } + + connection <- DatabaseConnector::connect(resultsConnectionDetails) + on.exit(DatabaseConnector::disconnect(connection)) + + # Create the results model + sql <- ResultModelManager::generateSqlSchema(schemaDefinition = self$getResultsDataModelSpecification()) + sql <- SqlRender::render(sql = sql, warnOnMissingParameters = TRUE, database_schema = resultsDatabaseSchema) + sql <- SqlRender::translate(sql = sql, targetDialect = resultsConnectionDetails$dbms) + DatabaseConnector::executeSql(connection, sql) + }, + #' @description Get the results data model specification for the module + #' @template tablePrefix + getResultsDataModelSpecification = function(tablePrefix = "") { + resultsDataModelSpecification <- CohortGenerator::readCsv( + file = private$.getResultsDataModelSpecificationFileLocation(), + warnOnCaseMismatch = FALSE + ) + resultsDataModelSpecification$tableName <- paste0(tablePrefix, self$tablePrefix, resultsDataModelSpecification$tableName) + return(resultsDataModelSpecification) + }, + #' @description Upload the results for the module + #' @template resultsConnectionDetails + #' @template analysisSpecifications + #' @template resultsDataModelSettings + uploadResults = function(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) { + super$uploadResults(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) + resultsFolder <- private$jobContext$moduleExecutionSettings$resultsSubFolder + exportFolder <- private$jobContext$moduleExecutionSettings$resultsSubFolder + resultsModelSpec <- self$getResultsDataModelSpecification() + + ResultModelManager::uploadResults( + connectionDetails = resultsConnectionDetails, + schema = resultsDataModelSettings$resultsDatabaseSchema, + resultsFolder = resultsFolder, + purgeSiteDataBeforeUploading = FALSE, + specifications = resultsModelSpec + ) + }, + #' @description Creates the CohortIncidence Module Specifications + #' @param irDesign The incidence rate design created from the CohortIncidence + #' package + createModuleSpecifications = function(irDesign = NULL) { + analysis <- list() + for (name in names(formals(self$createModuleSpecifications))) { + analysis[[name]] <- get(name) + } + + specifications <- super$createModuleSpecifications( + moduleSpecifications = analysis + ) + return(specifications) + }, + #' @description Validate the module specifications + #' @param moduleSpecifications The CohortIncidence module specifications + validateModuleSpecifications = function(moduleSpecifications) { + super$validateModuleSpecifications( + moduleSpecifications = moduleSpecifications + ) + irDesign <- CohortIncidence::IncidenceDesign$new(moduleSpecifications$settings$irDesign) + designJson <- rJava::J("org.ohdsi.analysis.cohortincidence.design.CohortIncidence")$fromJson(as.character(irDesign$asJSON())) + + invisible(designJson) + } + ), + private = list( + .enforceMinCellValue = function(data, fieldName, minValues, silent = FALSE) { + toCensor <- !is.na(data[, fieldName]) & data[, fieldName] < minValues & data[, fieldName] != 0 + if (!silent) { + percent <- round(100 * sum(toCensor) / nrow(data), 1) + private$.message( + " censoring ", + sum(toCensor), + " values (", + percent, + "%) from ", + fieldName, + " because value below minimum" + ) + } + data[toCensor, fieldName] <- -minValues + return(data) + }, + .enforceMinCellStats = function(data) { + # replace rates with NA for cencored outcomes + toCensor <- data[, "OUTCOMES"] < 0 + data[toCensor, "INCIDENCE_RATE_P100PY"] <- NA + + # replace proportions with NA for censored person_outcomes + toCensor <- data[, "PERSON_OUTCOMES"] < 0 + data[toCensor, "INCIDENCE_PROPORTION_P100P"] <- NA + + return(data) + }, + .getResultsDataModelSpecificationFileLocation = function() { + return(system.file( + file.path("csv", "cohortIncidenceRdms.csv"), + package = "Strategus" + )) + } + ) +) diff --git a/R/Module-CohortMethod.R b/R/Module-CohortMethod.R new file mode 100644 index 00000000..619fc2c7 --- /dev/null +++ b/R/Module-CohortMethod.R @@ -0,0 +1,187 @@ +# CohortMethodModule ------------- +#' @title New-user cohort studies with the \href{https://ohdsi.github.io/CohortMethod/}{HADES CohortMethod Package} +#' @export +#' @description +#' Module for performing new-user cohort studies against +#' the OMOP Common Data Model +CohortMethodModule <- R6::R6Class( + classname = "CohortMethodModule", + inherit = StrategusModule, + public = list( + #' @description Initialize the module + initialize = function() { + super$initialize() + }, + #' @description Executes the CohortMethod package + #' @template connectionDetails + #' @param analysisSpecifications The analysis specifications for the study + #' @template executionSettings + execute = function(connectionDetails, analysisSpecifications, executionSettings) { + super$.validateCdmExecutionSettings(executionSettings) + super$execute(connectionDetails, analysisSpecifications, executionSettings) + + jobContext <- private$jobContext + multiThreadingSettings <- CohortMethod::createDefaultMultiThreadingSettings(jobContext$moduleExecutionSettings$maxCores) + + args <- jobContext$settings + args$connectionDetails <- connectionDetails + args$cdmDatabaseSchema <- jobContext$moduleExecutionSettings$cdmDatabaseSchema + args$exposureDatabaseSchema <- jobContext$moduleExecutionSettings$workDatabaseSchema + args$exposureTable <- jobContext$moduleExecutionSettings$cohortTableNames$cohortTable + args$outcomeDatabaseSchema <- jobContext$moduleExecutionSettings$workDatabaseSchema + args$outcomeTable <- jobContext$moduleExecutionSettings$cohortTableNames$cohortTable + args$outputFolder <- jobContext$moduleExecutionSettings$workSubFolder + args$multiThreadingSettings <- multiThreadingSettings + args$cmDiagnosticThresholds <- NULL + do.call(CohortMethod::runCmAnalyses, args) + + exportFolder <- jobContext$moduleExecutionSettings$resultsSubFolder + CohortMethod::exportToCsv( + outputFolder = jobContext$moduleExecutionSettings$workSubFolder, + exportFolder = exportFolder, + databaseId = jobContext$moduleExecutionSettings$cdmDatabaseMetaData$databaseId, + minCellCount = jobContext$moduleExecutionSettings$minCellCount, + maxCores = jobContext$moduleExecutionSettings$maxCores, + cmDiagnosticThresholds = jobContext$settings$cmDiagnosticThresholds + ) + # TODO: Removing this to make the upload easier + # unlink(file.path(exportFolder, sprintf("Results_%s.zip", jobContext$moduleExecutionSettings$cdmDatabaseMetaData$databaseId))) + + resultsDataModelSpecification <- self$getResultsDataModelSpecification() + CohortGenerator::writeCsv( + x = resultsDataModelSpecification, + file = file.path(exportFolder, "resultsDataModelSpecification.csv"), + warnOnFileNameCaseMismatch = FALSE + ) + private$.message(paste("Results available at:", exportFolder)) + }, + #' @description Create the results data model for the module + #' @template resultsConnectionDetails + #' @template resultsDatabaseSchema + #' @template tablePrefix + createResultsDataModel = function(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix = "") { + super$createResultsDataModel(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix) + CohortMethod::createResultsDataModel( + connectionDetails = resultsConnectionDetails, + databaseSchema = resultsDatabaseSchema, + tablePrefix = tablePrefix + ) + }, + #' @description Get the results data model specification for the module + #' @template tablePrefix + getResultsDataModelSpecification = function(tablePrefix = "") { + resultsDataModelSpecification <- CohortGenerator::readCsv( + file = system.file( + file.path("csv", "resultsDataModelSpecification.csv"), + package = "CohortMethod" + ), + warnOnCaseMismatch = FALSE + ) + + # add the prefix to the tableName column + resultsDataModelSpecification$tableName <- paste0(tablePrefix, resultsDataModelSpecification$tableName) + return(resultsDataModelSpecification) + }, + #' @description Upload the results for the module + #' @template resultsConnectionDetails + #' @template analysisSpecifications + #' @template resultsDataModelSettings + uploadResults = function(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) { + super$uploadResults(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) + + # TODO: This is something CM does differently. + # Find the results zip file in the results sub folder + resultsFolder <- private$jobContext$moduleExecutionSettings$resultsSubFolder + zipFiles <- list.files( + path = resultsFolder, + pattern = "\\.zip$", + full.names = TRUE + ) + + if (length(zipFiles) > 0) { + zipFileName <- zipFiles[1] + } else { + # Create a zip file from the results in the directory + DatabaseConnector::createZipFile( + zipFile = "results.zip", + files = list.files(resultsFolder, pattern = ".*\\.csv$"), + rootFolder = resultsFolder + ) + zipFileName <- file.path(resultsFolder, "results.zip") + } + + # TODO: This function does not expose + # a way to specify the database identifier file + # which makes the purge problematic since I'm + # not sure how it will know what to purge... + CohortMethod::uploadResults( + connectionDetails = resultsConnectionDetails, + schema = resultsDataModelSettings$resultsDatabaseSchema, + zipFileName = zipFileName, + purgeSiteDataBeforeUploading = FALSE + ) + }, + #' @description Creates the CohortMethod Module Specifications + #' + #' @details + #' Run a list of analyses for the target-comparator-outcomes of interest. This function will run all + #' specified analyses against all hypotheses of interest, meaning that the total number of outcome + #' models is `length(cmAnalysisList) * length(targetComparatorOutcomesList)` (if all analyses specify an + #' outcome model should be fitted). When you provide several analyses it will determine whether any of + #' the analyses have anything in common, and will take advantage of this fact. For example, if we + #' specify several analyses that only differ in the way the outcome model is fitted, then this + #' function will extract the data and fit the propensity model only once, and re-use this in all the + #' analysis. + #' + #' After completion, a tibble containing references to all generated files can be obtained using the + #' [CohortMethod::getFileReference()] function. A summary of the analysis results can be obtained using the + #' [CohortMethod::getResultsSummary()] function. + #' + #' ## Analyses to Exclude + #' + #' Normally, `runCmAnalyses` will run all combinations of target-comparator-outcome-analyses settings. + #' However, sometimes we may not need all those combinations. Using the `analysesToExclude` argument, + #' we can remove certain items from the full matrix. This argument should be a data frame with at least + #' one of the following columns: + #' + #' @param cmAnalysisList A list of objects of type `cmAnalysis` as created using + #' the `[CohortMethod::createCmAnalysis] function. + #' @param targetComparatorOutcomesList A list of objects of type `targetComparatorOutcomes` as + #' created using the [CohortMethod::createTargetComparatorOutcomes] + #' function. + #' @param analysesToExclude Analyses to exclude. See the Analyses to Exclude section for details. + #' @param refitPsForEveryOutcome Should the propensity model be fitted for every outcome (i.e. + #' after people who already had the outcome are removed)? If + #' false, a single propensity model will be fitted, and people + #' who had the outcome previously will be removed afterwards. + #' @param refitPsForEveryStudyPopulation Should the propensity model be fitted for every study population + #' definition? If false, a single propensity model will be fitted, + #' and the study population criteria will be applied afterwards. + #' @param cmDiagnosticThresholds An object of type `CmDiagnosticThresholds` as created using + #' [CohortMethod::createCmDiagnosticThresholds()]. + #' + createModuleSpecifications = function(cmAnalysisList, + targetComparatorOutcomesList, + analysesToExclude = NULL, + refitPsForEveryOutcome = FALSE, + refitPsForEveryStudyPopulation = TRUE, + cmDiagnosticThresholds = CohortMethod::createCmDiagnosticThresholds()) { + analysis <- list() + for (name in names(formals(self$createModuleSpecifications))) { + analysis[[name]] <- get(name) + } + + specifications <- super$createModuleSpecifications( + moduleSpecifications = analysis + ) + return(specifications) + }, + #' @description Validate the module specifications + #' @param moduleSpecifications The CohortMethod module specifications + validateModuleSpecifications = function(moduleSpecifications) { + super$validateModuleSpecifications( + moduleSpecifications = moduleSpecifications + ) + } + ) +) diff --git a/R/Module-EvidenceSynthesis.R b/R/Module-EvidenceSynthesis.R new file mode 100644 index 00000000..e7bed3ea --- /dev/null +++ b/R/Module-EvidenceSynthesis.R @@ -0,0 +1,1014 @@ +# EvidenceSynthesisModule ------------- +#' @title Meta-analysis with the \href{https://ohdsi.github.io/EvidenceSynthesis/}{HADES EvidenceSynthesis Package} +#' @export +#' @description +#' Module for for combining causal effect estimates and study diagnostics +#' across multiple data sites in a distributed study. This includes functions +#' for performing meta-analysis and forest plots +EvidenceSynthesisModule <- R6::R6Class( + classname = "EvidenceSynthesisModule", + inherit = StrategusModule, + public = list( + #' @description Initialize the module + initialize = function() { + super$initialize() + }, + #' @description Executes the EvidenceSynthesis package + #' @template connectionDetails + #' @template analysisSpecifications + #' @template executionSettings + execute = function(connectionDetails, analysisSpecifications, executionSettings) { + super$.validateResultsExecutionSettings(executionSettings) + super$execute(connectionDetails, analysisSpecifications, executionSettings) + jobContext <- private$jobContext + + resultsFolder <- jobContext$moduleExecutionSettings$resultsSubFolder + if (!dir.exists(resultsFolder)) { + dir.create( + path = resultsFolder, + recursive = T + ) + } + private$.writeAnalysisSpecs( + analysisSpecs = jobContext$settings$evidenceSynthesisAnalysisList, + resultsFolder = resultsFolder + ) + + private$.executeEvidenceSynthesis( + connectionDetails = connectionDetails, + databaseSchema = jobContext$moduleExecutionSettings$resultsDatabaseSchema, + settings = jobContext$settings$evidenceSynthesisAnalysisList, + esDiagnosticThresholds = jobContext$settings$esDiagnosticThresholds, + resultsFolder = resultsFolder, + minCellCount = jobContext$moduleExecutionSettings$minCellCount, + maxCores = jobContext$moduleExecutionSettings$maxCores + ) + + file.copy( + from = private$.getResultsDataModelSpecificationFileLocation(), + to = file.path(jobContext$moduleExecutionSettings$resultsSubFolder, "resultsDataModelSpecification.csv") + ) + }, + #' @description Create the results data model for the module + #' @template resultsConnectionDetails + #' @template resultsDatabaseSchema + #' @template tablePrefix + createResultsDataModel = function(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix = "") { + super$createResultsDataModel(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix) + if (resultsConnectionDetails$dbms == "sqlite" & resultsDatabaseSchema != "main") { + stop("Invalid schema for sqlite, use databaseSchema = 'main'") + } + + connection <- DatabaseConnector::connect(resultsConnectionDetails) + on.exit(DatabaseConnector::disconnect(connection)) + + # Create the results model + sql <- ResultModelManager::generateSqlSchema( + csvFilepath = private$.getResultsDataModelSpecificationFileLocation() + ) + sql <- SqlRender::render(sql = sql, warnOnMissingParameters = TRUE, database_schema = resultsDatabaseSchema) + sql <- SqlRender::translate(sql = sql, targetDialect = resultsConnectionDetails$dbms) + DatabaseConnector::executeSql(connection, sql) + }, + #' @description Get the results data model specification for the module + #' @template tablePrefix + getResultsDataModelSpecification = function(tablePrefix = "") { + resultsDataModelSpecification <- CohortGenerator::readCsv( + file = private$.getResultsDataModelSpecificationFileLocation(), + warnOnCaseMismatch = FALSE + ) + + # add the prefix to the tableName column + resultsDataModelSpecification$tableName <- paste0(tablePrefix, resultsDataModelSpecification$tableName) + return(resultsDataModelSpecification) + }, + #' @description Upload the results for the module + #' @template resultsConnectionDetails + #' @template analysisSpecifications + #' @template resultsDataModelSettings + uploadResults = function(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) { + super$uploadResults(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) + jobContext <- private$jobContext + resultsFolder <- jobContext$moduleExecutionSettings$resultsSubFolder + + ResultModelManager::uploadResults( + connectionDetails = resultsConnectionDetails, + schema = resultsDataModelSettings$resultsDatabaseSchema, + resultsFolder = resultsFolder, + purgeSiteDataBeforeUploading = FALSE, # ES is not site specific + specifications = private$.getResultsDataModelSpecification() + ) + }, + #' @description Validate the module specifications + #' @param moduleSpecifications The EvidenceSynthesis module specifications + validateModuleSpecifications = function(moduleSpecifications) { + super$validateModuleSpecifications( + moduleSpecifications = moduleSpecifications + ) + }, + #' Create an evidence synthesis source + #' + #' @param sourceMethod The source method generating the estimates to synthesize. Can be "CohortMethod" or + #' "SelfControlledCaseSeries" + #' @param databaseIds The database IDs to include. Use `databaseIds = NULL` to include all database IDs. + #' @param analysisIds The source method analysis IDs to include. Use `analysisIds = NULL` to include all + #' analysis IDs. + #' @param likelihoodApproximation The type of likelihood approximation. Can be "adaptive grid" or "normal". + #' + #' @return + #' An object of type `EvidenceSynthesisSource`. + createEvidenceSynthesisSource = function(sourceMethod = "CohortMethod", + databaseIds = NULL, + analysisIds = NULL, + likelihoodApproximation = "adaptive grid") { + errorMessages <- checkmate::makeAssertCollection() + checkmate::assertChoice(sourceMethod, c("CohortMethod", "SelfControlledCaseSeries"), add = errorMessages) + if (is.character(databaseIds)) { + checkmate::assertCharacter(databaseIds, null.ok = TRUE, add = errorMessages) + } else { + checkmate::assertIntegerish(databaseIds, null.ok = TRUE, add = errorMessages) + } + checkmate::assertIntegerish(analysisIds, null.ok = TRUE, add = errorMessages) + checkmate::assertChoice(likelihoodApproximation, c("adaptive grid", "normal"), add = errorMessages) + checkmate::reportAssertions(collection = errorMessages) + + analysis <- list() + for (name in names(formals(self$createEvidenceSynthesisSource))) { + analysis[[name]] <- get(name) + } + class(analysis) <- "EvidenceSynthesisSource" + return(analysis) + }, + #' Create parameters for a random-effects meta-analysis + #' + #' @details + #' Use DerSimonian-Laird meta-analysis + #' + #' @param alpha The alpha (expected type I error) used for the confidence intervals. + #' @param evidenceSynthesisAnalysisId description + #' @param evidenceSynthesisDescription description + #' @param evidenceSynthesisSource description + #' @param controlType description + createRandomEffectsMetaAnalysis = function(alpha = 0.05, + evidenceSynthesisAnalysisId = 1, + evidenceSynthesisDescription = "Random-effects", + evidenceSynthesisSource = NULL, + controlType = "outcome") { + if (evidenceSynthesisSource$likelihoodApproximation != "normal") { + stop("Random-effects meta-analysis only supports normal approximation of the likelihood.") + } + analysis <- list() + for (name in names(formals(self$createRandomEffectsMetaAnalysis))) { + analysis[[name]] <- get(name) + } + class(analysis) <- c("RandomEffectsMetaAnalysis", "EvidenceSynthesisAnalysis") + return(analysis) + }, + #' Create a parameter object for the function computeFixedEffectMetaAnalysis + #' + #' @details + #' Create an object defining the parameter values. + #' + #' @param alpha The alpha (expected type I error) used for the confidence intervals. + #' @param evidenceSynthesisAnalysisId description + #' @param evidenceSynthesisDescription description + #' @param evidenceSynthesisSource description + #' @param controlType description + createFixedEffectsMetaAnalysis = function(alpha = 0.05, + evidenceSynthesisAnalysisId = 1, + evidenceSynthesisDescription = "Fixed-effects", + evidenceSynthesisSource = NULL, + controlType = "outcome") { + analysis <- list() + for (name in names(formals(self$createFixedEffectsMetaAnalysis))) { + analysis[[name]] <- get(name) + } + class(analysis) <- c("FixedEffectsMetaAnalysis", "EvidenceSynthesisAnalysis") + if (evidenceSynthesisSource$likelihoodApproximation != "normal") { + stop("Fixed-effects meta-analysis only supports normal approximation of the likelihood.") + } + return(analysis) + }, + #' Create a parameter object for the function computeBayesianMetaAnalysis + #' + #' @details + #' Create an object defining the parameter values. + #' + #' @param chainLength Number of MCMC iterations. + #' @param burnIn Number of MCMC iterations to consider as burn in. + #' @param subSampleFrequency Subsample frequency for the MCMC. + #' @param priorSd A two-dimensional vector with the standard deviation of the prior for mu and tau, respectively. + #' @param alpha The alpha (expected type I error) used for the credible intervals. + #' @param robust Whether or not to use a t-distribution model; default: FALSE. + #' @param df Degrees of freedom for the t-model, only used if robust is TRUE. + #' @param seed The seed for the random number generator. + #' @param evidenceSynthesisAnalysisId description + #' @param evidenceSynthesisDescription description + #' @param evidenceSynthesisSource description + #' @param controlType description + createBayesianMetaAnalysis = function(chainLength = 1100000, + burnIn = 1e+05, + subSampleFrequency = 100, + priorSd = c(2, 0.5), + alpha = 0.05, + robust = FALSE, + df = 4, + seed = 1, + evidenceSynthesisAnalysisId = 1, + evidenceSynthesisDescription = "Bayesian random-effects", + evidenceSynthesisSource = NULL, + controlType = "outcome") { + analysis <- list() + for (name in names(formals(self$createBayesianMetaAnalysis))) { + analysis[[name]] <- get(name) + } + class(analysis) <- c("BayesianMetaAnalysis", "EvidenceSynthesisAnalysis") + return(analysis) + }, + #' Create EvidenceSynthesis diagnostics thresholds + #' + #' @description + #' Threshold used to determine if we pass or fail diagnostics. + #' + #' @param mdrrThreshold What is the maximum allowed minimum detectable relative risk + #' (MDRR)? + #' @param easeThreshold What is the maximum allowed expected absolute systematic error + #' (EASE). + #' @param i2Threshold What is the maximum allowed I^2 (measure of between-database + #' heterogeneity in random-effects models)? + #' @param tauThreshold What is the maximum allowed tau (measure of between-database + #' heterogeneity in Bayesian random-effects models)? + #' + #' @return + #' An object of type `EsDiagnosticThresholds`. + createEsDiagnosticThresholds = function(mdrrThreshold = 10, + easeThreshold = 0.25, + i2Threshold = 0.4, + tauThreshold = log(2)) { + errorMessages <- checkmate::makeAssertCollection() + checkmate::assertNumeric(mdrrThreshold, len = 1, lower = 0, add = errorMessages) + checkmate::assertNumeric(easeThreshold, len = 1, lower = 0, add = errorMessages) + checkmate::assertNumeric(i2Threshold, len = 1, lower = 0, add = errorMessages) + checkmate::assertNumeric(tauThreshold, len = 1, lower = 0, add = errorMessages) + checkmate::reportAssertions(collection = errorMessages) + thresholds <- list( + mdrrThreshold = mdrrThreshold, + easeThreshold = easeThreshold, + i2Threshold = i2Threshold, + tauThreshold = tauThreshold + ) + class(thresholds) <- "EsDiagnosticThresholds" + return(thresholds) + }, + #' @description Creates the module Specifications + #' @param evidenceSynthesisAnalysisList A list of objects of type `EvidenceSynthesisAnalysis` as generated + #' by either the \href{../../Strategus/html/EvidenceSynthesisModule.html#method-createFixedEffectsMetaAnalysis}{\code{EvidenceSynthesisModule$createFixedEffectsMetaAnalysis()}} + #' or \href{../../Strategus/html/EvidenceSynthesisModule.html#method-createBayesianMetaAnalysis}{\code{EvidenceSynthesisModule$createBayesianMetaAnalysis()}} function. + #' @param esDiagnosticThresholds An object of type`EsDiagnosticThresholds` as generated by the + #' \href{../../Strategus/html/EvidenceSynthesisModule.html#method-createEsDiagnosticThresholds}{\code{EvidenceSynthesisModule$createEsDiagnosticThresholds()}} function. + createModuleSpecifications = function(evidenceSynthesisAnalysisList, + esDiagnosticThresholds = self$createEsDiagnosticThresholds()) { + errorMessages <- checkmate::makeAssertCollection() + checkmate::assertList(evidenceSynthesisAnalysisList, min.len = 1, add = errorMessages) + for (i in 1:length(evidenceSynthesisAnalysisList)) { + checkmate::assertClass(evidenceSynthesisAnalysisList[[i]], "EvidenceSynthesisAnalysis", add = errorMessages) + } + checkmate::assertClass(esDiagnosticThresholds, "EsDiagnosticThresholds", add = errorMessages) + checkmate::reportAssertions(collection = errorMessages) + + analysis <- list() + for (name in names(formals(self$createModuleSpecifications))) { + analysis[[name]] <- get(name) + } + + specifications <- super$createModuleSpecifications( + moduleSpecifications = analysis + ) + return(specifications) + } + ), + private = list( + .writeAnalysisSpecs = function(analysisSpecs, resultsFolder) { + message("Writing evidence synthesis analysis specifications") + tempFileName <- tempfile() + evidenceSynthesisAnalysis <- tibble() + for (analysisSettings in analysisSpecs) { + ParallelLogger::saveSettingsToJson(analysisSettings, tempFileName) + analysis <- tibble( + evidenceSynthesisAnalysisId = analysisSettings$evidenceSynthesisAnalysisId, + evidenceSynthesisDescription = analysisSettings$evidenceSynthesisDescription, + sourceMethod = analysisSettings$evidenceSynthesisSource$sourceMethod, + ) |> + mutate(definition = readChar(tempFileName, file.info(tempFileName)$size)) + evidenceSynthesisAnalysis <- bind_rows(evidenceSynthesisAnalysis, analysis) + } + unlink(tempFileName) + fileName <- file.path(resultsFolder, "es_analysis.csv") + CohortGenerator::writeCsv(evidenceSynthesisAnalysis, fileName) + }, + .ensureEmptyAndExists = function(outputTable, resultsFolder) { + diagnostics <- private$.createEmptyResult(outputTable) + fileName <- file.path(resultsFolder, paste0(outputTable, ".csv")) + private$.writeToCsv(data = diagnostics, fileName = fileName, append = FALSE) + }, + .executeEvidenceSynthesis = function(connectionDetails, databaseSchema, settings, esDiagnosticThresholds, resultsFolder, minCellCount, maxCores) { + connection <- DatabaseConnector::connect(connectionDetails) + on.exit(DatabaseConnector::disconnect(connection)) + + outputTables <- c( + "es_cm_result", + "es_cm_diagnostics_summary", + "es_sccs_result", + "es_sccs_diagnostics_summary" + ) + invisible(lapply(outputTables, function(x) { + private$.ensureEmptyAndExists(x, resultsFolder) + })) + + message("Performing evidence synthesis across databases") + invisible(lapply( + X = settings, + FUN = private$.doAnalysis, + connection = connection, + databaseSchema = databaseSchema, + resultsFolder = resultsFolder, + minCellCount = minCellCount, + esDiagnosticThresholds = esDiagnosticThresholds, + maxCores = maxCores + )) + }, + # analysisSettings = settings[[4]] + .doAnalysis = function(analysisSettings, connection, databaseSchema, resultsFolder, minCellCount, esDiagnosticThresholds, maxCores) { + perDbEstimates <- private$.getPerDatabaseEstimates( + connection = connection, + databaseSchema = databaseSchema, + evidenceSynthesisSource = analysisSettings$evidenceSynthesisSource + ) + if (nrow(perDbEstimates$estimates) == 0) { + message <- sprintf( + "No unblinded estimates found for source method '%s'", + analysisSettings$evidenceSynthesisSource$sourceMethod + ) + if (!is.null(analysisSettings$evidenceSynthesisSource$databaseIds)) { + message <- sprintf( + "%s restricting to database IDs %s", + message, + paste(analysisSettings$evidenceSynthesisSource$databaseIds, collapse = ", ") + ) + } + if (!is.null(analysisSettings$evidenceSynthesisSource$analysisIds)) { + message <- sprintf( + "%s restricting to analysis IDs %s", + message, + paste(analysisSettings$evidenceSynthesisSource$analysisIds, collapse = ", ") + ) + } + warning(message) + return() + } + + fullKeys <- perDbEstimates$estimates[, c(perDbEstimates$key, "analysisId")] |> + distinct() + + cluster <- ParallelLogger::makeCluster(min(10, maxCores)) + ParallelLogger::clusterRequire(cluster, "dplyr") + on.exit(ParallelLogger::stopCluster(cluster)) + + message(sprintf("Performing analysis %s (%s)", analysisSettings$evidenceSynthesisAnalysisId, analysisSettings$evidenceSynthesisDescription)) + estimates <- ParallelLogger::clusterApply( + cluster = cluster, + x = split(fullKeys, seq_len(nrow(fullKeys))), + fun = private$.doSingleEvidenceSynthesis, + perDbEstimates = perDbEstimates, + analysisSettings = analysisSettings, + minCellCount = minCellCount + ) + estimates <- bind_rows(estimates) + + message("- Calibrating estimates") + estimates <- estimates |> + inner_join(perDbEstimates$trueEffectSizes, by = intersect(names(estimates), names(perDbEstimates$trueEffectSizes))) + if (analysisSettings$controlType == "outcome") { + if (analysisSettings$evidenceSynthesisSource$sourceMethod == "CohortMethod") { + controlKey <- c("targetId", "comparatorId", "analysisId") + } else if (analysisSettings$evidenceSynthesisSource$sourceMethod == "SelfControlledCaseSeries") { + controlKey <- c("exposureId", "nestingCohortId", "covariateId", "analysisId") + } + } else if (analysisSettings$controlType == "exposure") { + if (analysisSettings$evidenceSynthesisSource$sourceMethod == "CohortMethod") { + controlKey <- c("outcomeId", "analysisId") + } else if (analysisSettings$evidenceSynthesisSource$sourceMethod == "SelfControlledCaseSeries") { + controlKey <- c("outcomeId", "analysisId") + } + } else { + stop(sprintf("Unknown control type '%s'", analysisSettings$controlType)) + } + groupKeys <- estimates[, controlKey] + groupKeys <- apply(groupKeys, 1, paste, collapse = "_") + + estimates <- ParallelLogger::clusterApply( + cluster = cluster, + x = split(estimates, groupKeys), + fun = private$.calibrateEstimates + ) + estimates <- bind_rows(estimates) |> + mutate(evidenceSynthesisAnalysisId = analysisSettings$evidenceSynthesisAnalysisId) + + # Save diagnostics + diagnostics <- estimates[, c(perDbEstimates$key, "analysisId", "evidenceSynthesisAnalysisId", "mdrr", "ease", "i2", "tau")] |> + mutate(mdrrDiagnostic = case_when( + is.na(.data$mdrr) ~ "NOT EVALUATED", + .data$mdrr < esDiagnosticThresholds$mdrrThreshold ~ "PASS", + TRUE ~ "FAIL" + )) |> + mutate(easeDiagnostic = case_when( + is.na(.data$ease) ~ "NOT EVALUATED", + abs(.data$ease) < esDiagnosticThresholds$easeThreshold ~ "PASS", + TRUE ~ "FAIL" + )) |> + mutate(i2Diagnostic = case_when( + is.na(.data$i2) ~ "NOT EVALUATED", + abs(.data$i2) < esDiagnosticThresholds$i2Threshold ~ "PASS", + TRUE ~ "FAIL" + )) |> + mutate(tauDiagnostic = case_when( + is.na(.data$tau) ~ "NOT EVALUATED", + abs(.data$tau) < esDiagnosticThresholds$tauThreshold ~ "PASS", + TRUE ~ "FAIL" + )) |> + mutate(unblind = ifelse(.data$mdrrDiagnostic != "FAIL" & + .data$easeDiagnostic != "FAIL" & + .data$i2Diagnostic != "FAIL" & + .data$tauDiagnostic != "FAIL", 1, 0)) + if (analysisSettings$evidenceSynthesisSource$sourceMethod == "CohortMethod") { + fileName <- file.path(resultsFolder, "es_cm_diagnostics_summary.csv") + } else if (analysisSettings$evidenceSynthesisSource$sourceMethod == "SelfControlledCaseSeries") { + fileName <- file.path(resultsFolder, "es_sccs_diagnostics_summary.csv") + } else { + stop(sprintf("Saving diagnostics summary not implemented for source method '%s'", analysisSettings$evidenceSynthesisSource$sourceMethod)) + } + private$.writeToCsv(data = diagnostics, fileName = fileName, append = TRUE) + + # Save estimates + estimates <- estimates |> + select(-"trueEffectSize", -"ease", -"i2", -"tau", -"mdrr") + if (analysisSettings$evidenceSynthesisSource$sourceMethod == "CohortMethod") { + estimates <- estimates |> + select(-"outcomeOfInterest") + fileName <- file.path(resultsFolder, "es_cm_result.csv") + } else if (analysisSettings$evidenceSynthesisSource$sourceMethod == "SelfControlledCaseSeries") { + fileName <- file.path(resultsFolder, "es_sccs_result.csv") + } else { + stop(sprintf("Saving results not implemented for source method '%s'", analysisSettings$evidenceSynthesisSource$sourceMethod)) + } + private$.writeToCsv(data = estimates, fileName = fileName, append = TRUE) + }, + # group = split(estimates, groupKeys)[[1]] + .calibrateEstimates = function(group) { + ncs <- group[!is.na(group$trueEffectSize) & group$trueEffectSize == 1 & !is.na(group$seLogRr), ] + pcs <- group[!is.na(group$trueEffectSize) & group$trueEffectSize != 1 & !is.na(group$seLogRr), ] + if (nrow(ncs) >= 5) { + null <- EmpiricalCalibration::fitMcmcNull(logRr = ncs$logRr, seLogRr = ncs$seLogRr) + ease <- EmpiricalCalibration::computeExpectedAbsoluteSystematicError(null) + calibratedP <- EmpiricalCalibration::calibrateP( + null = null, + logRr = group$logRr, + seLogRr = group$seLogRr, + twoSided = TRUE + ) + calibratedOneSidedP <- EmpiricalCalibration::calibrateP( + null = null, + logRr = group$logRr, + seLogRr = group$seLogRr, + twoSided = FALSE, + upper = TRUE + ) + if (nrow(pcs) >= 5) { + model <- EmpiricalCalibration::fitSystematicErrorModel( + logRr = c(ncs$logRr, pcs$logRr), + seLogRr = c(ncs$seLogRr, pcs$seLogRr), + trueLogRr = log(c(ncs$trueEffectSize, pcs$trueEffectSize)), + estimateCovarianceMatrix = FALSE + ) + } else { + model <- EmpiricalCalibration::convertNullToErrorModel(null) + } + calibratedCi <- EmpiricalCalibration::calibrateConfidenceInterval(model = model, logRr = group$logRr, seLogRr = group$seLogRr) + group$calibratedRr <- exp(calibratedCi$logRr) + group$calibratedCi95Lb <- exp(calibratedCi$logLb95Rr) + group$calibratedCi95Ub <- exp(calibratedCi$logUb95Rr) + group$calibratedP <- calibratedP$p + group$calibratedOneSidedP <- calibratedOneSidedP$p + group$calibratedLogRr <- calibratedCi$logRr + group$calibratedSeLogRr <- calibratedCi$seLogRr + group$ease <- ease$ease + } else { + group$calibratedRr <- NA + group$calibratedCi95Lb <- NA + group$calibratedCi95Ub <- NA + group$calibratedP <- NA + group$calibratedOneSidedP <- NA + group$calibratedLogRr <- NA + group$calibratedSeLogRr <- NA + group$ease <- NA + } + return(group) + }, + # row <- split(fullKeys, seq_len(nrow(fullKeys)))[[2]] + # row <- tibble(targetId = 8413, comparatorId = 8436, outcomeId = 1078, analysisId = 2) + .doSingleEvidenceSynthesis = function(row, perDbEstimates, analysisSettings, minCellCount) { + sumMinCellCount <- function(counts, minCellCount) { + if (length(counts) == 0) { + return(NA) + } + hasNegative <- any(counts < 0) + sumCount <- sum(abs(counts)) + if (sumCount == 0) { + return(sumCount) + } + if (hasNegative) { + if (sumCount < minCellCount) { + sumCount <- -minCellCount + } else { + sumCount <- -sumCount + } + } else { + if (sumCount < minCellCount) { + sumCount <- -minCellCount + } + } + return(sumCount) + } + computeMdrrFromSe <- function(seLogRr, alpha = 0.05, power = 0.8) { + # Based on the computation of a two-sided p-value, power can be computed as + # power = 1-pnorm(qnorm(1 - alpha/2) - (log(mdrr) / seLogRr))/2 + # That can be translated in into: + mdrr <- exp((qnorm(1 - alpha / 2) - qnorm(2 * (1 - power))) * seLogRr) + return(mdrr) + } + + subset <- perDbEstimates$estimates |> + inner_join(row, by = c(perDbEstimates$key, "analysisId")) + llApproximations <- perDbEstimates$llApproximations |> + inner_join(row, by = c(perDbEstimates$key, "analysisId")) + if (analysisSettings$evidenceSynthesisSource$likelihoodApproximation == "normal") { + llApproximations <- llApproximations |> + filter(!is.na(.data$logRr) & !is.na(.data$seLogRr)) + includedDbs <- llApproximations$databaseId + } else if (analysisSettings$evidenceSynthesisSource$likelihoodApproximation == "adaptive grid") { + includedDbs <- unique(llApproximations$databaseId) + llApproximations <- llApproximations |> + select( + point = .data$logRr, + value = .data$logLikelihood, + .data$databaseId + ) |> + group_by(.data$databaseId) |> + group_split() + } + nDatabases <- length(includedDbs) + subset <- subset |> + filter(.data$databaseId %in% includedDbs) + if (analysisSettings$evidenceSynthesisSource$sourceMethod == "CohortMethod") { + counts <- tibble( + targetSubjects = sumMinCellCount(subset$targetSubjects, minCellCount), + comparatorSubjects = sumMinCellCount(subset$comparatorSubjects, minCellCount), + targetDays = sumMinCellCount(subset$targetDays, 0), + comparatorDays = sumMinCellCount(subset$comparatorDays, 0), + targetOutcomes = sumMinCellCount(subset$targetOutcomes, minCellCount), + comparatorOutcomes = sumMinCellCount(subset$comparatorOutcomes, minCellCount), + ) + } else if (analysisSettings$evidenceSynthesisSource$sourceMethod == "SelfControlledCaseSeries") { + counts <- tibble( + outcomeSubjects = sumMinCellCount(subset$outcomeSubjects, minCellCount), + outcomeEvents = sumMinCellCount(subset$outcomeEvents, minCellCount), + outcomeObservationPeriods = sumMinCellCount(subset$outcomeObservationPeriods, 0), + observedDays = sumMinCellCount(subset$observedDays, 0), + covariateSubjects = sumMinCellCount(subset$covariateSubjects, minCellCount), + covariateDays = sumMinCellCount(subset$covariateDays, minCellCount), + covariateEras = sumMinCellCount(subset$covariateEras, minCellCount), + covariateOutcomes = sumMinCellCount(subset$covariateOutcomes, minCellCount) + ) + } else { + stop(sprintf("Aggregating counts not implemented for source method '%s'", analysisSettings$evidenceSynthesisSource$sourceMethod)) + } + + if (nDatabases == 0) { + estimate <- tibble( + rr = as.numeric(NA), + ci95Lb = as.numeric(NA), + ci95Ub = as.numeric(NA), + p = as.numeric(NA), + oneSidedP = as.numeric(NA), + logRr = as.numeric(NA), + seLogRr = as.numeric(NA), + i2 = as.numeric(NA), + tau = as.numeric(NA), + mdrr = as.numeric(Inf) + ) + } else if (nDatabases == 1) { + estimate <- tibble( + rr = exp(subset$logRr), + ci95Lb = subset$ci95Lb, + ci95Ub = subset$ci95Ub, + p = subset$p, + oneSidedP = if ("oneSidedP" %in% colnames(subset)) subset$oneSidedP else NA, + logRr = subset$logRr, + seLogRr = subset$seLogRr, + i2 = NA, + tau = NA, + mdrr = subset$mdrr + ) + } else { + if (is(analysisSettings, "FixedEffectsMetaAnalysis")) { + args <- analysisSettings + args$evidenceSynthesisAnalysisId <- NULL + args$evidenceSynthesisDescription <- NULL + args$evidenceSynthesisSource <- NULL + args$controlType <- NULL + args$data <- as.data.frame(llApproximations) + estimate <- do.call(EvidenceSynthesis::computeFixedEffectMetaAnalysis, args) + p <- EmpiricalCalibration::computeTraditionalP( + logRr = estimate$logRr, + seLogRr = estimate$seLogRr, + twoSided = TRUE + ) + oneSidedP <- EmpiricalCalibration::computeTraditionalP( + logRr = estimate$logRr, + seLogRr = estimate$seLogRr, + twoSided = FALSE, + upper = TRUE + ) + estimate <- estimate |> + as_tibble() |> + rename( + ci95Lb = lb, + ci95Ub = ub + ) |> + mutate( + i2 = NA, + tau = NA, + mdrr = computeMdrrFromSe(estimate$seLogRr), + p = !!p, + oneSidedP = !!oneSidedP + ) + } else if (is(analysisSettings, "RandomEffectsMetaAnalysis")) { + m <- meta::metagen( + TE = llApproximations$logRr, + seTE = llApproximations$seLogRr, + studlab = rep("", nrow(llApproximations)), + byvar = NULL, + control = list(maxiter = 1000), + sm = "RR", + level.comb = 1 - analysisSettings$alpha + ) + rfx <- summary(m)$random + oneSidedP <- EmpiricalCalibration::computeTraditionalP( + logRr = rfx$TE, + seLogRr = rfx$seTE, + twoSided = FALSE, + upper = TRUE + ) + estimate <- tibble( + rr = exp(rfx$TE), + ci95Lb = exp(rfx$lower), + ci95Ub = exp(rfx$upper), + p = rfx$p, + oneSidedP = !!oneSidedP, + logRr = rfx$TE, + seLogRr = rfx$seTE, + i2 = m$I2, + tau = NA, + mdrr = computeMdrrFromSe(rfx$seTE) + ) + } else if (is(analysisSettings, "BayesianMetaAnalysis")) { + args <- analysisSettings + args$evidenceSynthesisAnalysisId <- NULL + args$evidenceSynthesisDescription <- NULL + args$evidenceSynthesisSource <- NULL + args$controlType <- NULL + args$data <- llApproximations + estimate <- do.call(EvidenceSynthesis::computeBayesianMetaAnalysis, args) + p <- EmpiricalCalibration::computeTraditionalP( + logRr = estimate$logRr, + seLogRr = estimate$seLogRr, + twoSided = TRUE + ) + oneSidedP <- EmpiricalCalibration::computeTraditionalP( + logRr = estimate$logRr, + seLogRr = estimate$seLogRr, + twoSided = FALSE, + upper = TRUE + ) + estimate <- estimate |> + as_tibble() |> + transmute( + rr = exp(.data$mu), + ci95Lb = exp(.data$mu95Lb), + ci95Ub = exp(.data$mu95Ub), + p = !!p, + oneSidedP = !!oneSidedP, + logRr = .data$mu, + seLogRr = .data$muSe, + tau = .data$tau, + i2 = NA, + mdrr = computeMdrrFromSe(estimate$seLogRr) + ) + } + } + estimate <- bind_cols(row, estimate, counts) |> + mutate(nDatabases = nDatabases) + return(estimate) + }, + .hasUnblindForEvidenceSynthesisColumn = function(connection, databaseSchema, table) { + row <- DatabaseConnector::renderTranslateQuerySql( + connection = connection, + sql = "SELECT TOP 1 * FROM @database_schema.@table;", + database_schema = databaseSchema, + table = table, + snakeCaseToCamelCase = TRUE + ) + return("unlindForEvidenceSynthesis" %in% colnames(row)) + }, + .getPerDatabaseEstimates = function(connection, databaseSchema, evidenceSynthesisSource) { + if (evidenceSynthesisSource$sourceMethod == "CohortMethod") { + key <- c("targetId", "comparatorId", "outcomeId") + databaseIds <- evidenceSynthesisSource$databaseIds + analysisIds <- evidenceSynthesisSource$analysisIds + if (private$.hasUnblindForEvidenceSynthesisColumn(connection, databaseSchema, "cm_diagnostics_summary")) { + unblindColumn <- "unblind_for_evidence_synthesis" + } else { + unblindColumn <- "unblind" + } + # For backwards compatibility, when CohortMethod did not generate diagnostics + # for negative controls: if negative control (outcome_of_interest = 0) then + # still unblind. + sql <- "SELECT cm_result.*, + mdrr, + CASE + WHEN @unblind_column IS NULL THEN 1 - outcome_of_interest + ELSE @unblind_column + END AS unblind + FROM @database_schema.cm_result + INNER JOIN @database_schema.cm_target_comparator_outcome + ON cm_result.target_id = cm_target_comparator_outcome.target_id + AND cm_result.comparator_id = cm_target_comparator_outcome.comparator_id + AND cm_result.outcome_id = cm_target_comparator_outcome.outcome_id + LEFT JOIN @database_schema.cm_diagnostics_summary + ON cm_result.target_id = cm_diagnostics_summary.target_id + AND cm_result.comparator_id = cm_diagnostics_summary.comparator_id + AND cm_result.outcome_id = cm_diagnostics_summary.outcome_id + AND cm_result.analysis_id = cm_diagnostics_summary.analysis_id + AND cm_result.database_id = cm_diagnostics_summary.database_id + {@database_ids != ''| @analysis_ids != ''} ? {WHERE} + {@database_ids != ''} ? { cm_result.database_id IN (@database_ids)} + {@analysis_ids != ''} ? { {@database_ids != ''} ? {AND} cm_result.analysis_id IN (@analysis_ids)}; + " + estimates <- DatabaseConnector::renderTranslateQuerySql( + connection = connection, + sql = sql, + database_schema = databaseSchema, + unblind_column = unblindColumn, + database_ids = if (is.null(databaseIds)) "" else private$.quoteSql(databaseIds), + analysis_ids = if (is.null(analysisIds)) "" else analysisIds, + snakeCaseToCamelCase = TRUE + ) |> + as_tibble() + + # Temp hack: detect NA values that have been converted to 0 in the DB: + idx <- estimates$seLogRr == 0 + estimates$logRr[idx] <- NA + estimates$seLogRr[idx] <- NA + estimates$p[idx] <- NA + + if (evidenceSynthesisSource$likelihoodApproximation == "normal") { + llApproximations <- estimates |> + filter(.data$unblind == 1) |> + select( + "targetId", + "comparatorId", + "outcomeId", + "analysisId", + "databaseId", + "logRr", + "seLogRr" + ) + } else if (evidenceSynthesisSource$likelihoodApproximation == "adaptive grid") { + sql <- "SELECT cm_likelihood_profile.* + FROM @database_schema.cm_likelihood_profile + WHERE log_likelihood IS NOT NULL + {@database_ids != ''} ? { AND cm_likelihood_profile.database_id IN (@database_ids)} + {@analysis_ids != ''} ? { AND cm_likelihood_profile.analysis_id IN (@analysis_ids)}; + " + llApproximations <- DatabaseConnector::renderTranslateQuerySql( + connection = connection, + sql = sql, + database_schema = databaseSchema, + database_ids = if (is.null(databaseIds)) "" else private$.quoteSql(databaseIds), + analysis_ids = if (is.null(analysisIds)) "" else analysisIds, + snakeCaseToCamelCase = TRUE + ) |> + inner_join( + estimates |> + filter(.data$unblind == 1) |> + select( + "targetId", + "comparatorId", + "outcomeId", + "analysisId", + "databaseId", + ), + by = c("targetId", "comparatorId", "outcomeId", "analysisId", "databaseId") + ) + } else { + stop(sprintf("Unknown likelihood approximation '%s'.", evidenceSynthesisSource$likelihoodApproximation)) + } + sql <- "SELECT * + FROM @database_schema.cm_target_comparator_outcome; + " + trueEffectSizes <- DatabaseConnector::renderTranslateQuerySql( + connection = connection, + sql = sql, + database_schema = databaseSchema, + snakeCaseToCamelCase = TRUE + ) + trueEffectSizes <- trueEffectSizes |> + mutate(trueEffectSize = ifelse(!is.na(.data$trueEffectSize) & .data$trueEffectSize == 0, + NA, + .data$trueEffectSize + )) + } else if (evidenceSynthesisSource$sourceMethod == "SelfControlledCaseSeries") { + key <- c("exposureId", "nestingCohortId", "outcomeId", "exposuresOutcomeSetId", "covariateId") + databaseIds <- evidenceSynthesisSource$databaseIds + analysisIds <- evidenceSynthesisSource$analysisIds + if (private$.hasUnblindForEvidenceSynthesisColumn(connection, databaseSchema, "sccs_diagnostics_summary")) { + unblindColumn <- "unblind_for_evidence_synthesis" + } else { + unblindColumn <- "unblind" + } + sql <- "SELECT sccs_result.*, + sccs_covariate.era_id AS exposure_id, + outcome_id, + nesting_cohort_id, + mdrr, + CASE + WHEN @unblind_column IS NULL THEN CASE WHEN true_effect_size IS NULL THEN 0 ELSE 1 END + ELSE @unblind_column + END AS unblind + FROM @database_schema.sccs_result + INNER JOIN @database_schema.sccs_exposures_outcome_set + ON sccs_result.exposures_outcome_set_id = sccs_exposures_outcome_set.exposures_outcome_set_id + INNER JOIN @database_schema.sccs_covariate + ON sccs_result.database_id = sccs_covariate.database_id + AND sccs_result.exposures_outcome_set_id = sccs_covariate.exposures_outcome_set_id + AND sccs_result.covariate_id = sccs_covariate.covariate_id + AND sccs_result.analysis_id = sccs_covariate.analysis_id + INNER JOIN @database_schema.sccs_exposure + ON sccs_result.exposures_outcome_set_id = sccs_exposure.exposures_outcome_set_id + AND sccs_covariate.era_id = sccs_exposure.era_id + LEFT JOIN @database_schema.sccs_diagnostics_summary + ON sccs_result.exposures_outcome_set_id = sccs_diagnostics_summary.exposures_outcome_set_id + AND sccs_result.covariate_id = sccs_diagnostics_summary.covariate_id + AND sccs_result.analysis_id = sccs_diagnostics_summary.analysis_id + AND sccs_result.database_id = sccs_diagnostics_summary.database_id + {@database_ids != ''| @analysis_ids != ''} ? {WHERE} + {@database_ids != ''} ? { sccs_result.database_id IN (@database_ids)} + {@analysis_ids != ''} ? { {@database_ids != ''} ? {AND} sccs_result.analysis_id IN (@analysis_ids)}; + " + estimates <- DatabaseConnector::renderTranslateQuerySql( + connection = connection, + sql = sql, + database_schema = databaseSchema, + unblind_column = unblindColumn, + database_ids = if (is.null(databaseIds)) "" else private$.quoteSql(databaseIds), + analysis_ids = if (is.null(analysisIds)) "" else analysisIds, + snakeCaseToCamelCase = TRUE + ) |> + as_tibble() + + # Temp hack: detect NA values that have been converted to 0 in the DB: + idx <- estimates$seLogRr == 0 + estimates$logRr[idx] <- NA + estimates$seLogRr[idx] <- NA + estimates$p[idx] <- NA + + if (evidenceSynthesisSource$likelihoodApproximation == "normal") { + llApproximations <- estimates |> + filter(.data$unblind == 1) |> + select( + "exposuresOutcomeSetId", + "exposureId", + "nestingCohortId", + "outcomeId", + "covariateId", + "analysisId", + "databaseId", + "logRr", + "seLogRr" + ) + } else if (evidenceSynthesisSource$likelihoodApproximation == "adaptive grid") { + sql <- "SELECT sccs_likelihood_profile.* + FROM @database_schema.sccs_likelihood_profile + WHERE log_likelihood IS NOT NULL + {@database_ids != ''} ? { AND sccs_likelihood_profile.database_id IN (@database_ids)} + {@analysis_ids != ''} ? { AND sccs_likelihood_profile.analysis_id IN (@analysis_ids)}; + " + llApproximations <- DatabaseConnector::renderTranslateQuerySql( + connection = connection, + sql = sql, + database_schema = databaseSchema, + database_ids = if (is.null(databaseIds)) "" else private$.quoteSql(databaseIds), + analysis_ids = if (is.null(analysisIds)) "" else analysisIds, + snakeCaseToCamelCase = TRUE + ) |> + inner_join( + estimates |> + filter(.data$unblind == 1) |> + select( + "exposuresOutcomeSetId", + "exposureId", + "nestingCohortId", + "outcomeId", + "covariateId", + "analysisId", + "databaseId", + ), + by = c("exposuresOutcomeSetId", "covariateId", "analysisId", "databaseId") + ) + } else { + stop(sprintf("Unknown likelihood approximation '%s'.", evidenceSynthesisSource$likelihoodApproximation)) + } + sql <- "SELECT DISTINCT sccs_exposure.exposures_outcome_set_id, + sccs_covariate.analysis_id, + sccs_covariate.era_id AS exposure_id, + nesting_cohort_id, + outcome_id, + sccs_covariate.covariate_id, + true_effect_size + FROM @database_schema.sccs_exposure + INNER JOIN @database_schema.sccs_exposures_outcome_set + ON sccs_exposure.exposures_outcome_set_id = sccs_exposures_outcome_set.exposures_outcome_set_id + INNER JOIN @database_schema.sccs_covariate + ON sccs_exposure.era_id = sccs_covariate.era_id + AND sccs_exposure.exposures_outcome_set_id = sccs_covariate.exposures_outcome_set_id + INNER JOIN @database_schema.sccs_covariate_analysis + ON sccs_covariate.analysis_id = sccs_covariate_analysis.analysis_id + AND sccs_covariate.covariate_analysis_id = sccs_covariate_analysis.covariate_analysis_id + WHERE sccs_covariate_analysis.variable_of_interest = 1; + " + trueEffectSizes <- DatabaseConnector::renderTranslateQuerySql( + connection = connection, + sql = sql, + database_schema = databaseSchema, + snakeCaseToCamelCase = TRUE + ) + trueEffectSizes <- trueEffectSizes |> + mutate(trueEffectSize = ifelse(!is.na(.data$trueEffectSize) & .data$trueEffectSize == 0, + NA, + .data$trueEffectSize + )) + } else { + stop(sprintf("Evidence synthesis for source method '%s' hasn't been implemented yet.", evidenceSynthesisSource$sourceMethod)) + } + return(list( + key = key, + estimates = estimates, + llApproximations = llApproximations, + trueEffectSizes = trueEffectSizes + )) + }, + .writeToCsv = function(data, fileName, append) { + tableName <- gsub(".csv$", "", basename(fileName)) + names <- colnames(private$.createEmptyResult(tableName)) + data <- data[, names] + data <- SqlRender::camelCaseToSnakeCaseNames(data) + readr::write_csv(data, fileName, append = append) + }, + .createEmptyResult = function(tableName = "") { + columns <- private$.getResultsDataModelSpecification() |> + filter(.data$tableName == !!tableName) |> + pull(.data$columnName) |> + SqlRender::snakeCaseToCamelCase() + result <- vector(length = length(columns)) + names(result) <- columns + result <- as_tibble(t(result), name_repair = "check_unique") + result <- result[FALSE, ] + return(result) + }, + .quoteSql = function(values) { + return(paste0("'", paste(values, collapse = "', '"), "'")) + }, + .getResultsDataModelSpecification = function() { + rdms <- CohortGenerator::readCsv( + file = private$.getResultsDataModelSpecificationFileLocation() + ) + return(rdms) + }, + .getResultsDataModelSpecificationFileLocation = function() { + return(system.file( + file.path("csv", "evidenceSynthesisRdms.csv"), + package = "Strategus" + )) + } + ) +) diff --git a/R/Module-PatientLevelPrediction.R b/R/Module-PatientLevelPrediction.R new file mode 100644 index 00000000..a97856b0 --- /dev/null +++ b/R/Module-PatientLevelPrediction.R @@ -0,0 +1,195 @@ +# PatientLevelPredictionModule ------------- +#' @title Patient-level prediction with the \href{https://ohdsi.github.io/PatientLevelPrediction/}{HADES PatientLevelPrediction Package} +#' @export +#' @description +#' Module for performing patient-level prediction in an observational +#' database in the OMOP Common Data Model. +PatientLevelPredictionModule <- R6::R6Class( + classname = "PatientLevelPredictionModule", + inherit = StrategusModule, + public = list( + #' @field tablePrefix The table prefix to append to the results tables + tablePrefix = "plp_", + #' @description Initialize the module + initialize = function() { + super$initialize() + }, + #' @description Executes the PatientLevelPrediction package + #' @template connectionDetails + #' @template analysisSpecifications + #' @template executionSettings + execute = function(connectionDetails, analysisSpecifications, executionSettings) { + super$.validateCdmExecutionSettings(executionSettings) + super$execute(connectionDetails, analysisSpecifications, executionSettings) + + jobContext <- private$jobContext + cohortDefinitionSet <- super$.createCohortDefinitionSetFromJobContext() + workFolder <- jobContext$moduleExecutionSettings$workSubFolder + resultsFolder <- jobContext$moduleExecutionSettings$resultsSubFolder + + # Creating database details + databaseDetails <- PatientLevelPrediction::createDatabaseDetails( + connectionDetails = connectionDetails, + cdmDatabaseSchema = jobContext$moduleExecutionSettings$cdmDatabaseSchema, + cohortDatabaseSchema = jobContext$moduleExecutionSettings$workDatabaseSchema, + cdmDatabaseName = jobContext$moduleExecutionSettings$connectionDetailsReference, + cdmDatabaseId = jobContext$moduleExecutionSettings$cdmDatabaseMetaData$databaseId, + tempEmulationSchema = jobContext$moduleExecutionSettings$tempEmulationSchema, + cohortTable = jobContext$moduleExecutionSettings$cohortTableNames$cohortTable, + outcomeDatabaseSchema = jobContext$moduleExecutionSettings$workDatabaseSchema, + outcomeTable = jobContext$moduleExecutionSettings$cohortTableNames$cohortTable + ) + + jobContext$settings <- private$.setCovariateSchemaTable( + modelDesignList = jobContext$settings$modelDesignList, + cohortDatabaseSchema = jobContext$moduleExecutionSettings$workDatabaseSchema, + cohortTable = jobContext$moduleExecutionSettings$cohortTableNames$cohortTable + ) + + # run the models + PatientLevelPrediction::runMultiplePlp( + databaseDetails = databaseDetails, + modelDesignList = jobContext$settings, + cohortDefinitions = cohortDefinitionSet, + saveDirectory = workFolder + ) + + private$.message("Export data to csv files") + + sqliteConnectionDetails <- DatabaseConnector::createConnectionDetails( + dbms = "sqlite", + server = file.path(workFolder, "sqlite", "databaseFile.sqlite") + ) + + PatientLevelPrediction::extractDatabaseToCsv( + connectionDetails = sqliteConnectionDetails, + databaseSchemaSettings = PatientLevelPrediction::createDatabaseSchemaSettings( + resultSchema = "main", # sqlite settings + tablePrefix = "", # sqlite settings + targetDialect = "sqlite", + tempEmulationSchema = NULL + ), + csvFolder = file.path(resultsFolder), + fileAppend = NULL + ) + + resultsDataModel <- self$getResultsDataModelSpecification() + CohortGenerator::writeCsv( + x = resultsDataModel, + file = file.path(resultsFolder, "resultsDataModelSpecification.csv"), + warnOnFileNameCaseMismatch = F + ) + + private$.message(paste("Results available at:", resultsFolder)) + }, + #' @description Create the results data model for the module + #' @template resultsConnectionDetails + #' @template resultsDatabaseSchema + #' @template tablePrefix + createResultsDataModel = function(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix = self$tablePrefix) { + super$createResultsDataModel(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix) + PatientLevelPrediction::createPlpResultTables( + connectionDetails = resultsConnectionDetails, + targetDialect = resultsConnectionDetails$dbms, + resultSchema = resultsDatabaseSchema, + deleteTables = F, + createTables = T, + tablePrefix = tablePrefix + ) + }, + #' @description Get the results data model specification for the module + #' @template tablePrefix + getResultsDataModelSpecification = function(tablePrefix = "") { + resultsDataModelSpecification <- CohortGenerator::readCsv( + file = private$.getResultsDataModelSpecificationFileLocation() + ) + + # add the prefix to the tableName column + resultsDataModelSpecification$tableName <- paste0(tablePrefix, self$tablePrefix, resultsDataModelSpecification$tableName) + return(resultsDataModelSpecification) + }, + #' @description Upload the results for the module + #' @template resultsConnectionDetails + #' @template analysisSpecifications + #' @template resultsDataModelSettings + uploadResults = function(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) { + super$uploadResults(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) + + databaseSchemaSettings <- PatientLevelPrediction::createDatabaseSchemaSettings( + resultSchema = resultsDataModelSettings$resultsDatabaseSchema, + tablePrefix = self$tablePrefix, + targetDialect = resultsConnectionDetails$dbms + ) + + resultsFolder <- private$jobContext$moduleExecutionSettings$resultsSubFolder + # TODO: This function does not expose + # a way to specify the database identifier file + # which makes the purge problematic since I'm + # not sure how it will know what to purge... + PatientLevelPrediction::insertCsvToDatabase( + csvFolder = resultsFolder, + connectionDetails = resultsConnectionDetails, + databaseSchemaSettings = databaseSchemaSettings, + modelSaveLocation = file.path(resultsFolder, "dbmodels"), + csvTableAppend = "" + ) + }, + #' @description Creates the PatientLevelPrediction Module Specifications + #' @param modelDesignList A list of model designs created using \code{PatientLevelPrediction::createModelDesign()} + createModuleSpecifications = function(modelDesignList) { + analysis <- list() + for (name in names(formals(self$createModuleSpecifications))) { + analysis[[name]] <- get(name) + } + + specifications <- super$createModuleSpecifications( + moduleSpecifications = analysis + ) + return(specifications) + }, + #' @description Validate the module specifications + #' @param moduleSpecifications The PatientLevelPrediction module specifications + validateModuleSpecifications = function(moduleSpecifications) { + super$validateModuleSpecifications( + moduleSpecifications = moduleSpecifications + ) + } + ), + private = list( + .setCovariateSchemaTable = function( + modelDesignList, + cohortDatabaseSchema, + cohortTable) { + if (inherits(modelDesignList, "modelDesign")) { + modelDesignList <- list(modelDesignList) + } + + for (i in 1:length(modelDesignList)) { + covariateSettings <- modelDesignList[[i]]$covariateSettings + + if (inherits(covariateSettings, "covariateSettings")) { + covariateSettings <- list(covariateSettings) + } + + for (j in 1:length(covariateSettings)) { + if ("cohortDatabaseSchema" %in% names(covariateSettings[[j]])) { + covariateSettings[[j]]$cohortDatabaseSchema <- cohortDatabaseSchema + } + if ("cohortTable" %in% names(covariateSettings[[j]])) { + covariateSettings[[j]]$cohortTable <- cohortTable + } + } + + modelDesignList[[i]]$covariateSettings <- covariateSettings + } + + return(modelDesignList) + }, + .getResultsDataModelSpecificationFileLocation = function() { + return(system.file( + file.path("settings", "resultsDataModelSpecification.csv"), + package = "PatientLevelPrediction" + )) + } + ) +) diff --git a/R/Module-SelfControlledCaseSeries.R b/R/Module-SelfControlledCaseSeries.R new file mode 100644 index 00000000..a5b53776 --- /dev/null +++ b/R/Module-SelfControlledCaseSeries.R @@ -0,0 +1,158 @@ +# SelfControlledCaseSeriesModule ------------- +#' @title Self-Controlled Case Series design with the \href{https://ohdsi.github.io/SelfControlledCaseSeries/}{HADES SelfControlledCaseSeries Package} +#' @export +#' @description +#' Module for performing Self-Controlled Case Series (SCCS) analyses +#' against the OMOP Common Data Model. +SelfControlledCaseSeriesModule <- R6::R6Class( + classname = "SelfControlledCaseSeriesModule", + inherit = StrategusModule, + public = list( + #' @field tablePrefix The table prefix for results tables + tablePrefix = "sccs_", + #' @description Initialize the module + initialize = function() { + super$initialize() + }, + #' @description Executes the SelfControlledCaseSeries package + #' @template connectionDetails + #' @template analysisSpecifications + #' @template executionSettings + execute = function(connectionDetails, analysisSpecifications, executionSettings) { + super$.validateCdmExecutionSettings(executionSettings) + super$execute(connectionDetails, analysisSpecifications, executionSettings) + + jobContext <- private$jobContext + sccsMultiThreadingSettings <- SelfControlledCaseSeries::createDefaultSccsMultiThreadingSettings(jobContext$moduleExecutionSettings$maxCores) + + args <- jobContext$settings + args$connectionDetails <- connectionDetails + args$cdmDatabaseSchema <- jobContext$moduleExecutionSettings$cdmDatabaseSchema + args$exposureDatabaseSchema <- jobContext$moduleExecutionSettings$workDatabaseSchema + args$exposureTable <- jobContext$moduleExecutionSettings$cohortTableNames$cohortTable + args$outcomeDatabaseSchema <- jobContext$moduleExecutionSettings$workDatabaseSchema + args$outcomeTable <- jobContext$moduleExecutionSettings$cohortTableNames$cohortTable + args$nestingCohortDatabaseSchema <- jobContext$moduleExecutionSettings$workDatabaseSchema + args$nestingCohortTable <- jobContext$moduleExecutionSettings$cohortTableNames$cohortTable + args$customCovariateDatabaseSchema <- jobContext$moduleExecutionSettings$workDatabaseSchema + args$customCovariateTable <- jobContext$moduleExecutionSettings$cohortTableNames$cohortTable + args$outputFolder <- jobContext$moduleExecutionSettings$workSubFolder + args$sccsMultiThreadingSettings <- sccsMultiThreadingSettings + args$sccsDiagnosticThresholds <- NULL + do.call(SelfControlledCaseSeries::runSccsAnalyses, args) + + exportFolder <- jobContext$moduleExecutionSettings$resultsSubFolder + SelfControlledCaseSeries::exportToCsv( + outputFolder = jobContext$moduleExecutionSettings$workSubFolder, + exportFolder = exportFolder, + databaseId = jobContext$moduleExecutionSettings$cdmDatabaseMetaData$databaseId, + minCellCount = jobContext$moduleExecutionSettings$minCellCount, + sccsDiagnosticThresholds = jobContext$settings$sccsDiagnosticThresholds + ) + # TODO: Removing this to make the upload easier + # unlink(file.path(exportFolder, sprintf("Results_%s.zip", jobContext$moduleExecutionSettings$cdmDatabaseMetaData$databaseId))) + + resultsDataModel <- self$getResultsDataModelSpecification() + resultsDataModel <- resultsDataModel[file.exists(file.path(exportFolder, paste0(resultsDataModel$tableName, ".csv"))), ] + if (any(!startsWith(resultsDataModel$tableName, self$tablePrefix))) { + stop("Table names do not have required prefix") + } + CohortGenerator::writeCsv( + x = resultsDataModel, + file = file.path(exportFolder, "resultsDataModelSpecification.csv"), + warnOnFileNameCaseMismatch = FALSE + ) + + private$.message(paste("Results available at:", exportFolder)) + }, + #' @description Create the results data model for the module + #' @template resultsConnectionDetails + #' @template resultsDatabaseSchema + #' @template tablePrefix + createResultsDataModel = function(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix = "") { + super$createResultsDataModel(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix) + # Note: not passing the tablePrefix argument to + # createResultsDataModel since the SCCS results + # model already contains the "sccs_" table prefix + SelfControlledCaseSeries::createResultsDataModel( + connectionDetails = resultsConnectionDetails, + databaseSchema = resultsDatabaseSchema, + ) + }, + #' @description Get the results data model specification for the module + #' @template tablePrefix + getResultsDataModelSpecification = function(tablePrefix = "") { + resultsDataModelSpecification <- CohortGenerator::readCsv( + file = system.file("csv", "resultsDataModelSpecification.csv", package = "SelfControlledCaseSeries"), + warnOnCaseMismatch = FALSE + ) + + # add the prefix to the tableName column + resultsDataModelSpecification$tableName <- paste0(tablePrefix, tablePrefix, resultsDataModelSpecification$tableName) + return(resultsDataModelSpecification) + }, + #' @description Upload the results for the module + #' @template resultsConnectionDetails + #' @template analysisSpecifications + #' @template resultsDataModelSettings + uploadResults = function(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) { + super$uploadResults(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) + + # TODO: This is something SCCS does differently. + # Find the results zip file in the results sub folder + resultsFolder <- private$jobContext$moduleExecutionSettings$resultsSubFolder + zipFiles <- list.files( + path = resultsFolder, + pattern = "\\.zip$", + full.names = TRUE + ) + + if (length(zipFiles) > 0) { + zipFileName <- zipFiles[1] + } else { + # Create a zip file from the results in the directory + DatabaseConnector::createZipFile( + zipFile = "results.zip", + files = list.files(resultsFolder, pattern = ".*\\.csv$"), + rootFolder = resultsFolder + ) + zipFileName <- file.path(resultsFolder, "results.zip") + } + + SelfControlledCaseSeries::uploadResults( + connectionDetails = resultsConnectionDetails, + schema = resultsDataModelSettings$resultsDatabaseSchema, + zipFileName = zipFileName, + purgeSiteDataBeforeUploading = FALSE + ) + }, + #' @description Creates the SelfControlledCaseSeries Module Specifications + #' @param sccsAnalysisList description + #' @param exposuresOutcomeList description + #' @param analysesToExclude description + #' @param combineDataFetchAcrossOutcomes description + #' @param sccsDiagnosticThresholds description + createModuleSpecifications = function(sccsAnalysisList, + exposuresOutcomeList, + analysesToExclude = NULL, + combineDataFetchAcrossOutcomes = FALSE, + sccsDiagnosticThresholds = SelfControlledCaseSeries::createSccsDiagnosticThresholds()) { + analysis <- list() + for (name in names(formals(self$createModuleSpecifications))) { + analysis[[name]] <- get(name) + } + + specifications <- super$createModuleSpecifications( + moduleSpecifications = analysis + ) + return(specifications) + }, + #' @description Validate the module specifications + #' @param moduleSpecifications The SelfControlledCaseSeries module specifications + validateModuleSpecifications = function(moduleSpecifications) { + super$validateModuleSpecifications( + moduleSpecifications = moduleSpecifications + ) + } + ) +) diff --git a/R/ModuleEnv.R b/R/ModuleEnv.R deleted file mode 100644 index 03139f36..00000000 --- a/R/ModuleEnv.R +++ /dev/null @@ -1,123 +0,0 @@ -# Copyright 2024 Observational Health Data Sciences and Informatics -# -# This file is part of Strategus -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -.handleInjectVar <- function(x) { - hVar <- function(x) { - if (is.character(x)) { - return(sprintf('"%s"', x)) - } else { - return(sprintf("%s", x)) - } - } - - if (length(x) == 1) { - return(hVar(x)) - } else if (is.vector(x)) { - innerVars <- hVar(x) - return(paste0("c(", paste(innerVars, collapse = ", "), ")")) - } else { - stop("cannot handle complex data structures in variable injection") - } -} - -#' Load module execution space inside and renv -#' inspired by targets::tar_script but allowing custom variable execution -#' -#' Designed to allow more human readable code that is executed inside a module as well as simple variable substitution -#' for injecting constants (e.g. simple parameters or file paths used inside and outside of modules) -#' -#' This pattern also allows dependency injection which could be used if you don't want to use and renv and (instead) -#' would like to use docker images or just execution in the base environment for testing/debugging -#' -#' @param code code block to execute -#' @param moduleFolder Instantiated Strategus module folder -#' @param injectVars list of var names list(name=value) to replace (e.g. replace list(foo = "some string") will -#' find the pattern foo and replace it with the string some string - be careful! -#' @param tempScriptFile tempFile to write script to -#' @param job run as rstudio job -#' @param processName String name for process -#' @returns NULL invisibly -withModuleRenv <- function(code, - moduleFolder, - injectVars = list(), - tempScriptFile = tempfile(fileext = ".R"), - job = FALSE, - processName = paste(moduleFolder, "_renv_run")) { - # convert human readable code to a string for writing - script <- as.character(substitute(code))[-1] - # Insert variables - for (name in names(injectVars)) { - rep <- .handleInjectVar(injectVars[[name]]) - script <- gsub(name, rep, script) - } - - # Attach renv options() from the calling environment to the renv::run context - # renv options are prefixed with "renv." as described in - # https://rstudio.github.io/renv/reference/config.html - envOptions <- options() - renvOptions <- envOptions[grepl("renv\\.", names(envOptions))] - if (length(renvOptions) > 0) { - for (i in 1:length(renvOptions)) { - script <- c(.copyOptionForScript( - optionName = names(renvOptions)[[i]], - optionValue = renvOptions[[i]] - ), script) - } - } - - # Turning off verbose output to hide renv output - # unless the user has set this option to TRUE. - if (!getOption(x = "renv.verbose", default = FALSE)) { - options(renv.verbose = FALSE) - } - - # Import the Strategus functions we need to use in the module scripts - script <- c("retrieveConnectionDetails <- ", base::deparse(Strategus::retrieveConnectionDetails), script) - script <- c("unlockKeyring <- ", base::deparse(Strategus::unlockKeyring), script) - - # Write file and execute script inside an renv - fileConn <- file(tempScriptFile) - writeLines(script, fileConn) - close(fileConn) - renv::run( - script = tempScriptFile, - job = job, - name = processName, - project = moduleFolder - ) - return(invisible(NULL)) -} - -.getLocalLibraryScipt <- function(x) { - libPath <- file.path(find.package(x), "../") - sprintf("library(%s, lib.loc = '%s')", x, libPath) -} - -.copyOptionForScript <- function(optionName, optionValue) { - if (is.logical(optionValue) || is.numeric(optionValue)) { - sprintf("options(%s = %s)", optionName, optionValue) - } else if (is.character(optionValue) && length(optionValue) == 1) { - sprintf("options(%s = '%s')", optionName, optionValue) - } else if (is.character(optionValue) && length(optionValue) > 1) { - sprintf("options(%s = c('%s'))", optionName, paste(optionValue, collapse = "','")) - } else { - paste0("# option = ", optionName, " - could not be passed to this file, likely because it is a function.") - } -} - -.formatAndNormalizeFilePathForScript <- function(filePath) { - return(gsub("\\\\", "/", normalizePath(path = filePath, mustWork = F))) -} diff --git a/R/ModuleInstantiation.R b/R/ModuleInstantiation.R deleted file mode 100644 index 6aa6403d..00000000 --- a/R/ModuleInstantiation.R +++ /dev/null @@ -1,523 +0,0 @@ -# Copyright 2024 Observational Health Data Sciences and Informatics -# -# This file is part of Strategus -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -#' Ensure all modules are instantiated -#' -#' @description -#' Ensure that all modules referenced in the analysis specifications are instantiated -#' locally in the folder specified in the `INSTANTIATED_MODULES_FOLDER` environmental -#' variable. -#' -#' Missing modules will be fetched from remote repositories. -#' -#' This function will also check whether there are different versions of the same -#' module specified, which is not allowed, and whether all modules required by the -#' specified modules are also instantiated. -#' -#' @template AnalysisSpecifications -#' -#' @template forceVerification -#' -#' @template enforceModuleDependencies -#' -#' @return -#' A list containing the install status of all modules -#' (TRUE if all are installed properly) and a tibble listing -#' the instantiated modules. -#' -#' @export -ensureAllModulesInstantiated <- function(analysisSpecifications, forceVerification = FALSE, enforceModuleDependencies = TRUE) { - modules <- getModuleTable(analysisSpecifications, distinct = TRUE) - - # Verify only one version per module: - multipleVersionsPerModule <- modules %>% - group_by(module) %>% - summarise(versions = n()) %>% - filter(versions > 1) - if (nrow(multipleVersionsPerModule) > 0) { - stop(sprintf( - "Only one version per module allowed in a single analyses specification.\nMultiple versions found for module(s) `%s`.", - paste(multipleVersionsPerModule$module, collapse = "', '") - )) - } - - # Ensure all required modules are instantiated: - for (i in 1:nrow(modules)) { - ensureModuleInstantiated( - module = modules$module[i], - version = modules$version[i], - remoteRepo = modules$remoteRepo[i], - remoteUsername = modules$remoteUsername[i] - ) - } - - # Check required dependencies have been declare in the specification - # unless the user has set enforceModuleDependencies == FALSE - checkModuleDependencies( - modules = modules, - enforceModuleDependencies = enforceModuleDependencies - ) - - # Verify all modules are properly installed - moduleInstallStatus <- list() - for (i in 1:nrow(modules)) { - status <- verifyModuleInstallation( - module = modules$module[i], - version = modules$version[i], - forceVerification = forceVerification - ) - moduleInstallStatus[[length(moduleInstallStatus) + 1]] <- status - } - attr(modules, "moduleInstallStatus") <- moduleInstallStatus - - installStatus <- unlist(lapply(moduleInstallStatus, FUN = function(x) { - x$moduleInstalled - })) - if (!all(installStatus)) { - problemModules <- moduleInstallStatus[!installStatus] - message("There were ", length(problemModules), " issue(s) found with your Strategus modules!") - for (i in seq_along(problemModules)) { - message("Issue #", i, ": Module ", problemModules[[i]]$moduleFolder, " could not install the following R packages:") - print(problemModules[[i]]$issues) - } - message("To fix these issues, open the module project (.Rproj file) at the path specified above and re-run \"renv::restore()\" and correct all issues") - } - - return( - list( - allModulesInstalled = all(installStatus), - modules = modules - ) - ) -} - - -#' Verify a module is properly installed -#' -#' @description -#' In some instances a module may fail to instantiate and install due to problems -#' when calling renv::restore for the module's renv.lock file. This function -#' will allow you to surface inconsistencies between the module renv.lock file -#' and the module's renv project library. This function will check to that a -#' module has been properly installed using internal functions of the `renv` -#' package. If a module is verified to work via this function, the hash of -#' the module's renv.lock file will be written to a text file in the module -#' directory to indicate that it is ready for use. This will allow subsequent -#' calls to work faster since the initial verification process can take some -#' time.It is possible to re-run the verification of a module -#' by using the `forceVerification` parameter. -#' -#' To fix issues with a module, you will need to open the module's .Rproj in -#' RStudio instance and debug the issues when calling renv::restore(). -#' -#' @param module The name of the module to verify (i.e. "CohortGeneratorModule") -#' -#' @param version The version of the module to verify (i.e. "0.2.1") -#' -#' @param silent When TRUE output of this verification process is suppressed -#' -#' @template forceVerification -#' -#' @return -#' A list with the output of the consistency check -#' -#' @export -verifyModuleInstallation <- function(module, version, silent = FALSE, forceVerification = FALSE) { - # Internal helper function - verifyModuleInstallationReturnValue <- function(moduleFolder, moduleInstalled, issues = NULL) { - returnVal <- list( - moduleFolder = moduleFolder, - moduleInstalled = moduleInstalled, - issues = issues - ) - return(returnVal) - } - - moduleFolder <- getModuleFolder(module, version) - if (!dir.exists(moduleFolder)) { - if (!silent) { - warning("Module ", module, ", Version: ", version, " not found at: ", moduleFolder, ". This means the module was never installed.") - } - return( - verifyModuleInstallationReturnValue( - moduleFolder = moduleFolder, - moduleInstalled = FALSE - ) - ) - } - - if (!silent) { - message("Verifying module: ", module, ", (", version, ") at ", moduleFolder, "...", appendLF = F) - } - moduleStatusFileName <- "moduleStatus.txt" - renvLockFileName <- "renv.lock" - - # If the lock file doesn't exist, we're not sure if we're dealing with a module. - if (!file.exists(file.path(moduleFolder, renvLockFileName))) { - if (!silent) { - message("ERROR - renv.lock file missing.") - } - return( - verifyModuleInstallationReturnValue( - moduleFolder = moduleFolder, - moduleInstalled = FALSE - ) - ) - } - - # Check to see if we've already performed the verification by looking at the - # moduleStatus.txt file to see if the md5 in that file matches the one - # created by hashing the renv.lock file - lockfileContents <- ParallelLogger::loadSettingsFromJson( - fileName = file.path(moduleFolder, renvLockFileName) - ) - lockfileHash <- digest::digest( - object = lockfileContents, - algo = "md5" - ) - if (!forceVerification && file.exists(file.path(moduleFolder, moduleStatusFileName))) { - lockfileHashFromModuleStatusFile <- SqlRender::readSql( - sourceFile = file.path(moduleFolder, moduleStatusFileName) - ) - - # If the values match, the module is installed correctly - # return and exit - if (lockfileHashFromModuleStatusFile == lockfileHash) { - if (!silent) { - message("MODULE READY!") - } - return( - verifyModuleInstallationReturnValue( - moduleFolder = moduleFolder, - moduleInstalled = TRUE - ) - ) - } - } - - - # Now perform the consistency check to verify that the renv::restore() - # process executed successfully. We must do this in the module's context - Strategus:::withModuleRenv( - code = { - # Get the renv project status and then identify the packages used - # in the project to determine if there were issues when restoring - # the project from the renv.lock file. - projectStatus <- renv::status() - - # Identify the list of package dependencies by using - # the data returned from renv::status() and - # renv::dependencies for the project. - library <- names(projectStatus$library$Packages) - lockfile <- names(projectStatus$lockfile$Packages) - packages <- sort(union(renv::dependencies(quiet = TRUE)$Package, "renv")) - packages <- sort(unique(c(library, lockfile, packages))) - projectStatus$packages <- packages - saveRDS( - object = list( - library = library, - lockfile = lockfile, - packages = packages - ), - file = "projectStatus.rds" - ) - }, - moduleFolder = moduleFolder - ) - - # The module's project status is written to the - # file system. Now we can get the module status and use the information - # to determine the restoration status - projectStatus <- readRDS(file.path(moduleFolder, "projectStatus.rds")) - - library <- projectStatus$library - lockfile <- projectStatus$lockfile - packages <- projectStatus$packages - - packageStatus <- data.frame( - package = packages, - installed = packages %in% library, - recorded = packages %in% lockfile, - used = packages %in% packages - ) - - # If all of the used & recorded packages are installed, then - # return TRUE for the module installed status. If not, return - # FALSE and set an attribute of the list that contains the issues - # discovered - ok <- packageStatus$installed & (packageStatus$used == packageStatus$recorded) - issues <- packageStatus[!ok, , drop = FALSE] - missing <- !issues$installed - issues$installed <- ifelse(issues$installed, "y", "n") - issues$recorded <- ifelse(issues$recorded, "y", "n") - issues$used <- ifelse(issues$used, "y", if (any(missing)) "?" else "n") - issues <- issues[issues$installed == "n" & issues$recorded == "y" & issues$used == "y", ] - - moduleInstalled <- nrow(issues) == 0 - - if (isTRUE(moduleInstalled)) { - if (!silent) { - message("MODULE READY!") - } - # Write the contents of the md5 hash of the module's - # renv.lock file to the file system to note that the - # module's install status was successful and verified - SqlRender::writeSql( - sql = lockfileHash, - targetFile = file.path(moduleFolder, "moduleStatus.txt") - ) - } else { - if (!silent) { - message("MODULE HAS ISSUES!") - } - } - - return( - verifyModuleInstallationReturnValue( - moduleFolder = moduleFolder, - moduleInstalled = moduleInstalled, - issues = issues - ) - ) -} - - -#' Install the latest release of a module -#' -#' @description -#' This function will call out to the OHDSI GitHub repo to find the latest -#' version of the module and attempt to install it. Only modules that are listed -#' in the `getModuleList()` function are allowed since it will have a known -#' GitHub location. -#' -#' @param moduleName The name of the module to install (i.e. "CohortGeneratorModule"). -#' This parameter must match a value found in the `module` column of `getModuleList()` -#' -#' @return -#' None - this function is called for its side effects -#' -#' @export -installLatestModule <- function(moduleName) { - assertModulesFolderSetting(x = Sys.getenv("INSTANTIATED_MODULES_FOLDER")) - instantiatedModulesFolder <- Sys.getenv("INSTANTIATED_MODULES_FOLDER") - # Verify that the user's GITHUB_PAT is set properly - # otherwise we may hit a rate limit - if (Sys.getenv("GITHUB_PAT") == "") { - stop("You must set your GITHUB_PAT to use this function. Please use the function `usethis::create_github_token()` and try again after restarting your R session.") - } - moduleList <- getModuleList() - if (isFALSE(moduleName %in% moduleList$module)) { - stop("Module: ", module, " not found in the list from Strategus::getModuleList().") - } - moduleDetails <- moduleList %>% - dplyr::filter(module == moduleName) - urlTemplate <- "https://api.%s/repos/%s/%s/releases/latest" - baseUrl <- sprintf(urlTemplate, moduleDetails$remoteRepo, moduleDetails$remoteUsername, moduleDetails$module) - req <- httr2::request(base_url = baseUrl) |> - httr2::req_headers( - "Authorization" = paste0("Bearer ", Sys.getenv("GITHUB_PAT")), - "X-GitHub-Api-Version" = "2022-11-28" - ) - response <- httr2::req_perform(req) - release <- jsonlite::fromJSON(httr2::resp_body_string(response)) - version <- gsub("v", "", release$tag_name, ignore.case = TRUE) - moduleFolder <- ensureModuleInstantiated( - module = moduleDetails$module, - version = version, - remoteRepo = moduleDetails$remoteRepo, - remoteUsername = moduleDetails$remoteUsername - ) - rlang::inform(paste0("Installed ", moduleName, " to ", moduleFolder)) -} - -extractDependencies <- function(modules) { - extractDependenciesSingleModule <- function(module) { - moduleFolder <- getModuleFolder(module$module, module$version) - metaData <- getModuleMetaData(moduleFolder) - dependencies <- tibble( - module = module$module, - dependsOn = as.character(metaData$Dependencies) - ) - return(dependencies) - } - dependencies <- lapply(split(modules, 1:nrow(modules)), extractDependenciesSingleModule) %>% - bind_rows() - return(dependencies) -} - -checkModuleDependencies <- function(modules, enforceModuleDependencies) { - # Check required dependencies have been declare in the specification - # unless the user has set enforceModuleDependencies == FALSE - dependencies <- extractDependencies(modules) - missingDependencies <- dependencies %>% - filter(!dependsOn %in% modules$module) - if (nrow(missingDependencies) > 0 && enforceModuleDependencies) { - message <- paste( - c( - "Detected missing dependencies:", - sprintf("- Missing module '%s' required by module '%s'", missingDependencies$dependsOn, missingDependencies$module) - ), - collapse = "\n" - ) - stop(message) - } -} - -getModuleTable <- function(analysisSpecifications, distinct = FALSE) { - modules <- lapply( - analysisSpecifications$moduleSpecifications, - function(x) { - tibble( - module = x$module, - version = x$version, - remoteRepo = x$remoteRepo, - remoteUsername = x$remoteUsername - ) - } - ) %>% - bind_rows() - if (distinct) { - modules <- modules %>% - distinct(module, version, .keep_all = TRUE) - } - return(modules) -} - -getModuleMetaData <- function(moduleFolder) { - jsonFileName <- file.path(moduleFolder, "MetaData.json") - if (!file.exists(jsonFileName)) { - stop(sprintf("Meta-data JSON not found in '%s'.", moduleFolder)) - } - metaData <- ParallelLogger::loadSettingsFromJson(jsonFileName) - return(metaData) -} - -getModuleFolder <- function(module, version) { - assertModulesFolderSetting(x = Sys.getenv("INSTANTIATED_MODULES_FOLDER")) - moduleFolder <- file.path(Sys.getenv("INSTANTIATED_MODULES_FOLDER"), sprintf("%s_%s", module, version)) - invisible(moduleFolder) -} - -ensureModuleInstantiated <- function(module, version, remoteRepo, remoteUsername) { - assertModulesFolderSetting(x = Sys.getenv("INSTANTIATED_MODULES_FOLDER")) - instantiatedModulesFolder <- Sys.getenv("INSTANTIATED_MODULES_FOLDER") - if (!dir.exists(instantiatedModulesFolder)) { - dir.create(instantiatedModulesFolder, recursive = TRUE) - } - moduleFolder <- getModuleFolder(module, version) - if (!dir.exists(moduleFolder)) { - instantiateModule(module, version, remoteRepo, remoteUsername, moduleFolder) - } - return(moduleFolder) -} - -instantiateModule <- function(module, version, remoteRepo, remoteUsername, moduleFolder) { - dir.create(moduleFolder) - success <- FALSE - on.exit(if (!success) unlink(moduleFolder, recursive = TRUE)) - moduleFile <- file.path(moduleFolder, sprintf("%s_%s.zip", module, version)) - if (module == "TestModule1") { - # For unit testing purposes only: get module from inst/testdata folder - file.copy( - from = system.file( - file.path("testdata", basename(moduleFile)), - package = utils::packageName() - ), - to = moduleFolder - ) - } else { - moduleUrl <- sprintf("https://%s/%s/%s/archive/refs/tags/v%s.zip", remoteRepo, remoteUsername, module, version) - utils::download.file(url = moduleUrl, destfile = moduleFile) - } - utils::unzip(zipfile = moduleFile, exdir = moduleFolder) - unlink(moduleFile) - # At this point, the unzipped folders will likely exist in a sub folder. - # Move all files from that sub folder to the main module folder - subFolders <- list.dirs(path = moduleFolder, recursive = FALSE) - if (length(subFolders) > 0) { - for (i in 1:length(subFolders)) { - R.utils::copyDirectory( - from = subFolders[i], - to = moduleFolder, - recursive = TRUE - ) - unlink(subFolders[i], recursive = TRUE) - } - } - - # Verify the structure of the module to ensure that - # it contains the proper files required by renv - # before we restore from the renv.lock file - renvDependencies <- getModuleRenvDependencies(moduleFolder) - if (nrow(renvDependencies) > 0) { - message <- paste( - c( - sprintf("The module '%s' (v%s) is missing the following files required by renv:", module, version), - sprintf("- Missing renv dependency '%s'", renvDependencies$fileName), - "As a result, Strategus cannot use this module as part of the execution pipeline otherwise it may corrupt your R library.", - "Please check to see if a newer version of this module exists and update your analysis specification to use that module instead." - ), - collapse = "\n" - ) - stop(message) - } - - withModuleRenv( - code = { - renv::restore(prompt = FALSE) - }, - moduleFolder = moduleFolder, - injectVars = list(moduleFolder = moduleFolder) - ) - success <- TRUE -} - -getModuleRenvDependencies <- function(moduleFolder) { - renvRequiredFiles <- c( - ".Rprofile", - "renv.lock", - "renv/activate.R", - "renv/settings.json" - ) - - missingFiles <- tibble::enframe(renvRequiredFiles) %>% - dplyr::mutate(fileExists = file.exists(file.path(moduleFolder, value))) %>% - dplyr::rename(fileName = value) %>% - dplyr::select("fileName", "fileExists") %>% - dplyr::filter(fileExists == FALSE) - - invisible(missingFiles) -} - -getModuleTablePrefixes <- function(moduleList) { - moduleTablePrefix <- tibble::tibble() - for (i in 1:nrow(moduleList)) { - moduleMetaData <- getModuleMetaData( - moduleFolder = getModuleFolder( - module = moduleList$module[i], - version = moduleList$version[i] - ) - ) - moduleTablePrefix <- moduleTablePrefix %>% - bind_rows(tibble::tibble( - moduleName = moduleList$module[i], - moduleVersion = moduleList$version[i], - tablePrefix = moduleMetaData$TablePrefix - )) - } - - invisible(moduleTablePrefix) -} diff --git a/R/RenvHelpers.R b/R/RenvHelpers.R deleted file mode 100644 index 822f7774..00000000 --- a/R/RenvHelpers.R +++ /dev/null @@ -1,232 +0,0 @@ -#' Compare two renv.lock files -#' -#' @description -#' Used to compare renv.lock files and return the results in a data.frame. -#' The return value will include a "full join" representation of the packages -#' across the two lock files. -#' -#' @param filename1 The first renv.lock file name -#' -#' @param filename2 The second renv.lock file name -#' -#' @return -#' A data.frame with the comparison of the rev.lock files -#' -#' @export -compareLockFiles <- function(filename1, filename2) { - # Read the lock files - lockfile1 <- renv::lockfile_read( - file = filename1 - ) - - lockfile2 <- renv::lockfile_read( - file = filename2 - ) - - # Compare lock files - lockfile1Packages <- lockFileToDataFrame(lockfile1) - names(lockfile1Packages) <- paste0("lockfile1", names(lockfile1Packages)) - lockfile2Packages <- lockFileToDataFrame(lockfile2) - names(lockfile2Packages) <- paste0("lockfile2", names(lockfile2Packages)) - mergedLockFilePackages <- merge( - x = lockfile1Packages, - y = lockfile2Packages, - by.x = "lockfile1Name", - by.y = "lockfile2Name", - all = TRUE - ) - return(mergedLockFilePackages) -} - -#' Synchronize renv.lock files and overwrite the target file -#' (read the description) -#' -#' @description -#' Used to synchronize the values from the "source of truth" renv.lock file to -#' the target renv.lock file. Packages are compared (by name) and if the version -#' of the package in the "source of truth" is greater the one found in the -#' target, the target renv.lock file will be updated. This function will -#' automatically update the target file. -#' -#' Version comparison is handled by the `semver` package and since most packages -#' use semantic versioning. When a package does not use semantic versioning, -#' a warning is provided so the user can review. -#' -#' @param sourceOfTruthLockFileName The renv.lock file to use as the source of -#' truth -#' -#' @param targetLockFileName The target renv.lock file that will be synced with -#' the source of truth -#' -#' @return -#' A data.frame containing the different packages and their version that -#' were involved in the synchronization process -#' -#' @export -syncLockFile <- function(sourceOfTruthLockFileName, targetLockFileName) { - findPackageByName <- function(list, packageName) { - index <- which(sapply(list, function(x) x$Package == packageName)) - return(index) - } - - # Read the lock files - sourceOfTruthLockFile <- renv::lockfile_read( - file = sourceOfTruthLockFileName - ) - targetLockFile <- renv::lockfile_read( - file = targetLockFileName - ) - - # Compare the lock files to get the differences in package versions - comparedLockFiles <- compareLockFiles( - filename1 = sourceOfTruthLockFileName, - filename2 = targetLockFileName - ) - verDiffs <- comparedLockFiles[!is.na(comparedLockFiles$lockfile2Version) & - comparedLockFiles$lockfile1Version != comparedLockFiles$lockfile2Version, ] - verDiffs <- verDiffs[!is.na(verDiffs$lockfile1Name), ] - - if (nrow(verDiffs) == 0) { - rlang::inform("Lock files are already in sync.") - return(invisible(NULL)) - } - - # Update the target lock file based on the source of truth - for (i in 1:nrow(verDiffs)) { - index <- findPackageByName(targetLockFile$Packages, verDiffs[i, ]$lockfile1Name) - tryCatch(expr = { - semverPattern <- "^\\d+\\.\\d+\\.\\d+(?:-[0-9A-Za-z-]+(?:\\.[0-9A-Za-z-]+)*)?(?:\\+[0-9A-Za-z-]+)?$" - sourceOfTruthVersion <- verDiffs[i, ]$lockfile1Version - targetVersion <- targetLockFile$Packages[[index]]$Version - if (grepl(semverPattern, sourceOfTruthVersion) && grepl(semverPattern, targetVersion)) { - sourceOfTruthVersion <- semver::parse_version(sourceOfTruthVersion) - targetVersion <- semver::parse_version(targetVersion) - if (sourceOfTruthVersion > targetVersion) { - rlang::inform( - message = paste(verDiffs[i, ]$lockfile1Name, "[", targetVersion, "->", sourceOfTruthVersion, "]") - ) - targetLockFile$Packages[[index]]$Version <- verDiffs[i, ]$lockfile1Version - if (!is.na(verDiffs[i, ]$lockfile1RemoteRef)) { - targetLockFile$Packages[[index]]$RemoteRef <- verDiffs[i, ]$lockfile1RemoteRef - } - } else { - rlang::inform( - message = paste(verDiffs[i, ]$lockfile1Name, "[ SKIPPING - ", targetVersion, ">", sourceOfTruthVersion, "]") - ) - } - } else { - rlang::warn(paste0("Package: [", verDiffs[i, ]$lockfile1Name, "] - version number could not be parsed. Please inspect manually as it may require an upgrade.")) - } - }, error = function(err) { - rlang::inform("An error occurred:", utils::str(err), "\n") - }) - } - - # Save the updated lock file - renv::lockfile_write( - lockfile = targetLockFile, - file = targetLockFileName - ) - - return(invisible(verDiffs)) -} - -#' Validate an renv.lock file to ensure it is ready for use by Strategus -#' -#' @description -#' Will check an renv.lock file for a module to verify that it only references -#' tagged packages and includes the packages required by Strategus. It will -#' also check for suggested packages that are useful for testing, such as -#' RSQLite. -#' -#' @param filename The renv.lock file to validate -#' -#' @export -validateLockFile <- function(filename) { - # Read the lock file - lockFile <- renv::lockfile_read( - file = filename - ) - # Create a data.frame from the renv.lock file - df <- lockFileToDataFrame( - lf = lockFile - ) - - # Check that the mandatory dependencies are met - message("Checking mandatory packages...", appendLF = F) - if (length(mandatoryPackages()) != nrow(df[df$Name %in% mandatoryPackages(), ])) { - missingPkgs <- setdiff(mandatoryPackages(), df[df$Name %in% mandatoryPackages(), ]$Name) - message("FAILED!") - message(" -- Missing the mandatory packages: ", paste(missingPkgs, collapse = ", ")) - message(" Please record these missing dependencies in your renv.lock file.") - } else { - message("PASSED!") - } - - # Check for suggested packages - message("Checking suggested packages...", appendLF = F) - if (length(suggestedPacakges()) != nrow(df[df$Name %in% suggestedPacakges(), ])) { - missingPkgs <- setdiff(suggestedPacakges(), df[df$Name %in% suggestedPacakges(), ]$Name) - message("WARNING!") - message(" -- Missing the suggested packages: ", paste(missingPkgs, collapse = ", ")) - message(" This is an optional set of dependencies so you may decide if you wish to have them in your renv.lock file.") - } else { - message("PASSED!") - } - - # Check that we're using declared versions of all packages - message("Checking all package using tagged versions in RemoteRef...", appendLF = F) - # Start by filtering out the CRAN Repository entries - dfFiltered <- df[tolower(df$Source) != "repository", ] - if (!all(grepl("^(v)?\\d+(\\.\\d+){2}$", dfFiltered$RemoteRef))) { - message("FAILED! Please check the following packages:") - problemPkgs <- dfFiltered[!grepl("^(v)?\\d+(\\.\\d+){2}$", dfFiltered$RemoteRef), ] - for (i in 1:nrow(problemPkgs)) { - message(paste0(" -- Package: ", problemPkgs$Name[[i]], "; RemoteRef: ", problemPkgs$RemoteRef[[i]])) - } - message(" Please ensure you are only including tagged versions of package dependencies in your renv.lock file.") - } else { - message("PASSED!") - } -} - -#' List of mandatory packages for a Strategus module -#' -#' @keywords internal -mandatoryPackages <- function() { - return(c( - "CohortGenerator", - "DatabaseConnector", - "keyring", - "ParallelLogger", - "renv", - "SqlRender" - )) -} - -#' List of suggested packages for a Strategus module -#' -#' @keywords internal -suggestedPacakges <- function() { - return(c("RSQLite")) -} - - -#' Convert a lock file to a data.frame -#' -#' @keywords internal -lockFileToDataFrame <- function(lf) { - df <- data.frame() - for (i in 1:length(lf$Packages)) { - df <- rbind( - df, - data.frame( - Name = lf$Packages[[i]]$Package, - Version = lf$Packages[[i]]$Version, - Source = lf$Packages[[i]]$Source, - RemoteRef = ifelse(is.null(lf$Packages[[i]]$RemoteRef), yes = NA, no = lf$Packages[[i]]$RemoteRef) - ) - ) - } - return(df) -} diff --git a/R/ResultDataModel.R b/R/ResultDataModel.R new file mode 100644 index 00000000..06cea307 --- /dev/null +++ b/R/ResultDataModel.R @@ -0,0 +1,89 @@ +# Copyright 2024 Observational Health Data Sciences and Informatics +# +# This file is part of Strategus +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +#' Create Result Data Model +#' +#' @description +#' Use this at the study design stage to create data models for modules +#' This functions loads modules and executes any custom code to create +#' the results data model in the specified schema in the results database. +#' +#' @template AnalysisSpecifications +#' @param resultsDataModelSettings The results data model settings as created using [@seealso [createResultsDataModelSettings()]] +#' @template resultsConnectionDetails +#' +#' @export +createResultDataModel <- function(analysisSpecifications, + resultsDataModelSettings, + resultsConnectionDetails) { + errorMessages <- checkmate::makeAssertCollection() + checkmate::assertClass(analysisSpecifications, "AnalysisSpecifications", add = errorMessages) + checkmate::assertClass(resultsDataModelSettings, "ResultsDataModelSettings", add = errorMessages) + checkmate::assertClass(resultsConnectionDetails, "ConnectionDetails", add = errorMessages) + checkmate::reportAssertions(collection = errorMessages) + + # The DatabaseMetaData is a special case... + .createDatabaseMetadataResultsDataModel( + resultsConnectionDetails = resultsConnectionDetails, + resultsDataModelSettings = resultsDataModelSettings + ) + + for (i in 1:length(analysisSpecifications$moduleSpecifications)) { + moduleName <- analysisSpecifications$moduleSpecifications[[i]]$module + moduleObj <- get(moduleName)$new() + moduleObj$createResultsDataModel( + resultsConnectionDetails = resultsConnectionDetails, + resultsDatabaseSchema = resultsDataModelSettings$resultsDatabaseSchema + ) + } +} + +#' Upload results +#' +#' @description +#' +#' Upload the results for a given analysis +#' +#' @template AnalysisSpecifications +#' @template resultsDataModelSettings +#' @template resultsConnectionDetails +#' +#' @export +uploadResults <- function(analysisSpecifications, + resultsDataModelSettings, + resultsConnectionDetails) { + errorMessages <- checkmate::makeAssertCollection() + checkmate::assertClass(analysisSpecifications, "AnalysisSpecifications", add = errorMessages) + checkmate::assertClass(resultsDataModelSettings, "ResultsDataModelSettings", add = errorMessages) + checkmate::assertClass(resultsConnectionDetails, "ConnectionDetails", add = errorMessages) + checkmate::reportAssertions(collection = errorMessages) + + # The DatabaseMetaData is a special case... + .uploadDatabaseMetadata( + resultsConnectionDetails = resultsConnectionDetails, + resultsDataModelSettings = resultsDataModelSettings + ) + + for (i in 1:length(analysisSpecifications$moduleSpecifications)) { + moduleName <- analysisSpecifications$moduleSpecifications[[i]]$module + moduleObj <- get(moduleName)$new() + moduleObj$uploadResults( + resultsConnectionDetails = resultsConnectionDetails, + analysisSpecifications = analysisSpecifications, + resultsDataModelSettings = resultsDataModelSettings + ) + } +} diff --git a/R/ResultModelCreation.R b/R/ResultModelCreation.R deleted file mode 100644 index 5c13455a..00000000 --- a/R/ResultModelCreation.R +++ /dev/null @@ -1,295 +0,0 @@ -# Copyright 2024 Observational Health Data Sciences and Informatics -# -# This file is part of Strategus -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -#' Create Result Data Models -#' @description -#' Use this at the study design stage to create data models for modules -#' This functions loads modules and executes any custom code to create schemas in a results database -#' If recreate is set to TRUE all existing data will be removed, otherwise -#' -#' @inheritParams execute -#' -#' @export -createResultDataModels <- function(analysisSpecifications, - executionSettings, - executionScriptFolder = NULL, - keyringName = NULL, - restart = FALSE, - enforceModuleDependencies = TRUE) { - errorMessages <- checkmate::makeAssertCollection() - keyringList <- keyring::keyring_list() - checkmate::assertClass(analysisSpecifications, "AnalysisSpecifications", add = errorMessages) - checkmate::assertClass(executionSettings, "ResultsExecutionSettings", add = errorMessages) - checkmate::assertChoice(x = keyringName, choices = keyringList$keyring, null.ok = TRUE, add = errorMessages) - checkmate::reportAssertions(collection = errorMessages) - - modules <- ensureAllModulesInstantiated( - analysisSpecifications = analysisSpecifications, - enforceModuleDependencies = enforceModuleDependencies - ) - - if (isFALSE(modules$allModulesInstalled)) { - stop("Stopping execution due to module issues") - } - - - if (is.null(executionScriptFolder)) { - executionScriptFolder <- tempfile("strategusTempSettings") - dir.create(executionScriptFolder) - on.exit(unlink(executionScriptFolder, recursive = TRUE)) - } else if (!restart) { - if (dir.exists(executionScriptFolder)) { - unlink(executionScriptFolder, recursive = TRUE) - } - dir.create(executionScriptFolder, recursive = TRUE) - } - # Normalize path to convert from relative to absolute path - executionScriptFolder <- normalizePath(executionScriptFolder, mustWork = F) - - script <- file.path(executionScriptFolder, "SchemaScript.R") - ## - # Code execution inside targets block - ## - targets::tar_script( - { - ## - # Generated by Strategus - not advisable to edit by hand - ## - analysisSpecificationsLoad <- readRDS(analysisSpecificationsFileName) - - targets::tar_option_set(packages = c("Strategus", "keyring"), imports = c("Strategus", "keyring")) - targetList <- list( - targets::tar_target(analysisSpecifications, readRDS(analysisSpecificationsFileName)), - targets::tar_target(executionSettings, readRDS(executionSettingsFileName)), - targets::tar_target(keyringSettings, readRDS(keyringSettingsFileName)) - ) - - for (i in 1:length(analysisSpecificationsLoad$moduleSpecifications)) { - moduleSpecification <- analysisSpecificationsLoad$moduleSpecifications[[i]] - targetName <- sprintf("%s_%d_schema_creation", moduleSpecification$module, i) - - # Use of tar_target_raw allows dynamic names - targetList[[length(targetList) + 1]] <- targets::tar_target_raw(targetName, - substitute(Strategus:::runSchemaCreation(analysisSpecifications, keyringSettings, i, executionSettings), - env = list(i = i) - ), - deps = c("analysisSpecifications", "keyringSettings", "executionSettings") - ) - } - targetList - }, - script = script - ) - - # Store settings objects in the temp folder so they are available in targets - analysisSpecificationsFileName <- .formatAndNormalizeFilePathForScript(file.path(executionScriptFolder, "analysisSpecifications.rds")) - saveRDS(analysisSpecifications, analysisSpecificationsFileName) - executionSettingsFileName <- .formatAndNormalizeFilePathForScript(file.path(executionScriptFolder, "executionSettings.rds")) - saveRDS(executionSettings, executionSettingsFileName) - keyringSettingsFileName <- .formatAndNormalizeFilePathForScript(file.path(executionScriptFolder, "keyringSettings.rds")) - saveRDS(list(keyringName = keyringName), keyringSettingsFileName) - - # Generate target names by module type - moduleToTargetNames <- list() - for (i in 1:length(analysisSpecifications$moduleSpecifications)) { - moduleSpecification <- analysisSpecifications$moduleSpecifications[[i]] - targetName <- sprintf("%s_%d", moduleSpecification$module, i) - moduleToTargetNames[[length(moduleToTargetNames) + 1]] <- tibble( - module = moduleSpecification$module, - targetName = targetName - ) - } - moduleToTargetNames <- bind_rows(moduleToTargetNames) - moduleToTargetNamesFileName <- .formatAndNormalizeFilePathForScript(file.path(executionScriptFolder, "moduleTargetNames.rds")) - saveRDS(moduleToTargetNames, moduleToTargetNamesFileName) - - # Settings required inside script. There is probably a much cleaner way of doing this - writeLines(c( - sprintf("analysisSpecificationsFileName <- '%s'", analysisSpecificationsFileName), - sprintf("executionSettingsFileName <- '%s'", executionSettingsFileName), - sprintf("keyringSettingsFileName <- '%s'", keyringSettingsFileName), - sprintf("moduleToTargetNamesFileName <- '%s'", moduleToTargetNamesFileName), - readLines(script) - ), script) - - targets::tar_make(script = script) -} - - -#' Create module(s) result data model -#' @description -#' This function will create the results data model for the modules in the -#' `analysisSpecifications`. A module can implement its own results data model -#' creation function by implementing the function `createDataModelSchema` in -#' its Main.R. The default behavior is to use the `ResultsModelManager` to create -#' the results data model based on the `resultsDataModelSpecification.csv` in the -#' module's results folder. -#' -#' @template AnalysisSpecifications -#' @param keyringSettings The keyringSettings from the executionSettings context -#' @param moduleIndex The index of the module in the analysis specification -#' @template executionSettings -#' @param ... For future expansion -runSchemaCreation <- function(analysisSpecifications, keyringSettings, moduleIndex, executionSettings, ...) { - checkmate::assert_multi_class(x = executionSettings, classes = c("ResultsExecutionSettings")) - moduleSpecification <- analysisSpecifications$moduleSpecifications[[moduleIndex]] - - module <- moduleSpecification$module - version <- moduleSpecification$version - remoteRepo <- moduleSpecification$remoteRepo - remoteUsername <- moduleSpecification$remoteUsername - moduleInstallation <- verifyModuleInstallation(module, version, silent = TRUE) - moduleFolder <- moduleInstallation$moduleFolder - if (isFALSE(moduleInstallation$moduleInstalled)) { - stop("Stopping since module is not properly installed!") - } - - # Create job context - moduleExecutionSettings <- executionSettings - moduleExecutionSettings$workSubFolder <- file.path(executionSettings$workFolder, sprintf("%s_%d", module, moduleIndex)) - moduleExecutionSettings$resultsSubFolder <- file.path(executionSettings$resultsFolder, sprintf("%s_%d", module, moduleIndex)) - - if (!dir.exists(moduleExecutionSettings$workSubFolder)) { - dir.create(moduleExecutionSettings$workSubFolder, recursive = TRUE) - } - if (!dir.exists(moduleExecutionSettings$resultsSubFolder)) { - dir.create(moduleExecutionSettings$resultsSubFolder, recursive = TRUE) - } - - jobContext <- list( - sharedResources = analysisSpecifications$sharedResources, - settings = moduleSpecification$settings, - moduleExecutionSettings = moduleExecutionSettings, - keyringSettings = keyringSettings - ) - jobContextFileName <- .formatAndNormalizeFilePathForScript(file.path(moduleExecutionSettings$workSubFolder, "jobContext.rds")) - saveRDS(jobContext, jobContextFileName) - dataModelExportPath <- .formatAndNormalizeFilePathForScript(file.path(moduleExecutionSettings$workSubFolder, "resultsDataModelSpecification.csv")) - - - doneFile <- .formatAndNormalizeFilePathForScript(file.path(jobContext$moduleExecutionSettings$resultsSubFolder, "schema.creation")) - if (file.exists(doneFile)) { - unlink(doneFile) - } - ## code executed inside renv only has scoped variables - withModuleRenv( - code = { - createDataModelSchema <- NULL - - getDataModelSpecifications <- function(...) { - if (file.exists("resultsDataModelSpecification.csv")) { - res <- CohortGenerator::readCsv( - file = "resultsDataModelSpecification.csv" - ) - return(res) - } - return(NULL) - } - - source("Main.R") - - jobContext <- readRDS(jobContextFileName) - specifications <- getDataModelSpecifications(jobContext) - - if (Sys.getenv("FORCE_RENV_USE", "") == "TRUE") { - renv::use(lockfile = "renv.lock") - } - - ParallelLogger::addDefaultFileLogger(jobContext$moduleExecutionSettings$logFileName) - ParallelLogger::addDefaultFileLogger(file.path(jobContext$moduleExecutionSettings$resultsSubFolder, "log.txt")) - ParallelLogger::addDefaultErrorReportLogger(file.path(jobContext$moduleExecutionSettings$resultsSubFolder, "errorReportR.txt")) - - message("START SCHEMA CREATION: ", moduleName) - # Main.R can override default behaviour by implementing this function - if (is.function(createDataModelSchema)) { - # If the keyring is locked, unlock it, set the value and then re-lock it - keyringName <- jobContext$keyringSettings$keyringName - keyringLocked <- unlockKeyring(keyringName = keyringName) - - resultsConnectionDetails <- keyring::key_get(jobContext$moduleExecutionSettings$resultsConnectionDetailsReference, keyring = keyringName) - resultsConnectionDetails <- ParallelLogger::convertJsonToSettings(resultsConnectionDetails) - resultsConnectionDetails <- do.call(DatabaseConnector::createConnectionDetails, resultsConnectionDetails) - jobContext$moduleExecutionSettings$resultsConnectionDetails <- resultsConnectionDetails - - createDataModelSchema(jobContext) - - if (keyringLocked) { - keyring::keyring_lock(keyring = keyringName) - } - writeLines("schema.created", doneFile) - } else if (is.data.frame(specifications)) { - # Export schema to readable location - CohortGenerator::writeCsv( - x = specifications, - file = dataModelExportPath, - warnOnCaseMismatch = FALSE - ) - writeLines("specifications.written", doneFile) - } else { - warning("Module does not include data specifications file or createDataModelSchema function") - CohortGenerator::writeCsv( - x = specifications, - file = dataModelExportPath, - warnOnCaseMismatch = FALSE - ) - writeLines("specifications.not.written", doneFile) - } - message("FINISH SCHEMA CREATION: ", moduleName) - - ParallelLogger::unregisterLogger("DEFAULT_FILE_LOGGER", silent = TRUE) - ParallelLogger::unregisterLogger("DEFAULT_ERRORREPORT_LOGGER", silent = TRUE) - }, - moduleFolder = moduleFolder, - tempScriptFile = file.path(moduleExecutionSettings$workSubFolder, "SchemaCreation.R"), - injectVars = list( - jobContextFileName = jobContextFileName, - dataModelExportPath = dataModelExportPath, - moduleName = module, - doneFile = doneFile - ) - ) - - workStatus <- readLines(doneFile) - if (workStatus == "specifications.written") { - moduleInfo <- ParallelLogger::loadSettingsFromJson(file.path(moduleFolder, "MetaData.json")) - keyringName <- jobContext$keyringSettings$keyringName - keyringLocked <- Strategus::unlockKeyring(keyringName = keyringName) - - resultsConnectionDetails <- keyring::key_get(jobContext$moduleExecutionSettings$resultsConnectionDetailsReference, keyring = keyringName) - resultsConnectionDetails <- ParallelLogger::convertJsonToSettings(resultsConnectionDetails) - resultsConnectionDetails <- do.call(DatabaseConnector::createConnectionDetails, resultsConnectionDetails) - - connection <- DatabaseConnector::connect(resultsConnectionDetails) - on.exit(DatabaseConnector::disconnect(connection)) - - sql <- ResultModelManager::generateSqlSchema(csvFilepath = dataModelExportPath) - DatabaseConnector::renderTranslateExecuteSql(connection, - sql, - table_prefix = moduleInfo$TablePrefix, - database_schema = jobContext$moduleExecutionSettings$resultsDatabaseSchema - ) - - if (keyringLocked) { - keyring::keyring_lock(keyring = keyringName) - } - } else if (workStatus == "schema.created") { - message("Result schema creation handled inside module execution envrionment") - } else { - message("Schema not created for module") - } - - return(list(dummy = 123)) -} diff --git a/R/ResultsUpload.R b/R/ResultsUpload.R deleted file mode 100644 index ece4ec07..00000000 --- a/R/ResultsUpload.R +++ /dev/null @@ -1,196 +0,0 @@ -# Copyright 2024 Observational Health Data Sciences and Informatics -# -# This file is part of Strategus -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -# Results upload callbacks for inserting results in to a database -runResultsUpload <- function(analysisSpecifications, keyringSettings, moduleIndex, executionSettings, ...) { - checkmate::assert_multi_class(x = executionSettings, classes = c("ExecutionSettings")) - moduleSpecification <- analysisSpecifications$moduleSpecifications[[moduleIndex]] - - module <- moduleSpecification$module - version <- moduleSpecification$version - remoteRepo <- moduleSpecification$remoteRepo - remoteUsername <- moduleSpecification$remoteUsername - moduleInstallation <- verifyModuleInstallation(module, version, silent = TRUE) - moduleFolder <- moduleInstallation$moduleFolder - if (isFALSE(moduleInstallation$moduleInstalled)) { - stop("Stopping since module is not properly installed!") - } - - # Create job context - moduleExecutionSettings <- executionSettings - moduleExecutionSettings$workSubFolder <- normalizePath(file.path(executionSettings$workFolder, sprintf("%s_%d", module, moduleIndex)), mustWork = F) - moduleExecutionSettings$resultsSubFolder <- normalizePath(file.path(executionSettings$resultsFolder, sprintf("%s_%d", module, moduleIndex)), mustWork = F) - - if (!is(executionSettings, "CdmExecutionSettings")) { - stop("Unhandled executionSettings class! Must be CdmExecutionSettings instance") - } - - if (!dir.exists(moduleExecutionSettings$resultsSubFolder)) { - stop("results not found") - } - jobContext <- list( - sharedResources = analysisSpecifications$sharedResources, - settings = moduleSpecification$settings, - moduleExecutionSettings = moduleExecutionSettings, - keyringSettings = keyringSettings - ) - jobContextFileName <- .formatAndNormalizeFilePathForScript(file.path(moduleExecutionSettings$workSubFolder, "jobContext.rds")) - saveRDS(jobContext, jobContextFileName) - dataModelExportPath <- .formatAndNormalizeFilePathForScript(file.path(moduleExecutionSettings$workSubFolder, "resultsDataModelSpecification.csv")) - - doneFile <- .formatAndNormalizeFilePathForScript(file.path(jobContext$moduleExecutionSettings$resultsSubFolder, "results.uploaded")) - if (file.exists(doneFile)) { - unlink(doneFile) - } - - tempScriptFile <- file.path(moduleExecutionSettings$workSubFolder, "UploadScript.R") - ParallelLogger::addDefaultFileLogger(jobContext$moduleExecutionSettings$logFileName) - on.exit(ParallelLogger::unregisterLogger("DEFAULT_FILE_LOGGER", silent = TRUE)) - - ## - # Module space executed code - ## - withModuleRenv( - { - uploadResultsCallback <- NULL - - getDataModelSpecifications <- function(...) { - ParallelLogger::logInfo("Getting result model specification") - rdmsFilePath <- file.path(jobContext$moduleExecutionSettings$resultsSubFolder, "resultsDataModelSpecification.csv") - if (file.exists(rdmsFilePath)) { - res <- CohortGenerator::readCsv( - file = rdmsFilePath - ) - return(res) - } - ParallelLogger::logInfo("No result model specification found") - return(NULL) - } - source("Main.R") - moduleInfo <- ParallelLogger::loadSettingsFromJson("MetaData.json") - jobContext <- readRDS(jobContextFileName) - specifications <- getDataModelSpecifications(jobContext) - - ParallelLogger::addDefaultFileLogger(jobContext$moduleExecutionSettings$logFileName) - ParallelLogger::addDefaultFileLogger(file.path(jobContext$moduleExecutionSettings$resultsSubFolder, "log.txt")) - ParallelLogger::addDefaultErrorReportLogger(file.path(jobContext$moduleExecutionSettings$resultsSubFolder, "errorReportR.txt")) - - if (Sys.getenv("FORCE_RENV_USE", "") == "TRUE") { - renv::use(lockfile = "renv.lock") - } - - message("START MODULE RESULTS UPLOAD: ", moduleName) - # Override default behaviour and do module specific upload inside module context? - if (is.function(uploadResultsCallback)) { - ParallelLogger::logInfo("Calling module result upload functionality") - # If the keyring is locked, unlock it, set the value and then re-lock it - ParallelLogger::logInfo("-- Getting result database credentials") - keyringName <- jobContext$keyringSettings$keyringName - keyringLocked <- unlockKeyring(keyringName = keyringName) - resultsConnectionDetails <- keyring::key_get(jobContext$moduleExecutionSettings$resultsConnectionDetailsReference, keyring = keyringName) - resultsConnectionDetails <- ParallelLogger::convertJsonToSettings(resultsConnectionDetails) - resultsConnectionDetails <- do.call(DatabaseConnector::createConnectionDetails, resultsConnectionDetails) - jobContext$moduleExecutionSettings$resultsConnectionDetails <- resultsConnectionDetails - ParallelLogger::logInfo("-- Executing upload callback") - uploadResultsCallback(jobContext) - if (keyringLocked) { - keyring::keyring_lock(keyring = keyringName) - } - ParallelLogger::logInfo("-- Upload completed") - writeLines("results.uploaded", doneFile) - } else if (is.null(specifications)) { - ParallelLogger::logInfo("No result specifications found, assuming module has produced no results") - # NO spect file Status - warning("data model specifications not loaded from module - skipping results upload") - writeLines("no.spec.found", doneFile) - } else { - # Spec file written - ParallelLogger::logInfo("Writing spec for result upload outside of module context") - CohortGenerator::writeCsv( - x = specifications, - file = dataModelExportPath, - warnOnFileNameCaseMismatch = FALSE - ) - writeLines("specifications.written", doneFile) - } - - message("FINISH MODULE RESULTS UPLOAD: ", moduleName) - ParallelLogger::unregisterLogger("DEFAULT_FILE_LOGGER", silent = TRUE) - ParallelLogger::unregisterLogger("DEFAULT_ERRORREPORT_LOGGER", silent = TRUE) - }, - moduleFolder = moduleFolder, - tempScriptFile = tempScriptFile, - injectVars = list( - jobContextFileName = jobContextFileName, - dataModelExportPath = dataModelExportPath, - moduleName = module, - doneFile = doneFile - ) - ) - ## - # end Module executed code - ## - if (!file.exists(doneFile)) { - message <- paste( - "Module did not complete. To debug:", - sprintf(" rstudioapi::openProject('%s', newSession = TRUE)", moduleFolder), - sprintf(" file.edit('%s')", tempScriptFile), - sep = "\n" - ) - stop(message) - } - - workStatus <- readLines(doneFile) - - if (workStatus == "specifications.written") { - message("Uploading results according to module specification") - specifications <- CohortGenerator::readCsv(dataModelExportPath) - - keyringName <- jobContext$keyringSettings$keyringName - keyringLocked <- Strategus::unlockKeyring(keyringName = keyringName) - - message("Getting result database credentials") - resultsConnectionDetails <- keyring::key_get(jobContext$moduleExecutionSettings$resultsConnectionDetailsReference, keyring = keyringName) - resultsConnectionDetails <- ParallelLogger::convertJsonToSettings(resultsConnectionDetails) - resultsConnectionDetails <- do.call(DatabaseConnector::createConnectionDetails, resultsConnectionDetails) - jobContext$moduleExecutionSettings$resultsConnectionDetails <- resultsConnectionDetails - - message("Calling RMM for upload") - ResultModelManager::uploadResults( - connectionDetails = jobContext$moduleExecutionSettings$resultsConnectionDetails, - schema = jobContext$moduleExecutionSettings$resultsDatabaseSchema, - resultsFolder = jobContext$moduleExecutionSettings$resultsSubFolder, - forceOverWriteOfSpecifications = FALSE, - purgeSiteDataBeforeUploading = FALSE, - databaseIdentifierFile = file.path(executionSettings$resultsFolder, "DatabaseMetaData", "database_meta_data.csv"), - runCheckAndFixCommands = FALSE, - warnOnMissingTable = TRUE, - specifications = specifications - ) - - message("Upload completed") - if (keyringLocked) { - keyring::keyring_lock(keyring = keyringName) - } - } else if (workStatus == "results.uploaded") { - message("Result upload handled inside module execution envrionment") - } else { - message("Results not uploaded for module") - } - - return(list(dummy = 123)) -} diff --git a/R/RunModule.R b/R/RunModule.R deleted file mode 100644 index 5aebcfa1..00000000 --- a/R/RunModule.R +++ /dev/null @@ -1,142 +0,0 @@ -# Copyright 2024 Observational Health Data Sciences and Informatics -# -# This file is part of Strategus -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# Note: Using S3 for consistency with settings objects in PLP, CohortMethod, and -# FeatureExtraction. If we want to use S4 or R6 we need to first adapt those -# packages. This will be difficult, since these settings objects are used throughout -# these packages, and are for example used in do.call() calls. We should also -# carefully consider serialization and deserialization to JSON, which currently -# uses custom functionality in ParallelLogger to maintain object attributes. - -runModule <- function(analysisSpecifications, keyringSettings, moduleIndex, executionSettings, ...) { - checkmate::assert_multi_class(x = executionSettings, classes = c("CdmExecutionSettings", "ResultsExecutionSettings")) - moduleSpecification <- analysisSpecifications$moduleSpecifications[[moduleIndex]] - module <- moduleSpecification$module - version <- moduleSpecification$version - remoteRepo <- moduleSpecification$remoteRepo - remoteUsername <- moduleSpecification$remoteUsername - moduleInstallation <- verifyModuleInstallation(module, version) - moduleFolder <- moduleInstallation$moduleFolder - if (isFALSE(moduleInstallation$moduleInstalled)) { - stop(paste0("Stopping since module is not properly installed! Module folder: ", moduleInstallation$moduleFolder)) - } - - # Create job context - moduleExecutionSettings <- executionSettings - moduleExecutionSettings$workSubFolder <- file.path(executionSettings$workFolder, sprintf("%s_%d", module, moduleIndex)) - moduleExecutionSettings$resultsSubFolder <- file.path(executionSettings$resultsFolder, sprintf("%s_%d", module, moduleIndex)) - - if (!dir.exists(moduleExecutionSettings$workSubFolder)) { - dir.create(moduleExecutionSettings$workSubFolder, recursive = TRUE) - } - if (!dir.exists(moduleExecutionSettings$resultsSubFolder)) { - dir.create(moduleExecutionSettings$resultsSubFolder, recursive = TRUE) - } - jobContext <- list( - sharedResources = analysisSpecifications$sharedResources, - settings = moduleSpecification$settings, - moduleExecutionSettings = moduleExecutionSettings, - keyringSettings = keyringSettings - ) - jobContextFileName <- .formatAndNormalizeFilePathForScript(file.path(moduleExecutionSettings$workSubFolder, "jobContext.rds")) - saveRDS(jobContext, jobContextFileName) - - tempScriptFile <- .formatAndNormalizeFilePathForScript(file.path(moduleExecutionSettings$workSubFolder, "StrategusScript.R")) - doneFile <- .formatAndNormalizeFilePathForScript(file.path(jobContext$moduleExecutionSettings$resultsSubFolder, "done")) - if (file.exists(doneFile)) { - unlink(doneFile) - } - - if (is(executionSettings, "CdmExecutionSettings")) { - isCdmExecution <- TRUE - } else if (is(executionSettings, "ResultsExecutionSettings")) { - isCdmExecution <- FALSE - } else { - stop("Unhandled executionSettings class! Must be one of the following: CdmExecutionSettings, ResultsExecutionSettings") - } - withModuleRenv( - code = { - ############################ - # Generated by strategus - do not modify by hand - ############################ - source("Main.R") - jobContext <- readRDS(jobContextFileName) - - keyringName <- jobContext$keyringSettings$keyringName - # unlockKeyring will be injected automatically - keyringLocked <- unlockKeyring(keyringName = keyringName) - - ParallelLogger::addDefaultFileLogger(jobContext$moduleExecutionSettings$logFileName) - ParallelLogger::addDefaultFileLogger(file.path(jobContext$moduleExecutionSettings$resultsSubFolder, "log.txt")) - ParallelLogger::addDefaultErrorReportLogger(file.path(jobContext$moduleExecutionSettings$resultsSubFolder, "errorReport.R")) - - options(andromedaTempFolder = file.path(jobContext$moduleExecutionSettings$workFolder, "andromedaTemp")) - options(sqlRenderTempEmulationSchema = jobContext$moduleExecutionSettings$tempEmulationSchema) - options(databaseConnectorIntegerAsNumeric = jobContext$moduleExecutionSettings$integerAsNumeric) - options(databaseConnectorInteger64AsNumeric = jobContext$moduleExecutionSettings$integer64AsNumeric) - - if (Sys.getenv("FORCE_RENV_USE", "") == "TRUE") { - renv::use(lockfile = "renv.lock") - } - - # NOTE: injected variable isResultsExecution - will look strange outside of Strategus definition - # NOTE: retrieveConnectionDetails function is injected by withModuleRenv - if (isCdmExecution) { - connectionDetails <- retrieveConnectionDetails( - connectionDetailsReference = jobContext$moduleExecutionSettings$connectionDetailsReference, - keyringName = keyringName - ) - jobContext$moduleExecutionSettings$connectionDetails <- connectionDetails - } else { - resultsConnectionDetails <- retrieveConnectionDetails( - connectionDetailsReference = jobContext$moduleExecutionSettings$resultsConnectionDetailsReference, - keyringName = keyringName - ) - jobContext$moduleExecutionSettings$resultsConnectionDetails <- resultsConnectionDetails - } - if (keyringLocked) { - keyring::keyring_lock(keyring = keyringName) - } - message("START MODULE RUN: ", moduleName) - execute(jobContext) - message("FINISH MODULE RUN: ", moduleName) - - ParallelLogger::unregisterLogger("DEFAULT_FILE_LOGGER", silent = TRUE) - ParallelLogger::unregisterLogger("DEFAULT_ERRORREPORT_LOGGER", silent = TRUE) - writeLines("done", doneFile) - }, - tempScriptFile = tempScriptFile, - moduleFolder = moduleFolder, - injectVars = list( - doneFile = doneFile, - isCdmExecution = isCdmExecution, - jobContextFileName = jobContextFileName, - moduleName = module - ) - ) - - if (!file.exists(doneFile)) { - message <- paste( - "Module did not complete. To debug:", - sprintf(" rstudioapi::openProject('%s', newSession = TRUE)", moduleFolder), - sprintf(" file.edit('%s')", tempScriptFile), - sep = "\n" - ) - stop(message) - } - - return(list(dummy = 123)) -} diff --git a/R/Settings.R b/R/Settings.R index 5503d098..33247113 100644 --- a/R/Settings.R +++ b/R/Settings.R @@ -21,25 +21,9 @@ # carefully consider serialization and deserialization to JSON, which currently # uses custom functionality in ParallelLogger to maintain object attributes. -#' Create an empty analysis specifications object. -#' -#' @return -#' An object of type `AnalysisSpecifications`. -#' -#' @export -createEmptyAnalysisSpecificiations <- function() { - analysisSpecifications <- list( - sharedResources = list(), - moduleSpecifications = list() - ) - class(analysisSpecifications) <- "AnalysisSpecifications" - return(analysisSpecifications) -} - -#' Add shared resources to analysis specifications +#' Add shared resources (i.e. cohorts) to analysis specifications #' -#' @param analysisSpecifications An object of type `AnalysisSpecifications` as created -#' by [createEmptyAnalysisSpecificiations()]. +#' @template analysisSpecifications #' @param sharedResources An object of type `SharedResources`. #' #' @return @@ -56,11 +40,10 @@ addSharedResources <- function(analysisSpecifications, sharedResources) { return(analysisSpecifications) } -#' Add module specifications to analysis specifications +#' Add generic module specifications to analysis specifications #' -#' @param analysisSpecifications An object of type `AnalysisSpecifications` as created -#' by [createEmptyAnalysisSpecificiations()]. -#' @param moduleSpecifications An object of type `ModuleSpecifications`. +#' @template analysisSpecifications +#' @template moduleSpecifications #' #' @return #' Returns the `analysisSpecifications` object with the module specifications added. @@ -76,10 +59,187 @@ addModuleSpecifications <- function(analysisSpecifications, moduleSpecifications return(analysisSpecifications) } +#' Add Characterization module specifications to analysis specifications +#' +#' @template analysisSpecifications +#' @param moduleSpecifications Created by the \href{../../docs/reference/CharacterizationModule.html#method-CharacterizationModule-createModuleSpecifications}{\code{CharacterizationModule$createModuleSpecifications()}} function. +#' +#' @return +#' Returns the `analysisSpecifications` object with the module specifications added. +#' +#' @export +addCharacterizationModuleSpecifications <- function(analysisSpecifications, moduleSpecifications) { + return( + addAndValidateModuleSpecifications( + moduleName = "CharacterizationModule", + analysisSpecifications = analysisSpecifications, + moduleSpecifications = moduleSpecifications + ) + ) +} + +#' Add Cohort Diagnostics module specifications to analysis specifications +#' +#' @template analysisSpecifications +#' @param moduleSpecifications Created by the \href{../../docs/reference/CohortDiagnosticsModule.html#method-CohortDiagnosticsModule-createModuleSpecifications}{\code{CohortDiagnosticsModule$createModuleSpecifications()}} function. +#' +#' @return +#' Returns the `analysisSpecifications` object with the module specifications added. +#' +#' @export +addCohortDiagnosticsModuleSpecifications <- function(analysisSpecifications, moduleSpecifications) { + return( + addAndValidateModuleSpecifications( + moduleName = "CohortDiagnosticsModule", + analysisSpecifications = analysisSpecifications, + moduleSpecifications = moduleSpecifications + ) + ) +} + +#' Add Cohort Generator module specifications to analysis specifications +#' +#' @template analysisSpecifications +#' @param moduleSpecifications Created by the \href{../../docs/reference/CohortGeneratorModule.html#method-CohortGeneratorModule-createModuleSpecifications}{\code{CohortGeneratorModule$createModuleSpecifications()}} function. +#' +#' @return +#' Returns the `analysisSpecifications` object with the module specifications added. +#' +#' @export +addCohortGeneratorModuleSpecifications <- function(analysisSpecifications, moduleSpecifications) { + return( + addAndValidateModuleSpecifications( + moduleName = "CohortGeneratorModule", + analysisSpecifications = analysisSpecifications, + moduleSpecifications = moduleSpecifications + ) + ) +} + +#' Add Cohort Incidence module specifications to analysis specifications +#' +#' @template analysisSpecifications +#' @param moduleSpecifications Created by the \href{../../docs/reference/CohortIncidenceModule.html#method-CohortIncidenceModule-createModuleSpecifications}{\code{CohortIncidenceModule$createModuleSpecifications()}} function. +#' +#' @return +#' Returns the `analysisSpecifications` object with the module specifications added. +#' +#' @export +addCohortIncidenceModuleSpecifications <- function(analysisSpecifications, moduleSpecifications) { + return( + addAndValidateModuleSpecifications( + moduleName = "CohortIncidenceModule", + analysisSpecifications = analysisSpecifications, + moduleSpecifications = moduleSpecifications + ) + ) +} + +#' Add Cohort Method module specifications to analysis specifications +#' +#' @template analysisSpecifications +#' @param moduleSpecifications Created by the \href{../../docs/reference/CohortMethodModule.html#method-CohortMethodModule-createModuleSpecifications}{\code{CohortMethodModule$createModuleSpecifications()}} function. +#' +#' @return +#' Returns the `analysisSpecifications` object with the module specifications added. +#' +#' @export +addCohortMethodeModuleSpecifications <- function(analysisSpecifications, moduleSpecifications) { + return( + addAndValidateModuleSpecifications( + moduleName = "CohortMethodModule", + analysisSpecifications = analysisSpecifications, + moduleSpecifications = moduleSpecifications + ) + ) +} + +#' Add Evidence Synthesis module specifications to analysis specifications +#' +#' @template analysisSpecifications +#' @param moduleSpecifications Created by the \href{../../docs/reference/EvidenceSynthesisModule.html#method-EvidenceSynthesisModule-createModuleSpecifications}{\code{EvidenceSynthesisModule$createModuleSpecifications()}} function. +#' +#' @return +#' Returns the `analysisSpecifications` object with the module specifications added. +#' +#' @export +addEvidenceSynthesisModuleSpecifications <- function(analysisSpecifications, moduleSpecifications) { + return( + addAndValidateModuleSpecifications( + moduleName = "EvidenceSynthesisModule", + analysisSpecifications = analysisSpecifications, + moduleSpecifications = moduleSpecifications + ) + ) +} + +#' Add Patient Level Prediction module specifications to analysis specifications +#' +#' @template analysisSpecifications +#' @param moduleSpecifications Created by the \href{../../docs/reference/PatientLevelPredictionModule.html#method-PatientLevelPredictionModule-createModuleSpecifications}{\code{PatientLevelPredictionModule$createModuleSpecifications()}} function. +#' +#' @return +#' Returns the `analysisSpecifications` object with the module specifications added. +#' +#' @export +addPatientLevelPredictionModuleSpecifications <- function(analysisSpecifications, moduleSpecifications) { + return( + addAndValidateModuleSpecifications( + moduleName = "PatientLevelPredictionModule", + analysisSpecifications = analysisSpecifications, + moduleSpecifications = moduleSpecifications + ) + ) +} + +#' Add Self Controlled Case Series Module module specifications to analysis specifications +#' +#' @template analysisSpecifications +#' @param moduleSpecifications Created by the \href{../../docs/reference/SelfControlledCaseSeriesModule.html#method-SelfControlledCaseSeriesModule-createModuleSpecifications}{\code{SelfControlledCaseSeriesModule$createModuleSpecifications()}} function. +#' +#' @return +#' Returns the `analysisSpecifications` object with the module specifications added. +#' +#' @export +addSelfControlledCaseSeriesModuleSpecifications <- function(analysisSpecifications, moduleSpecifications) { + return( + addAndValidateModuleSpecifications( + moduleName = "SelfControlledCaseSeriesModule", + analysisSpecifications = analysisSpecifications, + moduleSpecifications = moduleSpecifications + ) + ) +} + +addAndValidateModuleSpecifications <- function(moduleName, analysisSpecifications, moduleSpecifications) { + moduleObj <- get(moduleName)$new() + moduleObj$validateModuleSpecifications(moduleSpecifications) + analysisSpecifications <- addModuleSpecifications( + analysisSpecifications = analysisSpecifications, + moduleSpecifications = moduleSpecifications + ) + return(analysisSpecifications) +} + + +#' Create an empty analysis specifications object. +#' +#' @return +#' An object of type `AnalysisSpecifications`. +#' +#' @export +createEmptyAnalysisSpecificiations <- function() { + analysisSpecifications <- list( + sharedResources = list(), + moduleSpecifications = list() + ) + class(analysisSpecifications) <- "AnalysisSpecifications" + return(analysisSpecifications) +} + + #' Create CDM execution settings #' -#' @param connectionDetailsReference A string that can be used to retrieve database connection details from a secure local -#' store. #' @param workDatabaseSchema A database schema where intermediate data can be stored. The user (as identified in the #' connection details) will need to have write access to this database schema. #' @param cdmDatabaseSchema The database schema containing the data in CDM format. The user (as identified in the @@ -89,22 +249,23 @@ addModuleSpecifications <- function(analysisSpecifications, moduleSpecifications #' [CohortGenerator::getCohortTableNames()] function. #' @param tempEmulationSchema Some database platforms like Oracle and Impala do not truly support temp tables. To emulate temp tables, provide a schema with write privileges where temp tables can be created. #' @param workFolder A folder in the local file system where intermediate results can be written. -#' @param resultsFolder A folder in the local file system where the module output will be written. +#' @template resultsFolder #' @param logFileName Logging information from Strategus and all modules will be located in this file. Individual modules will continue to have their own module-specific logs. By default this will be written to the root of the `resultsFolder` #' @param minCellCount The minimum number of subjects contributing to a count before it can be included #' in results. -#' @param integerAsNumeric Logical: should 32-bit integers be converted to numeric (double) values? If FALSE 32-bit integers will be represented using R's native `Integer` class. Default is TRUE -#' @param integer64AsNumeric Logical: should 64-bit integers be converted to numeric (double) values? If FALSE 64-bit integers will be represented using `bit64::integer64`. Default is TRUE -#' @param resultsConnectionDetailsReference A string that can be used to retrieve the results database connection -#' details from a secure local store. -#' @param resultsDatabaseSchema A schema where the results tables are stored +#' @param incremental This value will be passed to each module that supports execution in an incremental manner. Modules +#' and their underlying packages may use the `workFolder` contents to determine their state of execution +#' and attempt to pick up where they left off when this value is set to TRUE. +#' @param maxCores The maximum number of processing cores to use for execution. The default is to +#' use all available cores on the machine. +#' @param modulesToExecute (Optional) A vector with the list of modules to execute. When an empty vector/NULL is supplied (default), +#' all modules in the analysis specification are executed. #' #' @return #' An object of type `ExecutionSettings`. #' #' @export -createCdmExecutionSettings <- function(connectionDetailsReference, - workDatabaseSchema, +createCdmExecutionSettings <- function(workDatabaseSchema, cdmDatabaseSchema, cohortTableNames = CohortGenerator::getCohortTableNames(cohortTable = "cohort"), tempEmulationSchema = getOption("sqlRenderTempEmulationSchema"), @@ -112,12 +273,10 @@ createCdmExecutionSettings <- function(connectionDetailsReference, resultsFolder, logFileName = file.path(resultsFolder, "strategus-log.txt"), minCellCount = 5, - integerAsNumeric = getOption("databaseConnectorIntegerAsNumeric", default = TRUE), - integer64AsNumeric = getOption("databaseConnectorInteger64AsNumeric", default = TRUE), - resultsConnectionDetailsReference = NULL, - resultsDatabaseSchema = NULL) { + incremental = TRUE, + maxCores = parallel::detectCores(), + modulesToExecute = c()) { errorMessages <- checkmate::makeAssertCollection() - checkmate::assertCharacter(connectionDetailsReference, len = 1, add = errorMessages) checkmate::assertCharacter(workDatabaseSchema, len = 1, add = errorMessages) checkmate::assertCharacter(cdmDatabaseSchema, len = 1, add = errorMessages) checkmate::assertList(cohortTableNames, add = errorMessages) @@ -125,10 +284,9 @@ createCdmExecutionSettings <- function(connectionDetailsReference, checkmate::assertCharacter(resultsFolder, len = 1, add = errorMessages) checkmate::assertCharacter(logFileName, len = 1, add = errorMessages) checkmate::assertInt(minCellCount, add = errorMessages) - checkmate::assertLogical(integerAsNumeric, max.len = 1, add = errorMessages) - checkmate::assertLogical(integer64AsNumeric, max.len = 1, add = errorMessages) - checkmate::assertCharacter(resultsConnectionDetailsReference, null.ok = TRUE, add = errorMessages) - checkmate::assertCharacter(resultsDatabaseSchema, null.ok = TRUE, add = errorMessages) + checkmate::assertLogical(incremental, add = errorMessages) + checkmate::assertInt(maxCores, add = errorMessages) + checkmate::assertVector(modulesToExecute, null.ok = TRUE, add = errorMessages) checkmate::reportAssertions(collection = errorMessages) # Normalize paths to convert relative paths to absolute paths @@ -136,59 +294,46 @@ createCdmExecutionSettings <- function(connectionDetailsReference, resultsFolder <- normalizePath(resultsFolder, mustWork = F) logFileName <- normalizePath(logFileName, mustWork = F) - executionSettings <- list( - connectionDetailsReference = connectionDetailsReference, - workDatabaseSchema = workDatabaseSchema, - cdmDatabaseSchema = cdmDatabaseSchema, - cohortTableNames = cohortTableNames, - tempEmulationSchema = tempEmulationSchema, - workFolder = workFolder, - resultsFolder = resultsFolder, - logFileName = logFileName, - minCellCount = minCellCount, - integerAsNumeric = integerAsNumeric, - integer64AsNumeric = integer64AsNumeric, - resultsConnectionDetailsReference = resultsConnectionDetailsReference, - resultsDatabaseSchema = resultsDatabaseSchema - ) + executionSettings <- list() + for (name in names(formals(createCdmExecutionSettings))) { + executionSettings[[name]] <- get(name) + } class(executionSettings) <- c("CdmExecutionSettings", "ExecutionSettings") return(executionSettings) } #' Create Results execution settings #' -#' @param resultsConnectionDetailsReference A string that can be used to retrieve the results database connection -#' details from a secure local store. -#' @param resultsDatabaseSchema A schema where the results tables are stored +#' @template resultsDatabaseSchema #' @param workFolder A folder in the local file system where intermediate results can be written. -#' @param resultsFolder A folder in the local file system where the module output will be written. +#' @template resultsFolder #' @param logFileName Logging information from Strategus and all modules will be located in this file. Individual modules will continue to have their own module-specific logs. By default this will be written to the root of the `resultsFolder` #' @param minCellCount The minimum number of subjects contributing to a count before it can be included #' in results. -#' @param integerAsNumeric Logical: should 32-bit integers be converted to numeric (double) values? If FALSE 32-bit integers will be represented using R's native `Integer` class. Default is TRUE -#' @param integer64AsNumeric Logical: should 64-bit integers be converted to numeric (double) values? If FALSE 64-bit integers will be represented using `bit64::integer64`. Default is TRUE +#' @param maxCores The maximum number of processing cores to use for execution. The default is to +#' use all available cores on the machine. +#' @param modulesToExecute (Optional) A vector with the list of modules to execute. When an empty vector/NULL is supplied (default), +#' all modules in the analysis specification are executed. #' #' @return #' An object of type `ExecutionSettings`. #' #' @export -createResultsExecutionSettings <- function(resultsConnectionDetailsReference, - resultsDatabaseSchema, +createResultsExecutionSettings <- function(resultsDatabaseSchema, workFolder, resultsFolder, logFileName = file.path(resultsFolder, "strategus-log.txt"), minCellCount = 5, - integerAsNumeric = getOption("databaseConnectorIntegerAsNumeric", default = TRUE), - integer64AsNumeric = getOption("databaseConnectorInteger64AsNumeric", default = TRUE)) { + maxCores = parallel::detectCores(), + modulesToExecute = c()) { errorMessages <- checkmate::makeAssertCollection() - checkmate::assertCharacter(resultsConnectionDetailsReference, len = 1, add = errorMessages) checkmate::assertCharacter(resultsDatabaseSchema, len = 1, add = errorMessages) checkmate::assertCharacter(workFolder, len = 1, add = errorMessages) checkmate::assertCharacter(resultsFolder, len = 1, add = errorMessages) checkmate::assertCharacter(logFileName, len = 1, add = errorMessages) checkmate::assertInt(minCellCount, add = errorMessages) - checkmate::assertLogical(integerAsNumeric, max.len = 1, add = errorMessages) - checkmate::assertLogical(integer64AsNumeric, max.len = 1, add = errorMessages) + checkmate::assertInt(maxCores, add = errorMessages) + checkmate::assertVector(modulesToExecute, null.ok = TRUE, add = errorMessages) checkmate::reportAssertions(collection = errorMessages) # Normalize paths to convert relative paths to absolute paths @@ -196,193 +341,45 @@ createResultsExecutionSettings <- function(resultsConnectionDetailsReference, resultsFolder <- normalizePath(resultsFolder, mustWork = F) logFileName <- normalizePath(logFileName, mustWork = F) - executionSettings <- list( - resultsConnectionDetailsReference = resultsConnectionDetailsReference, - resultsDatabaseSchema = resultsDatabaseSchema, - workFolder = workFolder, - resultsFolder = resultsFolder, - logFileName = logFileName, - minCellCount = minCellCount, - integerAsNumeric = integerAsNumeric, - integer64AsNumeric = integer64AsNumeric - ) + executionSettings <- list() + for (name in names(formals(createResultsExecutionSettings))) { + executionSettings[[name]] <- get(name) + } class(executionSettings) <- c("ResultsExecutionSettings", "ExecutionSettings") return(executionSettings) } - - -# Note: assuming connectionDetails objects remain stable across the various module -# versions. - -#' Store connection details in a secure location -#' -#' @param connectionDetails An object of type `connectionDetails` as created by the -#' [DatabaseConnector::createConnectionDetails()] function. -#' @param connectionDetailsReference A string that can be used to retrieve the settings from -#' the secure store. -#' -#' @template keyringName +#' Create Results Data Model Settings #' -#' @seealso [retrieveConnectionDetails()] -#' -#' @return -#' Does not return anything. Is called for the side effect of having the connection details -#' stored. -#' -#' @export -storeConnectionDetails <- function(connectionDetails, connectionDetailsReference, keyringName = NULL) { - errorMessages <- checkmate::makeAssertCollection() - # Get the keyring list and verify that the keyring specified exists. - # In the case of the default NULL keyring, this will be represented as an empty - # string in the keyring list - keyringList <- keyring::keyring_list() - if (is(connectionDetails, "connectionDetails")) { - checkmate::assertClass(connectionDetails, "connectionDetails", add = errorMessages) - } else { - checkmate::assertClass(connectionDetails, "ConnectionDetails", add = errorMessages) - } - checkmate::assertCharacter(connectionDetailsReference, len = 1, add = errorMessages) - checkmate::assertChoice(x = keyringName, choices = keyringList$keyring, null.ok = TRUE, add = errorMessages) - checkmate::reportAssertions(collection = errorMessages) - - # Evaluate functions used to secure details to allow serialization: - for (i in 1:length(connectionDetails)) { - if (is.function(connectionDetails[[i]])) { - detail <- connectionDetails[[i]]() - if (is.null(detail)) { - connectionDetails[[i]] <- .nullList() # Fixes Issue #74 - } else { - connectionDetails[[i]] <- connectionDetails[[i]]() - } - } - } - connectionDetails <- ParallelLogger::convertSettingsToJson(connectionDetails) - # If the keyring is locked, unlock it, set the value and then re-lock it - keyringLocked <- unlockKeyring(keyringName = keyringName) - keyring::key_set_with_value(connectionDetailsReference, password = connectionDetails, keyring = keyringName) - if (keyringLocked) { - keyring::keyring_lock(keyring = keyringName) - } - invisible(NULL) -} - -#' Retrieve connection details from the secure location -#' -#' @param connectionDetailsReference A string that can be used to retrieve the settings from -#' the secure store. -#' -#' @template keyringName +#' @description +#' The results data model settings are used to create the results data +#' model and to upload results. #' -#' @seealso [storeConnectionDetails()] +#' @template resultsDatabaseSchema +#' @template resultsFolder +#' @param logFileName Log location for data model operations #' #' @return -#' Returns an object of type `connectionDetails`. +#' An object of type `ResultsDataModelSettings` #' #' @export -retrieveConnectionDetails <- function(connectionDetailsReference, keyringName = NULL) { - keyringList <- keyring::keyring_list() +createResultsDataModelSettings <- function(resultsDatabaseSchema, + resultsFolder, + logFileName = file.path(resultsFolder, "strategus-results-data-model-log.txt")) { errorMessages <- checkmate::makeAssertCollection() - checkmate::assertCharacter(connectionDetailsReference, len = 1, add = errorMessages) - checkmate::assertLogical(x = (is.null(keyringName) || keyringName %in% keyringList$keyring), add = errorMessages) + checkmate::assertCharacter(resultsDatabaseSchema, len = 1, add = errorMessages) + checkmate::assertCharacter(resultsFolder, len = 1, add = errorMessages) + checkmate::assertCharacter(logFileName, len = 1, add = errorMessages) checkmate::reportAssertions(collection = errorMessages) - if (!connectionDetailsReference %in% keyring::key_list(keyring = keyringName)$service) { - stop("Connection details with connectionDetailsReference = \"", connectionDetailsReference, "\" were not found in your keyring. Please check that you have used the Strategus storeConnectionDetails function to save your connection details with this connectionDetailsReference name.") - } - - # If the keyring is locked, unlock it, set the value and then re-lock it - keyringLocked <- unlockKeyring(keyringName = keyringName) - - connectionDetails <- keyring::key_get(connectionDetailsReference, keyring = keyringName) - connectionDetails <- ParallelLogger::convertJsonToSettings(connectionDetails) - - # Ensure that NA values are converted to NULL prior to calling - # DatabaseConnector. To do this, we'll construct a new connectionDetails - # list from keyring where the connectionDetails are NOT NA. This will - # allow for calling DatabaseConnector::createConnectionDetails with - # NULL values where NAs are present in the serialized version of the - # connectionDetails from keyring. - connectionDetailsConstructedFromKeyring <- list() - for (i in 1:length(connectionDetails)) { - if (isFALSE(is.na(connectionDetails[[i]]))) { - connectionDetailsConstructedFromKeyring[names(connectionDetails)[i]] <- connectionDetails[[i]] - } - } - - connectionDetails <- do.call(DatabaseConnector::createConnectionDetails, connectionDetailsConstructedFromKeyring) - - if (keyringLocked) { - keyring::keyring_lock(keyring = keyringName) - } - - return(connectionDetails) -} - -#' Provides a list of HADES modules to run through Strategus -#' -#' @description -#' This function provides a list of modules and their locations -#' that may be used with Strategus. -#' -#' @return -#' A data.frame() of modules that work with Strategus. This will contain: -#' module = The name of the module -#' version = The version of the module -#' remote_repo = The remote location of the module (i.e. github.com) -#' remote_username = The organization of the module (i.e. OHDSI) -#' module_type = 'cdm' or 'results'. 'cdm' refers to modules that are designed to work against -#' patient level data in the OMOP CDM format. 'results' refers to modules that are designed -#' to work against a results database containing output from a 'cdm' module. -#' -#' @export -getModuleList <- function() { - moduleList <- CohortGenerator::readCsv(file = system.file("csv/modules.csv", - package = "Strategus", - mustWork = TRUE - )) - return(moduleList) -} - -#' Helper function to unlock a keyring -#' -#' @description -#' This helper function is used to unlock a keyring by using the password -#' stored in Sys.getenv("STRATEGUS_KEYRING_PASSWORD"). It will alert -#' the user if the environment variable with the password is not set. -#' -#' @template keyringName -#' -#' @return -#' Returns TRUE if the keyring was unlocked using the password otherwise -#' it returns FALSE -#' -#' @export -unlockKeyring <- function(keyringName) { - # If the keyring is locked, unlock it, set the value and then re-lock it - keyringLocked <- keyring::keyring_is_locked(keyring = keyringName) - if (keyringLocked) { - x <- Sys.getenv("STRATEGUS_KEYRING_PASSWORD") - if (length(x) == 0 || x == "") { - stop(paste0("STRATEGUS_KEYRING_PASSWORD NOT FOUND. STRATEGUS_KEYRING_PASSWORD must be set using Sys.setenv(STRATEGUS_KEYRING_PASSWORD = \"\") to unlock the keyring: ", keyringName)) - } - keyring::keyring_unlock(keyring = keyringName, password = Sys.getenv("STRATEGUS_KEYRING_PASSWORD")) - } - return(keyringLocked) -} + # Normalize paths to convert relative paths to absolute paths + resultsFolder <- normalizePath(resultsFolder, mustWork = F) + logFileName <- normalizePath(logFileName, mustWork = F) -#' @keywords internal -.checkModuleFolderSetting <- function(x) { - if (length(x) == 0 || x == "") { - return(paste0("INSTANTIATED_MODULES_FOLDER environment variable has not been set. INSTANTIATED_MODULES_FOLDER must be set using Sys.setenv(INSTANTIATED_MODULES_FOLDER = \"/somepath\")")) - } else { - return(TRUE) + executionSettings <- list() + for (name in names(formals(createResultsDataModelSettings))) { + executionSettings[[name]] <- get(name) } -} - -#' Used when serializing connection details to retain NULL values -#' -#' @keywords internal -.nullList <- function() { - invisible(list(NULL)) + class(executionSettings) <- c("ResultsDataModelSettings") + return(executionSettings) } diff --git a/R/ShareResults.R b/R/ShareResults.R index d6f1da9a..fbdb4088 100644 --- a/R/ShareResults.R +++ b/R/ShareResults.R @@ -6,8 +6,7 @@ #' relative paths to the root of the `resultsFolder` #' which is generally found in `executionSettings$resultsFolder`. #' -#' @param resultsFolder The folder holding the study results. This is found in -#' `executionSettings$resultsFolder`. +#' @template resultsFolder #' #' @param zipFile The path to the zip file to be created. #' diff --git a/R/Strategus.R b/R/Strategus.R index c3315edc..3c94d018 100644 --- a/R/Strategus.R +++ b/R/Strategus.R @@ -21,7 +21,6 @@ #' @import dplyr #' @import CohortGenerator #' @import DatabaseConnector +#' @import R6 #' @importFrom methods is NULL - -assertModulesFolderSetting <- checkmate::makeAssertionFunction(.checkModuleFolderSetting) diff --git a/R/StrategusModule.R b/R/StrategusModule.R new file mode 100644 index 00000000..8e4f7d49 --- /dev/null +++ b/R/StrategusModule.R @@ -0,0 +1,296 @@ +# Job Context ------------- +#' @title Job context holds the elements of the analysis specification +#' and execution settings necessary to execute a module. +#' @description +#' This is an internal class used by the StrategusModule (and child classes) +#' execute function +#' @noRd +#' @keywords internal +JobContext <- R6::R6Class( + classname = "JobContext", + public = list( + #' @field sharedResources Shared resources for execution + #' TODO: Revisit to break this into fields for cohorts, subsets, + #' negative controls, + sharedResources = list(), + #' @field settings Module settings + settings = list(), + #' @field moduleExecutionSettings Module execution settings + moduleExecutionSettings = list() + ) +) + +# StrategusModule ------------- +#' @title StrategusModule defines the base class for each HADES module +#' @export +#' @description +#' StrategusModule serves as an internal base class that defines the core +#' functions and structure to be inherited and implemented by any specific +#' HADES module. It provides a standardized framework for creating modular +#' components within the Strategus pipeline. +StrategusModule <- R6::R6Class( + classname = "StrategusModule", + public = list( + #' @field moduleName The name of the module taken from the class name. + #' This is set in the constructor of the class. + moduleName = "", + #' @field moduleClassName The class name that identifies + #' the module specifications in the overall analysis specification. + #' This is set in the constructor of the class. + moduleClassName = "", + #' @field internalModuleSpecificationClassName A constant value. + #' The base class name that identifies a module specification + #' in the analysis specification. + internalModuleSpecificationClassName = "ModuleSpecifications", + #' @field internalSharedResourcesClassName A constant value. The class name + #' that identifies the shared resources section in the overall analysis + #' specification. + internalSharedResourcesClassName = "SharedResources", + #' @description Initialize the module + initialize = function() { + self$moduleName <- class(self)[[1]] + self$moduleClassName <- paste0(self$moduleName, "Specifications") + }, + #' @description Executes the module + #' @template connectionDetails + #' @template analysisSpecifications + #' @template executionSettings + execute = function(connectionDetails, analysisSpecifications, executionSettings) { + errorMessages <- checkmate::makeAssertCollection() + checkmate::assertClass(connectionDetails, "ConnectionDetails", add = errorMessages) + checkmate::assertClass(analysisSpecifications, "AnalysisSpecifications", add = errorMessages) + checkmate::assertClass(executionSettings, "ExecutionSettings", add = errorMessages) + checkmate::reportAssertions(collection = errorMessages) + + # Setup the job context + private$.createJobContext(analysisSpecifications, executionSettings) + private$.message("EXECUTING: ", self$moduleName) + }, + #' @description Create the results data model for the module + #' @template resultsConnectionDetails + #' @template resultsDatabaseSchema + #' @template tablePrefix + createResultsDataModel = function(resultsConnectionDetails, resultsDatabaseSchema, tablePrefix = "") { + errorMessages <- checkmate::makeAssertCollection() + checkmate::assertClass(resultsConnectionDetails, "ConnectionDetails", add = errorMessages) + checkmate::assertCharacter(resultsDatabaseSchema, len = 1, add = errorMessages) + checkmate::reportAssertions(collection = errorMessages) + private$.message("CREATE RESULTS DATA MODEL: ", self$moduleName) + }, + #' @description Get the results data model specification for the module + #' @template tablePrefix + getResultsDataModelSpecification = function(tablePrefix = "") { + }, + #' @description Upload the results for the module + #' @template resultsConnectionDetails + #' @template analysisSpecifications + #' @template resultsDataModelSettings + uploadResults = function(resultsConnectionDetails, analysisSpecifications, resultsDataModelSettings) { + errorMessages <- checkmate::makeAssertCollection() + checkmate::assertClass(resultsConnectionDetails, "ConnectionDetails", add = errorMessages) + checkmate::assertClass(resultsDataModelSettings, "ResultsDataModelSettings", add = errorMessages) + checkmate::reportAssertions(collection = errorMessages) + + # Setup the job context + private$.createJobContext(analysisSpecifications, resultsDataModelSettings) + private$.message("UPLOAD RESULTS: ", self$moduleName) + }, + #' @description Base function for creating the module settings object. + #' Each module will have its own implementation and this base class method + #' will be used to ensure the class of the specifications is set properly. + #' @template moduleSpecifications + createModuleSpecifications = function(moduleSpecifications) { + moduleSpecifications <- list( + module = self$moduleName, + settings = moduleSpecifications + ) + class(moduleSpecifications) <- c(self$internalModuleSpecificationClassName, self$moduleClassName) + return(moduleSpecifications) + }, + #' @description Base function for creating the shared resources settings object. + #' Each module will have its own implementation if it needs to create + #' a shared resource. + #' @param className The class name of the shared resources specifications + #' @param sharedResourcesSpecifications The shared resources specifications + createSharedResourcesSpecifications = function(className, sharedResourcesSpecifications) { + class(sharedResourcesSpecifications) <- c(className, self$internalSharedResourcesClassName) + return(sharedResourcesSpecifications) + }, + #' @description Base function for validating the module settings object. + #' Each module will have its own implementation and this base class method + #' will be used to ensure the module specifications are valid ahead of + #' execution + #' @template moduleSpecifications + validateModuleSpecifications = function(moduleSpecifications) { + errorMessages <- checkmate::makeAssertCollection() + checkmate::assertClass(moduleSpecifications, self$internalModuleSpecificationClassName) + checkmate::assertClass(moduleSpecifications, self$moduleClassName) + checkmate::reportAssertions(collection = errorMessages) + }, + #' @description Base function for validating the shared resources + #' specification settings object. Each module will have its own + #' implementation and this base class method will be used to ensure + #' the module specifications are valid ahead of execution + #' @param className The class name of the shared resources specifications + #' @param sharedResourcesSpecifications The shared resources specifications + validateSharedResourcesSpecifications = function(className, sharedResourcesSpecifications) { + errorMessages <- checkmate::makeAssertCollection() + checkmate::assertClass(sharedResourcesSpecifications, self$internalSharedResourcesClassName) + checkmate::assertClass(sharedResourcesSpecifications, className) + checkmate::reportAssertions(collection = errorMessages) + } + ), + private = list( + jobContext = JobContext$new(), + .message = function(...) { + rlang::inform(paste0(...)) + }, + .createJobContext = function(analysisSpecifications, executionSettings) { + # Make sure this is created each call + private$jobContext <- JobContext$new() + # Get the moduleSpecification from the analysis specification + # for the current class name. + moduleSpecification <- private$.getModuleSpecification( + analysisSpecifications = analysisSpecifications, + moduleName = self$moduleName + ) + if (is.null(moduleSpecification)) { + stop(paste0(self$moduleName, " settings could not be found in the analysis specification.")) + } + private$jobContext$settings <- moduleSpecification$settings + + # Assemble the job context from the analysis specification + # for the given module. + private$jobContext$sharedResources <- analysisSpecifications$sharedResources + private$jobContext$moduleExecutionSettings <- executionSettings + private$jobContext$moduleExecutionSettings$resultsSubFolder <- file.path(private$jobContext$moduleExecutionSettings$resultsFolder, self$moduleName) + + if (is(private$jobContext$moduleExecutionSettings, "ExecutionSettings")) { + private$jobContext$moduleExecutionSettings$workSubFolder <- file.path(private$jobContext$moduleExecutionSettings$workFolder, self$moduleName) + } + }, + .getModuleSpecification = function(analysisSpecifications, moduleName) { + moduleSpecification <- NULL + for (i in 1:length(analysisSpecifications$moduleSpecifications)) { + curModuleName <- analysisSpecifications$moduleSpecifications[[i]]$module + if (tolower(curModuleName) == tolower(moduleName)) { + moduleSpecification <- analysisSpecifications$moduleSpecifications[[i]] + } + } + return(moduleSpecification) + }, + .getSharedResourceByClassName = function(sharedResources, className) { + returnVal <- NULL + for (i in 1:length(sharedResources)) { + if (className %in% class(sharedResources[[i]])) { + returnVal <- sharedResources[[i]] + break + } + } + invisible(returnVal) + }, + .createCohortDefinitionSetFromJobContext = function(generateStats) { + jobContext <- private$jobContext + cohortDefinitions <- list() + if (length(jobContext$sharedResources) <= 0) { + stop("No shared resources found") + } + cohortDefinitionSharedResource <- private$.getSharedResourceByClassName( + sharedResources = jobContext$sharedResources, + class = "CohortDefinitionSharedResources" + ) + if (is.null(cohortDefinitionSharedResource)) { + stop("Cohort definition shared resource not found!") + } + if ((is.null(cohortDefinitionSharedResource$subsetDefs) && !is.null(cohortDefinitionSharedResource$cohortSubsets)) || + (!is.null(cohortDefinitionSharedResource$subsetDefs) && is.null(cohortDefinitionSharedResource$cohortSubsets))) { + stop("Cohort subset functionality requires specifying cohort subset definition & cohort subset identifiers.") + } + cohortDefinitionSet <- private$.getCohortDefinitionSetFromSharedResource( + cohortDefinitionSharedResource = cohortDefinitionSharedResource, + generateStats = generateStats + ) + return(cohortDefinitionSet) + }, + .getCohortDefinitionSetFromSharedResource = function(cohortDefinitionSharedResource, generateStats) { + cohortDefinitions <- cohortDefinitionSharedResource$cohortDefinitions + if (length(cohortDefinitions) <= 0) { + stop("No cohort definitions found") + } + cohortDefinitionSet <- CohortGenerator::createEmptyCohortDefinitionSet() + for (i in 1:length(cohortDefinitions)) { + cohortJson <- cohortDefinitions[[i]]$cohortDefinition + cohortExpression <- CirceR::cohortExpressionFromJson(cohortJson) + cohortSql <- CirceR::buildCohortQuery(cohortExpression, options = CirceR::createGenerateOptions(generateStats = generateStats)) + cohortDefinitionSet <- rbind(cohortDefinitionSet, data.frame( + cohortId = as.double(cohortDefinitions[[i]]$cohortId), + cohortName = cohortDefinitions[[i]]$cohortName, + sql = cohortSql, + json = cohortJson, + stringsAsFactors = FALSE + )) + } + + if (length(cohortDefinitionSharedResource$subsetDefs)) { + subsetDefinitions <- lapply(cohortDefinitionSharedResource$subsetDefs, CohortGenerator::CohortSubsetDefinition$new) + for (subsetDef in subsetDefinitions) { + ind <- which(sapply(cohortDefinitionSharedResource$cohortSubsets, function(y) subsetDef$definitionId %in% y$subsetId)) + targetCohortIds <- unlist(lapply(cohortDefinitionSharedResource$cohortSubsets[ind], function(y) y$targetCohortId)) + cohortDefinitionSet <- CohortGenerator::addCohortSubsetDefinition( + cohortDefinitionSet = cohortDefinitionSet, + cohortSubsetDefintion = subsetDef, + targetCohortIds = targetCohortIds + ) + } + } + + return(cohortDefinitionSet) + }, + .createNegativeControlOutcomeSettingsFromJobContext = function() { + jobContext <- private$jobContext + negativeControlSharedResource <- private$.getSharedResourceByClassName( + sharedResources = jobContext$sharedResources, + className = "NegativeControlOutcomeSharedResources" + ) + if (!is.null(negativeControlSharedResource)) { + negativeControlOutcomes <- negativeControlSharedResource$negativeControlOutcomes$negativeControlOutcomeCohortSet + if (length(negativeControlOutcomes) <= 0) { + stop("Negative control outcome shared resource found but no negative control outcomes were provided.") + } + negativeControlOutcomeCohortSet <- CohortGenerator::createEmptyNegativeControlOutcomeCohortSet() + for (i in 1:length(negativeControlOutcomes)) { + nc <- negativeControlOutcomes[[i]] + negativeControlOutcomeCohortSet <- rbind( + negativeControlOutcomeCohortSet, + data.frame( + cohortId = as.numeric(nc$cohortId), + cohortName = nc$cohortName, + outcomeConceptId = as.numeric(nc$outcomeConceptId) + ) + ) + } + invisible(list( + cohortSet = negativeControlOutcomeCohortSet, + occurrenceType = negativeControlSharedResource$negativeControlOutcomes$occurrenceType, + detectOnDescendants = negativeControlSharedResource$negativeControlOutcomes$detectOnDescendants + )) + } else { + invisible(list( + cohortSet = NULL, + occurrenceType = "all", + detectOnDescendants = FALSE + )) + } + }, + .validateCdmExecutionSettings = function(executionSettings) { + errorMessages <- checkmate::makeAssertCollection() + checkmate::assertClass(executionSettings, "CdmExecutionSettings", add = errorMessages) + checkmate::assertInt(executionSettings$maxCores, lower = 1, upper = parallel::detectCores()) + }, + .validateResultsExecutionSettings = function(executionSettings) { + errorMessages <- checkmate::makeAssertCollection() + checkmate::assertClass(executionSettings, "ResultsExecutionSettings", add = errorMessages) + checkmate::assertInt(executionSettings$maxCores, lower = 1, upper = parallel::detectCores()) + } + ) +) diff --git a/README.md b/README.md index 84782492..f83814fb 100644 --- a/README.md +++ b/README.md @@ -4,16 +4,15 @@ Strategus [![Build Status](https://github.com/OHDSI/Strategus/actions/workflows/R_CMD_check_Hades.yaml/badge.svg?branch=main)](https://github.com/OHDSI/Strategus/actions/workflows/R_CMD_check_Hades.yaml/badge.svg?branch=main) [![codecov.io](https://codecov.io/github/OHDSI/Strategus/coverage.svg?branch=main)](https://codecov.io/github/OHDSI/Strategus?branch=main) - Introduction ============ -Strategus is an R package for coordinating and executing analytics using HADES modules. Please see the [Introduction To Strategus](https://ohdsi.github.io/Strategus/articles/IntroductionToStrategus.html) for more details. +Strategus is an R package for coordinating and executing analytics using [OHDSI HADES](https://ohdsi.github.io/Hades/) modules. Please see the [Introduction To Strategus](https://ohdsi.github.io/Strategus/articles/IntroductionToStrategus.html) for more details. Features ======== - Design study analysis specifications - Execute study analysis specifications against the OMOP CDM -- Modular design for encapsulating analytics [vignette](https://ohdsi.github.io/Strategus/articles/CreatingModules.html) +- Upload and review study results Technology ============ @@ -33,23 +32,13 @@ Installation install.packages("remotes") remotes::install_github("ohdsi/Strategus") ``` -3. If using Linux, please refer to the [keyring Linux secret service setup](https://r-lib.github.io/keyring/index.html#linux) as this is required to execute studies using Strategus. In addition to those instructions, members of the OHDSI community have shared the following guidance: - -Run in a terminal the following before installing keyring: - -```bash -sudo yum install libsodium libsodium-devel -sudo yum install libsecret libsecret-devel -sudo chmod 777 /home/idies/.config -``` - User Documentation ================== Documentation can be found on the [package website](https://ohdsi.github.io/Strategus). PDF versions of the documentation are also available: -* Package manual: [Strategus.pdf](https://raw.githubusercontent.com/OHDSI/Strategus/main/extras/Strategus.pdf) -* Vignette: [Creating Strategus Modules](https://github.com/OHDSI/Strategus/raw/main/inst/doc/CreatingModules.pdf) +- Package manual: [Strategus.pdf](https://raw.githubusercontent.com/OHDSI/Strategus/main/extras/Strategus.pdf) +- Vignette: [Creating HADES Modules](https://github.com/OHDSI/Strategus/raw/main/inst/doc/CreatingModules.pdf) Support ======= diff --git a/Strategus.Rproj b/Strategus.Rproj index 3edb226c..69743d80 100644 --- a/Strategus.Rproj +++ b/Strategus.Rproj @@ -16,6 +16,7 @@ AutoAppendNewline: Yes StripTrailingWhitespace: Yes BuildType: Package +PackageUseDevtools: Yes PackageInstallArgs: --no-multiarch --with-keep.source PackageBuildArgs: --resave-data PackageCheckArgs: --no-manual --no-build-vignettes diff --git a/_pkgdown.yml b/_pkgdown.yml index 885ee2a4..843cd5d7 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -1,17 +1,119 @@ +url: https://ohdsi.github.io/Strategus/ + template: - params: + bootstrap: 5 + bslib: bootswatch: cosmo + includes: + in_header: home: links: - text: Ask a question href: http://forums.ohdsi.org +reference: + - title: "Create analysis specifications" + desc: > + Functions for creating the analysis specification to execute. An analysis + specification includes one or more Strategus HADES module settings which + are added to the analysis specification. + contents: + - addCharacterizationModuleSpecifications + - addCohortDiagnosticsModuleSpecifications + - addCohortGeneratorModuleSpecifications + - addCohortIncidenceModuleSpecifications + - addCohortMethodeModuleSpecifications + - addEvidenceSynthesisModuleSpecifications + - addModuleSpecifications + - addPatientLevelPredictionModuleSpecifications + - addSelfControlledCaseSeriesModuleSpecifications + - addSharedResources + - createEmptyAnalysisSpecificiations + + - title: "Executing a study" + desc: > + These functions are used to create the settings necessary to execute + a study as defined by the contents of the analysis specification. + contents: + - execute + - createCdmExecutionSettings + - createResultsExecutionSettings + - getCdmDatabaseMetaData + + - title: "HADES Modules" + - subtitle: "OMOP CDM HADES Modules" + desc: > + These modules are designed to run against your OMOP CDM to carry + out their analyses. + contents: + - CharacterizationModule + - CohortDiagnosticsModule + - CohortGeneratorModule + - CohortIncidenceModule + - CohortMethodModule + - PatientLevelPredictionModule + - SelfControlledCaseSeriesModule + - subtitle: "Results HADES Modules" + desc: > + These modules are designed to run against results that are produced + by one or more OMOP CDM HADES Modules. Results must be stored in + a PostgreSQL database. + contents: + - EvidenceSynthesisModule + + - title: "Results Data Model Creation & Upload" + desc: > + These functions are used to create the PostgreSQL results data model + tables and to upload results produced by the HADES modules. + contents: + - createResultDataModel + - createResultsDataModelSettings + - uploadResults + + - title: "Sharing results" + desc: > + These functions are used to prepare results to share with a + network study coordinator + contents: + - zipResults + + - title: "Internal R6 Class" + desc: > + This is a list of internal classes used by Strategus developers + contents: + - StrategusModule + navbar: + bg: dark structure: + left: + - reference + - articles + - changelog + - resultsmodel right: [hades, github] components: + reference: + text: Reference + href: reference/index.html + changelog: + text: Changelog + href: news/index.html + resultsmodel: + text: Results model documentation + href: results-schema/index.html hades: text: hadesLogo href: https://ohdsi.github.io/Hades + aria-label: hadesLogo + +articles: +- title: Articles + navbar: ~ + contents: + - IntroductionToStrategus + - CreatingAnalysisSpecification + - ExecuteStrategus + - WorkingWithResults diff --git a/docs/404.html b/docs/404.html deleted file mode 100644 index a68b54eb..00000000 --- a/docs/404.html +++ /dev/null @@ -1,127 +0,0 @@ - - - - - - - -Page not found (404) • Strategus - - - - - - - - - - - -
-
- - - - -
-
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-

Page not found (404)

-
- -Content not found. Please use links in the navbar. - -
- - - -
- - - -
-

-

Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

-
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-

Site built with pkgdown 2.0.9.

-
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- - - - - - - - diff --git a/docs/articles/CreatingAnalysisSpecification.html b/docs/articles/CreatingAnalysisSpecification.html deleted file mode 100644 index e2cef9fa..00000000 --- a/docs/articles/CreatingAnalysisSpecification.html +++ /dev/null @@ -1,617 +0,0 @@ - - - - - - - -Creating Analysis Specification • Strategus - - - - - - - - - - - - -
-
- - - - -
-
-
-

Creating Analysis Specification

-

Anthony G. -Sena

- -

2024-06-04

- - Source: vignettes/CreatingAnalysisSpecification.Rmd - - -
- - - -
-

Creating an analysis specification -

-

This walk through will show how to use Strategus to -define an analysis specification on an example study using cohorts from -the example problem What is the risk of gastrointestinal (GI) bleed -in new users of celecoxib compared to new users of diclofenac? as -described in the Book -Of OHDSI Chapter 12 on Population Level Estimation

-
-

Setting up your R environment -

-

To start, we must install the HADES libraries in order to -create the settings for the analysis specification. The following script -will install the necessary HADES packages for this vignette.

-
-# Install correct versions of HADES packages
-remotes::install_github("ohdsi/CohortGenerator", ref = "v0.9.0")
-remotes::install_github("ohdsi/CohortDiagnostics", ref = "v3.2.5")
-remotes::install_github("ohdsi/Characterization", ref = "v0.2.0")
-remotes::install_github("ohdsi/CohortIncidence", ref = "v3.3.0")
-remotes::install_github("ohdsi/CohortMethod", ref = "v5.3.0")
-remotes::install_github("ohdsi/SelfControlledCaseSeries", ref = "v5.2.0")
-remotes::install_github("ohdsi/PatientLevelPrediction", ref = "v6.3.6")
-
-
-

Cohorts for the study -

-

To start, we’ll need to define cohorts and negative control outcomes -to use in our example analysis specification. We’ve included the cohorts -and negative control outcomes in the Strategus package for -this example and the code below will load them for use when assembling -the analysis specification.

-
-library(CohortGenerator)
-cohortDefinitionSet <- getCohortDefinitionSet(
-  settingsFileName = "testdata/Cohorts.csv",
-  jsonFolder = "testdata/cohorts",
-  sqlFolder = "testdata/sql",
-  packageName = "Strategus"
-)
-ncoCohortSet <- readCsv(file = system.file("testdata/negative_controls_concept_set.csv",
-  package = "Strategus"
-))
-
-

Cohort Definitions & Negative Control Outcomes -

-

This is the list of cohort definitions we will use when assembling -the analysis specification for Strategus.

-
-kable(cohortDefinitionSet[, c("cohortId", "cohortName")])
-

And the negative control outcomes when performing empirical -calibration.

-
-kable(ncoCohortSet)
-
-
-
-
-

Assembling HADES modules -

-

The building blocks of the Strategus analysis -specification are HADES modules. For purposes of this walk through, a -module is a specific analytic task you would like to perform. As shown -in the subsequent sections, the high-level pattern for using a module -consists of:

-
    -
  1. Download the module’s settings function.
    2. -
  2. Create the module specifications using the settings function(s) from -the module
    3. -
  3. Compose the analysis pipeline from one or more module settings
    4. -
-
-

CohortGenerator Module Settings -

-

The following code downloads the settings functions from the -CohortGeneratorModule which then activates some additional -functions we can use for creating the analysis specification. In the -analysis specification, we will add the cohort definitions and negative -control outcomes to the sharedResources section since these -elements may be used by any of the HADES modules. To do this, we will -use the createCohortSharedResourceSpecifications and -createNegativeControlOutcomeCohortSharedResourceSpecifications -functions respectively. In addition, we will use the -cohortGeneratorModuleSpecifications function to specify the -cohort generation settings.

-
-source("https://raw.githubusercontent.com/OHDSI/CohortGeneratorModule/v0.4.1/SettingsFunctions.R")
-
-# Create the cohort definition shared resource element for the analysis specification
-cohortDefinitionSharedResource <- createCohortSharedResourceSpecifications(
-  cohortDefinitionSet = cohortDefinitionSet
-)
-
-# Create the negative control outcome shared resource element for the analysis specification
-ncoSharedResource <- createNegativeControlOutcomeCohortSharedResourceSpecifications(
-  negativeControlOutcomeCohortSet = ncoCohortSet,
-  occurrenceType = "all",
-  detectOnDescendants = TRUE
-)
-
-# Create the module specification
-cohortGeneratorModuleSpecifications <- createCohortGeneratorModuleSpecifications(
-  incremental = TRUE,
-  generateStats = TRUE
-)
-
-
-

CohortDiagnostics Module Settings -

-

The following code creates the -cohortDiagnosticsModuleSpecifications to run cohort -diagnostics on the cohorts in the study.

-
-source("https://raw.githubusercontent.com/OHDSI/CohortDiagnosticsModule/v0.2.0/SettingsFunctions.R")
-cohortDiagnosticsModuleSpecifications <- createCohortDiagnosticsModuleSpecifications(
-  runInclusionStatistics = TRUE,
-  runIncludedSourceConcepts = TRUE,
-  runOrphanConcepts = TRUE,
-  runTimeSeries = FALSE,
-  runVisitContext = TRUE,
-  runBreakdownIndexEvents = TRUE,
-  runIncidenceRate = TRUE,
-  runCohortRelationship = TRUE,
-  runTemporalCohortCharacterization = TRUE,
-  incremental = FALSE
-)
-
-
-

CohortIncidence Module Settings -

-

The following code creates the -cohortIncidenceModuleSpecifications to perform an incidence -rate analysis for the target cohorts and outcome in this study.

-
-source("https://raw.githubusercontent.com/OHDSI/CohortIncidenceModule/v0.4.1/SettingsFunctions.R")
-library(CohortIncidence)
-targets <- list(
-  createCohortRef(id = 1, name = "Celecoxib"),
-  createCohortRef(id = 2, name = "Diclofenac"),
-  createCohortRef(id = 4, name = "Celecoxib Age >= 30"),
-  createCohortRef(id = 5, name = "Diclofenac Age >= 30")
-)
-outcomes <- list(createOutcomeDef(id = 1, name = "GI bleed", cohortId = 3, cleanWindow = 9999))
-
-tars <- list(
-  createTimeAtRiskDef(id = 1, startWith = "start", endWith = "end"),
-  createTimeAtRiskDef(id = 2, startWith = "start", endWith = "start", endOffset = 365)
-)
-analysis1 <- createIncidenceAnalysis(
-  targets = c(1, 2, 4, 5),
-  outcomes = c(1),
-  tars = c(1, 2)
-)
-
-irDesign <- createIncidenceDesign(
-  targetDefs = targets,
-  outcomeDefs = outcomes,
-  tars = tars,
-  analysisList = list(analysis1),
-  strataSettings = createStrataSettings(
-    byYear = TRUE,
-    byGender = TRUE
-  )
-)
-
-cohortIncidenceModuleSpecifications <- createCohortIncidenceModuleSpecifications(
-  irDesign = irDesign$toList()
-)
-
-
-

Characterization Module Settings -

-

The following code creates the -characterizationModuleSpecifications to perform an -characterization analysis for the target cohorts and outcome in this -study.

-
-source("https://raw.githubusercontent.com/OHDSI/CharacterizationModule/v0.6.0/SettingsFunctions.R")
-characterizationModuleSpecifications <- createCharacterizationModuleSpecifications(
-  targetIds = c(1, 2),
-  outcomeIds = 3,
-  covariateSettings = FeatureExtraction::createDefaultCovariateSettings(),
-  dechallengeStopInterval = 30,
-  dechallengeEvaluationWindow = 30,
-  timeAtRisk = data.frame(
-    riskWindowStart = c(1, 1),
-    startAnchor = c("cohort start", "cohort start"),
-    riskWindowEnd = c(0, 365),
-    endAnchor = c("cohort end", "cohort end")
-  )
-)
-
-
-

CohortMethod Module Settings -

-

The following code creates the -cohortMethodModuleSpecifications to perform a comparative -cohort analysis for this study.

-
-library(CohortMethod)
-source("https://raw.githubusercontent.com/OHDSI/CohortMethodModule/v0.3.1/SettingsFunctions.R")
-negativeControlOutcomes <- lapply(
-  X = ncoCohortSet$cohortId,
-  FUN = createOutcome,
-  outcomeOfInterest = FALSE,
-  trueEffectSize = 1,
-  priorOutcomeLookback = 30
-)
-
-outcomesOfInterest <- lapply(
-  X = 3,
-  FUN = createOutcome,
-  outcomeOfInterest = TRUE
-)
-
-outcomes <- append(
-  negativeControlOutcomes,
-  outcomesOfInterest
-)
-
-tcos1 <- CohortMethod::createTargetComparatorOutcomes(
-  targetId = 1,
-  comparatorId = 2,
-  outcomes = outcomes,
-  excludedCovariateConceptIds = c(1118084, 1124300)
-)
-tcos2 <- CohortMethod::createTargetComparatorOutcomes(
-  targetId = 4,
-  comparatorId = 5,
-  outcomes = outcomes,
-  excludedCovariateConceptIds = c(1118084, 1124300)
-)
-
-targetComparatorOutcomesList <- list(tcos1, tcos2)
-
-covarSettings <- FeatureExtraction::createDefaultCovariateSettings(addDescendantsToExclude = TRUE)
-
-getDbCmDataArgs <- CohortMethod::createGetDbCohortMethodDataArgs(
-  washoutPeriod = 183,
-  firstExposureOnly = TRUE,
-  removeDuplicateSubjects = "remove all",
-  maxCohortSize = 100000,
-  covariateSettings = covarSettings
-)
-
-createStudyPopArgs <- CohortMethod::createCreateStudyPopulationArgs(
-  minDaysAtRisk = 1,
-  riskWindowStart = 0,
-  startAnchor = "cohort start",
-  riskWindowEnd = 30,
-  endAnchor = "cohort end"
-)
-
-matchOnPsArgs <- CohortMethod::createMatchOnPsArgs()
-fitOutcomeModelArgs <- CohortMethod::createFitOutcomeModelArgs(modelType = "cox")
-createPsArgs <- CohortMethod::createCreatePsArgs(
-  stopOnError = FALSE,
-  control = Cyclops::createControl(cvRepetitions = 1)
-)
-computeSharedCovBalArgs <- CohortMethod::createComputeCovariateBalanceArgs()
-computeCovBalArgs <- CohortMethod::createComputeCovariateBalanceArgs(
-  covariateFilter = FeatureExtraction::getDefaultTable1Specifications()
-)
-
-cmAnalysis1 <- CohortMethod::createCmAnalysis(
-  analysisId = 1,
-  description = "No matching, simple outcome model",
-  getDbCohortMethodDataArgs = getDbCmDataArgs,
-  createStudyPopArgs = createStudyPopArgs,
-  fitOutcomeModelArgs = fitOutcomeModelArgs
-)
-
-cmAnalysis2 <- CohortMethod::createCmAnalysis(
-  analysisId = 2,
-  description = "Matching on ps and covariates, simple outcomeModel",
-  getDbCohortMethodDataArgs = getDbCmDataArgs,
-  createStudyPopArgs = createStudyPopArgs,
-  createPsArgs = createPsArgs,
-  matchOnPsArgs = matchOnPsArgs,
-  computeSharedCovariateBalanceArgs = computeSharedCovBalArgs,
-  computeCovariateBalanceArgs = computeCovBalArgs,
-  fitOutcomeModelArgs = fitOutcomeModelArgs
-)
-
-cmAnalysisList <- list(cmAnalysis1, cmAnalysis2)
-
-analysesToExclude <- NULL
-
-
-cohortMethodModuleSpecifications <- createCohortMethodModuleSpecifications(
-  cmAnalysisList = cmAnalysisList,
-  targetComparatorOutcomesList = targetComparatorOutcomesList,
-  analysesToExclude = analysesToExclude
-)
-
-
-

SelfControlledCaseSeries Module Settings -

-

The following code creates the -cohortMethodModuleSpecifications to perform a comparative -cohort analysis for this study.

-
-library(SelfControlledCaseSeries)
-source("https://raw.githubusercontent.com/OHDSI/SelfControlledCaseSeriesModule/v0.5.0/SettingsFunctions.R")
-
-# Exposures-outcomes -----------------------------------------------------------
-negativeControlOutcomeIds <- ncoCohortSet$cohortId
-outcomeOfInterestIds <- c(3)
-exposureOfInterestIds <- c(1, 2)
-
-exposuresOutcomeList <- list()
-for (exposureOfInterestId in exposureOfInterestIds) {
-  for (outcomeOfInterestId in outcomeOfInterestIds) {
-    exposuresOutcomeList[[length(exposuresOutcomeList) + 1]] <- createExposuresOutcome(
-      outcomeId = outcomeOfInterestId,
-      exposures = list(createExposure(exposureId = exposureOfInterestId))
-    )
-  }
-  for (negativeControlOutcomeId in negativeControlOutcomeIds) {
-    exposuresOutcomeList[[length(exposuresOutcomeList) + 1]] <- createExposuresOutcome(
-      outcomeId = negativeControlOutcomeId,
-      exposures = list(createExposure(exposureId = exposureOfInterestId, trueEffectSize = 1))
-    )
-  }
-}
-
-# Analysis settings ------------------------------------------------------------
-getDbSccsDataArgs <- SelfControlledCaseSeries::createGetDbSccsDataArgs(
-  studyStartDate = "",
-  studyEndDate = "",
-  maxCasesPerOutcome = 1e6,
-  useNestingCohort = TRUE,
-  nestingCohortId = 1,
-  deleteCovariatesSmallCount = 0
-)
-
-createStudyPopulation6AndOlderArgs <- SelfControlledCaseSeries::createCreateStudyPopulationArgs(
-  minAge = 18,
-  naivePeriod = 365
-)
-
-covarPreExp <- SelfControlledCaseSeries::createEraCovariateSettings(
-  label = "Pre-exposure",
-  includeEraIds = "exposureId",
-  start = -30,
-  end = -1,
-  endAnchor = "era start"
-)
-
-covarExposureOfInt <- SelfControlledCaseSeries::createEraCovariateSettings(
-  label = "Main",
-  includeEraIds = "exposureId",
-  start = 0,
-  startAnchor = "era start",
-  end = 0,
-  endAnchor = "era end",
-  profileLikelihood = TRUE,
-  exposureOfInterest = TRUE
-)
-
-calendarTimeSettings <- SelfControlledCaseSeries::createCalendarTimeCovariateSettings(
-  calendarTimeKnots = 5,
-  allowRegularization = TRUE,
-  computeConfidenceIntervals = FALSE
-)
-
-seasonalitySettings <- SelfControlledCaseSeries::createSeasonalityCovariateSettings(
-  seasonKnots = 5,
-  allowRegularization = TRUE,
-  computeConfidenceIntervals = FALSE
-)
-
-createSccsIntervalDataArgs <- SelfControlledCaseSeries::createCreateSccsIntervalDataArgs(
-  eraCovariateSettings = list(covarPreExp, covarExposureOfInt),
-  seasonalityCovariateSettings = seasonalitySettings,
-  calendarTimeCovariateSettings = calendarTimeSettings,
-  minCasesForTimeCovariates = 100000
-)
-
-fitSccsModelArgs <- SelfControlledCaseSeries::createFitSccsModelArgs(
-  control = Cyclops::createControl(
-    cvType = "auto",
-    selectorType = "byPid",
-    startingVariance = 0.1,
-    seed = 1,
-    resetCoefficients = TRUE,
-    noiseLevel = "quiet"
-  )
-)
-
-sccsAnalysis1 <- SelfControlledCaseSeries::createSccsAnalysis(
-  analysisId = 1,
-  description = "SCCS age 18-",
-  getDbSccsDataArgs = getDbSccsDataArgs,
-  createStudyPopulationArgs = createStudyPopulation6AndOlderArgs,
-  createIntervalDataArgs = createSccsIntervalDataArgs,
-  fitSccsModelArgs = fitSccsModelArgs
-)
-
-sccsAnalysisList <- list(sccsAnalysis1)
-
-# SCCS module specs ------------------------------------------------------------
-sccsModuleSpecifications <- creatSelfControlledCaseSeriesModuleSpecifications(
-  sccsAnalysisList = sccsAnalysisList,
-  exposuresOutcomeList = exposuresOutcomeList,
-  combineDataFetchAcrossOutcomes = FALSE
-)
-
-
-

PatientLevelPrediction Module Settings -

-

The following code creates the plpModuleSpecifications -to perform a self-controlled case series analysis for this study.

-
-source("https://raw.githubusercontent.com/OHDSI/PatientLevelPredictionModule/v0.3.0/SettingsFunctions.R")
-
-makeModelDesignSettings <- function(targetId, outcomeId, popSettings, covarSettings) {
-  invisible(PatientLevelPrediction::createModelDesign(
-    targetId = targetId,
-    outcomeId = outcomeId,
-    restrictPlpDataSettings = PatientLevelPrediction::createRestrictPlpDataSettings(),
-    populationSettings = popSettings,
-    covariateSettings = covarSettings,
-    preprocessSettings = PatientLevelPrediction::createPreprocessSettings(),
-    modelSettings = PatientLevelPrediction::setLassoLogisticRegression(),
-    splitSettings = PatientLevelPrediction::createDefaultSplitSetting(),
-    runCovariateSummary = T
-  ))
-}
-
-plpPopulationSettings <- PatientLevelPrediction::createStudyPopulationSettings(
-  startAnchor = "cohort start",
-  riskWindowStart = 1,
-  endAnchor = "cohort start",
-  riskWindowEnd = 365,
-  minTimeAtRisk = 1
-)
-plpCovarSettings <- FeatureExtraction::createDefaultCovariateSettings()
-
-modelDesignList <- list()
-for (i in 1:length(exposureOfInterestIds)) {
-  for (j in 1:length(outcomeOfInterestIds)) {
-    modelDesignList <- append(
-      modelDesignList,
-      list(
-        makeModelDesignSettings(
-          targetId = exposureOfInterestIds[i],
-          outcomeId = outcomeOfInterestIds[j],
-          popSettings = plpPopulationSettings,
-          covarSettings = plpCovarSettings
-        )
-      )
-    )
-  }
-}
-
-plpModuleSpecifications <- createPatientLevelPredictionModuleSpecifications(modelDesignList = modelDesignList)
-
-
-
-

Strategus Analysis Specifications -

-

Finally, we will use the various shared resources and module -specifications to construct the full set of analysis specifications and -save it to the file system in JSON format.

-
-analysisSpecifications <- createEmptyAnalysisSpecificiations() %>%
-  addSharedResources(cohortDefinitionSharedResource) %>%
-  addSharedResources(ncoSharedResource) %>%
-  addModuleSpecifications(cohortGeneratorModuleSpecifications) %>%
-  addModuleSpecifications(cohortDiagnosticsModuleSpecifications) %>%
-  addModuleSpecifications(cohortIncidenceModuleSpecifications) %>%
-  addModuleSpecifications(characterizationModuleSpecifications) %>%
-  addModuleSpecifications(cohortMethodModuleSpecifications) %>%
-  addModuleSpecifications(sccsModuleSpecifications) %>%
-  addModuleSpecifications(plpModuleSpecifications)
-
-ParallelLogger::saveSettingsToJson(analysisSpecifications, file.path(params$analysisSettingsPath, params$analysisSettingsFileName))
-
-
- - - -
- - - -
-

-

Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

-
- -
-

-

Site built with pkgdown 2.0.9.

-
- -
-
- - - - - - - - diff --git a/docs/articles/CreatingModules.html b/docs/articles/CreatingModules.html deleted file mode 100644 index 6aa95ae1..00000000 --- a/docs/articles/CreatingModules.html +++ /dev/null @@ -1,434 +0,0 @@ - - - - - - - -Creating Strategus Modules • Strategus - - - - - - - - - - - - -
-
- - - - -
-
-
-

Creating Strategus Modules

-

Anthony G. -Sena

- -

2024-06-04

- - Source: vignettes/CreatingModules.Rmd - - -
- - - -
-

Background -

-

This document aims to document the steps necessary to create analytic -module that is compatible with Strategus. Please treat -this document as a work in progress as Strategus is -still under development.

-
-
-

Getting Started -

-

A Strategus analytic module is an R Project that uses renv. -NOTE: Please make sure you are using renv > 1.0.0 -when creating a new analytic module to make sure it is compatible with -Strategus.

-

A Strategus module will contain the following files:

-

[01;34mmodule_skeleton
[0m
-+-- 
[01;34mextras
[0m
-|   +-- 
[32mCreateJobContextForTesting.R
[0m
-|   \-- 
[32mModuleMaintenance.R
[0m
-+-- 
[32mMain.R
[0m
-+-- MetaData.json
-+-- NEWS.md
-+-- README.md
-+-- 
[01;34mrenv
[0m
-|   +-- 
[32mactivate.R
[0m
-|   +-- settings.dcf
-|   \-- settings.json
-+-- renv.lock
-+-- 
[01;34mresources
[0m
-|   +-- exampleAnalysisSpecifications.json
-|   \-- resultsDataModelSpecification.csv
-+-- 
[32mSettingsFunctions.R
[0m
-+-- 
[01;34mtests
[0m
-|   +-- 
[32mtest-eunomia.R
[0m
-|   +-- testJobContext.rds
-|   \-- 
[32mtestScript.R
[0m
-\-- YourProjectModule.Rproj
-

Here we will detail how each file is used by Strategus and what is -required in the contents of the file.

-
-

Creating YourProjectModule.Rproj and activating -renv -

-

This is the R Project (.Rproj) file for your module and should end in -“Module”. You may create this as a standard R Project via RStudio. Once -the project is created, please use renv::init() to set up -the renv folder as shown above. This will create the -necessary .RProfile in the root of your project and the -renv subfolder with the necessary R code for -renv’s operations.

-
-
-

README.md -

-

This is a standard README markdown file that describes the -module.

-
-
-

NEWS.md -

-

This is a standard NEWS markdown file that is a change log for your -module. See this -post for more information.

-
-
-

MetaData.json -

-

MetaData.json holds information that describes the module and its -dependencies:

-
{
-  "Name": "CohortGeneratorModule",
-  "Version": "0.0.1",
-  "Dependencies": ["SomePrerequisiteModule"],
-  "TablePrefix": "cg_"
-}
-

To detail the contents of the JSON file:

-
    -
  • -Name: The name of the module
    • -
  • -Version: The version of the module. This should -have a corresponding git tag in the repository when the module is -released otherwise Strategus will not be able to download it.
    • -
  • -Dependencies: A list of modules that are required -to have successfully executed BEFORE this module is -executed. If there are no dependencies, leave this as an empty array -[].
    • -
  • -TablePrefix: The prefix to use when creating the -results tables in the resultsDataModelSpecification.csv. -Please see Main.R for more information on how this -value is used.
    • -
-
-
-

Main.R -

-

This file holds the main executable for your module. This file must -contain a function called execute(jobContext).

-
execute <- function(jobContext) {
-  # VALIDATE THE jobContext
-  rlang::inform("Validating inputs")
-  
-  # YOUR VALIDATION CODE GOES HERE....
-  
-  # EXECUTE THE ANALYTICS
-  rlang::inform("Executing")
-  
-  # YOUR EXECUTION CODE GOES HERE....
-  
-  # ASSEMBLE AND .ZIP THE RESULTS
-  rlang::inform("Export data")
-  
-  # YOUR CODE GOES HERE....
-}
-

As shown in the code above, your execute(jobContext) -should handle: validating the jobContext object to ensure -it has all of the information necessary for your code to function, a -section to execute the analytics and finally code to assemble the -output. Here we will describe the requirements for the way in which your -module must output its results:

-
    -
  • A single .ZIP file is created that holds all of the result files as -described below.
    • -
  • Output files are required to be in .CSV format. Use CohortGenerator -v0.5.0 or higher which contains a helper function for -writeCsv() which will ensure your output is formatted -properly. For more information, please see: https://ohdsi.github.io/CohortGenerator/reference/writeCsv.html. -IMPORTANT: File names must correspond to the -table names that are specified in the -resultsModuleSpecification.csv.
    • -
  • You must include a file named -resultsModuleSpecification.csv in your output directory. -The format of this file is as follows:
    • -
-
table_name,column_name,data_type,is_required,primary_key,empty_is_na
-my_table,cohort_id,bigint,Yes,Yes,No
-my_table,cohort_name,varchar,Yes,No,No
-my_table,generation_status,varchar,No,No,No
-my_table,start_time,Timestamp,No,No,No
-my_table,end_time,Timestamp,No,No,No
-my_table,database_id,varchar,Yes,Yes,No
-

The resultsModuleSpecification.csv has the following -columns:

-
    -
  • -table_name: The table name to use to hold the -data.
    • -
  • -column_name: The column name in the table.
    • -
  • -data_type: The data type for the column. See https://www.postgresql.org/docs/current/datatype.html -for examples.
    • -
  • -is_required: Will this column allow for NULL -values? Yes/No
    • -
  • -primary_key: Is this column part of the table’s -primary key? Yes/No
    • -
-
-
-

SettingsFunctions.R -

-

This file contains one or more functions required to create the -module settings for use in Strategus. We plan to later remove this -requirement when we can describe the module specification using the OpenAPI 3.0 Specification. -For now, your module should contain a function similar to the -following:

-
createCohortGeneratorModuleSpecifications <- function(incremental = TRUE,
-                                                      generateStats = TRUE) {
-  analysis <- list()
-  for (name in names(formals(createCohortGeneratorModuleSpecifications))) {
-    analysis[[name]] <- get(name)
-  }
-
-  checkmate::assert_file_exists("MetaData.json")
-  moduleInfo <- ParallelLogger::loadSettingsFromJson("MetaData.json")
-  
-  specifications <- list(module = moduleInfo$Name,
-                         version = moduleInfo$Version,
-                         remoteRepo = "github.com",
-                         remoteUsername = "ohdsi",
-                         settings = analysis)
-  class(specifications) <- c("CohortGeneratorModuleSpecifications", "ModuleSpecifications")
-  return(specifications)
-}
-

As shown above, this example comes from the -CohortGeneratorModule and the function name reflects the -fact that the function will create the settings used to dictate the -behavior of the module. The parameters of the function will differ based -on the requirements of your module - if there are choices to be made -when running your module, you should include these as parameters to your -module specification function.

-

Internal to the function above, the formal parameters to the function -are used to construct a list() named analysis -which holds the analysis settings. Next the MetaData.json -file is used to obtain the module name/version for inclusion in the -specifications list. The specifications list -contains the remoteRepo and remoteUsername -properties to indicate where your module is stored on GitHub. Finally, -we set the class() of the specifications -object to -c("CohortGeneratorModuleSpecifications", "ModuleSpecifications"). -For your module, you will want to substitute -"CohortGeneratorModuleSpecifications" for the name of your -module and retain the "ModuleSpecifications" in the -vector.

-

The following JSON fragment shows how the output of -createCohortGeneratorModuleSpecifications() is used in the -moduleSpecifications section of the overall analysis -settings JSON for Strategus:

-
{
-  "sharedResources": [
-    {
-      "cohortDefinitions": [
-        {
-          "cohortId": "1",
-          "cohortName": "celecoxib",
-          "cohortDefinition": "...truncated..."
-        }
-      ],
-      "attr_class": ["CohortDefinitionSharedResources", "SharedResources"]
-    }
-  ],
-  "moduleSpecifications": [
-    {
-      "module": "CohortGeneratorModule",
-      "version": "0.0.1",
-      "remoteRepo": "github.com",
-      "remoteUsername": "ohdsi",
-      "settings": {
-        "incremental": true,
-        "generateStats": true
-      },
-      "attr_class": ["CohortGeneratorModuleSpecifications", "ModuleSpecifications"]
-    }
-  ],
-  "attr_class": "AnalysisSpecifications"
-}
-
-
-

renv.lock -

-

Each module will make use of renv to -capture its R package dependencies. Furthermore, Strategus will make use -of the renv settings in your module to create a run-time -environment when executing your module to ensure all of the necessary -dependencies are available to your module.

-

It is recommended to use the HADES-wide renv.lock file which is -available at https://github.com/OHDSI/Hades/blob/main/hadesWideReleases. -Find the most recent release based on the folder name and copy the -renv.lock file into the root of your module project.

-

If you need to install additional dependencies for your project, use -renv::record() to record it in the lock file.

-
-
-
-

Extra files -

-

It is advisable to add an extras folder to your project -to include other useful files for managing and testing your module. -We’ll detail those files here:

-
-

ModuleMaintenance.R -

-

This file is used to store utility functions for your module, such as -the code mentioned earlier for generating the renv.lock file. Here is an example of the contents -of ModuleMaintenance.R:

-
# Format and check code:
-styler::style_dir()
-OhdsiRTools::updateCopyrightYearFolder()
-OhdsiRTools::findNonAsciiStringsInFolder()
-devtools::spell_check()
-
-# Generate renv lock file and activate renv:
-OhdsiRTools::createRenvLockFile(
-  rootPackage = "CohortGenerator",
-  includeRootPackage = TRUE,
-  mode = "description",
-  additionalRequiredPackages = c("checkmate", "CirceR")
-)
-renv::init()
-
-
-

Test Files -

-

The following file is used to create a test jobContext for use in the -execute(jobContext) as described in Main.R:

-

https://github.com/OHDSI/CohortGeneratorModule/blob/main/extras/test/CreateJobContext.R

-

And the following file is used to create a test harness for running -your module:

-

https://github.com/OHDSI/CohortGeneratorModule/blob/main/extras/test/TestModuleStandalone.R

-
-
-
- - - -
- - - -
-

-

Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

-
- -
-

-

Site built with pkgdown 2.0.9.

-
- -
-
- - - - - - - - diff --git a/docs/articles/ExecuteStrategus.html b/docs/articles/ExecuteStrategus.html deleted file mode 100644 index 0907a48f..00000000 --- a/docs/articles/ExecuteStrategus.html +++ /dev/null @@ -1,261 +0,0 @@ - - - - - - - -Execute Strategus • Strategus - - - - - - - - - - - - -
-
- - - - -
-
-
-

Execute Strategus

-

Anthony G. -Sena

- -

2024-06-04

- - Source: vignettes/ExecuteStrategus.Rmd - - -
- - - -

A Strategus study is defined by analysis specifications. -These specifications describe which modules to run, with which settings. -The ‘Creating Analysis Specification’ vignette describes how to create -analysis specifications. In this vignette, we demonstrate how to run a -study once it is specified.

-
-

Creating execution settings -

-

In addition to analysis specifications, Strategus also requires -execution settings. The execution settings specify how the -study should be executed in a specific environment, for example how to -connect to a database, and what local folders to use. Many Strategus -studies run against data in the OMOP Common Data Model (CDM), and in -this vignette we focus on this type of studies. (Other studies, such as -meta-analyses, may run against results data instead). In this example, -we will make use of the Eunomia data set which is an -OMOP CDM with simulated data used for example purposes. When running a -study against your own CDM data, you will need to specify the database -connection details for your environment. Execution settings for studies -against the CDM can be created using -createCdmExecutionSettings().

-

Note that Strategus uses keyring to store -the connection information securely, so that sensitive information is -not stored directly in the executionSettings variable.

-
-

Storing the connection details -

-

In this example, we first create a connectionDetails -reference for Eunomia. In your environment, the -connectionDetails would be specific to your OMOP CDM -connection.

-
-library(Strategus)
-folder <- "c:/strategus"
-
-# Note: specifying the `databaseFile` so the Eunomia database is permanent, not temporary:
-connectionDetails <- Eunomia::getEunomiaConnectionDetails(
-  databaseFile = file.path(outputFolder, "cdm.sqlite")
-)
-
## attempting to download GiBleed
-
## attempting to extract and load: D:/eunomiaData/GiBleed_5.3.zip to: D:/eunomiaData/GiBleed_5.3.sqlite
-

Next we will use Strategus to store the connection -details and provide a connectionDetailsReference that -Strategus will use to look up the connection details.

-
-storeConnectionDetails(
-  connectionDetails = connectionDetails,
-  connectionDetailsReference = "eunomia"
-)
-

Note that we only need to store connection details once. We can -re-use these details in all future studies.

-
-
-

Creating an execution settings object -

-

Next, we will use Strategus to create the CDM execution -settings. The connectionDetailsReference refers to the -connection details we stored earlier:

-
-executionSettings <- createCdmExecutionSettings(
-  connectionDetailsReference = "eunomia",
-  workDatabaseSchema = "main",
-  cdmDatabaseSchema = "main",
-  cohortTableNames = CohortGenerator::getCohortTableNames(),
-  workFolder = file.path(outputFolder, "work_folder"),
-  resultsFolder = file.path(outputFolder, "results_folder"),
-  minCellCount = 5
-)
-

Finally, we can write out the execution settings to the file system -to capture this information.

-
-ParallelLogger::saveSettingsToJson(
-  object = executionSettings,
-  file.path(outputFolder, "eunomiaExecutionSettings.json")
-)
-
-
-
-

Executing the study -

-
-

Specifying the instantiated modules folder -

-

Strategus studies use modules to perform the analytics, and each -module has a version. Different studies can use the same modules, but a -single study can only use one version of a particular module. These -modules need to be instantiated before they can be executed, a sometimes -time-consuming task. We must specify a global location where these -modules will be instantiated so that, once a module is instantiated, it -can be used in all future studies:

-
-Sys.setenv("INSTANTIATED_MODULES_FOLDER" = "c:/strategus/modules")
-

We recommend adding this environmental variable to your -.renviron file, so it is always set.

-
-
-

Running the study -

-

For this study, we will use analysis specifications created -elsewhere, and the execution settings we created earlier:

-
-analysisSpecifications <- ParallelLogger::loadSettingsFromJson(
-  fileName = system.file("testdata/analysisSpecification.json",
-    package = "Strategus"
-  )
-)
-
-executionSettings <- ParallelLogger::loadSettingsFromJson(
-  fileName = file.path(outputFolder, "eunomiaExecutionSettings.json")
-)
-

And finally we execute the study:

-
-execute(
-  analysisSpecifications = analysisSpecifications,
-  executionSettings = executionSettings,
-  executionScriptFolder = file.path(outputFolder, "script_folder")
-)
-

This will first instantiate all the modules if they haven’t already -been instantiated, and will then execute each module in sequence -according to the analysis specifications. The results will appear in -subfolders of the ‘results_folder’, as specified in the execution -settings.

-
-
-
- - - -
- - - -
-

-

Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

-
- -
-

-

Site built with pkgdown 2.0.9.

-
- -
-
- - - - - - - - diff --git a/docs/articles/IntroductionToStrategus.html b/docs/articles/IntroductionToStrategus.html deleted file mode 100644 index 03e69b9f..00000000 --- a/docs/articles/IntroductionToStrategus.html +++ /dev/null @@ -1,188 +0,0 @@ - - - - - - - -Introduction to Strategus • Strategus - - - - - - - - - - - - -
-
- - - - -
-
-
-

Introduction to Strategus

-

Anthony G. -Sena

- -

2024-06-04

- - Source: vignettes/IntroductionToStrategus.Rmd - - -
- - - -
-

Introduction to Strategus -

-

The Strategus package is a new approach for coordinating -and executing analytics using HADES modules. The goal is to have OHDSI -network sites install Strategus and exchange an analysis -specification in JSON format to execute a network study. The analysis -specification will capture all of the design choices that pertain to the -methods used in a given study. The analysis specification format aims to -allow for combining different HADES modules together as a pipeline to -execute a study. In addition, the analysis specification makes use of -specific HADES module versions to clearly state which modules are -required to run the study with the aim to make the execution and results -reproducible.

-
-

Using Strategus -

-

The high-level steps in using Strategus consists of the -following:

-
    -
  1. Create the analysis specification for the study. This will include -things like picking the cohorts for the study, the analyses to perform -(i.e. Cohort Diagnostics, Comparative Cohort Study, etc) and the choices -for each analysis. See here for more -details.
    2. -
  2. Create the execution settings that specify how to connect to the -OMOP CDM in your environment. See here for more details.
    3. -
  3. Execute the study using Strategus which will require -both the analysis specification and the execution settings in order to -run the study and extract the results. See here for more details.
    4. -
  4. Upload the results and use Shiny to view the results Coming -Soon.
    5. -
-
-
-

What is a HADES module? -

-

A HADES module aims to standardize the input and output produced by a -HADES package. It also self-describes the R dependencies it needs to run -properly via Strategus.

-

From a technical perspective, a HADES module is a lightweight R -script uses the Strategus JSON analysis specification to -call one or more HADES packages to produce a standardized set of -results. The HADES module contains an renv lock file which -enumerates the module’s R package dependencies. Taken together, the -module provides a reproducible way to execute a step in an analysis by -ensuring the proper dependencies are available along with the code that -was used to execute the analysis.

-

For more information on how to create modules, see here

-
-
-
- - - -
- - - -
-

-

Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

-
- -
-

-

Site built with pkgdown 2.0.9.

-
- -
-
- - - - - - - - diff --git a/docs/articles/index.html b/docs/articles/index.html deleted file mode 100644 index c537728a..00000000 --- a/docs/articles/index.html +++ /dev/null @@ -1,104 +0,0 @@ - -Articles • Strategus - - -
-
- - - -
-
-
-

Articles

-
- -
-

All vignettes

-

- -
Creating Analysis Specification
-
-
Creating Strategus Modules
-
-
Execute Strategus
-
-
Introduction to Strategus
-
-
-
-
- - -
-

Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

-
- -
-

Site built with pkgdown 2.0.9.

-
- -
- - - - - - - - diff --git a/docs/authors.html b/docs/authors.html deleted file mode 100644 index 95108baa..00000000 --- a/docs/authors.html +++ /dev/null @@ -1,131 +0,0 @@ - -Authors and Citation • Strategus - - -
-
- - - -
-
-
-
-

Authors and Citation

-
- - -
  • -

    Martijn Schuemie. Author. -

    -
    • -
  • -

    Anthony Sena. Author, maintainer. -

    -
    • -
  • -

    Jamie Gilbert. Author. -

    -
    • -
  • -

    Observational Health Data Science and Informatics. Copyright holder. -

    -
    • -
-
-
-

Citation

- Source: DESCRIPTION -
-
- - -

Schuemie M, Sena A, Gilbert J (2024). -Strategus: Coordinating and Executing Analytics Using HADES Modules. -https://ohdsi.github.io/Strategus, https://github.com/OHDSI/Strategus. -

- 
@Manual{,
-  title = {Strategus: Coordinating and Executing Analytics Using HADES Modules},
-  author = {Martijn Schuemie and Anthony Sena and Jamie Gilbert},
-  year = {2024},
-  note = {https://ohdsi.github.io/Strategus, https://github.com/OHDSI/Strategus},
-}
- -
- -
- - - -
-

Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

-
- -
-

Site built with pkgdown 2.0.9.

-
- -
- - - - - - - - diff --git a/docs/bootstrap-toc.css b/docs/bootstrap-toc.css deleted file mode 100644 index 5a859415..00000000 --- a/docs/bootstrap-toc.css +++ /dev/null @@ -1,60 +0,0 @@ -/*! - * Bootstrap Table of Contents v0.4.1 (http://afeld.github.io/bootstrap-toc/) - * Copyright 2015 Aidan Feldman - * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */ - -/* modified from https://github.com/twbs/bootstrap/blob/94b4076dd2efba9af71f0b18d4ee4b163aa9e0dd/docs/assets/css/src/docs.css#L548-L601 */ - -/* All levels of nav */ -nav[data-toggle='toc'] .nav > li > a { - display: block; - padding: 4px 20px; - font-size: 13px; - font-weight: 500; - color: #767676; -} -nav[data-toggle='toc'] .nav > li > a:hover, -nav[data-toggle='toc'] .nav > li > a:focus { - padding-left: 19px; - color: #563d7c; - text-decoration: none; - background-color: transparent; - border-left: 1px solid #563d7c; -} -nav[data-toggle='toc'] .nav > .active > a, -nav[data-toggle='toc'] .nav > .active:hover > a, -nav[data-toggle='toc'] .nav > .active:focus > a { - padding-left: 18px; - font-weight: bold; - color: #563d7c; - background-color: transparent; - border-left: 2px solid #563d7c; -} - -/* Nav: second level (shown on .active) */ -nav[data-toggle='toc'] .nav .nav { - display: none; /* Hide by default, but at >768px, show it */ - padding-bottom: 10px; -} -nav[data-toggle='toc'] .nav .nav > li > a { - padding-top: 1px; - padding-bottom: 1px; - padding-left: 30px; - font-size: 12px; - font-weight: normal; -} -nav[data-toggle='toc'] .nav .nav > li > a:hover, -nav[data-toggle='toc'] .nav .nav > li > a:focus { - padding-left: 29px; -} -nav[data-toggle='toc'] .nav .nav > .active > a, -nav[data-toggle='toc'] .nav .nav > .active:hover > a, -nav[data-toggle='toc'] .nav .nav > .active:focus > a { - padding-left: 28px; - font-weight: 500; -} - -/* from https://github.com/twbs/bootstrap/blob/e38f066d8c203c3e032da0ff23cd2d6098ee2dd6/docs/assets/css/src/docs.css#L631-L634 */ -nav[data-toggle='toc'] .nav > .active > ul { - display: block; -} diff --git a/docs/bootstrap-toc.js b/docs/bootstrap-toc.js deleted file mode 100644 index 1cdd573b..00000000 --- a/docs/bootstrap-toc.js +++ /dev/null @@ -1,159 +0,0 @@ -/*! - * Bootstrap Table of Contents v0.4.1 (http://afeld.github.io/bootstrap-toc/) - * Copyright 2015 Aidan Feldman - * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */ -(function() { - 'use strict'; - - window.Toc = { - helpers: { - // return all matching elements in the set, or their descendants - findOrFilter: function($el, selector) { - // http://danielnouri.org/notes/2011/03/14/a-jquery-find-that-also-finds-the-root-element/ - // http://stackoverflow.com/a/12731439/358804 - var $descendants = $el.find(selector); - return $el.filter(selector).add($descendants).filter(':not([data-toc-skip])'); - }, - - generateUniqueIdBase: function(el) { - var text = $(el).text(); - var anchor = text.trim().toLowerCase().replace(/[^A-Za-z0-9]+/g, '-'); - return anchor || el.tagName.toLowerCase(); - }, - - generateUniqueId: function(el) { - var anchorBase = this.generateUniqueIdBase(el); - for (var i = 0; ; i++) { - var anchor = anchorBase; - if (i > 0) { - // add suffix - anchor += '-' + i; - } - // check if ID already exists - if (!document.getElementById(anchor)) { - return anchor; - } - } - }, - - generateAnchor: function(el) { - if (el.id) { - return el.id; - } else { - var anchor = this.generateUniqueId(el); - el.id = anchor; - return anchor; - } - }, - - createNavList: function() { - return $('
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- } // else use the current $context - - $context.append($newNav); - - $prevNav = $newNav; - }); - }, - - parseOps: function(arg) { - var opts; - if (arg.jquery) { - opts = { - $nav: arg - }; - } else { - opts = arg; - } - opts.$scope = opts.$scope || $(document.body); - return opts; - } - }, - - // accepts a jQuery object, or an options object - init: function(opts) { - opts = this.helpers.parseOps(opts); - - // ensure that the data attribute is in place for styling - opts.$nav.attr('data-toggle', 'toc'); - - var $topContext = this.helpers.createChildNavList(opts.$nav); - var topLevel = this.helpers.getTopLevel(opts.$scope); - var $headings = this.helpers.getHeadings(opts.$scope, topLevel); - this.helpers.populateNav($topContext, topLevel, $headings); - } - }; - - $(function() { - $('nav[data-toggle="toc"]').each(function(i, el) { - var $nav = $(el); - Toc.init($nav); - }); - }); -})(); diff --git a/docs/docsearch.css b/docs/docsearch.css deleted file mode 100644 index e5f1fe1d..00000000 --- a/docs/docsearch.css +++ /dev/null @@ -1,148 +0,0 @@ -/* Docsearch -------------------------------------------------------------- */ -/* - Source: https://github.com/algolia/docsearch/ - License: MIT -*/ - -.algolia-autocomplete { - display: block; 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- padding-top: 0 -} - -.algolia-autocomplete .algolia-docsearch-suggestion--subcategory-column { - float: none; - width: auto; - padding: 0; - text-align: left -} - -.algolia-autocomplete .algolia-docsearch-suggestion--content { - float: none; - width: auto; - padding: 0 -} - -.algolia-autocomplete .algolia-docsearch-suggestion--content::before { - display: none -} - -.algolia-autocomplete .ds-suggestion:not(:first-child) .algolia-docsearch-suggestion--category-header { - padding-top: .75rem; - margin-top: .75rem; - border-top: 1px solid rgba(0, 0, 0, .1) -} - -.algolia-autocomplete .ds-suggestion .algolia-docsearch-suggestion--subcategory-column { - display: block; - padding: .1rem 1rem; - margin-bottom: 0.1; - font-size: 1.0em; - font-weight: 400 - /* display: none */ -} - -.algolia-autocomplete .algolia-docsearch-suggestion--title { - display: block; - padding: .25rem 1rem; - margin-bottom: 0; - font-size: 0.9em; - font-weight: 400 -} - -.algolia-autocomplete .algolia-docsearch-suggestion--text { - padding: 0 1rem .5rem; - margin-top: -.25rem; - font-size: 0.8em; - font-weight: 400; - line-height: 1.25 -} - -.algolia-autocomplete .algolia-docsearch-footer { - width: 110px; - height: 20px; - z-index: 3; - margin-top: 10.66667px; - float: right; - font-size: 0; - line-height: 0; -} - -.algolia-autocomplete .algolia-docsearch-footer--logo { - background-image: url("data:image/svg+xml;utf8,"); - background-repeat: no-repeat; - background-position: 50%; - background-size: 100%; - overflow: hidden; - text-indent: -9000px; - width: 100%; - height: 100%; - display: block; - transform: translate(-8px); -} - -.algolia-autocomplete .algolia-docsearch-suggestion--highlight { - color: #FF8C00; - background: rgba(232, 189, 54, 0.1) -} - - -.algolia-autocomplete .algolia-docsearch-suggestion--text .algolia-docsearch-suggestion--highlight { - box-shadow: inset 0 -2px 0 0 rgba(105, 105, 105, .5) -} - -.algolia-autocomplete .ds-suggestion.ds-cursor .algolia-docsearch-suggestion--content { - background-color: rgba(192, 192, 192, .15) -} diff --git a/docs/docsearch.js b/docs/docsearch.js deleted file mode 100644 index b35504cd..00000000 --- a/docs/docsearch.js +++ /dev/null @@ -1,85 +0,0 @@ -$(function() { - - // register a handler to move the focus to the search bar - // upon pressing shift + "/" (i.e. "?") - $(document).on('keydown', function(e) { - if (e.shiftKey && e.keyCode == 191) { - e.preventDefault(); - $("#search-input").focus(); - } - }); - - $(document).ready(function() { - // do keyword highlighting - /* modified from https://jsfiddle.net/julmot/bL6bb5oo/ */ - var mark = function() { - - var referrer = document.URL ; - var paramKey = "q" ; - - if (referrer.indexOf("?") !== -1) { - var qs = referrer.substr(referrer.indexOf('?') + 1); - var qs_noanchor = qs.split('#')[0]; - var qsa = qs_noanchor.split('&'); - var keyword = ""; - - for (var i = 0; i < qsa.length; i++) { - var currentParam = qsa[i].split('='); - - if (currentParam.length !== 2) { - continue; - } - - if (currentParam[0] == paramKey) { - keyword = decodeURIComponent(currentParam[1].replace(/\+/g, "%20")); - } - } - - if (keyword !== "") { - $(".contents").unmark({ - done: function() { - $(".contents").mark(keyword); - } - }); - } - } - }; - - mark(); - }); -}); - -/* Search term highlighting ------------------------------*/ - -function matchedWords(hit) { - var words = []; - - var hierarchy = hit._highlightResult.hierarchy; - // loop to fetch from lvl0, lvl1, etc. - for (var idx in hierarchy) { - words = words.concat(hierarchy[idx].matchedWords); - } - - var content = hit._highlightResult.content; - if (content) { - words = words.concat(content.matchedWords); - } - - // return unique words - var words_uniq = [...new Set(words)]; - return words_uniq; -} - -function updateHitURL(hit) { - - var words = matchedWords(hit); - var url = ""; - - if (hit.anchor) { - url = hit.url_without_anchor + '?q=' + escape(words.join(" ")) + '#' + hit.anchor; - } else { - url = hit.url + '?q=' + escape(words.join(" ")); - } - - return url; -} diff --git a/docs/index.html b/docs/index.html deleted file mode 100644 index 1d214a67..00000000 --- a/docs/index.html +++ /dev/null @@ -1,239 +0,0 @@ - - - - - - - -Coordinating and Executing Analytics Using HADES Modules • Strategus - - - - - - - - - - - - -
    -
    - - - - -
    -
    - -
    -

    Strategus -

    -

    Build Status codecov.io

    -
    -
    -

    Introduction -

    -

    Strategus is an R package for coordinating and executing analytics using HADES modules. Please see the Introduction To Strategus for more details.

    -
    -
    -

    Features -

    -
      -
    • Design study analysis specifications
      • -
    • Execute study analysis specifications against the OMOP CDM
      • -
    • Modular design for encapsulating analytics vignette -
      • -
    -
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    Technology -

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    Strategus is an R package.

    -
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    System Requirements -

    -

    Requires R (version 4.2.0 or higher). Installation on Windows requires RTools. Libraries used in Strategus require Java. Strategus requires you to setup your GitHub Personal Access Token as described here

    -
    -
    -

    Installation -

    -
      -

    1. See the instructions here for configuring your R environment, including RTools, Java and your GitHub Personal Access Token.

      2. -

    2. In R, use the following commands to download and install Strategus:

      3. -
    -
    -install.packages("remotes")
-remotes::install_github("ohdsi/Strategus")
    -
      -
    1. If using Linux, please refer to the keyring Linux secret service setup as this is required to execute studies using Strategus. In addition to those instructions, members of the OHDSI community have shared the following guidance:
      2. -
    -

    Run in a terminal the following before installing keyring:

    -
    sudo yum install libsodium libsodium-devel
-sudo yum install libsecret libsecret-devel
-sudo chmod 777 /home/idies/.config
    -
    -
    -

    User Documentation -

    -

    Documentation can be found on the package website.

    -

    PDF versions of the documentation are also available: * Package manual: Strategus.pdf * Vignette: Creating Strategus Modules

    -
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    -

    Support -

    - -
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    Contributing -

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    Read here how you can contribute to this package.

    -
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    -

    License -

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    Strategus is licensed under Apache License 2.0

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    Development -

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    Strategus is being developed in R Studio.

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    -

    Development status -

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    Strategus is under active development.

    -
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    - -
    - - -
    - - -
    -

    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

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    Site built with pkgdown 2.0.9.

    -
    - -
    -
    - - - - - - - - diff --git a/docs/link.svg b/docs/link.svg deleted file mode 100644 index 88ad8276..00000000 --- a/docs/link.svg +++ /dev/null @@ -1,12 +0,0 @@ - - - - - - diff --git a/docs/news/index.html b/docs/news/index.html deleted file mode 100644 index 6d16928e..00000000 --- a/docs/news/index.html +++ /dev/null @@ -1,171 +0,0 @@ - -Changelog • Strategus - - -
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    Changelog

    - Source: NEWS.md -
    - -
    -

    Strategus 0.3.0

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    • Provide option to skip modules (#87)
      • -
    • Central log file for execution (#132)
      • -
    • Create function to collect all results into a single ZIP file for sharing (#46)
      • -
    • Install latest modules (#125)
      • -
    -
    -

    Strategus 0.2.1

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    • Update SelfControlledCaseSeries Module to v0.4.1
      • -
    -
    -

    Strategus 0.2.0

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    • Add functions for developers to help with renv.lock file validation (#69)
      • -
    • Use renv project profiles for modules (#94)
      • -
    • Convert relative paths to absolute path before passing to a module (#99)
      • -
    • Address missing package dependencies in modules (#99)
      • -
    • Throw informative error message when connection detail reference not set in keyring (#100)
      • -
    • Validate execution settings (#101)
      • -
    • Pass temp emulation schema properly (#76)
      • -
    • Remove local library package dependencies (#96)
      • -
    -
    -

    Strategus 0.1.0

    -
    • Adds an initial implementation for uploading results to a results database (#72)
      • -
    • Robust handling of connection details via keyring (#74)
      • -
    • Ensures uniqueness of all CDM tables when gathering database metadata (#82)
      • -
    • -tempEmulationSchema added to execution settings and passed properly to modules (#82)
      • -
    • Adding logging to module initalization to detect renv restore errors (#82)
      • -
    • Adopt HADES-wide lock file in latest versions of all modules (#83)
      • -
    • Use renv >= v1.0.0 for all modules and Strategus (#83)
      • -
    • Add GitHub unit tests for HADES adopted version (currently v4.2.3) and the latest R versions for all modules and Strategus. (#83)
      • -
    • Ensure all Strategus GitHub unit tests run on all operating systems and available OHDSI test database platforms (#83)
      • -
    • Use CDM v5.4 schemas for all unit tests (#85)
      • -
    • Allow for passing renvconfiguration options when running Strategus (#88)
      • -
    • Adds SQL for test cohorts to package (#1)
      • -
    -
    -

    Strategus 0.0.6

    -
    • Update SCCS module reference inst/testdata/analysisSpecification.json -
      • -
    -
    -

    Strategus 0.0.5

    -
    • Required metadata tables check fails with DatabaseConnector < 6.0 (#61)
      • -
    • Update module references and add script to run Strategus on Eunomia in extras/ExecuteStrategusOnEunomia.R (#66)
      • -
    -
    -

    Strategus 0.0.4

    -
    • Add DB Platform Tests (#53)
      • -
    • Add error handling for missing/empty tables (#54)
      • -
    • Remove uniqueness check for module table prefix (#55)
      • -
    -
    -

    Strategus 0.0.3

    -
    • Breaking change: removed function createExecutionSettings() and replaced with 2 new functions: createCdmExecutionSettings() and createResultsExecutionSettings(). (#19)
      • -
    • Added Vignettes (#23)
      • -
    • Provide better support for keyring to handle named/locked keyrings (#24)
      • -
    • Add function to list Strategus modules (#30)
      • -
    • Fixes from testing (#36)
      • -
    • Enforce module structure for proper use with renv (#37)
      • -
    • Support CDM 5.4 source table format (#41)
      • -
    • Add unit tests (#47)
      • -
    -
    -

    Strategus 0.0.2

    -
    • Updates renv to 0.15.5
      • -
    • Call renv::use() for each module
      • -
    -
    -

    Strategus 0.0.1

    -

    Initial version

    -
    -
    - - - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/pkgdown.css b/docs/pkgdown.css deleted file mode 100644 index 80ea5b83..00000000 --- a/docs/pkgdown.css +++ /dev/null @@ -1,384 +0,0 @@ -/* Sticky footer */ - -/** - * Basic idea: https://philipwalton.github.io/solved-by-flexbox/demos/sticky-footer/ - * Details: https://github.com/philipwalton/solved-by-flexbox/blob/master/assets/css/components/site.css - * - * .Site -> body > .container - * .Site-content -> body > .container .row - * .footer -> footer - * - * Key idea seems to be to ensure that .container and __all its parents__ - * have height set to 100% - * - */ - -html, body { - height: 100%; -} - -body { - position: relative; -} - -body > .container { - display: flex; - height: 100%; - flex-direction: column; -} - -body > .container .row { - flex: 1 0 auto; -} - -footer { - margin-top: 45px; - padding: 35px 0 36px; - border-top: 1px solid #e5e5e5; - color: #666; - display: flex; - flex-shrink: 0; -} -footer p { - margin-bottom: 0; -} -footer div { - flex: 1; 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- - var nav_path = paths(links[i].pathname); - - var length = prefix_length(nav_path, cur_path); - if (length > max_length) { - max_length = length; - pos = i; - } - } - - // Add class to parent
  • , and enclosing
  • if in dropdown - if (pos >= 0) { - var menu_anchor = $(links[pos]); - menu_anchor.parent().addClass("active"); - menu_anchor.closest("li.dropdown").addClass("active"); - } - }); - - function paths(pathname) { - var pieces = pathname.split("/"); - pieces.shift(); // always starts with / - - var end = pieces[pieces.length - 1]; - if (end === "index.html" || end === "") - pieces.pop(); - return(pieces); - } - - // Returns -1 if not found - function prefix_length(needle, haystack) { - if (needle.length > haystack.length) - return(-1); - - // Special case for length-0 haystack, since for loop won't run - if (haystack.length === 0) { - return(needle.length === 0 ? 0 : -1); - } - - for (var i = 0; i < haystack.length; i++) { - if (needle[i] != haystack[i]) - return(i); - } - - return(haystack.length); - } - - /* Clipboard --------------------------*/ - - function changeTooltipMessage(element, msg) { - var tooltipOriginalTitle=element.getAttribute('data-original-title'); - element.setAttribute('data-original-title', msg); - $(element).tooltip('show'); - element.setAttribute('data-original-title', tooltipOriginalTitle); - } - - if(ClipboardJS.isSupported()) { - $(document).ready(function() { - var copyButton = ""; - - $("div.sourceCode").addClass("hasCopyButton"); - - // Insert copy buttons: - $(copyButton).prependTo(".hasCopyButton"); - - // Initialize tooltips: - $('.btn-copy-ex').tooltip({container: 'body'}); - - // Initialize clipboard: - var clipboardBtnCopies = new ClipboardJS('[data-clipboard-copy]', { - text: function(trigger) { - return trigger.parentNode.textContent.replace(/\n#>[^\n]*/g, ""); - } - }); - - clipboardBtnCopies.on('success', function(e) { - changeTooltipMessage(e.trigger, 'Copied!'); - e.clearSelection(); - }); - - clipboardBtnCopies.on('error', function() { - changeTooltipMessage(e.trigger,'Press Ctrl+C or Command+C to copy'); - }); - }); - } -})(window.jQuery || window.$) diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml deleted file mode 100644 index 2b21a248..00000000 --- a/docs/pkgdown.yml +++ /dev/null @@ -1,10 +0,0 @@ -pandoc: 3.1.11 -pkgdown: 2.0.9 -pkgdown_sha: ~ -articles: - CreatingAnalysisSpecification: CreatingAnalysisSpecification.html - CreatingModules: CreatingModules.html - ExecuteStrategus: ExecuteStrategus.html - IntroductionToStrategus: IntroductionToStrategus.html -last_built: 2024-06-04T21:18Z - diff --git a/docs/pull_request_template.html b/docs/pull_request_template.html deleted file mode 100644 index 93b0b8d9..00000000 --- a/docs/pull_request_template.html +++ /dev/null @@ -1,105 +0,0 @@ - -NA • Strategus - - -
    -
    - - - -
    -
    -
    -

    NA

    -
    - - -

    Before you do a pull request, you should always file an issue and make sure the package maintainer agrees that it’s a problem, and is happy with your basic proposal for fixing it. We don’t want you to spend a bunch of time on something that we don’t think is a good idea.

    -

    Additional requirements for pull requests:

    -

    • Adhere to the Developer Guidelines as well as the OHDSI Code Style.

      • -

    • If possible, add unit tests for new functionality you add.

      • -

    • Restrict your pull request to solving the issue at hand. Do not try to ‘improve’ parts of the code that are not related to the issue. If you feel other parts of the code need better organization, create a separate issue for that.

      • -

    • Make sure you pass R check without errors and warnings before submitting.

      • -

    • Always target the develop branch, and make sure you are up-to-date with the develop branch.

      • -
    - - - -
    - - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.7.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/Strategus-package.html b/docs/reference/Strategus-package.html deleted file mode 100644 index 9197d743..00000000 --- a/docs/reference/Strategus-package.html +++ /dev/null @@ -1,116 +0,0 @@ - -Strategus: Coordinating and Executing Analytics Using HADES Modules — Strategus-package • Strategus - - -
    -
    - - - -
    -
    -
    -

    Strategus: Coordinating and Executing Analytics Using HADES Modules

    - Source: R/Strategus.R - -
    - -
    -

    An R package for coordinating and executing analytics using HADES modules.

    -
    - - - -
    -

    Author

    -

    Maintainer: Anthony Sena sena@ohdsi.org

    -

    Authors:

    Other contributors:

    • Observational Health Data Science and Informatics [copyright holder]

      • -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/addModuleSpecifications.html b/docs/reference/addModuleSpecifications.html deleted file mode 100644 index 27bf3b31..00000000 --- a/docs/reference/addModuleSpecifications.html +++ /dev/null @@ -1,122 +0,0 @@ - -Add module specifications to analysis specifications — addModuleSpecifications • Strategus - - -
    -
    - - - -
    -
    -
    -

    Add module specifications to analysis specifications

    - Source: R/Settings.R - -
    - -
    -

    Add module specifications to analysis specifications

    -
    - -
    - 
    addModuleSpecifications(analysisSpecifications, moduleSpecifications)
    -
    - -
    -

    Arguments

    -
    analysisSpecifications
    -

    An object of type AnalysisSpecifications as created -by createEmptyAnalysisSpecificiations().

    - - -
    moduleSpecifications
    -

    An object of type ModuleSpecifications.

    - -
    -
    -

    Value

    - - -

    Returns the analysisSpecifications object with the module specifications added.

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/addSharedResources.html b/docs/reference/addSharedResources.html deleted file mode 100644 index 14c5998c..00000000 --- a/docs/reference/addSharedResources.html +++ /dev/null @@ -1,122 +0,0 @@ - -Add shared resources to analysis specifications — addSharedResources • Strategus - - -
    -
    - - - -
    -
    -
    -

    Add shared resources to analysis specifications

    - Source: R/Settings.R - -
    - -
    -

    Add shared resources to analysis specifications

    -
    - -
    - 
    addSharedResources(analysisSpecifications, sharedResources)
    -
    - -
    -

    Arguments

    -
    analysisSpecifications
    -

    An object of type AnalysisSpecifications as created -by createEmptyAnalysisSpecificiations().

    - - -
    sharedResources
    -

    An object of type SharedResources.

    - -
    -
    -

    Value

    - - -

    Returns the analysisSpecifications object with the module specifications added.

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/compareLockFiles.html b/docs/reference/compareLockFiles.html deleted file mode 100644 index ecb363ca..00000000 --- a/docs/reference/compareLockFiles.html +++ /dev/null @@ -1,125 +0,0 @@ - -Compare two renv.lock files — compareLockFiles • Strategus - - -
    -
    - - - -
    -
    -
    -

    Compare two renv.lock files

    - Source: R/RenvHelpers.R - -
    - -
    -

    Used to compare renv.lock files and return the results in a data.frame. -The return value will include a "full join" representation of the packages -across the two lock files.

    -
    - -
    - 
    compareLockFiles(filename1, filename2)
    -
    - -
    -

    Arguments

    -
    filename1
    -

    The first renv.lock file name

    - - -
    filename2
    -

    The second renv.lock file name

    - -
    -
    -

    Value

    - - -

    A data.frame with the comparison of the rev.lock files

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/createCdmExecutionSettings.html b/docs/reference/createCdmExecutionSettings.html deleted file mode 100644 index 666f165e..00000000 --- a/docs/reference/createCdmExecutionSettings.html +++ /dev/null @@ -1,186 +0,0 @@ - -Create CDM execution settings — createCdmExecutionSettings • Strategus - - -
    -
    - - - -
    -
    -
    -

    Create CDM execution settings

    - Source: R/Settings.R - -
    - -
    -

    Create CDM execution settings

    -
    - -
    - 
    createCdmExecutionSettings(
-  connectionDetailsReference,
-  workDatabaseSchema,
-  cdmDatabaseSchema,
-  cohortTableNames = CohortGenerator::getCohortTableNames(cohortTable = "cohort"),
-  tempEmulationSchema = getOption("sqlRenderTempEmulationSchema"),
-  workFolder,
-  resultsFolder,
-  logFileName = file.path(resultsFolder, "strategus-log.txt"),
-  minCellCount = 5,
-  integerAsNumeric = getOption("databaseConnectorIntegerAsNumeric", default = TRUE),
-  integer64AsNumeric = getOption("databaseConnectorInteger64AsNumeric", default = TRUE),
-  resultsConnectionDetailsReference = NULL,
-  resultsDatabaseSchema = NULL
-)
    -
    - -
    -

    Arguments

    -
    connectionDetailsReference
    -

    A string that can be used to retrieve database connection details from a secure local -store.

    - - -
    workDatabaseSchema
    -

    A database schema where intermediate data can be stored. The user (as identified in the -connection details) will need to have write access to this database schema.

    - - -
    cdmDatabaseSchema
    -

    The database schema containing the data in CDM format. The user (as identified in the -connection details) will need to have read access to this database schema.

    - - -
    cohortTableNames
    -

    An object identifying the various cohort table names that will be created in the -workDatabaseSchema. This object can be created using the -CohortGenerator::getCohortTableNames() function.

    - - -
    tempEmulationSchema
    -

    Some database platforms like Oracle and Impala do not truly support temp tables. To emulate temp tables, provide a schema with write privileges where temp tables can be created.

    - - -
    workFolder
    -

    A folder in the local file system where intermediate results can be written.

    - - -
    resultsFolder
    -

    A folder in the local file system where the module output will be written.

    - - -
    logFileName
    -

    Logging information from Strategus and all modules will be located in this file. Individual modules will continue to have their own module-specific logs. By default this will be written to the root of the resultsFolder

    - - -
    minCellCount
    -

    The minimum number of subjects contributing to a count before it can be included -in results.

    - - -
    integerAsNumeric
    -

    Logical: should 32-bit integers be converted to numeric (double) values? If FALSE 32-bit integers will be represented using R's native Integer class. Default is TRUE

    - - -
    integer64AsNumeric
    -

    Logical: should 64-bit integers be converted to numeric (double) values? If FALSE 64-bit integers will be represented using bit64::integer64. Default is TRUE

    - - -
    resultsConnectionDetailsReference
    -

    A string that can be used to retrieve the results database connection -details from a secure local store.

    - - -
    resultsDatabaseSchema
    -

    A schema where the results tables are stored

    - -
    -
    -

    Value

    - - -

    An object of type ExecutionSettings.

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/createEmptyAnalysisSpecificiations.html b/docs/reference/createEmptyAnalysisSpecificiations.html deleted file mode 100644 index 10fbe085..00000000 --- a/docs/reference/createEmptyAnalysisSpecificiations.html +++ /dev/null @@ -1,111 +0,0 @@ - -Create an empty analysis specifications object. — createEmptyAnalysisSpecificiations • Strategus - - -
    -
    - - - -
    -
    -
    -

    Create an empty analysis specifications object.

    - Source: R/Settings.R - -
    - -
    -

    Create an empty analysis specifications object.

    -
    - -
    - 
    createEmptyAnalysisSpecificiations()
    -
    - -
    -

    Value

    - - -

    An object of type AnalysisSpecifications.

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/createExecutionSettings.html b/docs/reference/createExecutionSettings.html deleted file mode 100644 index 2e8536c9..00000000 --- a/docs/reference/createExecutionSettings.html +++ /dev/null @@ -1,131 +0,0 @@ - -Create execution settings — createExecutionSettings • Strategus - - -
    -
    - - - -
    -
    -
    -

    Create execution settings

    - Source: R/Settings.R - -
    - -
    -

    Create execution settings

    -
    - -
    - 
    createExecutionSettings(
-  connectionDetailsReference,
-  workDatabaseSchema,
-  cdmDatabaseSchema,
-  cohortTableNames = CohortGenerator::getCohortTableNames(cohortTable = "cohort"),
-  workFolder,
-  resultsFolder,
-  minCellCount = 5
-)
    -
    - -
    -

    Arguments

    -
    connectionDetailsReference
    -

    A string that can be used to retrieve database connection details from a secure local -store.

    -
    workDatabaseSchema
    -

    A database schema where intermediate data can be stored. The user (as identified in the -connection details) will need to have write access to this database schema.

    -
    cdmDatabaseSchema
    -

    The database schema containing the data in CDM format. The user (as identified in the -connection details) will need to have read access to this database schema.

    -
    cohortTableNames
    -

    An object identifying the various cohort table names that will be created in the -workDatabaseSchema. This object can be created using the -CohortGenerator::getCohortTableNames() function.

    -
    workFolder
    -

    A folder in the local file system where intermediate results can be written.

    -
    resultsFolder
    -

    A folder in the local file system where the module output will be written.

    -
    minCellCount
    -

    The minimum number of subjects contributing to a count before it can be included -in results.

    -
    -
    -

    Value

    -

    An object of type ExecutionSettings.

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie.

    -
    - -
    -

    Site built with pkgdown 2.0.3.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/createResultDataModels.html b/docs/reference/createResultDataModels.html deleted file mode 100644 index a2563a20..00000000 --- a/docs/reference/createResultDataModels.html +++ /dev/null @@ -1,159 +0,0 @@ - -Create Result Data Models — createResultDataModels • Strategus - - -
    -
    - - - -
    -
    -
    -

    Create Result Data Models

    - Source: R/ResultModelCreation.R - -
    - -
    -

    Use this at the study design stage to create data models for modules -This functions loads modules and executes any custom code to create schemas in a results database -If recreate is set to TRUE all existing data will be removed, otherwise

    -
    - -
    - 
    createResultDataModels(
-  analysisSpecifications,
-  executionSettings,
-  executionScriptFolder = NULL,
-  keyringName = NULL,
-  restart = FALSE,
-  enforceModuleDependencies = TRUE
-)
    -
    - -
    -

    Arguments

    -
    analysisSpecifications
    -

    An object of type AnalysisSpecifications as created -by createEmptyAnalysisSpecificiations().

    - - -
    executionSettings
    -

    An object of type ExecutionSettings as created -by createCdmExecutionSettings() or createResultsExecutionSettings().

    - - -
    executionScriptFolder
    -

    Optional: the path to use for storing the execution script. -when NULL, this function will use a temporary -file location to create the script to execute.

    - - -
    keyringName
    -

    The name of the keyring to operate on. This function assumes you have -created the keyring before calling this function. It defaults to -NULL to select the default keyring. If the keyring is password -protected, the password must be stored in the environment variable -STRATEGUS_KEYRING_PASSWORD so it is retrieved using the command -Sys.getenv("STRATEGUS_KEYRING_PASSWORD")

    - - -
    restart
    -

    Restart run? Requires executionScriptFolder to be specified, and be -the same as the executionScriptFolder used in the run to restart.

    - - -
    enforceModuleDependencies
    -

    When set to TRUE, Strategus will enforce -module dependencies that are declared by each module. For example, the -CohortDiagnostics module declares a dependency on the CohortGenerator module -and Strategus will require that an analysis specification declare that both -modules must exist in order to execute the analysis. When set to FALSE, -Strategus will not enforce these module dependencies which assumes you have -properly run all module dependencies yourself. Setting this to FALSE is not -recommended since it is potentially unsafe.

    - -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/createResultsExecutionSettings.html b/docs/reference/createResultsExecutionSettings.html deleted file mode 100644 index 687a16c7..00000000 --- a/docs/reference/createResultsExecutionSettings.html +++ /dev/null @@ -1,156 +0,0 @@ - -Create Results execution settings — createResultsExecutionSettings • Strategus - - -
    -
    - - - -
    -
    -
    -

    Create Results execution settings

    - Source: R/Settings.R - -
    - -
    -

    Create Results execution settings

    -
    - -
    - 
    createResultsExecutionSettings(
-  resultsConnectionDetailsReference,
-  resultsDatabaseSchema,
-  workFolder,
-  resultsFolder,
-  logFileName = file.path(resultsFolder, "strategus-log.txt"),
-  minCellCount = 5,
-  integerAsNumeric = getOption("databaseConnectorIntegerAsNumeric", default = TRUE),
-  integer64AsNumeric = getOption("databaseConnectorInteger64AsNumeric", default = TRUE)
-)
    -
    - -
    -

    Arguments

    -
    resultsConnectionDetailsReference
    -

    A string that can be used to retrieve the results database connection -details from a secure local store.

    - - -
    resultsDatabaseSchema
    -

    A schema where the results tables are stored

    - - -
    workFolder
    -

    A folder in the local file system where intermediate results can be written.

    - - -
    resultsFolder
    -

    A folder in the local file system where the module output will be written.

    - - -
    logFileName
    -

    Logging information from Strategus and all modules will be located in this file. Individual modules will continue to have their own module-specific logs. By default this will be written to the root of the resultsFolder

    - - -
    minCellCount
    -

    The minimum number of subjects contributing to a count before it can be included -in results.

    - - -
    integerAsNumeric
    -

    Logical: should 32-bit integers be converted to numeric (double) values? If FALSE 32-bit integers will be represented using R's native Integer class. Default is TRUE

    - - -
    integer64AsNumeric
    -

    Logical: should 64-bit integers be converted to numeric (double) values? If FALSE 64-bit integers will be represented using bit64::integer64. Default is TRUE

    - -
    -
    -

    Value

    - - -

    An object of type ExecutionSettings.

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/dot-nullList.html b/docs/reference/dot-nullList.html deleted file mode 100644 index 4aa0444f..00000000 --- a/docs/reference/dot-nullList.html +++ /dev/null @@ -1,105 +0,0 @@ - -Used when serializing connection details to retain NULL values — .nullList • Strategus - - -
    -
    - - - -
    -
    -
    -

    Used when serializing connection details to retain NULL values

    - Source: R/Settings.R - -
    - -
    -

    Used when serializing connection details to retain NULL values

    -
    - -
    - 
    .nullList()
    -
    - - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/ensureAllModulesInstantiated.html b/docs/reference/ensureAllModulesInstantiated.html deleted file mode 100644 index 1002ff06..00000000 --- a/docs/reference/ensureAllModulesInstantiated.html +++ /dev/null @@ -1,155 +0,0 @@ - -Ensure all modules are instantiated — ensureAllModulesInstantiated • Strategus - - -
    -
    - - - -
    -
    -
    -

    Ensure all modules are instantiated

    - Source: R/ModuleInstantiation.R - -
    - -
    -

    Ensure that all modules referenced in the analysis specifications are instantiated -locally in the folder specified in the INSTANTIATED_MODULES_FOLDER environmental -variable.

    -

    Missing modules will be fetched from remote repositories.

    -

    This function will also check whether there are different versions of the same -module specified, which is not allowed, and whether all modules required by the -specified modules are also instantiated.

    -
    - -
    - 
    ensureAllModulesInstantiated(
-  analysisSpecifications,
-  forceVerification = FALSE,
-  enforceModuleDependencies = TRUE
-)
    -
    - -
    -

    Arguments

    -
    analysisSpecifications
    -

    An object of type AnalysisSpecifications as created -by createEmptyAnalysisSpecificiations().

    - - -
    forceVerification
    -

    When set to TRUE, the verification process is forced -to re-evaluate if a module is properly installed. The default is FALSE -since if a module is successfully validated, the module will contain -the hash value of the module's renv.lock file in the file system so it can -by-pass running this check every time.

    - - -
    enforceModuleDependencies
    -

    When set to TRUE, Strategus will enforce -module dependencies that are declared by each module. For example, the -CohortDiagnostics module declares a dependency on the CohortGenerator module -and Strategus will require that an analysis specification declare that both -modules must exist in order to execute the analysis. When set to FALSE, -Strategus will not enforce these module dependencies which assumes you have -properly run all module dependencies yourself. Setting this to FALSE is not -recommended since it is potentially unsafe.

    - -
    -
    -

    Value

    - - -

    A list containing the install status of all modules -(TRUE if all are installed properly) and a tibble listing -the instantiated modules.

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/execute.html b/docs/reference/execute.html deleted file mode 100644 index add3fed6..00000000 --- a/docs/reference/execute.html +++ /dev/null @@ -1,162 +0,0 @@ - -Execute analysis specifications. — execute • Strategus - - -
    -
    - - - -
    -
    -
    -

    Execute analysis specifications.

    - Source: R/Execution.R - -
    - -
    -

    Execute analysis specifications.

    -
    - -
    - 
    execute(
-  analysisSpecifications,
-  executionSettings,
-  executionScriptFolder = NULL,
-  keyringName = NULL,
-  restart = FALSE,
-  enforceModuleDependencies = TRUE
-)
    -
    - -
    -

    Arguments

    -
    analysisSpecifications
    -

    An object of type AnalysisSpecifications as created -by createEmptyAnalysisSpecificiations().

    - - -
    executionSettings
    -

    An object of type ExecutionSettings as created -by createCdmExecutionSettings() or createResultsExecutionSettings().

    - - -
    executionScriptFolder
    -

    Optional: the path to use for storing the execution script. -when NULL, this function will use a temporary -file location to create the script to execute.

    - - -
    keyringName
    -

    The name of the keyring to operate on. This function assumes you have -created the keyring before calling this function. It defaults to -NULL to select the default keyring. If the keyring is password -protected, the password must be stored in the environment variable -STRATEGUS_KEYRING_PASSWORD so it is retrieved using the command -Sys.getenv("STRATEGUS_KEYRING_PASSWORD")

    - - -
    restart
    -

    Restart run? Requires executionScriptFolder to be specified, and be -the same as the executionScriptFolder used in the run to restart.

    - - -
    enforceModuleDependencies
    -

    When set to TRUE, Strategus will enforce -module dependencies that are declared by each module. For example, the -CohortDiagnostics module declares a dependency on the CohortGenerator module -and Strategus will require that an analysis specification declare that both -modules must exist in order to execute the analysis. When set to FALSE, -Strategus will not enforce these module dependencies which assumes you have -properly run all module dependencies yourself. Setting this to FALSE is not -recommended since it is potentially unsafe.

    - -
    -
    -

    Value

    - - -

    Does not return anything. Is called for the side-effect of executing the specified -analyses.

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/getModuleList.html b/docs/reference/getModuleList.html deleted file mode 100644 index 85ac4375..00000000 --- a/docs/reference/getModuleList.html +++ /dev/null @@ -1,120 +0,0 @@ - -Provides a list of HADES modules to run through Strategus — getModuleList • Strategus - - -
    -
    - - - -
    -
    -
    -

    Provides a list of HADES modules to run through Strategus

    - Source: R/Settings.R - -
    - -
    -

    This function provides a list of modules and their locations -that may be used with Strategus.

    -
    - -
    - 
    getModuleList()
    -
    - -
    -

    Value

    - - -

    A data.frame() of modules that work with Strategus. This will contain: -module = The name of the module -version = The version of the module -remote_repo = The remote location of the module (i.e. github.com) -remote_username = The organization of the module (i.e. OHDSI) -module_type = 'cdm' or 'results'. 'cdm' refers to modules that are designed to work against -patient level data in the OMOP CDM format. 'results' refers to modules that are designed -to work against a results database containing output from a 'cdm' module.

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/index.html b/docs/reference/index.html deleted file mode 100644 index 923e4843..00000000 --- a/docs/reference/index.html +++ /dev/null @@ -1,179 +0,0 @@ - -Function reference • Strategus - - -
    -
    - - - -
    -
    -
    -

    Reference

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    -

    All functions

    -

    -
    -

    addModuleSpecifications()

    -

    Add module specifications to analysis specifications

    -

    addSharedResources()

    -

    Add shared resources to analysis specifications

    -

    compareLockFiles()

    -

    Compare two renv.lock files

    -

    createCdmExecutionSettings()

    -

    Create CDM execution settings

    -

    createEmptyAnalysisSpecificiations()

    -

    Create an empty analysis specifications object.

    -

    createResultDataModels()

    -

    Create Result Data Models

    -

    createResultsExecutionSettings()

    -

    Create Results execution settings

    -

    ensureAllModulesInstantiated()

    -

    Ensure all modules are instantiated

    -

    execute()

    -

    Execute analysis specifications.

    -

    getModuleList()

    -

    Provides a list of HADES modules to run through Strategus

    -

    installLatestModule()

    -

    Install the latest release of a module

    -

    retrieveConnectionDetails()

    -

    Retrieve connection details from the secure location

    -

    runSchemaCreation()

    -

    Create module(s) result data model

    -

    storeConnectionDetails()

    -

    Store connection details in a secure location

    -

    syncLockFile()

    -

    Synchronize renv.lock files and overwrite the target file (read the description)

    -

    unlockKeyring()

    -

    Helper function to unlock a keyring

    -

    validateLockFile()

    -

    Validate an renv.lock file to ensure it is ready for use by Strategus

    -

    verifyModuleInstallation()

    -

    Verify a module is properly installed

    -

    withModuleRenv()

    -

    Load module execution space inside and renv inspired by targets::tar_script but allowing custom variable execution

    -

    zipResults()

    -

    Create a zip file with all study results for sharing with study coordinator

    - - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/installLatestModule.html b/docs/reference/installLatestModule.html deleted file mode 100644 index 7d1634fe..00000000 --- a/docs/reference/installLatestModule.html +++ /dev/null @@ -1,124 +0,0 @@ - -Install the latest release of a module — installLatestModule • Strategus - - -
    -
    - - - -
    -
    -
    -

    Install the latest release of a module

    - Source: R/ModuleInstantiation.R - -
    - -
    -

    This function will call out to the OHDSI GitHub repo to find the latest -version of the module and attempt to install it. Only modules that are listed -in the getModuleList() function are allowed since it will have a known -GitHub location.

    -
    - -
    - 
    installLatestModule(moduleName)
    -
    - -
    -

    Arguments

    -
    moduleName
    -

    The name of the module to install (i.e. "CohortGeneratorModule"). -This parameter must match a value found in the module column of getModuleList()

    - -
    -
    -

    Value

    - - -

    None - this function is called for its side effects

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/lockFileToDataFrame.html b/docs/reference/lockFileToDataFrame.html deleted file mode 100644 index e77aaffa..00000000 --- a/docs/reference/lockFileToDataFrame.html +++ /dev/null @@ -1,105 +0,0 @@ - -Convert a lock file to a data.frame — lockFileToDataFrame • Strategus - - -
    -
    - - - -
    -
    -
    -

    Convert a lock file to a data.frame

    - Source: R/RenvHelpers.R - -
    - -
    -

    Convert a lock file to a data.frame

    -
    - -
    - 
    lockFileToDataFrame(lf)
    -
    - - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/mandatoryPackages.html b/docs/reference/mandatoryPackages.html deleted file mode 100644 index c3a909c8..00000000 --- a/docs/reference/mandatoryPackages.html +++ /dev/null @@ -1,105 +0,0 @@ - -List of mandatory packages for a Strategus module — mandatoryPackages • Strategus - - -
    -
    - - - -
    -
    -
    -

    List of mandatory packages for a Strategus module

    - Source: R/RenvHelpers.R - -
    - -
    -

    List of mandatory packages for a Strategus module

    -
    - -
    - 
    mandatoryPackages()
    -
    - - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/retrieveConnectionDetails.html b/docs/reference/retrieveConnectionDetails.html deleted file mode 100644 index 56432e61..00000000 --- a/docs/reference/retrieveConnectionDetails.html +++ /dev/null @@ -1,131 +0,0 @@ - -Retrieve connection details from the secure location — retrieveConnectionDetails • Strategus - - -
    -
    - - - -
    -
    -
    -

    Retrieve connection details from the secure location

    - Source: R/Settings.R - -
    - -
    -

    Retrieve connection details from the secure location

    -
    - -
    - 
    retrieveConnectionDetails(connectionDetailsReference, keyringName = NULL)
    -
    - -
    -

    Arguments

    -
    connectionDetailsReference
    -

    A string that can be used to retrieve the settings from -the secure store.

    - - -
    keyringName
    -

    The name of the keyring to operate on. This function assumes you have -created the keyring before calling this function. It defaults to -NULL to select the default keyring. If the keyring is password -protected, the password must be stored in the environment variable -STRATEGUS_KEYRING_PASSWORD so it is retrieved using the command -Sys.getenv("STRATEGUS_KEYRING_PASSWORD")

    - -
    -
    -

    Value

    - - -

    Returns an object of type connectionDetails.

    -
    -
    -

    See also

    -

    storeConnectionDetails()

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/runSchemaCreation.html b/docs/reference/runSchemaCreation.html deleted file mode 100644 index 46d5973d..00000000 --- a/docs/reference/runSchemaCreation.html +++ /dev/null @@ -1,145 +0,0 @@ - -Create module(s) result data model — runSchemaCreation • Strategus - - -
    -
    - - - -
    -
    -
    -

    Create module(s) result data model

    - Source: R/ResultModelCreation.R - -
    - -
    -

    This function will create the results data model for the modules in the -analysisSpecifications. A module can implement its own results data model -creation function by implementing the function createDataModelSchema in -its Main.R. The default behavior is to use the ResultsModelManager to create -the results data model based on the resultsDataModelSpecification.csv in the -module's results folder.

    -
    - -
    - 
    runSchemaCreation(
-  analysisSpecifications,
-  keyringSettings,
-  moduleIndex,
-  executionSettings,
-  ...
-)
    -
    - -
    -

    Arguments

    -
    analysisSpecifications
    -

    An object of type AnalysisSpecifications as created -by createEmptyAnalysisSpecificiations().

    - - -
    keyringSettings
    -

    The keyringSettings from the executionSettings context

    - - -
    moduleIndex
    -

    The index of the module in the analysis specification

    - - -
    executionSettings
    -

    An object of type ExecutionSettings as created -by createCdmExecutionSettings() or createResultsExecutionSettings().

    - - -
    ...
    -

    For future expansion

    - -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/storeConnectionDetails.html b/docs/reference/storeConnectionDetails.html deleted file mode 100644 index 1ae81fc6..00000000 --- a/docs/reference/storeConnectionDetails.html +++ /dev/null @@ -1,141 +0,0 @@ - -Store connection details in a secure location — storeConnectionDetails • Strategus - - -
    -
    - - - -
    -
    -
    -

    Store connection details in a secure location

    - Source: R/Settings.R - -
    - -
    -

    Store connection details in a secure location

    -
    - -
    - 
    storeConnectionDetails(
-  connectionDetails,
-  connectionDetailsReference,
-  keyringName = NULL
-)
    -
    - -
    -

    Arguments

    -
    connectionDetails
    -

    An object of type connectionDetails as created by the -DatabaseConnector::createConnectionDetails() function.

    - - -
    connectionDetailsReference
    -

    A string that can be used to retrieve the settings from -the secure store.

    - - -
    keyringName
    -

    The name of the keyring to operate on. This function assumes you have -created the keyring before calling this function. It defaults to -NULL to select the default keyring. If the keyring is password -protected, the password must be stored in the environment variable -STRATEGUS_KEYRING_PASSWORD so it is retrieved using the command -Sys.getenv("STRATEGUS_KEYRING_PASSWORD")

    - -
    -
    -

    Value

    - - -

    Does not return anything. Is called for the side effect of having the connection details -stored.

    -
    - - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/suggestedPacakges.html b/docs/reference/suggestedPacakges.html deleted file mode 100644 index 7168ba3e..00000000 --- a/docs/reference/suggestedPacakges.html +++ /dev/null @@ -1,105 +0,0 @@ - -List of suggested packages for a Strategus module — suggestedPacakges • Strategus - - -
    -
    - - - -
    -
    -
    -

    List of suggested packages for a Strategus module

    - Source: R/RenvHelpers.R - -
    - -
    -

    List of suggested packages for a Strategus module

    -
    - -
    - 
    suggestedPacakges()
    -
    - - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/syncLockFile.html b/docs/reference/syncLockFile.html deleted file mode 100644 index bf88a5fe..00000000 --- a/docs/reference/syncLockFile.html +++ /dev/null @@ -1,138 +0,0 @@ - -Synchronize renv.lock files and overwrite the target file (read the description) — syncLockFile • Strategus - - -
    -
    - - - -
    -
    -
    -

    Synchronize renv.lock files and overwrite the target file (read the description)

    - Source: R/RenvHelpers.R - -
    - -
    -

    Used to synchronize the values from the "source of truth" renv.lock file to -the target renv.lock file. Packages are compared (by name) and if the version -of the package in the "source of truth" is greater the one found in the -target, the target renv.lock file will be updated. This function will -automatically update the target file.

    -

    Version comparison is handled by the semver package and since most packages -use semantic versioning. When a package does not use semantic versioning, -a warning is provided so the user can review.

    -
    - -
    - 
    syncLockFile(sourceOfTruthLockFileName, targetLockFileName)
    -
    - -
    -

    Arguments

    -
    sourceOfTruthLockFileName
    -

    The renv.lock file to use as the source of -truth

    - - -
    targetLockFileName
    -

    The target renv.lock file that will be synced with -the source of truth

    - -
    -
    -

    Value

    - - -

    A data.frame containing the different packages and their version that -were involved in the synchronization process

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/unlockKeyring.html b/docs/reference/unlockKeyring.html deleted file mode 100644 index ac620664..00000000 --- a/docs/reference/unlockKeyring.html +++ /dev/null @@ -1,127 +0,0 @@ - -Helper function to unlock a keyring — unlockKeyring • Strategus - - -
    -
    - - - -
    -
    -
    -

    Helper function to unlock a keyring

    - Source: R/Settings.R - -
    - -
    -

    This helper function is used to unlock a keyring by using the password -stored in Sys.getenv("STRATEGUS_KEYRING_PASSWORD"). It will alert -the user if the environment variable with the password is not set.

    -
    - -
    - 
    unlockKeyring(keyringName)
    -
    - -
    -

    Arguments

    -
    keyringName
    -

    The name of the keyring to operate on. This function assumes you have -created the keyring before calling this function. It defaults to -NULL to select the default keyring. If the keyring is password -protected, the password must be stored in the environment variable -STRATEGUS_KEYRING_PASSWORD so it is retrieved using the command -Sys.getenv("STRATEGUS_KEYRING_PASSWORD")

    - -
    -
    -

    Value

    - - -

    Returns TRUE if the keyring was unlocked using the password otherwise -it returns FALSE

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/validateLockFile.html b/docs/reference/validateLockFile.html deleted file mode 100644 index 192738e5..00000000 --- a/docs/reference/validateLockFile.html +++ /dev/null @@ -1,117 +0,0 @@ - -Validate an renv.lock file to ensure it is ready for use by Strategus — validateLockFile • Strategus - - -
    -
    - - - -
    -
    -
    -

    Validate an renv.lock file to ensure it is ready for use by Strategus

    - Source: R/RenvHelpers.R - -
    - -
    -

    Will check an renv.lock file for a module to verify that it only references -tagged packages and includes the packages required by Strategus. It will -also check for suggested packages that are useful for testing, such as -RSQLite.

    -
    - -
    - 
    validateLockFile(filename)
    -
    - -
    -

    Arguments

    -
    filename
    -

    The renv.lock file to validate

    - -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/verifyModuleInstallation.html b/docs/reference/verifyModuleInstallation.html deleted file mode 100644 index 2ffcca3b..00000000 --- a/docs/reference/verifyModuleInstallation.html +++ /dev/null @@ -1,162 +0,0 @@ - -Verify a module is properly installed — verifyModuleInstallation • Strategus - - -
    -
    - - - -
    -
    -
    -

    Verify a module is properly installed

    - Source: R/ModuleInstantiation.R - -
    - -
    -

    In some instances a module may fail to instantiate and install due to problems -when calling renv::restore for the module's renv.lock file. This function -will allow you to surface inconsistencies between the module renv.lock file -and the module's renv project library. This function will check to that a -module has been properly installed using internal functions of the renv -package. If a module is verified to work via this function, the hash of -the module's renv.lock file will be written to a text file in the module -directory to indicate that it is ready for use. This will allow subsequent -calls to work faster since the initial verification process can take some -time.It is possible to re-run the verification of a module -by using the forceVerification parameter.

    -

    To fix issues with a module, you will need to open the module's .Rproj in -RStudio instance and debug the issues when calling renv::restore().

    -
    - -
    - 
    verifyModuleInstallation(
-  module,
-  version,
-  silent = FALSE,
-  forceVerification = FALSE
-)
    -
    - -
    -

    Arguments

    -
    module
    -

    The name of the module to verify (i.e. "CohortGeneratorModule")

    - - -
    version
    -

    The version of the module to verify (i.e. "0.2.1")

    - - -
    silent
    -

    When TRUE output of this verification process is suppressed

    - - -
    forceVerification
    -

    When set to TRUE, the verification process is forced -to re-evaluate if a module is properly installed. The default is FALSE -since if a module is successfully validated, the module will contain -the hash value of the module's renv.lock file in the file system so it can -by-pass running this check every time.

    - -
    -
    -

    Value

    - - -

    A list with the output of the consistency check

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/withModuleRenv.html b/docs/reference/withModuleRenv.html deleted file mode 100644 index ef2dd7a6..00000000 --- a/docs/reference/withModuleRenv.html +++ /dev/null @@ -1,152 +0,0 @@ - -Load module execution space inside and renv inspired by targets::tar_script but allowing custom variable execution — withModuleRenv • Strategus - - -
    -
    - - - -
    -
    -
    -

    Load module execution space inside and renv inspired by targets::tar_script but allowing custom variable execution

    - Source: R/ModuleEnv.R - -
    - -
    -

    Designed to allow more human readable code that is executed inside a module as well as simple variable substituion -for injecting constants (e.g. simple parameters or file paths used inside and outside of modules)

    -
    - -
    - 
    withModuleRenv(
-  code,
-  moduleFolder,
-  injectVars = list(),
-  tempScriptFile = tempfile(fileext = ".R"),
-  job = FALSE,
-  processName = paste(moduleFolder, "_renv_run")
-)
    -
    - -
    -

    Arguments

    -
    code
    -

    code block to execute

    - - -
    moduleFolder
    -

    Instantiated Strategus module folder

    - - -
    injectVars
    -

    list of var names list(name=value) to replace (e.g. replace list(foo = "some string") will -find the pattern foo and replace it with the string some string - be careful!

    - - -
    tempScriptFile
    -

    tempFile to write script to

    - - -
    job
    -

    run as rstudio job

    - - -
    processName
    -

    String name for process

    - -
    -
    -

    Value

    - - -

    NULL invisibly

    -
    -
    -

    Details

    -

    This pattern also allows dependency injection which could be used if you don't want to use and renv and (instead) -would like to use docker images or just execution in the base environment for testing/debugging

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/reference/zipResults.html b/docs/reference/zipResults.html deleted file mode 100644 index a1a3498f..00000000 --- a/docs/reference/zipResults.html +++ /dev/null @@ -1,130 +0,0 @@ - -Create a zip file with all study results for sharing with study coordinator — zipResults • Strategus - - -
    -
    - - - -
    -
    -
    -

    Create a zip file with all study results for sharing with study coordinator

    - Source: R/ShareResults.R - -
    - -
    -

    Create a zip file with all study results for sharing with study coordinator

    -
    - -
    - 
    zipResults(resultsFolder, zipFile)
    -
    - -
    -

    Arguments

    -
    resultsFolder
    -

    The folder holding the study results. This is found in -executionSettings$resultsFolder.

    - - -
    zipFile
    -

    The path to the zip file to be created.

    - -
    -
    -

    Value

    - - -

    Does not return anything. Is called for the side-effect of creating the -zip file with results.

    -
    -
    -

    Details

    -

    Creates a .zip file of the .csv files found in the -resultsFolder. The resulting .zip file will have -relative paths to the root of the resultsFolder -which is generally found in executionSettings$resultsFolder.

    -
    - -
    - -
    - - -
    -

    Developed by Martijn Schuemie, Anthony Sena, Jamie Gilbert.

    -
    - -
    -

    Site built with pkgdown 2.0.9.

    -
    - -
    - - - - - - - - diff --git a/docs/sitemap.xml b/docs/sitemap.xml deleted file mode 100644 index 1ccb0285..00000000 --- a/docs/sitemap.xml +++ /dev/null @@ -1,114 +0,0 @@ - - - - /404.html - - - /articles/CreatingAnalysisSpecification.html - - - /articles/CreatingModules.html - - - /articles/ExecuteStrategus.html - - - /articles/index.html - - - /articles/IntroductionToStrategus.html - - - /authors.html - - - /index.html - - - /news/index.html - - - /pull_request_template.html - - - /reference/addModuleSpecifications.html - - - /reference/addSharedResources.html - - - /reference/compareLockFiles.html - - - /reference/createCdmExecutionSettings.html - - - /reference/createEmptyAnalysisSpecificiations.html - - - /reference/createExecutionSettings.html - - - /reference/createResultDataModels.html - - - /reference/createResultsExecutionSettings.html - - - /reference/dot-nullList.html - - - /reference/ensureAllModulesInstantiated.html - - - /reference/execute.html - - - /reference/getModuleList.html - - - /reference/index.html - - - /reference/installLatestModule.html - - - /reference/lockFileToDataFrame.html - - - /reference/mandatoryPackages.html - - - /reference/retrieveConnectionDetails.html - - - /reference/runSchemaCreation.html - - - /reference/storeConnectionDetails.html - - - /reference/Strategus-package.html - - - /reference/suggestedPacakges.html - - - /reference/syncLockFile.html - - - /reference/unlockKeyring.html - - - /reference/validateLockFile.html - - - /reference/verifyModuleInstallation.html - - - /reference/withModuleRenv.html - - - /reference/zipResults.html - - diff --git a/extras/DocumentResultsDataModel.R b/extras/DocumentResultsDataModel.R new file mode 100644 index 00000000..b6944ffe --- /dev/null +++ b/extras/DocumentResultsDataModel.R @@ -0,0 +1,191 @@ +# ------------------------------------------------------------------------------ +# This script does the following: +# - Uses a local PG instance to create the results data model. The data +# model is then exported to produce a SQL script that is then used by GHA +# to build the SchemaSpy results data model documentation. +# - Creates the SchemaSpy SchemaMeta.xml used to build the documentation. +# This XML contains the table descriptions, column descriptions and +# FK relationships between the entities. +# (https://schemaspy.readthedocs.io/en/latest/configuration/schemaMeta.html) +# +# Notes about resources found in the /extras/rdms directory: +# - table_descriptions.csv: Hand currated table descriptions. Column descriptions +# come from the module rdms files. +# - SqlExtractor.java: Program to parse out the OhdsiShinyModules R files to +# extract the SQL used by the results viewer. The output of this program is +# contained in ohdsi_shiny_modules_sql_queries.csv +# - SqlJoinRelationshipExtractor.java: Program to parse +# ohdsi_shiny_modules_sql_queries.csv and identify the JOIN clauses to +# document the relationships in the data model. Results of this program are +# in ohdsi_shiny_modules_table_relationships.csv. +# - results_table_realtionships.xlsx: Manually reviewed the ohdsi_shiny_modules_table_relationships.csv +# and extracted the list of tables and their foreign key relationships. +# - results_table_relationships.csv: Exported the unique entries from +# results_table_realtionships.xlsx. This resource is then used when constructing +# the SchemaSpy SchemaMeta.xml +# ------------------------------------------------------------------------------ +library(Strategus) +library(dplyr) + +# fullResultsDataModel will hold the full results model to create the +# SchemaSpyMeta.xml +fullResultsDataModel <- tibble::tibble() +rdms <- CohortGenerator::readCsv( + file = system.file( + file.path("csv", "databaseMetaDataRdms.csv"), + package = "Strategus" + ), + warnOnCaseMismatch = F +) +rdms$tableDefinedBy <- "Strategus" + +fullResultsDataModel <- fullResultsDataModel %>% + bind_rows(rdms %>% select(tableDefinedBy, tableName, columnName, description)) + +sql <- "-- Strategus Tables\n" +sql <- paste0(sql, ResultModelManager::generateSqlSchema(schemaDefinition = rdms)) + +# Iterate over all of the modules in the project +# and produce the full results data model specification +# for each module +moduleFileList <- list.files("./R", pattern = "^Module-.*\\.R$") +fileNameCleaned <- sub("^Module-", "", moduleFileList) # Remove "Module-" +fileNameCleaned <- sub("\\.R$", "", fileNameCleaned) # Remove ".R" +moduleList <- paste0(fileNameCleaned, "Module") + +for(module in moduleList) { + m <- get(module)$new() + rdms <- m$getResultsDataModelSpecification() + + sql <- paste0(sql, "-- ", module, " Tables\n") + sql <- paste0(sql, ResultModelManager::generateSqlSchema(schemaDefinition = rdms)) + + if (!"description" %in% colnames(rdms)) { + rdms$description <- "" + } + rdms$tableDefinedBy <- module + + fullResultsDataModel <- fullResultsDataModel %>% + bind_rows(rdms %>% select(tableDefinedBy, tableName, columnName, description)) +} + +# NOTE: This code was to initially save the table information to a csv file +# that will be manually edited to include the table descriptions +# tableDescriptions <- fullResultsDataModel %>% +# select(tableDefinedBy, tableName) %>% +# distinct() %>% +# mutate(description = "") %>% +# arrange(tableName) +# CohortGenerator::writeCsv( +# x = tableDescriptions, +# file = "./extras/rdms/table_descriptions.csv" +# ) + +# Save the OHDSI-SQL +SqlRender::writeSql( + sql = sql, + targetFile = "./extras/rdms/full_data_model_ohdsi.sql" +) + +# Render for PostgreSQL +pgSql <- SqlRender::render( + sql = sql, + database_schema = "results" +) +pgSql <- SqlRender::translate( + sql = pgSql, + targetDialect = "postgresql" +) +SqlRender::writeSql( + sql = pgSql, + targetFile = "./extras/rdms/full_data_model_pg.sql" +) + +# Write out the SchemaSpy SchemaMeta.xml --------------------------- +library(xml2) + +# Create the root element with attributes +schemaMeta <- xml_new_root("schemaMeta", + "xmlns:xsi" = "http://www.w3.org/2001/XMLSchema-instance", + "xsi:noNamespaceSchemaLocation" = "http://schemaspy.org/xsd/6/schemameta.xsd") + +# Add comments node +xml_add_child( + schemaMeta, + "comments", + "The tables in the results data model are grouped using a unique prefix for + each Strategus module. For example, the CharacterizationModule results tables + all start with \"c_\".") + +# Create tables node +tables <- xml_add_child(schemaMeta, "tables") + +# Iterate over the fullResultsDataModel to create the descriptions +# of the tables & columns. +uniqueTableNames <- unique(fullResultsDataModel$tableName) +tableDescriptions <- CohortGenerator::readCsv( + file = "./extras/rdms/table_descriptions.csv" +) +resultsTableRelationships <-CohortGenerator::readCsv( + file = "./extras/rdms/results_table_relationships.csv" +) +for (i in seq_along(uniqueTableNames)) { + # Add table node with attributes + currentTableName <- uniqueTableNames[i] + #print(currentTableName) + # Get the table description, if it exists + currentTableDescriptionInfo <- tableDescriptions %>% + filter(.data$tableName == currentTableName) + currentTableDescription <- "" + if (nrow(currentTableDescriptionInfo) == 1) { + currentTableDescription <- paste0(currentTableDescriptionInfo$tableDefinedBy[1], ": ", currentTableDescriptionInfo$description[1]) + } + table <- xml_add_child(tables, "table", name = currentTableName, comments = currentTableDescription) + + # Get the columns + columnsForCurrentTable <- fullResultsDataModel %>% + filter(.data$tableName == currentTableName) + + for (j in 1:nrow(columnsForCurrentTable)) { + curColumnName <- columnsForCurrentTable$columnName[j] + description <- columnsForCurrentTable$description[j] + #print(paste0(" -- ", curColumnName)) + # Add column node with attributes + columnNode <- xml_add_child(table, "column", name = curColumnName, comments = description) + # Determine if this table + column has a FK relationship to any other tables + curColumnFk <- resultsTableRelationships %>% + filter(.data$tableName == currentTableName & .data$columnName == curColumnName) + if (nrow(curColumnFk) > 0) { + #print(paste0("-- FK FOUND FOR: ", currentTableName, ".", curColumnName)) + for (k in 1:nrow(curColumnFk)) { + fkTable <- curColumnFk$fkTableName[k] + fkColumn <- curColumnFk$fkColumnName[k] + xml_add_child(columnNode, "foreignKey", table = fkTable, column = fkColumn) + } + } + } +} + +# Write the XML string to a file, omitting the XML declaration +write_xml(schemaMeta, "./extras/rdms/schema_meta.xml") + + +# Used to create the DB locally to assist in documenting the +# results model. +# connectionDetails <- DatabaseConnector::createConnectionDetails( +# dbms = "postgresql", +# server = "127.0.0.1/strategus", +# user = "user", +# password = "password" +# ) +# connection <- DatabaseConnector::connect(connectionDetails) +# DatabaseConnector::executeSql( +# connection = connection, +# sql = "drop schema results cascade;create schema results;" +# ) +# sql <- SqlRender::readSql("./extras/rdms/full_data_model_pg.sql") +# DatabaseConnector::executeSql( +# connection = connection, +# sql = sql +# ) +# DatabaseConnector::disconnect(connection) diff --git a/extras/ESModule-SimulateResultsForTesting.R b/extras/ESModule-SimulateResultsForTesting.R new file mode 100644 index 00000000..edce0d9e --- /dev/null +++ b/extras/ESModule-SimulateResultsForTesting.R @@ -0,0 +1,99 @@ +# This file was part of EvidenceSynthesisModule + +library(dplyr) +source("extras/ESModule-SimulationFunctions.R") + +databaseFile <- "inst/testdata/esmodule/results.sqlite" +if (file.exists(databaseFile)) { + unlink(databaseFile) +} +connection <- DatabaseConnector::connect(dbms = "sqlite", server = databaseFile) + +# Simulate CohortMethod data --------------------------------------------------- + +targetId <- 1 +comparatorId <- 2 +# outcomeId <- 1 +for (outcomeId in 1:26) { + message(sprintf("Simulating outcome %d", outcomeId)) + outcomeOfInterest <- outcomeId == 1 + trueEffectSize <- if_else(outcomeOfInterest, 2, 1) + cmTargetComparatorOutcome <- tibble( + targetId = targetId, + comparatorId = comparatorId, + outcomeId = outcomeId, + trueEffectSize = trueEffectSize, + outcomeOfInterest = outcomeOfInterest + ) + DatabaseConnector::insertTable( + connection = connection, + databaseSchema = "main", + tableName = "cm_target_comparator_outcome", + data = cmTargetComparatorOutcome, + createTable = outcomeId == 1, + dropTableIfExists = FALSE, + camelCaseToSnakeCase = TRUE + ) + for (analysisId in 1:4) { + simulateTco(targetId, comparatorId, outcomeId, analysisId, hazardRatio = trueEffectSize) + } +} + +# Simulate SCCS data ----------------------------------------------------------- +exposureId <- 100 +# outcomeId <- 1 +for (outcomeId in 1:26) { + message(sprintf("Simulating outcome %d", outcomeId)) + outcomeOfInterest <- outcomeId == 1 + trueEffectSize <- if_else(outcomeOfInterest, 2, 1) + + sccsExposuresOutcomeSet <- tibble( + exposuresOutcomeSetId = outcomeId, + outcomeId = !!outcomeId, + nestingCohortId = NA + ) + DatabaseConnector::insertTable( + connection = connection, + databaseSchema = "main", + tableName = "sccs_exposures_outcome_set", + data = sccsExposuresOutcomeSet, + createTable = outcomeId == 1, + dropTableIfExists = outcomeId == 1, + camelCaseToSnakeCase = TRUE + ) + + sccsExposure <- tibble( + exposuresOutcomeSetId = outcomeId, + eraId = !!exposureId, + trueEffectSize = ifelse(trueEffectSize == 1, 1, NA), + ) + DatabaseConnector::insertTable( + connection = connection, + databaseSchema = "main", + tableName = "sccs_exposure", + data = sccsExposure, + createTable = outcomeId == 1, + dropTableIfExists = outcomeId == 1, + camelCaseToSnakeCase = TRUE + ) + + sccsCovariateAnalysis <- tibble( + analysisId = 1:4, + covariateAnalysisId = 1, + variableOfInterest = 1 + ) + DatabaseConnector::insertTable( + connection = connection, + databaseSchema = "main", + tableName = "sccs_covariate_analysis", + data = sccsCovariateAnalysis, + createTable = outcomeId == 1, + dropTableIfExists = outcomeId == 1, + camelCaseToSnakeCase = TRUE + ) + + for (analysisId in 1:4) { + simulateEo(exposureId = exposureId, outcomeId = outcomeId, analysisId = analysisId, incidenceRateRatio = trueEffectSize) + } +} +DatabaseConnector::disconnect(connection) diff --git a/extras/ESModule-SimulationFunctions.R b/extras/ESModule-SimulationFunctions.R new file mode 100644 index 00000000..86606d7d --- /dev/null +++ b/extras/ESModule-SimulationFunctions.R @@ -0,0 +1,270 @@ +# Copyright 2024 Observational Health Data Sciences and Informatics +# +# This file is part of Strategus +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# Functions used in extras/ESModule-SimulateResultsForTesting.R + +library(survival) + +simulateTco <- function(targetId, comparatorId, outcomeId, analysisId, hazardRatio = 1, nSites = 10) { + simulationSettings <- EvidenceSynthesis::createSimulationSettings( + nSites = nSites, + n = 2500, + treatedFraction = 0.25, + hazardRatio = hazardRatio, + randomEffectSd = if_else(hazardRatio == 1, 0, 0.5) + ) + cmDiagnosticsSummary <- tibble( + targetId = targetId, + comparatorId = comparatorId, + outcomeId = outcomeId, + analysisId = analysisId, + databaseId = seq_len(nSites), + mdrr = 2, + unblind = runif(nSites) < 0.9 + ) + + populations <- EvidenceSynthesis::simulatePopulations(simulationSettings) + cmResult <- list() + cmLikelihoodProfile <- list() + # i = 1 + for (i in seq_along(populations)) { + population <- populations[[i]] + cyclopsData <- Cyclops::createCyclopsData(Surv(time, y) ~ x + strata(stratumId), + data = population, + modelType = "cox" + ) + cyclopsFit <- Cyclops::fitCyclopsModel(cyclopsData) + ci <- tryCatch( + { + confint(cyclopsFit, parm = 1, includePenalty = TRUE) + }, + error = function(e) { + c(0, -Inf, Inf) + } + ) + normal <- EvidenceSynthesis::approximateLikelihood(cyclopsFit, "x", approximation = "normal") + adaptiveGrid <- EvidenceSynthesis::approximateLikelihood(cyclopsFit, "x", approximation = "adaptive grid") + z <- normal$logRr / normal$seLogRr + p <- 2 * pmin(pnorm(z), 1 - pnorm(z)) + cmResult[[i]] <- tibble( + targetId = targetId, + comparatorId = comparatorId, + outcomeId = outcomeId, + analysisId = analysisId, + databaseId = i, + targetSubjects = sum(population$x == 1), + comparatorSubjects = sum(population$x == 0), + targetDays = sum(population$time[population$x == 1]), + comparatorDays = sum(population$time[population$x == 0]), + targetOutcomes = sum(population$y[population$x == 1]), + comparatorOutcomes = sum(population$y[population$x == 0]), + rr = exp(normal$logRr), + ci95Lb = exp(ci[2]), + ci95Ub = exp(ci[3]), + p = p, + logRr = normal$logRr, + seLogRr = normal$seLogRr + ) + cmLikelihoodProfile[[i]] <- adaptiveGrid %>% + rename( + logRr = .data$point, + logLikelihood = .data$value + ) %>% + mutate( + targetId = targetId, + comparatorId = comparatorId, + outcomeId = outcomeId, + analysisId = analysisId, + databaseId = i + ) + } + cmResult <- bind_rows(cmResult) + cmLikelihoodProfile <- bind_rows(cmLikelihoodProfile) + tablesExist <- DatabaseConnector::existsTable( + connection = connection, + databaseSchema = "main", + tableName = "cm_diagnostics_summary" + ) + + DatabaseConnector::insertTable( + connection = connection, + databaseSchema = "main", + tableName = "cm_diagnostics_summary", + data = cmDiagnosticsSummary, + createTable = !tablesExist, + dropTableIfExists = FALSE, + camelCaseToSnakeCase = TRUE + ) + DatabaseConnector::insertTable( + connection = connection, + databaseSchema = "main", + tableName = "cm_result", + data = cmResult, + createTable = !tablesExist, + dropTableIfExists = FALSE, + camelCaseToSnakeCase = TRUE + ) + DatabaseConnector::insertTable( + connection = connection, + databaseSchema = "main", + tableName = "cm_likelihood_profile", + data = cmLikelihoodProfile, + createTable = !tablesExist, + dropTableIfExists = FALSE, + camelCaseToSnakeCase = TRUE + ) +} + +simulateEo <- function(exposureId, outcomeId, analysisId, incidenceRateRatio = 1, nSites = 10) { + simulationRiskWindows <- list(SelfControlledCaseSeries::createSimulationRiskWindow(relativeRisks = incidenceRateRatio)) + + simulationSettings <- SelfControlledCaseSeries::createSccsSimulationSettings( + eraIds = exposureId, + simulationRiskWindows = simulationRiskWindows, + outcomeId = outcomeId + ) + sccsResult <- list() + sccsLikelihoodProfile <- list() + for (i in seq_len(nSites)) { + sccsData <- SelfControlledCaseSeries::simulateSccsData( + nCases = 1000, + settings = simulationSettings + ) + studyPop <- SelfControlledCaseSeries::createStudyPopulation( + sccsData = sccsData, + outcomeId = outcomeId, + firstOutcomeOnly = TRUE, + naivePeriod = 180 + ) + eraCovariateSettings <- SelfControlledCaseSeries::createEraCovariateSettings( + includeEraIds = exposureId, + profileLikelihood = TRUE + ) + sccsIntervalData <- SelfControlledCaseSeries::createSccsIntervalData( + studyPopulation = studyPop, + sccsData = sccsData, + eraCovariateSettings = eraCovariateSettings + ) + model <- SelfControlledCaseSeries::fitSccsModel( + sccsIntervalData = sccsIntervalData + ) + covariateSettings <- model$metaData$covariateSettingsList[[1]] + attrition <- model$metaData$attrition[nrow(model$metaData$attrition), ] + covariateStatistics <- model$metaData$covariateStatistics + estimate <- model$estimates + if (is.null(estimate) || nrow(estimate) == 0) { + p <- NA + } else { + z <- estimate$logRr / estimate$seLogRr + p <- 2 * pmin(pnorm(z), 1 - pnorm(z)) + } + sccsResult[[i]] <- tibble( + exposuresOutcomeSetId = outcomeId, + analysisId = analysisId, + covariateId = covariateSettings$outputIds[1], + outcomeSubjects = attrition$outcomeSubjects, + outcomeEvents = attrition$outcomeEvents, + outcomeObservationPeriods = attrition$outcomeObsPeriods, + observedDays = attrition$observedDays, + covariateSubjects = ifelse(nrow(covariateStatistics) == 0, 0, covariateStatistics$personCount), + covariateDays = ifelse(nrow(covariateStatistics) == 0, 0, covariateStatistics$dayCount), + covariateEras = ifelse(nrow(covariateStatistics) == 0, 0, covariateStatistics$eraCount), + covariateOutcomes = ifelse(nrow(covariateStatistics) == 0, 0, covariateStatistics$outcomeCount), + rr = ifelse(nrow(estimate) == 0, NA, exp(estimate$logRr)), + ci95Lb = ifelse(nrow(estimate) == 0, NA, exp(estimate$logLb95)), + ci95Ub = ifelse(nrow(estimate) == 0, NA, exp(estimate$logUb95)), + p = p, + logRr = ifelse(nrow(estimate) == 0, NA, estimate$logRr), + seLogRr = ifelse(nrow(estimate) == 0, NA, estimate$seLogRr), + llr = ifelse(nrow(estimate) == 0, NA, estimate$llr), + databaseId = i + ) + + sccsLikelihoodProfile[[i]] <- model$logLikelihoodProfiles[[1]] %>% + rename( + logRr = "point", + logLikelihood = "value" + ) %>% + mutate( + exposuresOutcomeSetId = outcomeId, + covariateId = covariateSettings$outputIds[1], + analysisId = analysisId, + databaseId = i + ) + } + sccsResult <- bind_rows(sccsResult) + sccsLikelihoodProfile <- bind_rows(sccsLikelihoodProfile) + tablesExist <- DatabaseConnector::existsTable( + connection = connection, + databaseSchema = "main", + tableName = "sccs_diagnostics_summary" + ) + + DatabaseConnector::insertTable( + connection = connection, + databaseSchema = "main", + tableName = "sccs_result", + data = sccsResult, + createTable = !tablesExist, + dropTableIfExists = FALSE, + camelCaseToSnakeCase = TRUE + ) + DatabaseConnector::insertTable( + connection = connection, + databaseSchema = "main", + tableName = "sccs_likelihood_profile", + data = sccsLikelihoodProfile, + createTable = !tablesExist, + dropTableIfExists = FALSE, + camelCaseToSnakeCase = TRUE + ) + + sccsDiagnosticsSummary <- tibble( + covariateId = 1000, + exposuresOutcomeSetId = !!outcomeId, + analysisId = !!analysisId, + databaseId = seq_len(nSites), + mdrr = 2, + unblind = runif(nSites) < 0.9 + ) + DatabaseConnector::insertTable( + connection = connection, + databaseSchema = "main", + tableName = "sccs_diagnostics_summary", + data = sccsDiagnosticsSummary, + createTable = !tablesExist, + dropTableIfExists = FALSE, + camelCaseToSnakeCase = TRUE + ) + + sccsCovariate <- tibble( + eraId = !!exposureId, + exposuresOutcomeSetId = !!outcomeId, + analysisId = !!analysisId, + databaseId = seq_len(nSites), + covariateId = 1000, + covariateAnalysisId = 1 + ) + DatabaseConnector::insertTable( + connection = connection, + databaseSchema = "main", + tableName = "sccs_covariate", + data = sccsCovariate, + createTable = !tablesExist, + dropTableIfExists = FALSE, + camelCaseToSnakeCase = TRUE + ) +} diff --git a/extras/ExampleWithResultsUpload.R b/extras/ExampleWithResultsUpload.R deleted file mode 100644 index 5e034be3..00000000 --- a/extras/ExampleWithResultsUpload.R +++ /dev/null @@ -1,96 +0,0 @@ -library(dplyr) -library(CohortGenerator) -library(Strategus) -library(ROhdsiWebApi) - -baseUrl <- "https://change.me:8443/WebAPI" - -atlasCohortIds <- c(5903, 5904) - -username <- "changeme" # Set to your atlas username -dbUsername <- username - -if (.Platform$OS.type == "unix") { - ROhdsiWebApi::authorizeWebApi(baseUrl = baseUrl, - webApiUsername = username, - webApiPassword = getPass::getPass(), - authMethod = "windows") -} else { - ROhdsiWebApi::authorizeWebApi(baseUrl = baseUrl, - authMethod = "windows") -} - -cohortDefinitionSet <- ROhdsiWebApi::exportCohortDefinitionSet(baseUrl = baseUrl, - cohortIds = atlasCohortIds, - generateStats = TRUE) - -dir.create("tmp", showWarnings = F) -source("https://raw.githubusercontent.com/OHDSI/CohortDiagnosticsModule/0.0.8/SettingsFunctions.R") - -cohortDiagnosticsModuleSpecifications <- createCohortDiagnosticsModuleSpecifications( - cohortIds = atlasCohortIds, - runInclusionStatistics = TRUE, - runIncludedSourceConcepts = TRUE, - runOrphanConcepts = TRUE, - runTimeSeries = FALSE, - runVisitContext = TRUE, - runBreakdownIndexEvents = TRUE, - runIncidenceRate = TRUE, - runCohortRelationship = TRUE, - runTemporalCohortCharacterization = TRUE, - incremental = TRUE -) - - -# Create analysis specifications --------------------------------------------- - -source("https://raw.githubusercontent.com/OHDSI/CohortGeneratorModule/main/SettingsFunctions.R") - -cohortDefinitionSharedResource <- createCohortSharedResourceSpecifications(cohortDefinitionSet) -cohortGeneratorModuleSpecifications <- createCohortGeneratorModuleSpecifications(incremental = TRUE, - generateStats = TRUE) - -analysisSpecifications <- Strategus::createEmptyAnalysisSpecificiations() %>% - addSharedResources(cohortDefinitionSharedResource) %>% - addModuleSpecifications(cohortGeneratorModuleSpecifications) %>% - Strategus::addModuleSpecifications(cohortDiagnosticsModuleSpecifications) - - -# Create execution settings ----------------------------------------------------- -connectionDetailsReference <- "eunomia-perm" -Strategus::storeConnectionDetails(Eunomia::getEunomiaConnectionDetails(file.path(normalizePath("tmp"), "eunomia-perm.sqlite")), connectionDetailsReference) - -resultsConnectionReference <- "result-store" -resultsConnectionDetails <- DatabaseConnector::createConnectionDetails(dbms = "sqlite", server = file.path(normalizePath("tmp"), "results.sqlite")) -Strategus::storeConnectionDetails(resultsConnectionDetails, resultsConnectionReference) - -# Note: this environmental variable should be set once for each compute node -Sys.setenv("INSTANTIATED_MODULES_FOLDER" = "~/tmp/StrategusInstantiatedModules") - -# This should be ran once and only once -resultsExecutitionSettings <- Strategus::createResultsExecutionSettings(resultsConnectionDetailsReference = "result-store", - resultsDatabaseSchema = "main", - workFolder = file.path(getwd(), "./tmp/strategusWork"), - resultsFolder = file.path(getwd(),"./tmp/strategusOutput")) - -# Create results schemas for all modules - this is only needed once -Strategus::createResultDataModels(analysisSpecifications = analysisSpecifications, executionSettings = resultsExecutitionSettings) - -# Note: Need to do only once: store con -executionSettings <- Strategus::createCdmExecutionSettings(connectionDetailsReference = connectionDetailsReference, - workDatabaseSchema = "main", - cdmDatabaseSchema = "main", - cohortTableNames = CohortGenerator::getCohortTableNames(cohortTable = "strategus_test"), - workFolder = file.path(getwd(), "./tmp/strategusWork"), - resultsFolder = file.path(getwd(),"./tmp/strategusOutput"), - minCellCount = 5, - resultsDatabaseSchema = "main", - resultsConnectionDetailsReference = resultsConnectionReference) - -ParallelLogger::saveSettingsToJson(executionSettings, "testExecutionSettings.json") - -# Execute analyses ------------------------------------------------------------- -unlink("_targets", recursive = TRUE) - -Strategus::execute(analysisSpecifications = analysisSpecifications, - executionSettings = executionSettings) diff --git a/extras/ExceptionHandlingSandbox.R b/extras/ExceptionHandlingSandbox.R new file mode 100644 index 00000000..f843d8d8 --- /dev/null +++ b/extras/ExceptionHandlingSandbox.R @@ -0,0 +1,69 @@ +# Create a simple class that throws an error upon execution +ExceptionThrowerModule <- R6::R6Class( + classname = "ExceptionThrowerModule", + inherit = Strategus:::StrategusModule, + public = list( + #' @description Initialize the module + initialize = function() { + super$initialize() + }, + execute = function(connectionDetails, analysisSpecifications, executionSettings) { + super$execute(connectionDetails, analysisSpecifications, executionSettings) + checkmate::assertClass(executionSettings, "CdmExecutionSettings") + private$errorFn("THROWING EXCEPTION") + } + ), + private = list( + errorFn = function(msg) { + stop(msg) + } + ) +) + +# Create a simple class that prints a message +SimpleModule <- R6::R6Class( + classname = "SimpleModule", + inherit = Strategus:::StrategusModule, + public = list( + #' @description Initialize the module + initialize = function() { + super$initialize() + }, + execute = function(connectionDetails, analysisSpecifications, executionSettings) { + super$execute(connectionDetails, analysisSpecifications, executionSettings) + checkmate::assertClass(executionSettings, "CdmExecutionSettings") + private$.message("Hello World") + } + ) +) + + +# Create a simple analysis spec with this module +etm <- ExceptionThrowerModule$new() +etmSpecs <- etm$createModuleSpecifications(list(foo = "bar")) + +sm <- SimpleModule$new() +smSpecs <- sm$createModuleSpecifications(list(foo = "bar")) + +analysisSpecifications <- Strategus::createEmptyAnalysisSpecificiations() |> + Strategus::addModuleSpecifications(smSpecs) |> + Strategus::addModuleSpecifications(etmSpecs) |> + Strategus::addModuleSpecifications(smSpecs) + +# Execute the study +executionSettings <- Strategus::createCdmExecutionSettings( + workDatabaseSchema = "main", + cdmDatabaseSchema = "main", + cohortTableNames = CohortGenerator::getCohortTableNames(cohortTable = "strategus_test"), + workFolder = file.path(getwd(), "workFolder"), + resultsFolder = file.path(getwd(), "resultsFolder"), + minCellCount = 5 +) + +connectionDetails <- Eunomia::getEunomiaConnectionDetails() +#debugonce(Strategus::execute) +executionStatus <- Strategus::execute( + analysisSpecifications = analysisSpecifications, + executionSettings = executionSettings, + connectionDetails = connectionDetails +) diff --git a/extras/ExecuteStrategusOnEunomia.R b/extras/ExecuteStrategusOnEunomia.R deleted file mode 100644 index 4adc266a..00000000 --- a/extras/ExecuteStrategusOnEunomia.R +++ /dev/null @@ -1,81 +0,0 @@ -#Install packages required for this script --------- -#install.packages("remotes") -#install.packages("ParallelLogger") -#remotes::install_github("OHDSI/Strategus") -#remotes::install_github("OHDSI/Eunomia") -#remotes::install_github("OHDSI/CohortGenerator") - -#Run the Eunomia study --------- -# Set the folder & environment variable for module storage -moduleFolder <- Sys.getenv("INSTANTIATED_MODULES_FOLDER") -studyFolder <- "C:/temp/strategus/EunomiaTestStudy" - - -if (!dir.exists(moduleFolder)) { - dir.create(moduleFolder, recursive = TRUE) -} -if (!dir.exists(studyFolder)) { - dir.create(studyFolder, recursive = TRUE) -} - -# Create the execution settings for Eunomia ---------- -connectionDetails <- Eunomia::getEunomiaConnectionDetails( - databaseFile = file.path(studyFolder, "cdm.sqlite") -) - -Strategus::storeConnectionDetails(connectionDetails = connectionDetails, - connectionDetailsReference = "eunomia") - -# Set the working directory to studyFolder -# and use relative paths to test -setwd(studyFolder) - -# Execute the study --------- -analysisSpecifications <- ParallelLogger::loadSettingsFromJson( - fileName = system.file("testdata/analysisSpecification.json", - package = "Strategus") -) - -resultsExecutionSettings <- Strategus::createResultsExecutionSettings( - resultsConnectionDetailsReference = "eunomia", - resultsDatabaseSchema = "main", - workFolder = file.path("schema_creation", "work_folder"), - resultsFolder = file.path("schema_creation", "results_folder") -) - -executionSettings <- Strategus::createCdmExecutionSettings( - connectionDetailsReference = "eunomia", - workDatabaseSchema = "main", - cdmDatabaseSchema = "main", - cohortTableNames = CohortGenerator::getCohortTableNames(), - workFolder = "work_folder", - resultsFolder = "results_folder", - minCellCount = 5, - resultsConnectionDetailsReference = "eunomia", - resultsDatabaseSchema = "main" -) - -ParallelLogger::saveSettingsToJson( - object = executionSettings, - file.path(studyFolder, "eunomiaExecutionSettings.json") -) - -executionSettings <- ParallelLogger::loadSettingsFromJson( - fileName = file.path(studyFolder, "eunomiaExecutionSettings.json") -) - -Strategus::storeConnectionDetails( - connectionDetails, - "eunomia" -) - -Strategus::createResultDataModels( - analysisSpecifications = analysisSpecifications, - executionSettings = resultsExecutionSettings -) - -Strategus::execute( - analysisSpecifications = analysisSpecifications, - executionSettings = executionSettings, - executionScriptFolder = file.path(studyFolder, "script_folder") -) diff --git a/extras/PackageMaintenance.R b/extras/PackageMaintenance.R index 0e911d14..6572c8a9 100644 --- a/extras/PackageMaintenance.R +++ b/extras/PackageMaintenance.R @@ -14,6 +14,8 @@ # See the License for the specific language governing permissions and # limitations under the License. +# Go document the full results data model -> DocumentResultsDataModel.R + # Manually delete package from library. Avoids "Already in use" message when rebuilding unloadNamespace("Strategus") .rs.restartR() @@ -28,61 +30,7 @@ OhdsiRTools::checkUsagePackage("Strategus") OhdsiRTools::updateCopyrightYearFolder() OhdsiRTools::findNonAsciiStringsInFolder() devtools::spell_check() - -# Update the module version information based on updates found on GitHub -library(dplyr) -# httr::set_config(httr::config(ssl_verifypeer = FALSE)) -updateModuleVersionInfo <- function() { - modules <- CohortGenerator::readCsv(file = "inst/csv/modules.csv") - modules <- modules %>% - select(-c("mainPackage", "mainPackageTag")) - # Get latest module versions --------------------------------------------------- - getLatestModuleVersion <- function(remoteRepo, remoteUsername, module) { - urlTemplate <- "https://api.%s/repos/%s/%s/releases/latest" - req <- httr2::request(base_url = sprintf(urlTemplate, remoteRepo, remoteUsername, module)) |> - httr2::req_headers("Authorization" = paste0("Bearer ", Sys.getenv("GITHUB_PAT")), - "X-GitHub-Api-Version" = "2022-11-28") - response <- httr2::req_perform(req) - release <- jsonlite::fromJSON(httr2::resp_body_string(response)) - return(release$tag_name) - } - versions <- tibble::tibble( - module = modules$module, - moduleVersion = mapply(getLatestModuleVersion, modules$remoteRepo, modules$remoteUsername, modules$module), - mainPackage = "", - mainPackageTag = "" - ) - # Get referenced main package tag ---------------------------------------------- - for (i in 1:nrow(modules)) { - module <- versions$module[i] - if (module == "CohortIncidenceModule") { - urlTemplate <- "https://raw.githubusercontent.com/OHDSI/%s/master/renv.lock" - } else { - urlTemplate <- "https://raw.githubusercontent.com/OHDSI/%s/main/renv.lock" - } - lock <- jsonlite::fromJSON(sprintf(urlTemplate, module)) - mainPackage <- gsub("Module", "", module) - versions$mainPackage[i] <- mainPackage - for (j in seq_along(lock$Packages)) { - if (lock$Packages[[j]]$Package == mainPackage) { - if (is.null(lock$Packages[[j]]$RemoteRef) || tolower(lock$Packages[[j]]$RemoteRef) == "head") { - versions$mainPackageTag[i] <- paste0("v", lock$Packages[[j]]$Version) - } else { - versions$mainPackageTag[i] <- lock$Packages[[j]]$RemoteRef - } - break - } - } - } - moduleList <- versions %>% - dplyr::inner_join(modules, by = c('module' = 'module')) %>% - dplyr::mutate(version = moduleVersion) %>% - dplyr::select(c(names(modules), "mainPackage", "mainPackageTag")) - - CohortGenerator::writeCsv(x = moduleList, - file = "inst/csv/modules.csv") -} -updateModuleVersionInfo() +devtools::document() # Create manual and vignettes: unlink("extras/Strategus.pdf") @@ -96,13 +44,6 @@ rmarkdown::render("vignettes/CreatingAnalysisSpecification.Rmd", number_sections = TRUE)) unlink("inst/doc/CreatingAnalysisSpecification.tex") -rmarkdown::render("vignettes/CreatingModules.Rmd", - output_file = "../inst/doc/CreatingModules.pdf", - rmarkdown::pdf_document(latex_engine = "pdflatex", - toc = TRUE, - number_sections = TRUE)) -unlink("inst/doc/CreatingModules.tex") - rmarkdown::render("vignettes/ExecuteStrategus.Rmd", output_file = "../inst/doc/ExecuteStrategus.pdf", rmarkdown::pdf_document(latex_engine = "pdflatex", @@ -117,36 +58,408 @@ rmarkdown::render("vignettes/IntroductionToStrategus.Rmd", number_sections = TRUE)) unlink("inst/doc/IntroductionToStrategus.tex") -pkgdown::build_site() -OhdsiRTools::fixHadesLogo() - -# Repackage the test module for unit testing -# NOTE: This is only necessary when the TestModule -# has been updated -testModuleRootFolder <- "extras/TestModule1-0.0.1" -targetModuleZipFile <- "TestModule1_0.0.1.zip" -testModuleFilesToRemove <- c( - file.path(testModuleRootFolder, ".RData"), - file.path(testModuleRootFolder, ".Rhistory") -) -testModuleDirToRemove <- c( - file.path(testModuleRootFolder, ".Rproj.user"), - file.path(testModuleRootFolder, "renv/library"), - file.path(testModuleRootFolder, "renv/profiles/dev/renv/library") -) -unlink(testModuleFilesToRemove) -unlink(testModuleDirToRemove, recursive = TRUE) - -oldwd <- getwd() -setwd("extras") -zip::zip( - zipfile = targetModuleZipFile, - files = list.files("TestModule1-0.0.1", all.files = TRUE, recursive = TRUE, include.dirs = TRUE, full.names = TRUE) -) -file.copy( - from = targetModuleZipFile, - to = file.path("../inst/testdata", targetModuleZipFile), - overwrite = TRUE -) -file.remove(targetModuleZipFile) -setwd(oldwd) +rmarkdown::render("vignettes/WorkingWithResults.Rmd", + output_file = "../inst/doc/WorkingWithResults.pdf", + rmarkdown::pdf_document(latex_engine = "pdflatex", + toc = TRUE, + number_sections = TRUE)) +unlink("inst/doc/WorkingWithResults.tex") + +# Produce a study analysis specification for testing ----------- +library(Strategus) +cohortDefinitionSet <- getCohortDefinitionSet( + settingsFileName = system.file("testdata/Cohorts.csv", package = "Strategus"), + jsonFolder = system.file("testdata/cohorts", package = "Strategus"), + sqlFolder = system.file("testdata/sql", package = "Strategus") +) +subsetOperations <- list( + createDemographicSubset( + name = "Demographic Criteria", + ageMin = 18, + ageMax = 64 + ) +) +subsetDef <- createCohortSubsetDefinition( + name = "test definition", + definitionId = 1, + subsetOperators = subsetOperations +) +cohortDefinitionSet <- cohortDefinitionSet |> + addCohortSubsetDefinition(subsetDef) + +ncoCohortSet <- readCsv(file = system.file("testdata/negative_controls_concept_set.csv", + package = "Strategus" +)) + +# Exposures-outcomes +negativeControlOutcomeIds <- ncoCohortSet$cohortId +outcomeOfInterestIds <- c(3) +exposureOfInterestIds <- c(1, 2) + +# Characterization ------------------------------- +cModuleSettingsCreator <- CharacterizationModule$new() +cModuleSpecifications <- cModuleSettingsCreator$createModuleSpecifications( + targetIds = c(1, 2), + outcomeIds = 3 +) + +# Cohort Diagnostics ----------------- +cdModuleSettingsCreator <- CohortDiagnosticsModule$new() +cdModuleSpecifications <- cdModuleSettingsCreator$createModuleSpecifications( + runInclusionStatistics = TRUE, + runIncludedSourceConcepts = TRUE, + runOrphanConcepts = TRUE, + runTimeSeries = FALSE, + runVisitContext = TRUE, + runBreakdownIndexEvents = TRUE, + runIncidenceRate = TRUE, + runCohortRelationship = TRUE, + runTemporalCohortCharacterization = TRUE +) + +# Cohort Generator ----------------- +cgModuleSettingsCreator <- CohortGeneratorModule$new() + +# Create the settings & validate them +cohortSharedResourcesSpecifications <- cgModuleSettingsCreator$createCohortSharedResourceSpecifications(cohortDefinitionSet) +cgModuleSettingsCreator$validateCohortSharedResourceSpecifications(cohortSharedResourcesSpecifications) + +ncoCohortSharedResourceSpecifications <- cgModuleSettingsCreator$createNegativeControlOutcomeCohortSharedResourceSpecifications(ncoCohortSet, "first", TRUE) +cgModuleSettingsCreator$validateNegativeControlOutcomeCohortSharedResourceSpecifications(ncoCohortSharedResourceSpecifications) + +cgModuleSpecifications <- cgModuleSettingsCreator$createModuleSpecifications() + +# Characterization ------------------------------- +cModuleSettingsCreator <- CharacterizationModule$new() +cModuleSpecifications <- cModuleSettingsCreator$createModuleSpecifications( + targetIds = c(1, 2), + outcomeIds = 3 +) + +# Cohort Incidence ----------------- +ciModuleSettingsCreator <- CohortIncidenceModule$new() +targets <- list( + CohortIncidence::createCohortRef(id = 1, name = "Celecoxib"), + CohortIncidence::createCohortRef(id = 2, name = "Diclofenac"), + CohortIncidence::createCohortRef(id = 4, name = "Celecoxib Age >= 30"), + CohortIncidence::createCohortRef(id = 5, name = "Diclofenac Age >= 30") +) +outcomes <- list(CohortIncidence::createOutcomeDef(id = 1, name = "GI bleed", cohortId = 3, cleanWindow = 9999)) + +tars <- list( + CohortIncidence::createTimeAtRiskDef(id = 1, startWith = "start", endWith = "end"), + CohortIncidence::createTimeAtRiskDef(id = 2, startWith = "start", endWith = "start", endOffset = 365) +) +analysis1 <- CohortIncidence::createIncidenceAnalysis( + targets = c(1, 2, 4, 5), + outcomes = c(1), + tars = c(1, 2) +) + +irDesign <- CohortIncidence::createIncidenceDesign( + targetDefs = targets, + outcomeDefs = outcomes, + tars = tars, + analysisList = list(analysis1), + strataSettings = CohortIncidence::createStrataSettings( + byYear = TRUE, + byGender = TRUE + ) +) + +ciModuleSpecifications <- ciModuleSettingsCreator$createModuleSpecifications( + irDesign = irDesign$toList() +) + +# Cohort Method ---------------------- +cmModuleSettingsCreator <- CohortMethodModule$new() +negativeControlOutcomes <- lapply( + X = ncoCohortSet$cohortId, + FUN = CohortMethod::createOutcome, + outcomeOfInterest = FALSE, + trueEffectSize = 1, + priorOutcomeLookback = 30 +) + +outcomesOfInterest <- lapply( + X = 3, + FUN = CohortMethod::createOutcome, + outcomeOfInterest = TRUE +) + +outcomes <- append( + negativeControlOutcomes, + outcomesOfInterest +) + +tcos1 <- CohortMethod::createTargetComparatorOutcomes( + targetId = 1, + comparatorId = 2, + outcomes = outcomes, + excludedCovariateConceptIds = c(1118084, 1124300) +) +tcos2 <- CohortMethod::createTargetComparatorOutcomes( + targetId = 4, + comparatorId = 5, + outcomes = outcomes, + excludedCovariateConceptIds = c(1118084, 1124300) +) + +targetComparatorOutcomesList <- list(tcos1, tcos2) + +covarSettings <- FeatureExtraction::createDefaultCovariateSettings(addDescendantsToExclude = TRUE) + +getDbCmDataArgs <- CohortMethod::createGetDbCohortMethodDataArgs( + washoutPeriod = 183, + firstExposureOnly = TRUE, + removeDuplicateSubjects = "remove all", + maxCohortSize = 100000, + covariateSettings = covarSettings +) + +createStudyPopArgs <- CohortMethod::createCreateStudyPopulationArgs( + minDaysAtRisk = 1, + riskWindowStart = 0, + startAnchor = "cohort start", + riskWindowEnd = 30, + endAnchor = "cohort end" +) + +matchOnPsArgs <- CohortMethod::createMatchOnPsArgs() +fitOutcomeModelArgs <- CohortMethod::createFitOutcomeModelArgs(modelType = "cox") +createPsArgs <- CohortMethod::createCreatePsArgs( + stopOnError = FALSE, + control = Cyclops::createControl(cvRepetitions = 1) +) +computeSharedCovBalArgs <- CohortMethod::createComputeCovariateBalanceArgs() +computeCovBalArgs <- CohortMethod::createComputeCovariateBalanceArgs( + covariateFilter = FeatureExtraction::getDefaultTable1Specifications() +) + +cmAnalysis1 <- CohortMethod::createCmAnalysis( + analysisId = 1, + description = "No matching, simple outcome model", + getDbCohortMethodDataArgs = getDbCmDataArgs, + createStudyPopArgs = createStudyPopArgs, + fitOutcomeModelArgs = fitOutcomeModelArgs +) + +cmAnalysis2 <- CohortMethod::createCmAnalysis( + analysisId = 2, + description = "Matching on ps and covariates, simple outcomeModel", + getDbCohortMethodDataArgs = getDbCmDataArgs, + createStudyPopArgs = createStudyPopArgs, + createPsArgs = createPsArgs, + matchOnPsArgs = matchOnPsArgs, + computeSharedCovariateBalanceArgs = computeSharedCovBalArgs, + computeCovariateBalanceArgs = computeCovBalArgs, + fitOutcomeModelArgs = fitOutcomeModelArgs +) + +cmAnalysisList <- list(cmAnalysis1, cmAnalysis2) + +analysesToExclude <- NULL + +cmModuleSpecifications <- cmModuleSettingsCreator$createModuleSpecifications( + cmAnalysisList = cmAnalysisList, + targetComparatorOutcomesList = targetComparatorOutcomesList, + analysesToExclude = analysesToExclude +) + +# EvidenceSythesis ------------------ +esModuleSettingsCreator = EvidenceSynthesisModule$new() +evidenceSynthesisSourceCm <- esModuleSettingsCreator$createEvidenceSynthesisSource( + sourceMethod = "CohortMethod", + likelihoodApproximation = "adaptive grid" +) +metaAnalysisCm <- esModuleSettingsCreator$createBayesianMetaAnalysis( + evidenceSynthesisAnalysisId = 1, + alpha = 0.05, + evidenceSynthesisDescription = "Bayesian random-effects alpha 0.05 - adaptive grid", + evidenceSynthesisSource = evidenceSynthesisSourceCm +) +evidenceSynthesisSourceSccs <- esModuleSettingsCreator$createEvidenceSynthesisSource( + sourceMethod = "SelfControlledCaseSeries", + likelihoodApproximation = "adaptive grid" +) +metaAnalysisSccs <- esModuleSettingsCreator$createBayesianMetaAnalysis( + evidenceSynthesisAnalysisId = 2, + alpha = 0.05, + evidenceSynthesisDescription = "Bayesian random-effects alpha 0.05 - adaptive grid", + evidenceSynthesisSource = evidenceSynthesisSourceSccs +) +evidenceSynthesisAnalysisList <- list(metaAnalysisCm, metaAnalysisSccs) +evidenceSynthesisAnalysisSpecifications <- esModuleSettingsCreator$createModuleSpecifications( + evidenceSynthesisAnalysisList +) +# PatientLevelPrediction ------------------------------- +plpModuleSettingsCreator <- PatientLevelPredictionModule$new() +makeModelDesignSettings <- function(targetId, outcomeId, popSettings, covarSettings) { + invisible(PatientLevelPrediction::createModelDesign( + targetId = targetId, + outcomeId = outcomeId, + restrictPlpDataSettings = PatientLevelPrediction::createRestrictPlpDataSettings(), + populationSettings = popSettings, + covariateSettings = covarSettings, + preprocessSettings = PatientLevelPrediction::createPreprocessSettings(), + modelSettings = PatientLevelPrediction::setLassoLogisticRegression(), + splitSettings = PatientLevelPrediction::createDefaultSplitSetting(), + runCovariateSummary = T + )) +} + +plpPopulationSettings <- PatientLevelPrediction::createStudyPopulationSettings( + startAnchor = "cohort start", + riskWindowStart = 1, + endAnchor = "cohort start", + riskWindowEnd = 365, + minTimeAtRisk = 1 +) +plpCovarSettings <- FeatureExtraction::createDefaultCovariateSettings() + +modelDesignList <- list() +for (i in 1:length(exposureOfInterestIds)) { + for (j in 1:length(outcomeOfInterestIds)) { + modelDesignList <- append( + modelDesignList, + list( + makeModelDesignSettings( + targetId = exposureOfInterestIds[i], + outcomeId = outcomeOfInterestIds[j], + popSettings = plpPopulationSettings, + covarSettings = plpCovarSettings + ) + ) + ) + } +} + +plpModuleSpecifications <- plpModuleSettingsCreator$createModuleSpecifications( + modelDesignList = modelDesignList +) + +# SelfControlledCaseSeries ------------------------------- +sccsModuleSettingsCreator <- SelfControlledCaseSeriesModule$new() + +exposuresOutcomeList <- list() +for (exposureOfInterestId in exposureOfInterestIds) { + for (outcomeOfInterestId in outcomeOfInterestIds) { + exposuresOutcomeList[[length(exposuresOutcomeList) + 1]] <- SelfControlledCaseSeries::createExposuresOutcome( + outcomeId = outcomeOfInterestId, + exposures = list(SelfControlledCaseSeries::createExposure(exposureId = exposureOfInterestId)) + ) + } + for (negativeControlOutcomeId in negativeControlOutcomeIds) { + exposuresOutcomeList[[length(exposuresOutcomeList) + 1]] <- SelfControlledCaseSeries::createExposuresOutcome( + outcomeId = negativeControlOutcomeId, + exposures = list(SelfControlledCaseSeries::createExposure(exposureId = exposureOfInterestId, trueEffectSize = 1)) + ) + } +} + +getDbSccsDataArgs <- SelfControlledCaseSeries::createGetDbSccsDataArgs( + studyStartDate = "", + studyEndDate = "", + maxCasesPerOutcome = 1e6, + useNestingCohort = TRUE, + nestingCohortId = 1, + deleteCovariatesSmallCount = 0 +) + +createStudyPopulation6AndOlderArgs <- SelfControlledCaseSeries::createCreateStudyPopulationArgs( + minAge = 18, + naivePeriod = 365 +) + +covarPreExp <- SelfControlledCaseSeries::createEraCovariateSettings( + label = "Pre-exposure", + includeEraIds = "exposureId", + start = -30, + end = -1, + endAnchor = "era start" +) + +covarExposureOfInt <- SelfControlledCaseSeries::createEraCovariateSettings( + label = "Main", + includeEraIds = "exposureId", + start = 0, + startAnchor = "era start", + end = 0, + endAnchor = "era end", + profileLikelihood = TRUE, + exposureOfInterest = TRUE +) + +calendarTimeSettings <- SelfControlledCaseSeries::createCalendarTimeCovariateSettings( + calendarTimeKnots = 5, + allowRegularization = TRUE, + computeConfidenceIntervals = FALSE +) + +seasonalitySettings <- SelfControlledCaseSeries::createSeasonalityCovariateSettings( + seasonKnots = 5, + allowRegularization = TRUE, + computeConfidenceIntervals = FALSE +) + +createSccsIntervalDataArgs <- SelfControlledCaseSeries::createCreateSccsIntervalDataArgs( + eraCovariateSettings = list(covarPreExp, covarExposureOfInt), + seasonalityCovariateSettings = seasonalitySettings, + calendarTimeCovariateSettings = calendarTimeSettings, + minCasesForTimeCovariates = 100000 +) + +fitSccsModelArgs <- SelfControlledCaseSeries::createFitSccsModelArgs( + control = Cyclops::createControl( + cvType = "auto", + selectorType = "byPid", + startingVariance = 0.1, + seed = 1, + resetCoefficients = TRUE, + noiseLevel = "quiet" + ) +) + +sccsAnalysis1 <- SelfControlledCaseSeries::createSccsAnalysis( + analysisId = 1, + description = "SCCS age 18-", + getDbSccsDataArgs = getDbSccsDataArgs, + createStudyPopulationArgs = createStudyPopulation6AndOlderArgs, + createIntervalDataArgs = createSccsIntervalDataArgs, + fitSccsModelArgs = fitSccsModelArgs +) + +sccsAnalysisList <- list(sccsAnalysis1) + +sccsModuleSpecifications <- sccsModuleSettingsCreator$createModuleSpecifications( + sccsAnalysisList = sccsAnalysisList, + exposuresOutcomeList = exposuresOutcomeList, + combineDataFetchAcrossOutcomes = FALSE +) + + +# Create analysis specifications CDM modules --------------- +cdmModulesAnalysisSpecifications <- createEmptyAnalysisSpecificiations() |> + addSharedResources(cohortSharedResourcesSpecifications) |> + addSharedResources(ncoCohortSharedResourceSpecifications) |> + addCharacterizationModuleSpecifications(cModuleSpecifications) |> + addCohortDiagnosticsModuleSpecifications(cdModuleSpecifications) |> + addCohortGeneratorModuleSpecifications(cgModuleSpecifications) |> + addCohortIncidenceModuleSpecifications(ciModuleSpecifications) |> + addCohortMethodeModuleSpecifications(cmModuleSpecifications) |> + addSelfControlledCaseSeriesModuleSpecifications(sccsModuleSpecifications) |> + addPatientLevelPredictionModuleSpecifications(plpModuleSpecifications) + +ParallelLogger::saveSettingsToJson( + object = cdmModulesAnalysisSpecifications, + fileName = "inst/testdata/cdmModulesAnalysisSpecifications.json" +) + +# Create analysis specifications results modules --------------- +cdmModulesAnalysisSpecifications <- createEmptyAnalysisSpecificiations() |> + addEvidenceSynthesisModuleSpecifications(evidenceSynthesisAnalysisSpecifications) + +ParallelLogger::saveSettingsToJson( + object = cdmModulesAnalysisSpecifications, + fileName = "inst/testdata/resultsModulesAnalysisSpecifications.json" +) diff --git a/extras/R6ClassFun.R b/extras/R6ClassFun.R new file mode 100644 index 00000000..fe300657 --- /dev/null +++ b/extras/R6ClassFun.R @@ -0,0 +1,537 @@ +library(Strategus) +library(CohortGenerator) + +# Setup some test data ------------ +cohortDefinitionSet <- getCohortDefinitionSet( + settingsFileName = "testdata/Cohorts.csv", + jsonFolder = "testdata/cohorts", + sqlFolder = "testdata/sql", + packageName = "Strategus" +) +subsetOperations <- list( + createDemographicSubset( + name = "Demographic Criteria", + ageMin = 18, + ageMax = 64 + ) +) +subsetDef <- createCohortSubsetDefinition( + name = "test definition", + definitionId = 1, + subsetOperators = subsetOperations +) +cohortDefinitionSet <- cohortDefinitionSet |> + addCohortSubsetDefinition(subsetDef) + +ncoCohortSet <- readCsv(file = system.file("testdata/negative_controls_concept_set.csv", + package = "Strategus" +)) + +# Create the analysis settings --------------- + +# Cohort Generator ----------------- +cgModuleSettingsCreator <- CohortGeneratorModule$new() + +# Create the settings & validate them +cohortSharedResourcesSpecifications <- cgModuleSettingsCreator$createCohortSharedResourceSpecifications(cohortDefinitionSet) +cgModuleSettingsCreator$validateCohortSharedResourceSpecifications(cohortSharedResourcesSpecifications) + +ncoCohortSharedResourceSpecifications <- cgModuleSettingsCreator$createNegativeControlOutcomeCohortSharedResourceSpecifications(ncoCohortSet, "first", TRUE) +cgModuleSettingsCreator$validateNegativeControlOutcomeCohortSharedResourceSpecifications(ncoCohortSharedResourceSpecifications) + +cgModuleSettings <- cgModuleSettingsCreator$createModuleSpecifications() +cgModuleSettingsCreator$validateModuleSpecifications(cgModuleSettings) + +# Characterization ------------------------------- +cModuleSettingsCreator <- CharacterizationModule$new() +cModuleSpecifications <- cModuleSettingsCreator$createModuleSpecifications( + targetIds = c(1, 2), + outcomeIds = 3 +) + +# Cohort Diagnostics ----------------- +cdModuleSettingsCreator <- CohortDiagnosticsModule$new() +cdModuleSpecifications <- cdModuleSettingsCreator$createModuleSpecifications( + runInclusionStatistics = TRUE, + runIncludedSourceConcepts = TRUE, + runOrphanConcepts = TRUE, + runTimeSeries = FALSE, + runVisitContext = TRUE, + runBreakdownIndexEvents = TRUE, + runIncidenceRate = TRUE, + runCohortRelationship = TRUE, + runTemporalCohortCharacterization = TRUE, + incremental = FALSE +) + +# Cohort Incidence ----------------- +library(CohortIncidence) +ciModuleSettingsCreator <- CohortIncidenceModule$new() +targets <- list( + createCohortRef(id = 1, name = "Celecoxib"), + createCohortRef(id = 2, name = "Diclofenac"), + createCohortRef(id = 4, name = "Celecoxib Age >= 30"), + createCohortRef(id = 5, name = "Diclofenac Age >= 30") +) +outcomes <- list(createOutcomeDef(id = 1, name = "GI bleed", cohortId = 3, cleanWindow = 9999)) + +tars <- list( + createTimeAtRiskDef(id = 1, startWith = "start", endWith = "end"), + createTimeAtRiskDef(id = 2, startWith = "start", endWith = "start", endOffset = 365) +) +analysis1 <- createIncidenceAnalysis( + targets = c(1, 2, 4, 5), + outcomes = c(1), + tars = c(1, 2) +) + +irDesign <- createIncidenceDesign( + targetDefs = targets, + outcomeDefs = outcomes, + tars = tars, + analysisList = list(analysis1), + strataSettings = createStrataSettings( + byYear = TRUE, + byGender = TRUE + ) +) + +ciModuleSettings <- ciModuleSettingsCreator$createModuleSpecifications( + irDesign = irDesign$toList() +) +ciModuleSettingsCreator$validateModuleSpecifications(ciModuleSettings) + +# Cohort Method ---------------------- +library(CohortMethod) +cmModuleSettingsCreator <- CohortMethodModule$new() +negativeControlOutcomes <- lapply( + X = ncoCohortSet$cohortId, + FUN = createOutcome, + outcomeOfInterest = FALSE, + trueEffectSize = 1, + priorOutcomeLookback = 30 +) + +outcomesOfInterest <- lapply( + X = 3, + FUN = createOutcome, + outcomeOfInterest = TRUE +) + +outcomes <- append( + negativeControlOutcomes, + outcomesOfInterest +) + +tcos1 <- CohortMethod::createTargetComparatorOutcomes( + targetId = 1, + comparatorId = 2, + outcomes = outcomes, + excludedCovariateConceptIds = c(1118084, 1124300) +) +tcos2 <- CohortMethod::createTargetComparatorOutcomes( + targetId = 4, + comparatorId = 5, + outcomes = outcomes, + excludedCovariateConceptIds = c(1118084, 1124300) +) + +targetComparatorOutcomesList <- list(tcos1, tcos2) + +covarSettings <- FeatureExtraction::createDefaultCovariateSettings(addDescendantsToExclude = TRUE) + +getDbCmDataArgs <- CohortMethod::createGetDbCohortMethodDataArgs( + washoutPeriod = 183, + firstExposureOnly = TRUE, + removeDuplicateSubjects = "remove all", + maxCohortSize = 100000, + covariateSettings = covarSettings +) + +createStudyPopArgs <- CohortMethod::createCreateStudyPopulationArgs( + minDaysAtRisk = 1, + riskWindowStart = 0, + startAnchor = "cohort start", + riskWindowEnd = 30, + endAnchor = "cohort end" +) + +matchOnPsArgs <- CohortMethod::createMatchOnPsArgs() +fitOutcomeModelArgs <- CohortMethod::createFitOutcomeModelArgs(modelType = "cox") +createPsArgs <- CohortMethod::createCreatePsArgs( + stopOnError = FALSE, + control = Cyclops::createControl(cvRepetitions = 1) +) +computeSharedCovBalArgs <- CohortMethod::createComputeCovariateBalanceArgs() +computeCovBalArgs <- CohortMethod::createComputeCovariateBalanceArgs( + covariateFilter = FeatureExtraction::getDefaultTable1Specifications() +) + +cmAnalysis1 <- CohortMethod::createCmAnalysis( + analysisId = 1, + description = "No matching, simple outcome model", + getDbCohortMethodDataArgs = getDbCmDataArgs, + createStudyPopArgs = createStudyPopArgs, + fitOutcomeModelArgs = fitOutcomeModelArgs +) + +cmAnalysis2 <- CohortMethod::createCmAnalysis( + analysisId = 2, + description = "Matching on ps and covariates, simple outcomeModel", + getDbCohortMethodDataArgs = getDbCmDataArgs, + createStudyPopArgs = createStudyPopArgs, + createPsArgs = createPsArgs, + matchOnPsArgs = matchOnPsArgs, + computeSharedCovariateBalanceArgs = computeSharedCovBalArgs, + computeCovariateBalanceArgs = computeCovBalArgs, + fitOutcomeModelArgs = fitOutcomeModelArgs +) + +cmAnalysisList <- list(cmAnalysis1, cmAnalysis2) + +analysesToExclude <- NULL + +cmModuleSpecifications <- cmModuleSettingsCreator$createModuleSpecifications( + cmAnalysisList = cmAnalysisList, + targetComparatorOutcomesList = targetComparatorOutcomesList, + analysesToExclude = analysesToExclude +) + +# SelfControlledCaseSeries ------------------------------- +library(SelfControlledCaseSeries) +sccsModuleSettingsCreator <- SelfControlledCaseSeriesModule$new() + +# Exposures-outcomes +negativeControlOutcomeIds <- ncoCohortSet$cohortId +outcomeOfInterestIds <- c(3) +exposureOfInterestIds <- c(1, 2) + +exposuresOutcomeList <- list() +for (exposureOfInterestId in exposureOfInterestIds) { + for (outcomeOfInterestId in outcomeOfInterestIds) { + exposuresOutcomeList[[length(exposuresOutcomeList) + 1]] <- createExposuresOutcome( + outcomeId = outcomeOfInterestId, + exposures = list(createExposure(exposureId = exposureOfInterestId)) + ) + } + for (negativeControlOutcomeId in negativeControlOutcomeIds) { + exposuresOutcomeList[[length(exposuresOutcomeList) + 1]] <- createExposuresOutcome( + outcomeId = negativeControlOutcomeId, + exposures = list(createExposure(exposureId = exposureOfInterestId, trueEffectSize = 1)) + ) + } +} + +getDbSccsDataArgs <- SelfControlledCaseSeries::createGetDbSccsDataArgs( + studyStartDate = "", + studyEndDate = "", + maxCasesPerOutcome = 1e6, + useNestingCohort = TRUE, + nestingCohortId = 1, + deleteCovariatesSmallCount = 0 +) + +createStudyPopulation6AndOlderArgs <- SelfControlledCaseSeries::createCreateStudyPopulationArgs( + minAge = 18, + naivePeriod = 365 +) + +covarPreExp <- SelfControlledCaseSeries::createEraCovariateSettings( + label = "Pre-exposure", + includeEraIds = "exposureId", + start = -30, + end = -1, + endAnchor = "era start" +) + +covarExposureOfInt <- SelfControlledCaseSeries::createEraCovariateSettings( + label = "Main", + includeEraIds = "exposureId", + start = 0, + startAnchor = "era start", + end = 0, + endAnchor = "era end", + profileLikelihood = TRUE, + exposureOfInterest = TRUE +) + +calendarTimeSettings <- SelfControlledCaseSeries::createCalendarTimeCovariateSettings( + calendarTimeKnots = 5, + allowRegularization = TRUE, + computeConfidenceIntervals = FALSE +) + +seasonalitySettings <- SelfControlledCaseSeries::createSeasonalityCovariateSettings( + seasonKnots = 5, + allowRegularization = TRUE, + computeConfidenceIntervals = FALSE +) + +createSccsIntervalDataArgs <- SelfControlledCaseSeries::createCreateSccsIntervalDataArgs( + eraCovariateSettings = list(covarPreExp, covarExposureOfInt), + seasonalityCovariateSettings = seasonalitySettings, + calendarTimeCovariateSettings = calendarTimeSettings, + minCasesForTimeCovariates = 100000 +) + +fitSccsModelArgs <- SelfControlledCaseSeries::createFitSccsModelArgs( + control = Cyclops::createControl( + cvType = "auto", + selectorType = "byPid", + startingVariance = 0.1, + seed = 1, + resetCoefficients = TRUE, + noiseLevel = "quiet" + ) +) + +sccsAnalysis1 <- SelfControlledCaseSeries::createSccsAnalysis( + analysisId = 1, + description = "SCCS age 18-", + getDbSccsDataArgs = getDbSccsDataArgs, + createStudyPopulationArgs = createStudyPopulation6AndOlderArgs, + createIntervalDataArgs = createSccsIntervalDataArgs, + fitSccsModelArgs = fitSccsModelArgs +) + +sccsAnalysisList <- list(sccsAnalysis1) + +sccsModuleSpecifications <- sccsModuleSettingsCreator$createModuleSpecifications( + sccsAnalysisList = sccsAnalysisList, + exposuresOutcomeList = exposuresOutcomeList, + combineDataFetchAcrossOutcomes = FALSE +) + +# PatientLevelPrediction ------------------------------- +plpModuleSettingsCreator <- PatientLevelPredictionModule$new() +makeModelDesignSettings <- function(targetId, outcomeId, popSettings, covarSettings) { + invisible(PatientLevelPrediction::createModelDesign( + targetId = targetId, + outcomeId = outcomeId, + restrictPlpDataSettings = PatientLevelPrediction::createRestrictPlpDataSettings(), + populationSettings = popSettings, + covariateSettings = covarSettings, + preprocessSettings = PatientLevelPrediction::createPreprocessSettings(), + modelSettings = PatientLevelPrediction::setLassoLogisticRegression(), + splitSettings = PatientLevelPrediction::createDefaultSplitSetting(), + runCovariateSummary = T + )) +} + +plpPopulationSettings <- PatientLevelPrediction::createStudyPopulationSettings( + startAnchor = "cohort start", + riskWindowStart = 1, + endAnchor = "cohort start", + riskWindowEnd = 365, + minTimeAtRisk = 1 +) +plpCovarSettings <- FeatureExtraction::createDefaultCovariateSettings() + +modelDesignList <- list() +for (i in 1:length(exposureOfInterestIds)) { + for (j in 1:length(outcomeOfInterestIds)) { + modelDesignList <- append( + modelDesignList, + list( + makeModelDesignSettings( + targetId = exposureOfInterestIds[i], + outcomeId = outcomeOfInterestIds[j], + popSettings = plpPopulationSettings, + covarSettings = plpCovarSettings + ) + ) + ) + } +} + +plpModuleSpecifications <- plpModuleSettingsCreator$createModuleSpecifications( + modelDesignList = modelDesignList +) + +# Create analysis specifications --------------- +analysisSpecifications <- createEmptyAnalysisSpecificiations() |> + addSharedResources(cohortSharedResourcesSpecifications) |> + addSharedResources(ncoCohortSharedResourceSpecifications) |> + addCohortGeneratorModuleSpecifications(cgModuleSettings) |> + addCohortDiagnosticsModuleSpecifications(cdModuleSpecifications) |> + addCharacterizationModuleSpecifications(cModuleSpecifications) |> + addCohortIncidenceModuleSpecifications(ciModuleSettings) |> + addCohortMethodeModuleSpecifications(cmModuleSpecifications) |> + addSelfControlledCaseSeriesModuleSpecifications(sccsModuleSpecifications) |> + addPatientLevelPredictionModuleSpecifications(plpModuleSpecifications) |> + +# Cleanup any prior results ----------------- +outputFolder <- "D:/TEMP/StrategusR6Testing" +unlink(outputFolder, recursive = T, force = T) +dir.create(outputFolder, recursive = T) + +# Execute ------------------- +ParallelLogger::saveSettingsToJson(analysisSpecifications, file.path(outputFolder, "analysisSettings.json")) +workFolder <- file.path(outputFolder, "work_folder") +resultsFolder <- file.path(outputFolder, "results_folder") + +executionSettings <- Strategus::createCdmExecutionSettings( + workDatabaseSchema = "main", + cdmDatabaseSchema = "main", + cohortTableNames = CohortGenerator::getCohortTableNames(cohortTable = "strategus_test"), + workFolder = workFolder, + resultsFolder = resultsFolder, + minCellCount = 5 +) + +connectionDetails <- Eunomia::getEunomiaConnectionDetails( + databaseFile = file.path(outputFolder, "Eunomia.sqlite"), + overwrite = TRUE +) +#debugonce(Strategus::execute) +Strategus::execute( + analysisSpecifications = analysisSpecifications, + executionSettings = executionSettings, + connectionDetails = connectionDetails +) + +# # # DEBUG CD +# cdModule <- CohortDiagnosticsModule$new() +# debugonce(cdModule$execute) +# executionSettings$databaseId = "Eunomia" +# cdModule$execute( +# analysisSpecifications = analysisSpecifications, +# executionSettings = executionSettings, +# connectionDetails = connectionDetails +# ) + +# Create empty results database ------------------------- +library(RSQLite) +if (file.exists(file.path(outputFolder, "results.sqlite"))) { + unlink(file.path(outputFolder, "results.sqlite")) +} +mydb <- dbConnect(RSQLite::SQLite(), file.path(outputFolder, "results.sqlite")) +dbDisconnect(mydb) + +resultsConnectionDetails <- DatabaseConnector::createConnectionDetails( + dbms = "sqlite", + server = file.path(outputFolder, "results.sqlite") +) + +# Create results data model ------------------------- +resultsDataModelSettings <- Strategus::createResultsDataModelSettings( + resultsDatabaseSchema = "main", + resultsFolder = executionSettings$resultsFolder, +) + +# NOTE: CI has not implemented this so it will error out. +Strategus::createResultDataModel( + analysisSpecifications = analysisSpecifications, + resultsDataModelSettings = resultsDataModelSettings, + resultsConnectionDetails = resultsConnectionDetails +) + +# Upload results --------------- +debugonce(Strategus::uploadResults) +Strategus::uploadResults( + analysisSpecifications = analysisSpecifications, + resultsDataModelSettings = resultsDataModelSettings, + resultsConnectionDetails = resultsConnectionDetails +) + +# Peek in the results database --------------- +# conn <- DatabaseConnector::connect(resultsConnectionDetails) +# DatabaseConnector::disconnect(conn) + +# Run EvidenceSythesis Module ------------------ +esModuleSettingsCreator = EvidenceSynthesisModule$new() +evidenceSynthesisSourceCm <- esModuleSettingsCreator$createEvidenceSynthesisSource( + sourceMethod = "CohortMethod", + likelihoodApproximation = "adaptive grid" +) +metaAnalysisCm <- esModuleSettingsCreator$createBayesianMetaAnalysis( + evidenceSynthesisAnalysisId = 1, + alpha = 0.05, + evidenceSynthesisDescription = "Bayesian random-effects alpha 0.05 - adaptive grid", + evidenceSynthesisSource = evidenceSynthesisSourceCm +) +evidenceSynthesisSourceSccs <- esModuleSettingsCreator$createEvidenceSynthesisSource( + sourceMethod = "SelfControlledCaseSeries", + likelihoodApproximation = "adaptive grid" +) +metaAnalysisSccs <- esModuleSettingsCreator$createBayesianMetaAnalysis( + evidenceSynthesisAnalysisId = 2, + alpha = 0.05, + evidenceSynthesisDescription = "Bayesian random-effects alpha 0.05 - adaptive grid", + evidenceSynthesisSource = evidenceSynthesisSourceSccs +) +evidenceSynthesisAnalysisList <- list(metaAnalysisCm, metaAnalysisSccs) +evidenceSynthesisAnalysisSpecifications <- esModuleSettingsCreator$createModuleSpecifications( + evidenceSynthesisAnalysisList +) +esAnalysisSpecifications <- Strategus::createEmptyAnalysisSpecificiations() |> + Strategus::addModuleSpecifications(evidenceSynthesisAnalysisSpecifications) + +ParallelLogger::saveSettingsToJson(esAnalysisSpecifications, file.path(outputFolder, "evidenceSynthesisAnalysisSpecifications.json")) + + +resultsExecutionSettings <- Strategus::createResultsExecutionSettings( + resultsDatabaseSchema = "main", + resultsFolder = file.path(outputFolder, "evidence_sythesis", "results_folder"), + workFolder = file.path(outputFolder, "evidence_sythesis", "work_folder") +) + +Strategus::execute( + analysisSpecifications = esAnalysisSpecifications, + executionSettings = resultsExecutionSettings, + connectionDetails = resultsConnectionDetails +) + +resultsDataModelSettings <- Strategus::createResultsDataModelSettings( + resultsDatabaseSchema = "main", + resultsFolder = resultsExecutionSettings$resultsFolder, +) + +Strategus::createResultDataModel( + analysisSpecifications = esAnalysisSpecifications, + resultsDataModelSettings = resultsDataModelSettings, + resultsConnectionDetails = resultsConnectionDetails +) + +Strategus::uploadResults( + analysisSpecifications = esAnalysisSpecifications, + resultsDataModelSettings = resultsDataModelSettings, + resultsConnectionDetails = resultsConnectionDetails +) + +# Review results -------------------------- +library(ShinyAppBuilder) #NOTE: remotes::install_github("OHDSI/ShinyAppBuilder", ref="estimation") +library(OhdsiShinyModules) #NOTE: remotes::install_github("OHDSI/OhdsiShinyModules", ref="estimation-updated") +# ADD OR REMOVE MODULES TAILORED TO YOUR STUDY +shinyConfig <- initializeModuleConfig() |> + addModuleConfig( + createDefaultAboutConfig() + ) |> + addModuleConfig( + createDefaultDatasourcesConfig() + ) |> + addModuleConfig( + createDefaultCohortGeneratorConfig() + ) |> + addModuleConfig( + createDefaultCohortDiagnosticsConfig() + ) |> + addModuleConfig( + createDefaultCharacterizationConfig() + ) |> + addModuleConfig( + createDefaultPredictionConfig() + ) |> + addModuleConfig( + createDefaultEstimationConfig() + ) + +# now create the shiny app based on the config file and view the results +# based on the connection +ShinyAppBuilder::createShinyApp( + config = shinyConfig, + connectionDetails = resultsConnectionDetails, + resultDatabaseSettings = createDefaultResultDatabaseSettings(schema = "main"), + title = "Celecoxib vs. Diclofinac for the risk of GI Bleed", + studyDescription = "This study is showcasing the capabilities of running Strategus on Eunomia." +) diff --git a/extras/Strategus.pdf b/extras/Strategus.pdf index 577e1b96..6c1e71bc 100644 Binary files a/extras/Strategus.pdf and b/extras/Strategus.pdf differ diff --git a/extras/TestAnalysisSpecifications.json b/extras/TestAnalysisSpecifications.json deleted file mode 100644 index 80d29713..00000000 --- a/extras/TestAnalysisSpecifications.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "sharedResources": [], - "moduleSpecifications": [ - { - "module": "TestModule1", - "version": "0.0.1", - "settings": { - "dataSetName": "cars" - }, - "attr_class": ["TestModule1Specifications", "ModuleSpecifications"] - } - ], - "attr_class": "AnalysisSpecifications" -} diff --git a/extras/TestExample.R b/extras/TestExample.R deleted file mode 100644 index 10bb735b..00000000 --- a/extras/TestExample.R +++ /dev/null @@ -1,51 +0,0 @@ -library(Strategus) -library(dplyr) - - -# Create analysis specifications --------------------------------------------- - -# Note: maybe this function should live in the module? -createTestModule1Specifications <- function(dataSetName = "cars") { - specifications <- list(module = "TestModule1", - version = "0.0.1", - settings = list(dataSetName = dataSetName)) - class(specifications) <- c("TestModule1Specifications", "ModuleSpecifications") - return(specifications) -} - -analysisSpecifications <- createEmptyAnalysisSpecificiations() %>% - addModuleSpecifications(createTestModule1Specifications()) - -ParallelLogger::saveSettingsToJson(analysisSpecifications, "extras/testAnalysisSpecifications.json") - - -# Create execution settings ----------------------------------------------------- -connectionDetailsReference <- "prod-1-mdcd" - -# Note: Need to do only once: store connection details in keyring: -connectionDetails <- DatabaseConnector::createConnectionDetails(dbms = "redshift", - connectionString = keyring::key_get("redShiftConnectionStringOhdaMdcd"), - user = keyring::key_get("redShiftUserName"), - password = keyring::key_get("redShiftPassword")) - -storeConnectionDetails(connectionDetails = connectionDetails, - connectionDetailsReference = connectionDetailsReference) - -executionSettings <- createCdmExecutionSettings(connectionDetailsReference = connectionDetailsReference, - workDatabaseSchema = "scratch_mschuemi", - cdmDatabaseSchema = "cdm_truven_mdcd_v1978", - cohortTableNames = CohortGenerator::getCohortTableNames(cohortTable = "strategus_test"), - workFolder = "c:/temp/strategusWork", - resultsFolder = "c:/temp/strategusOutput", - minCellCount = 5) - -ParallelLogger::saveSettingsToJson(executionSettings, "extras/testExecutionSettings.json") - -# Execute analyses ------------------------------------------------------------- - -# Note: this environmental variable should be set once for each compute node -Sys.setenv("INSTANTIATED_MODULES_FOLDER" = "c:/temp/StrategusInstantiatedModules") -unlink("_targets", recursive = TRUE) - -execute(analysisSpecifications = analysisSpecifications, - executionSettings = executionSettings) diff --git a/extras/TestModule1-0.0.1/.Rprofile b/extras/TestModule1-0.0.1/.Rprofile deleted file mode 100644 index 81b960f5..00000000 --- a/extras/TestModule1-0.0.1/.Rprofile +++ /dev/null @@ -1 +0,0 @@ -source("renv/activate.R") diff --git a/extras/TestModule1-0.0.1/.renvignore b/extras/TestModule1-0.0.1/.renvignore deleted file mode 100644 index 8b4af754..00000000 --- a/extras/TestModule1-0.0.1/.renvignore +++ /dev/null @@ -1,4 +0,0 @@ -SettingsFunctions.R - -extras/ -/tests/ diff --git a/extras/TestModule1-0.0.1/Main.R b/extras/TestModule1-0.0.1/Main.R deleted file mode 100644 index f4b95422..00000000 --- a/extras/TestModule1-0.0.1/Main.R +++ /dev/null @@ -1,132 +0,0 @@ -# Copyright 2024 Observational Health Data Sciences and Informatics -# -# This file is part of Strategus -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# Adding library references that are required for Strategus -library(CohortGenerator) -library(DatabaseConnector) -library(keyring) -library(ParallelLogger) -library(SqlRender) - -# Adding RSQLite so that we can test modules with Eunomia -library(RSQLite) - -execute <- function(jobContext) { - rlang::inform("Validating inputs") - checkmate::assert_list(x = jobContext) - if (is.null(jobContext$settings)) { - stop("Analysis settings not found in job context") - } - if (is.null(jobContext$sharedResources)) { - stop("Shared resources not found in job context") - } - if (is.null(jobContext$moduleExecutionSettings)) { - stop("Execution settings not found in job context") - } - - rlang::inform("Executing") - # Establish the connection and ensure the cleanup is performed - connection <- DatabaseConnector::connect(jobContext$moduleExecutionSettings$connectionDetails) - on.exit(DatabaseConnector::disconnect(connection)) - - sql <- "CREATE TABLE #Codesets ( - codeset_id int NOT NULL, - concept_id bigint NOT NULL - ) - ; - - INSERT INTO #Codesets (codeset_id, concept_id) - SELECT 0 as codeset_id, c.concept_id - FROM @cdm_database_schema.CONCEPT c - WHERE c.concept_id = 0 - ;" - - DatabaseConnector::renderTranslateExecuteSql( - connection = connection, - sql = sql, - tempEmulationSchema = jobContext$moduleExecutionSettings$tempEmulationSchema, - cdm_database_schema = jobContext$moduleExecutionSettings$cdmDatabaseSchema - ) - - data <- DatabaseConnector::renderTranslateQuerySql( - connection = connection, - sql = "SELECT * FROM #Codesets;", - tempEmulationSchema = jobContext$moduleExecutionSettings$tempEmulationSchema - ) - - DatabaseConnector::renderTranslateExecuteSql( - connection = connection, - sql = "TRUNCATE TABLE #Codesets; DROP TABLE #Codesets;", - tempEmulationSchema = jobContext$moduleExecutionSettings$tempEmulationSchema - ) - - message("Exporting data") - moduleInfo <- getModuleInfo() - resultsFolder <- jobContext$moduleExecutionSettings$resultsSubFolder - fileName <- file.path(resultsFolder, paste0(moduleInfo$TablePrefix, "unit_test.csv")) - readr::write_csv(data, fileName) - - # Set the table names in resultsDataModelSpecification.csv - moduleInfo <- getModuleInfo() - resultsDataModel <- CohortGenerator::readCsv( - file = "resultsDataModelSpecification.csv", - warnOnCaseMismatch = FALSE - ) - resultsDataModel$tableName <- paste0(moduleInfo$TablePrefix, resultsDataModel$tableName) - CohortGenerator::writeCsv( - x = resultsDataModel, - file = file.path(resultsFolder, "resultsDataModelSpecification.csv"), - warnOnCaseMismatch = FALSE, - warnOnFileNameCaseMismatch = FALSE, - warnOnUploadRuleViolations = FALSE - ) - - ParallelLogger::logTrace("Finished TestModule1") -} - -createDataModelSchema <- function(jobContext) { - checkmate::assert_class(jobContext$moduleExecutionSettings$resultsConnectionDetails, "ConnectionDetails") - checkmate::assert_string(jobContext$moduleExecutionSettings$resultsDatabaseSchema) - connectionDetails <- jobContext$moduleExecutionSettings$resultsConnectionDetails - moduleInfo <- getModuleInfo() - tablePrefix <- moduleInfo$TablePrefix - resultsDatabaseSchema <- jobContext$moduleExecutionSettings$resultsDatabaseSchema - resultsDataModel <- ResultModelManager::loadResultsDataModelSpecifications( - filePath = "resultsDataModelSpecification.csv" - ) - resultsDataModel$tableName <- paste0(tablePrefix, resultsDataModel$tableName) - sql <- ResultModelManager::generateSqlSchema( - schemaDefinition = resultsDataModel - ) - sql <- SqlRender::render( - sql = sql, - database_schema = resultsDatabaseSchema - ) - connection <- DatabaseConnector::connect( - connectionDetails = connectionDetails - ) - on.exit(DatabaseConnector::disconnect(connection)) - DatabaseConnector::executeSql( - connection = connection, - sql = sql - ) -} - -# Private methods ------------------------- -getModuleInfo <- function() { - checkmate::assert_file_exists("MetaData.json") - return(ParallelLogger::loadSettingsFromJson("MetaData.json")) -} diff --git a/extras/TestModule1-0.0.1/MetaData.json b/extras/TestModule1-0.0.1/MetaData.json deleted file mode 100644 index 02bf1fa8..00000000 --- a/extras/TestModule1-0.0.1/MetaData.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "Name": "TestModule1", - "Version": "0.0.1", - "Dependencies": [], - "TablePrefix": "tm1_" -} diff --git a/extras/TestModule1-0.0.1/SettingsFunctions.R b/extras/TestModule1-0.0.1/SettingsFunctions.R deleted file mode 100644 index a5ecbf83..00000000 --- a/extras/TestModule1-0.0.1/SettingsFunctions.R +++ /dev/null @@ -1,20 +0,0 @@ -#' Create specifications for the TestModule1 -#' -#' @return -#' An object of type `TestModule1Specifications`. -#' -#' @export -createTestModule1Specifications <- function() { - analysis <- list() - for (name in names(formals(createTestModule1Specifications))) { - analysis[[name]] <- get(name) - } - - specifications <- list( - module = "TestModule1", - version = "0.0.1", - settings = analysis - ) - class(specifications) <- c("TestModule1Specifications", "ModuleSpecifications") - return(specifications) -} diff --git a/extras/TestModule1-0.0.1/TestModule1.Rproj b/extras/TestModule1-0.0.1/TestModule1.Rproj deleted file mode 100644 index d64e28bb..00000000 --- a/extras/TestModule1-0.0.1/TestModule1.Rproj +++ /dev/null @@ -1,16 +0,0 @@ -Version: 1.0 - -RestoreWorkspace: Default -SaveWorkspace: Default -AlwaysSaveHistory: Default - -EnableCodeIndexing: Yes -UseSpacesForTab: Yes -NumSpacesForTab: 2 -Encoding: UTF-8 - -RnwWeave: knitr -LaTeX: pdfLaTeX - -AutoAppendNewline: Yes -StripTrailingWhitespace: Yes diff --git a/extras/TestModule1-0.0.1/extras/CreateJobContextForTesting.R b/extras/TestModule1-0.0.1/extras/CreateJobContextForTesting.R deleted file mode 100644 index 15c6dbe3..00000000 --- a/extras/TestModule1-0.0.1/extras/CreateJobContextForTesting.R +++ /dev/null @@ -1,46 +0,0 @@ -# Create a job context for testing purposes -library(Strategus) -library(dplyr) -source("SettingsFunctions.R") - -# Generic Helpers ---------------------------- -getModuleInfo <- function() { - checkmate::assert_file_exists("MetaData.json") - return(ParallelLogger::loadSettingsFromJson("MetaData.json")) -} - -# Sample Data Helpers ---------------------------- -testModule1Specifications <- createTestModule1Specifications() - -# Module Settings Spec ---------------------------- -analysisSpecifications <- createEmptyAnalysisSpecificiations() %>% - addModuleSpecifications(testModule1Specifications) - -executionSettings <- Strategus::createCdmExecutionSettings( - connectionDetailsReference = "dummy", - workDatabaseSchema = "main", - cdmDatabaseSchema = "main", - cohortTableNames = CohortGenerator::getCohortTableNames(cohortTable = "cohort"), - workFolder = "dummy", - resultsFolder = "dummy", - minCellCount = 5 -) - -# Job Context ---------------------------- -module <- "TestModule1" -moduleIndex <- 1 -moduleExecutionSettings <- executionSettings -moduleExecutionSettings$workSubFolder <- "dummy" -moduleExecutionSettings$resultsSubFolder <- "dummy" -moduleExecutionSettings$databaseId <- 123 -jobContext <- list( - sharedResources = analysisSpecifications$sharedResources, - settings = analysisSpecifications$moduleSpecifications[[moduleIndex]]$settings, - moduleExecutionSettings = moduleExecutionSettings -) -saveRDS(jobContext, "tests/testJobContext.rds") - -ParallelLogger::saveSettingsToJson( - object = analysisSpecifications, - fileName = "../../../inst/testdata/testModuleAnalysisSpecification.json" -) diff --git a/extras/TestModule1-0.0.1/extras/ModuleMaintenance.R b/extras/TestModule1-0.0.1/extras/ModuleMaintenance.R deleted file mode 100644 index 7b05233d..00000000 --- a/extras/TestModule1-0.0.1/extras/ModuleMaintenance.R +++ /dev/null @@ -1,241 +0,0 @@ -# Copyright 2024 Observational Health Data Sciences and Informatics -# -# This file is part of CohortGeneratorModule -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# Format and check code: -styler::style_dir() -OhdsiRTools::updateCopyrightYearFolder(path = ".", recursive = F) -OhdsiRTools::updateCopyrightYearFolder(path = "./extras", recursive = F) -OhdsiRTools::findNonAsciiStringsInFolder() - -# Generate renv lock file for default & dev profiles ------------ -# updatedPackages and updatedDevPackages are those packages that either -# 1. Cannot be synced between the HADES-wide lock file and the project lock files -# since they are not in semver format -# 2. Updates to HADES packages -# NOTE: Mandatory Strategus dependencies: -# CohortGenerator -# DatabaseConnector -# keyring -# ParallelLogger -# SqlRender -# are explicitly included in Main.R as library calls to allow renv's init() -# function to find them and include them even if they are not used in the -# module code. - -updatedPackages <- list( - list( - Package = "askpass", - Version = "1.2.0", - Source = "Repository", - Repository = "CRAN" - ), - "OHDSI/CohortGenerator@v0.8.1", - "OHDSI/ResultModelManager@v0.5.6" -) -updatedDevPackages <- list( - list( - Package = "evaluate", - Version = "0.22", - Source = "Repository", - Repository = "CRAN" - ), - "OHDSI/Eunomia@v1.0.2" -) - -# Deactivates and cleans the project to remove any/all old references -renv::deactivate(clean = TRUE) - -# Initialize the default profile --------- -renv::activate(profile = NULL) -# Use the implicit option so renv crawls the full project. -renv::init(settings = renv::settings$snapshot.type("implicit")) -# Record the explicit package versions mentioned above -renv::record(updatedPackages) -# Force a restore for the default profile -renv::restore(prompt = FALSE) - -# Initialize the dev profile ------------ -renv::activate(profile = "dev") # Creates a new profile called "dev" for development - -# Remove the "tests" directory from the .renvignore -# so the test dependencies are included in the dev lock file -file.copy(".renvignore", ".renvignore-backup", overwrite = TRUE) -ignoreFileContents <- readLines(".renvignore") -ignoreFileContents <- ignoreFileContents[!grepl("/tests/", ignoreFileContents)] -writeLines(ignoreFileContents, ".renvignore") - -# Capture the dependencies -renv::init(profile = "dev") # Init the 'dev' profile renv.lock with the explicit DESCRIPTION references - -# Record the updated packages -renv::record(c(updatedPackages, updatedDevPackages), lockfile = "renv/profiles/dev/renv.lock") - -# Force a restore for the dev profile -renv::restore(prompt = FALSE) - -# Restore the original .renvignore -unlink(".renvignore") -file.rename(".renvignore-backup", ".renvignore") - -# Re-activate the default profile - the dev profile is only used for unit tests -renv::activate(profile = NULL) # Sets the default profile as the default for the project - -# Sync lock files with HADES-wide lock file -------------- -hadesWideLockFileName <- normalizePath("hades-wide.lock") -unlink(hadesWideLockFileName) -utils::download.file( - url = "https://raw.githubusercontent.com/OHDSI/Hades/main/hadesWideReleases/2023Q3/renv.lock", - destfile = hadesWideLockFileName -) -# Verify the package versions across lock files -compareLockFiles <- function(filename1, filename2) { - # Read the lock files - lockfile1 <- renv::lockfile_read( - file = filename1 - ) - print(normalizePath(filename2)) - lockfile2 <- renv::lockfile_read( - file = filename2 - ) - # internal function to read lock file into data frame - lockFileToDataFrame <- function(lf) { - df <- data.frame() - for (i in 1:length(lf$Packages)) { - df <- rbind( - df, - data.frame( - Name = lf$Packages[[i]]$Package, - Version = lf$Packages[[i]]$Version, - RemoteRef = ifelse(is.null(lf$Packages[[i]]$RemoteRef), yes = NA, no = lf$Packages[[i]]$RemoteRef) - ) - ) - } - return(df) - } - lockfile1Packages <- lockFileToDataFrame(lockfile1) - names(lockfile1Packages) <- paste0("lockfile1", names(lockfile1Packages)) - lockfile2Packages <- lockFileToDataFrame(lockfile2) - names(lockfile2Packages) <- paste0("lockfile2", names(lockfile2Packages)) - mergedLockFilePackages <- merge( - x = lockfile1Packages, - y = lockfile2Packages, - by.x = "lockfile1Name", - by.y = "lockfile2Name", - all = TRUE - ) - return(mergedLockFilePackages) -} - -# Compare HADES-wide lock file to the dev lock file -hwVsProjDevLockFile <- compareLockFiles( - filename1 = hadesWideLockFileName, - filename2 = "renv/profiles/dev/renv.lock" -) -hwVsProjDevLockFile[!is.na(hwVsProjDevLockFile$lockfile2Version) & hwVsProjDevLockFile$lockfile1Version != hwVsProjDevLockFile$lockfile2Version, ] - -# Compare project default lock file to the dev lock file -projDevVsProjLockFile <- compareLockFiles( - filename1 = "renv/profiles/dev/renv.lock", - filename2 = "renv.lock" -) -projDevVsProjLockFile[!is.na(projDevVsProjLockFile$lockfile2Version) & projDevVsProjLockFile$lockfile1Version != projDevVsProjLockFile$lockfile2Version, ] - -# Given a source of truth lock file, update the target -# lock file. Only replace the version in the target -# lock file if the version is newer. Provide a warning -# for those packages that could not be evaluated by -# version # -renv::install("semver") -syncLockFile <- function(sourceOfTruthLockFileName, targetLockFileName) { - findPackageByName <- function(list, packageName) { - index <- which(sapply(list, function(x) x$Package == packageName)) - return(index) - } - - # Read the lock files - sourceOfTruthLockFile <- renv::lockfile_read( - file = sourceOfTruthLockFileName - ) - targetLockFile <- renv::lockfile_read( - file = targetLockFileName - ) - - # Compare the lock files to get the differences in package versions - comparedLockFiles <- compareLockFiles( - filename1 = sourceOfTruthLockFileName, - filename2 = targetLockFileName - ) - verDiffs <- comparedLockFiles[!is.na(comparedLockFiles$lockfile2Version) & - comparedLockFiles$lockfile1Version != comparedLockFiles$lockfile2Version, ] - verDiffs <- verDiffs[!is.na(verDiffs$lockfile1Name), ] - - if (nrow(verDiffs) == 0) { - rlang::inform("Lock files are already in sync.") - return(invisible(NULL)) - } - - # Update the target lock file based on the source of truth - for (i in 1:nrow(verDiffs)) { - index <- findPackageByName(targetLockFile$Packages, verDiffs[i, ]$lockfile1Name) - # Can we detect if the version is greater - tryCatch(expr = { - semverPattern <- "^\\d+\\.\\d+\\.\\d+(?:-[0-9A-Za-z-]+(?:\\.[0-9A-Za-z-]+)*)?(?:\\+[0-9A-Za-z-]+)?$" - sourceOfTruthVersion <- verDiffs[i, ]$lockfile1Version - targetVersion <- targetLockFile$Packages[[index]]$Version - if (grepl(semverPattern, sourceOfTruthVersion) && grepl(semverPattern, targetVersion)) { - sourceOfTruthVersion <- semver::parse_version(sourceOfTruthVersion) - targetVersion <- semver::parse_version(targetVersion) - if (sourceOfTruthVersion > targetVersion) { - rlang::inform( - message = paste(verDiffs[i, ]$lockfile1Name, "[", targetVersion, "->", sourceOfTruthVersion, "]") - ) - targetLockFile$Packages[[index]]$Version <- verDiffs[i, ]$lockfile1Version - if (!is.na(verDiffs[i, ]$lockfile1RemoteRef)) { - targetLockFile$Packages[[index]]$RemoteRef <- verDiffs[i, ]$lockfile1RemoteRef - } - } else { - rlang::inform( - message = paste(verDiffs[i, ]$lockfile1Name, "[ SKIPPING - ", targetVersion, ">", sourceOfTruthVersion, "]") - ) - } - } else { - rlang::warn(paste0("Package: [", verDiffs[i, ]$lockfile1Name, "] - version number could not be parsed. Please inspect manually as it may require an upgrade.")) - } - }, error = function(err) { - rlang::inform("An error occurred:", str(err), "\n") - }) - } - - # Save the updated lock file - renv::lockfile_write( - lockfile = targetLockFile, - file = targetLockFileName - ) -} - -syncLockFile( - sourceOfTruthLockFileName = hadesWideLockFileName, - targetLockFileName = "renv/profiles/dev/renv.lock" -) - -syncLockFile( - sourceOfTruthLockFileName = "renv/profiles/dev/renv.lock", - targetLockFileName = "renv.lock" -) - -# NOTE: Use the compare functions above to verify the files are in sync -# and add any dependencies that could not be synced automatically to the -# updatedPackages and updatedDevPackages respectively. diff --git a/extras/TestModule1-0.0.1/hades-wide.lock b/extras/TestModule1-0.0.1/hades-wide.lock deleted file mode 100644 index 089d5ad4..00000000 --- a/extras/TestModule1-0.0.1/hades-wide.lock +++ /dev/null @@ -1,1565 +0,0 @@ -{ - "R" : { - "Version" : "4.2.3", - "Repositories" : [ - { - "Name" : "CRAN", - "URL" : "https://cloud.r-project.org" - } - ] - }, - "Packages" : { - "cli" : { - "Package" : "cli", - "Version" : "3.6.1", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "glue" : { - "Package" : "glue", - "Version" : "1.6.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "rlang" : { - "Package" : "rlang", - "Version" : "1.1.1", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "lifecycle" : { - "Package" : "lifecycle", - "Version" : "1.0.3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "fansi" : { - "Package" : "fansi", - "Version" : "1.0.4", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "ps" : { - "Package" : "ps", - "Version" : "1.7.5", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "R6" : { - "Package" : "R6", - "Version" : "2.5.1", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "utf8" : { - "Package" : "utf8", - "Version" : "1.2.3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "vctrs" : { - "Package" : "vctrs", - "Version" : "0.6.3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "base64enc" : { - "Package" : "base64enc", - "Version" : "0.1-3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "digest" : { - "Package" : "digest", - "Version" : "0.6.33", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "ellipsis" : { - "Package" : "ellipsis", - "Version" : "0.3.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "fastmap" : { - "Package" : "fastmap", - "Version" : "1.1.1", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "magrittr" : { - "Package" : "magrittr", - "Version" : "2.0.3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "pillar" : { - "Package" : "pillar", - "Version" : "1.9.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "pkgconfig" : { - "Package" : "pkgconfig", - "Version" : "2.0.3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "processx" : { - "Package" : "processx", - "Version" : "3.8.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "rprojroot" : { - "Package" : "rprojroot", - "Version" : "2.0.3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "withr" : { - "Package" : "withr", - "Version" : "2.5.1", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "bit" : { - "Package" : "bit", - "Version" : "4.0.5", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "cachem" : { - "Package" : "cachem", - "Version" : "1.0.8", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "callr" : { - "Package" : "callr", - "Version" : "3.7.3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "cpp11" : { - "Package" : "cpp11", - "Version" : "0.4.6", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "crayon" : { - "Package" : "crayon", - "Version" : "1.5.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "desc" : { - "Package" : "desc", - "Version" : "1.4.2", - "Source" : "Repository", - "Repository" : "CRAN" - 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"Source" : "Repository", - "Repository" : "CRAN" - }, - "tidyselect" : { - "Package" : "tidyselect", - "Version" : "1.2.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "xfun" : { - "Package" : "xfun", - "Version" : "0.40", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "backports" : { - "Package" : "backports", - "Version" : "1.4.1", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "bit64" : { - "Package" : "bit64", - "Version" : "4.0.5", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "colorspace" : { - "Package" : "colorspace", - "Version" : "2.1-0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "diffobj" : { - "Package" : "diffobj", - "Version" : "0.3.5", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "dplyr" : { - "Package" : "dplyr", - "Version" : "1.1.3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "evaluate" : { - "Package" : "evaluate", - "Version" : "0.22", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "highr" : { - "Package" : "highr", - "Version" : "0.10", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "jquerylib" : { - "Package" : "jquerylib", - "Version" : "0.1.4", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "jsonlite" : { - "Package" : "jsonlite", - "Version" : "1.8.7", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "later" : { - "Package" : "later", - "Version" : "1.3.1", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "lattice" : { - "Package" : "lattice", - "Version" : "0.20-45", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "memoise" : { - "Package" : "memoise", - "Version" : "2.0.1", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "mime" : { - "Package" : "mime", - "Version" : "0.12", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "pkgbuild" : { - "Package" : "pkgbuild", - "Version" : "1.4.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "progress" : { - "Package" : "progress", - 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}, - "yaml": { - "Package": "yaml", - "Version": "2.3.7", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "0d0056cc5383fbc240ccd0cb584bf436" - }, - "zip": { - "Package": "zip", - "Version": "2.3.0", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "d98c94dacb7e0efcf83b0a133a705504" - } - } -} diff --git a/extras/TestModule1-0.0.1/renv/.gitignore b/extras/TestModule1-0.0.1/renv/.gitignore deleted file mode 100644 index 0ec0cbba..00000000 --- a/extras/TestModule1-0.0.1/renv/.gitignore +++ /dev/null @@ -1,7 +0,0 @@ -library/ -local/ -cellar/ -lock/ -python/ -sandbox/ -staging/ diff --git a/extras/TestModule1-0.0.1/renv/activate.R b/extras/TestModule1-0.0.1/renv/activate.R deleted file mode 100644 index cb5401f9..00000000 --- a/extras/TestModule1-0.0.1/renv/activate.R +++ /dev/null @@ -1,1180 +0,0 @@ - -local({ - - # the requested version of renv - version <- "1.0.3" - attr(version, "sha") <- NULL - - # the project directory - project <- getwd() - - # use start-up diagnostics if enabled - diagnostics <- Sys.getenv("RENV_STARTUP_DIAGNOSTICS", unset = "FALSE") - if (diagnostics) { - start <- Sys.time() - profile <- tempfile("renv-startup-", fileext = ".Rprof") - utils::Rprof(profile) - on.exit({ - utils::Rprof(NULL) - elapsed <- signif(difftime(Sys.time(), start, units = "auto"), digits = 2L) - writeLines(sprintf("- renv took %s to run the autoloader.", format(elapsed))) - writeLines(sprintf("- Profile: %s", profile)) - print(utils::summaryRprof(profile)) - }, add = TRUE) - } - - # figure out whether the autoloader is enabled - enabled <- local({ - - # first, check config option - override <- getOption("renv.config.autoloader.enabled") - if (!is.null(override)) - return(override) - - # next, check environment variables - # TODO: prefer using the configuration one in the future - envvars <- c( - "RENV_CONFIG_AUTOLOADER_ENABLED", - "RENV_AUTOLOADER_ENABLED", - "RENV_ACTIVATE_PROJECT" - ) - - for (envvar in envvars) { - envval <- Sys.getenv(envvar, unset = NA) - if (!is.na(envval)) - return(tolower(envval) %in% c("true", "t", "1")) - } - - # enable by default - TRUE - - }) - - if (!enabled) - return(FALSE) - - # avoid recursion - if (identical(getOption("renv.autoloader.running"), TRUE)) { - warning("ignoring recursive attempt to run renv autoloader") - return(invisible(TRUE)) - } - - # signal that we're loading renv during R startup - options(renv.autoloader.running = TRUE) - on.exit(options(renv.autoloader.running = NULL), add = TRUE) - - # signal that we've consented to use renv - options(renv.consent = TRUE) - - # load the 'utils' package eagerly -- this ensures that renv shims, which - # mask 'utils' packages, will come first on the search path - library(utils, lib.loc = .Library) - - # unload renv if it's already been loaded - if ("renv" %in% loadedNamespaces()) - unloadNamespace("renv") - - # load bootstrap tools - `%||%` <- function(x, y) { - if (is.null(x)) y else x - } - - catf <- function(fmt, ..., appendLF = TRUE) { - - quiet <- getOption("renv.bootstrap.quiet", default = FALSE) - if (quiet) - return(invisible()) - - msg <- sprintf(fmt, ...) - cat(msg, file = stdout(), sep = if (appendLF) "\n" else "") - - invisible(msg) - - } - - header <- function(label, - ..., - prefix = "#", - suffix = "-", - n = min(getOption("width"), 78)) - { - label <- sprintf(label, ...) - n <- max(n - nchar(label) - nchar(prefix) - 2L, 8L) - if (n <= 0) - return(paste(prefix, label)) - - tail <- paste(rep.int(suffix, n), collapse = "") - paste0(prefix, " ", label, " ", tail) - - } - - startswith <- function(string, prefix) { - substring(string, 1, nchar(prefix)) == prefix - } - - bootstrap <- function(version, library) { - - friendly <- renv_bootstrap_version_friendly(version) - section <- header(sprintf("Bootstrapping renv %s", friendly)) - catf(section) - - # attempt to download renv - catf("- Downloading renv ... ", appendLF = FALSE) - withCallingHandlers( - tarball <- renv_bootstrap_download(version), - error = function(err) { - catf("FAILED") - stop("failed to download:\n", conditionMessage(err)) - } - ) - catf("OK") - on.exit(unlink(tarball), add = TRUE) - - # now attempt to install - catf("- Installing renv ... ", appendLF = FALSE) - withCallingHandlers( - status <- renv_bootstrap_install(version, tarball, library), - error = function(err) { - catf("FAILED") - stop("failed to install:\n", conditionMessage(err)) - } - ) - catf("OK") - - # add empty line to break up bootstrapping from normal output - catf("") - - return(invisible()) - } - - renv_bootstrap_tests_running <- function() { - getOption("renv.tests.running", default = FALSE) - } - - renv_bootstrap_repos <- function() { - - # get CRAN repository - cran <- getOption("renv.repos.cran", "https://cloud.r-project.org") - - # check for repos override - repos <- Sys.getenv("RENV_CONFIG_REPOS_OVERRIDE", unset = NA) - if (!is.na(repos)) { - - # check for RSPM; if set, use a fallback repository for renv - rspm <- Sys.getenv("RSPM", unset = NA) - if (identical(rspm, repos)) - repos <- c(RSPM = rspm, CRAN = cran) - - return(repos) - - } - - # check for lockfile repositories - repos <- tryCatch(renv_bootstrap_repos_lockfile(), error = identity) - if (!inherits(repos, "error") && length(repos)) - return(repos) - - # retrieve current repos - repos <- getOption("repos") - - # ensure @CRAN@ entries are resolved - repos[repos == "@CRAN@"] <- cran - - # add in renv.bootstrap.repos if set - default <- c(FALLBACK = "https://cloud.r-project.org") - extra <- getOption("renv.bootstrap.repos", default = default) - repos <- c(repos, extra) - - # remove duplicates that might've snuck in - dupes <- duplicated(repos) | duplicated(names(repos)) - repos[!dupes] - - } - - renv_bootstrap_repos_lockfile <- function() { - - lockpath <- Sys.getenv("RENV_PATHS_LOCKFILE", unset = "renv.lock") - if (!file.exists(lockpath)) - return(NULL) - - lockfile <- tryCatch(renv_json_read(lockpath), error = identity) - if (inherits(lockfile, "error")) { - warning(lockfile) - return(NULL) - } - - repos <- lockfile$R$Repositories - if (length(repos) == 0) - return(NULL) - - keys <- vapply(repos, `[[`, "Name", FUN.VALUE = character(1)) - vals <- vapply(repos, `[[`, "URL", FUN.VALUE = character(1)) - names(vals) <- keys - - return(vals) - - } - - renv_bootstrap_download <- function(version) { - - sha <- attr(version, "sha", exact = TRUE) - - methods <- if (!is.null(sha)) { - - # attempting to bootstrap a development version of renv - c( - function() renv_bootstrap_download_tarball(sha), - function() renv_bootstrap_download_github(sha) - ) - - } else { - - # attempting to bootstrap a release version of renv - c( - function() renv_bootstrap_download_tarball(version), - function() renv_bootstrap_download_cran_latest(version), - function() renv_bootstrap_download_cran_archive(version) - ) - - } - - for (method in methods) { - path <- tryCatch(method(), error = identity) - if (is.character(path) && file.exists(path)) - return(path) - } - - stop("All download methods failed") - - } - - renv_bootstrap_download_impl <- function(url, destfile) { - - mode <- "wb" - - # https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17715 - fixup <- - Sys.info()[["sysname"]] == "Windows" && - substring(url, 1L, 5L) == "file:" - - if (fixup) - mode <- "w+b" - - args <- list( - url = url, - destfile = destfile, - mode = mode, - quiet = TRUE - ) - - if ("headers" %in% names(formals(utils::download.file))) - args$headers <- renv_bootstrap_download_custom_headers(url) - - do.call(utils::download.file, args) - - } - - renv_bootstrap_download_custom_headers <- function(url) { - - headers <- getOption("renv.download.headers") - if (is.null(headers)) - return(character()) - - if (!is.function(headers)) - stopf("'renv.download.headers' is not a function") - - headers <- headers(url) - if (length(headers) == 0L) - return(character()) - - if (is.list(headers)) - headers <- unlist(headers, recursive = FALSE, use.names = TRUE) - - ok <- - is.character(headers) && - is.character(names(headers)) && - all(nzchar(names(headers))) - - if (!ok) - stop("invocation of 'renv.download.headers' did not return a named character vector") - - headers - - } - - renv_bootstrap_download_cran_latest <- function(version) { - - spec <- renv_bootstrap_download_cran_latest_find(version) - type <- spec$type - repos <- spec$repos - - baseurl <- utils::contrib.url(repos = repos, type = type) - ext <- if (identical(type, "source")) - ".tar.gz" - else if (Sys.info()[["sysname"]] == "Windows") - ".zip" - else - ".tgz" - name <- sprintf("renv_%s%s", version, ext) - url <- paste(baseurl, name, sep = "/") - - destfile <- file.path(tempdir(), name) - status <- tryCatch( - renv_bootstrap_download_impl(url, destfile), - condition = identity - ) - - if (inherits(status, "condition")) - return(FALSE) - - # report success and return - destfile - - } - - renv_bootstrap_download_cran_latest_find <- function(version) { - - # check whether binaries are supported on this system - binary <- - getOption("renv.bootstrap.binary", default = TRUE) && - !identical(.Platform$pkgType, "source") && - !identical(getOption("pkgType"), "source") && - Sys.info()[["sysname"]] %in% c("Darwin", "Windows") - - types <- c(if (binary) "binary", "source") - - # iterate over types + repositories - for (type in types) { - for (repos in renv_bootstrap_repos()) { - - # retrieve package database - db <- tryCatch( - as.data.frame( - utils::available.packages(type = type, repos = repos), - stringsAsFactors = FALSE - ), - error = identity - ) - - if (inherits(db, "error")) - next - - # check for compatible entry - entry <- db[db$Package %in% "renv" & db$Version %in% version, ] - if (nrow(entry) == 0) - next - - # found it; return spec to caller - spec <- list(entry = entry, type = type, repos = repos) - return(spec) - - } - } - - # if we got here, we failed to find renv - fmt <- "renv %s is not available from your declared package repositories" - stop(sprintf(fmt, version)) - - } - - renv_bootstrap_download_cran_archive <- function(version) { - - name <- sprintf("renv_%s.tar.gz", version) - repos <- renv_bootstrap_repos() - urls <- file.path(repos, "src/contrib/Archive/renv", name) - destfile <- file.path(tempdir(), name) - - for (url in urls) { - - status <- tryCatch( - renv_bootstrap_download_impl(url, destfile), - condition = identity - ) - - if (identical(status, 0L)) - return(destfile) - - } - - return(FALSE) - - } - - renv_bootstrap_download_tarball <- function(version) { - - # if the user has provided the path to a tarball via - # an environment variable, then use it - tarball <- Sys.getenv("RENV_BOOTSTRAP_TARBALL", unset = NA) - if (is.na(tarball)) - return() - - # allow directories - if (dir.exists(tarball)) { - name <- sprintf("renv_%s.tar.gz", version) - tarball <- file.path(tarball, name) - } - - # bail if it doesn't exist - if (!file.exists(tarball)) { - - # let the user know we weren't able to honour their request - fmt <- "- RENV_BOOTSTRAP_TARBALL is set (%s) but does not exist." - msg <- sprintf(fmt, tarball) - warning(msg) - - # bail - return() - - } - - catf("- Using local tarball '%s'.", tarball) - tarball - - } - - renv_bootstrap_download_github <- function(version) { - - enabled <- Sys.getenv("RENV_BOOTSTRAP_FROM_GITHUB", unset = "TRUE") - if (!identical(enabled, "TRUE")) - return(FALSE) - - # prepare download options - pat <- Sys.getenv("GITHUB_PAT") - if (nzchar(Sys.which("curl")) && nzchar(pat)) { - fmt <- "--location --fail --header \"Authorization: token %s\"" - extra <- sprintf(fmt, pat) - saved <- options("download.file.method", "download.file.extra") - options(download.file.method = "curl", download.file.extra = extra) - on.exit(do.call(base::options, saved), add = TRUE) - } else if (nzchar(Sys.which("wget")) && nzchar(pat)) { - fmt <- "--header=\"Authorization: token %s\"" - extra <- sprintf(fmt, pat) - saved <- options("download.file.method", "download.file.extra") - options(download.file.method = "wget", download.file.extra = extra) - on.exit(do.call(base::options, saved), add = TRUE) - } - - url <- file.path("https://api.github.com/repos/rstudio/renv/tarball", version) - name <- sprintf("renv_%s.tar.gz", version) - destfile <- file.path(tempdir(), name) - - status <- tryCatch( - renv_bootstrap_download_impl(url, destfile), - condition = identity - ) - - if (!identical(status, 0L)) - return(FALSE) - - renv_bootstrap_download_augment(destfile) - - return(destfile) - - } - - # Add Sha to DESCRIPTION. This is stop gap until #890, after which we - # can use renv::install() to fully capture metadata. - renv_bootstrap_download_augment <- function(destfile) { - sha <- renv_bootstrap_git_extract_sha1_tar(destfile) - if (is.null(sha)) { - return() - } - - # Untar - tempdir <- tempfile("renv-github-") - on.exit(unlink(tempdir, recursive = TRUE), add = TRUE) - untar(destfile, exdir = tempdir) - pkgdir <- dir(tempdir, full.names = TRUE)[[1]] - - # Modify description - desc_path <- file.path(pkgdir, "DESCRIPTION") - desc_lines <- readLines(desc_path) - remotes_fields <- c( - "RemoteType: github", - "RemoteHost: api.github.com", - "RemoteRepo: renv", - "RemoteUsername: rstudio", - "RemotePkgRef: rstudio/renv", - paste("RemoteRef: ", sha), - paste("RemoteSha: ", sha) - ) - writeLines(c(desc_lines[desc_lines != ""], remotes_fields), con = desc_path) - - # Re-tar - local({ - old <- setwd(tempdir) - on.exit(setwd(old), add = TRUE) - - tar(destfile, compression = "gzip") - }) - invisible() - } - - # Extract the commit hash from a git archive. Git archives include the SHA1 - # hash as the comment field of the tarball pax extended header - # (see https://www.kernel.org/pub/software/scm/git/docs/git-archive.html) - # For GitHub archives this should be the first header after the default one - # (512 byte) header. - renv_bootstrap_git_extract_sha1_tar <- function(bundle) { - - # open the bundle for reading - # We use gzcon for everything because (from ?gzcon) - # > Reading from a connection which does not supply a 'gzip' magic - # > header is equivalent to reading from the original connection - conn <- gzcon(file(bundle, open = "rb", raw = TRUE)) - on.exit(close(conn)) - - # The default pax header is 512 bytes long and the first pax extended header - # with the comment should be 51 bytes long - # `52 comment=` (11 chars) + 40 byte SHA1 hash - len <- 0x200 + 0x33 - res <- rawToChar(readBin(conn, "raw", n = len)[0x201:len]) - - if (grepl("^52 comment=", res)) { - sub("52 comment=", "", res) - } else { - NULL - } - } - - renv_bootstrap_install <- function(version, tarball, library) { - - # attempt to install it into project library - dir.create(library, showWarnings = FALSE, recursive = TRUE) - output <- renv_bootstrap_install_impl(library, tarball) - - # check for successful install - status <- attr(output, "status") - if (is.null(status) || identical(status, 0L)) - return(status) - - # an error occurred; report it - header <- "installation of renv failed" - lines <- paste(rep.int("=", nchar(header)), collapse = "") - text <- paste(c(header, lines, output), collapse = "\n") - stop(text) - - } - - renv_bootstrap_install_impl <- function(library, tarball) { - - # invoke using system2 so we can capture and report output - bin <- R.home("bin") - exe <- if (Sys.info()[["sysname"]] == "Windows") "R.exe" else "R" - R <- file.path(bin, exe) - - args <- c( - "--vanilla", "CMD", "INSTALL", "--no-multiarch", - "-l", shQuote(path.expand(library)), - shQuote(path.expand(tarball)) - ) - - system2(R, args, stdout = TRUE, stderr = TRUE) - - } - - renv_bootstrap_platform_prefix <- function() { - - # construct version prefix - version <- paste(R.version$major, R.version$minor, sep = ".") - prefix <- paste("R", numeric_version(version)[1, 1:2], sep = "-") - - # include SVN revision for development versions of R - # (to avoid sharing platform-specific artefacts with released versions of R) - devel <- - identical(R.version[["status"]], "Under development (unstable)") || - identical(R.version[["nickname"]], "Unsuffered Consequences") - - if (devel) - prefix <- paste(prefix, R.version[["svn rev"]], sep = "-r") - - # build list of path components - components <- c(prefix, R.version$platform) - - # include prefix if provided by user - prefix <- renv_bootstrap_platform_prefix_impl() - if (!is.na(prefix) && nzchar(prefix)) - components <- c(prefix, components) - - # build prefix - paste(components, collapse = "/") - - } - - renv_bootstrap_platform_prefix_impl <- function() { - - # if an explicit prefix has been supplied, use it - prefix <- Sys.getenv("RENV_PATHS_PREFIX", unset = NA) - if (!is.na(prefix)) - return(prefix) - - # if the user has requested an automatic prefix, generate it - auto <- Sys.getenv("RENV_PATHS_PREFIX_AUTO", unset = NA) - if (auto %in% c("TRUE", "True", "true", "1")) - return(renv_bootstrap_platform_prefix_auto()) - - # empty string on failure - "" - - } - - renv_bootstrap_platform_prefix_auto <- function() { - - prefix <- tryCatch(renv_bootstrap_platform_os(), error = identity) - if (inherits(prefix, "error") || prefix %in% "unknown") { - - msg <- paste( - "failed to infer current operating system", - "please file a bug report at https://github.com/rstudio/renv/issues", - sep = "; " - ) - - warning(msg) - - } - - prefix - - } - - renv_bootstrap_platform_os <- function() { - - sysinfo <- Sys.info() - sysname <- sysinfo[["sysname"]] - - # handle Windows + macOS up front - if (sysname == "Windows") - return("windows") - else if (sysname == "Darwin") - return("macos") - - # check for os-release files - for (file in c("/etc/os-release", "/usr/lib/os-release")) - if (file.exists(file)) - return(renv_bootstrap_platform_os_via_os_release(file, sysinfo)) - - # check for redhat-release files - if (file.exists("/etc/redhat-release")) - return(renv_bootstrap_platform_os_via_redhat_release()) - - "unknown" - - } - - renv_bootstrap_platform_os_via_os_release <- function(file, sysinfo) { - - # read /etc/os-release - release <- utils::read.table( - file = file, - sep = "=", - quote = c("\"", "'"), - col.names = c("Key", "Value"), - comment.char = "#", - stringsAsFactors = FALSE - ) - - vars <- as.list(release$Value) - names(vars) <- release$Key - - # get os name - os <- tolower(sysinfo[["sysname"]]) - - # read id - id <- "unknown" - for (field in c("ID", "ID_LIKE")) { - if (field %in% names(vars) && nzchar(vars[[field]])) { - id <- vars[[field]] - break - } - } - - # read version - version <- "unknown" - for (field in c("UBUNTU_CODENAME", "VERSION_CODENAME", "VERSION_ID", "BUILD_ID")) { - if (field %in% names(vars) && nzchar(vars[[field]])) { - version <- vars[[field]] - break - } - } - - # join together - paste(c(os, id, version), collapse = "-") - - } - - renv_bootstrap_platform_os_via_redhat_release <- function() { - - # read /etc/redhat-release - contents <- readLines("/etc/redhat-release", warn = FALSE) - - # infer id - id <- if (grepl("centos", contents, ignore.case = TRUE)) - "centos" - else if (grepl("redhat", contents, ignore.case = TRUE)) - "redhat" - else - "unknown" - - # try to find a version component (very hacky) - version <- "unknown" - - parts <- strsplit(contents, "[[:space:]]")[[1L]] - for (part in parts) { - - nv <- tryCatch(numeric_version(part), error = identity) - if (inherits(nv, "error")) - next - - version <- nv[1, 1] - break - - } - - paste(c("linux", id, version), collapse = "-") - - } - - renv_bootstrap_library_root_name <- function(project) { - - # use project name as-is if requested - asis <- Sys.getenv("RENV_PATHS_LIBRARY_ROOT_ASIS", unset = "FALSE") - if (asis) - return(basename(project)) - - # otherwise, disambiguate based on project's path - id <- substring(renv_bootstrap_hash_text(project), 1L, 8L) - paste(basename(project), id, sep = "-") - - } - - renv_bootstrap_library_root <- function(project) { - - prefix <- renv_bootstrap_profile_prefix() - - path <- Sys.getenv("RENV_PATHS_LIBRARY", unset = NA) - if (!is.na(path)) - return(paste(c(path, prefix), collapse = "/")) - - path <- renv_bootstrap_library_root_impl(project) - if (!is.null(path)) { - name <- renv_bootstrap_library_root_name(project) - return(paste(c(path, prefix, name), collapse = "/")) - } - - renv_bootstrap_paths_renv("library", project = project) - - } - - renv_bootstrap_library_root_impl <- function(project) { - - root <- Sys.getenv("RENV_PATHS_LIBRARY_ROOT", unset = NA) - if (!is.na(root)) - return(root) - - type <- renv_bootstrap_project_type(project) - if (identical(type, "package")) { - userdir <- renv_bootstrap_user_dir() - return(file.path(userdir, "library")) - } - - } - - renv_bootstrap_validate_version <- function(version, description = NULL) { - - # resolve description file - # - # avoid passing lib.loc to `packageDescription()` below, since R will - # use the loaded version of the package by default anyhow. note that - # this function should only be called after 'renv' is loaded - # https://github.com/rstudio/renv/issues/1625 - description <- description %||% packageDescription("renv") - - # check whether requested version 'version' matches loaded version of renv - sha <- attr(version, "sha", exact = TRUE) - valid <- if (!is.null(sha)) - renv_bootstrap_validate_version_dev(sha, description) - else - renv_bootstrap_validate_version_release(version, description) - - if (valid) - return(TRUE) - - # the loaded version of renv doesn't match the requested version; - # give the user instructions on how to proceed - remote <- if (!is.null(description[["RemoteSha"]])) { - paste("rstudio/renv", description[["RemoteSha"]], sep = "@") - } else { - paste("renv", description[["Version"]], sep = "@") - } - - # display both loaded version + sha if available - friendly <- renv_bootstrap_version_friendly( - version = description[["Version"]], - sha = description[["RemoteSha"]] - ) - - fmt <- paste( - "renv %1$s was loaded from project library, but this project is configured to use renv %2$s.", - "- Use `renv::record(\"%3$s\")` to record renv %1$s in the lockfile.", - "- Use `renv::restore(packages = \"renv\")` to install renv %2$s into the project library.", - sep = "\n" - ) - catf(fmt, friendly, renv_bootstrap_version_friendly(version), remote) - - FALSE - - } - - renv_bootstrap_validate_version_dev <- function(version, description) { - expected <- description[["RemoteSha"]] - is.character(expected) && startswith(expected, version) - } - - renv_bootstrap_validate_version_release <- function(version, description) { - expected <- description[["Version"]] - is.character(expected) && identical(expected, version) - } - - renv_bootstrap_hash_text <- function(text) { - - hashfile <- tempfile("renv-hash-") - on.exit(unlink(hashfile), add = TRUE) - - writeLines(text, con = hashfile) - tools::md5sum(hashfile) - - } - - renv_bootstrap_load <- function(project, libpath, version) { - - # try to load renv from the project library - if (!requireNamespace("renv", lib.loc = libpath, quietly = TRUE)) - return(FALSE) - - # warn if the version of renv loaded does not match - renv_bootstrap_validate_version(version) - - # execute renv load hooks, if any - hooks <- getHook("renv::autoload") - for (hook in hooks) - if (is.function(hook)) - tryCatch(hook(), error = warnify) - - # load the project - renv::load(project) - - TRUE - - } - - renv_bootstrap_profile_load <- function(project) { - - # if RENV_PROFILE is already set, just use that - profile <- Sys.getenv("RENV_PROFILE", unset = NA) - if (!is.na(profile) && nzchar(profile)) - return(profile) - - # check for a profile file (nothing to do if it doesn't exist) - path <- renv_bootstrap_paths_renv("profile", profile = FALSE, project = project) - if (!file.exists(path)) - return(NULL) - - # read the profile, and set it if it exists - contents <- readLines(path, warn = FALSE) - if (length(contents) == 0L) - return(NULL) - - # set RENV_PROFILE - profile <- contents[[1L]] - if (!profile %in% c("", "default")) - Sys.setenv(RENV_PROFILE = profile) - - profile - - } - - renv_bootstrap_profile_prefix <- function() { - profile <- renv_bootstrap_profile_get() - if (!is.null(profile)) - return(file.path("profiles", profile, "renv")) - } - - renv_bootstrap_profile_get <- function() { - profile <- Sys.getenv("RENV_PROFILE", unset = "") - renv_bootstrap_profile_normalize(profile) - } - - renv_bootstrap_profile_set <- function(profile) { - profile <- renv_bootstrap_profile_normalize(profile) - if (is.null(profile)) - Sys.unsetenv("RENV_PROFILE") - else - Sys.setenv(RENV_PROFILE = profile) - } - - renv_bootstrap_profile_normalize <- function(profile) { - - if (is.null(profile) || profile %in% c("", "default")) - return(NULL) - - profile - - } - - renv_bootstrap_path_absolute <- function(path) { - - substr(path, 1L, 1L) %in% c("~", "/", "\\") || ( - substr(path, 1L, 1L) %in% c(letters, LETTERS) && - substr(path, 2L, 3L) %in% c(":/", ":\\") - ) - - } - - renv_bootstrap_paths_renv <- function(..., profile = TRUE, project = NULL) { - renv <- Sys.getenv("RENV_PATHS_RENV", unset = "renv") - root <- if (renv_bootstrap_path_absolute(renv)) NULL else project - prefix <- if (profile) renv_bootstrap_profile_prefix() - components <- c(root, renv, prefix, ...) - paste(components, collapse = "/") - } - - renv_bootstrap_project_type <- function(path) { - - descpath <- file.path(path, "DESCRIPTION") - if (!file.exists(descpath)) - return("unknown") - - desc <- tryCatch( - read.dcf(descpath, all = TRUE), - error = identity - ) - - if (inherits(desc, "error")) - return("unknown") - - type <- desc$Type - if (!is.null(type)) - return(tolower(type)) - - package <- desc$Package - if (!is.null(package)) - return("package") - - "unknown" - - } - - renv_bootstrap_user_dir <- function() { - dir <- renv_bootstrap_user_dir_impl() - path.expand(chartr("\\", "/", dir)) - } - - renv_bootstrap_user_dir_impl <- function() { - - # use local override if set - override <- getOption("renv.userdir.override") - if (!is.null(override)) - return(override) - - # use R_user_dir if available - tools <- asNamespace("tools") - if (is.function(tools$R_user_dir)) - return(tools$R_user_dir("renv", "cache")) - - # try using our own backfill for older versions of R - envvars <- c("R_USER_CACHE_DIR", "XDG_CACHE_HOME") - for (envvar in envvars) { - root <- Sys.getenv(envvar, unset = NA) - if (!is.na(root)) - return(file.path(root, "R/renv")) - } - - # use platform-specific default fallbacks - if (Sys.info()[["sysname"]] == "Windows") - file.path(Sys.getenv("LOCALAPPDATA"), "R/cache/R/renv") - else if (Sys.info()[["sysname"]] == "Darwin") - "~/Library/Caches/org.R-project.R/R/renv" - else - "~/.cache/R/renv" - - } - - renv_bootstrap_version_friendly <- function(version, shafmt = NULL, sha = NULL) { - sha <- sha %||% attr(version, "sha", exact = TRUE) - parts <- c(version, sprintf(shafmt %||% " [sha: %s]", substring(sha, 1L, 7L))) - paste(parts, collapse = "") - } - - renv_bootstrap_exec <- function(project, libpath, version) { - if (!renv_bootstrap_load(project, libpath, version)) - renv_bootstrap_run(version, libpath) - } - - renv_bootstrap_run <- function(version, libpath) { - - # perform bootstrap - bootstrap(version, libpath) - - # exit early if we're just testing bootstrap - if (!is.na(Sys.getenv("RENV_BOOTSTRAP_INSTALL_ONLY", unset = NA))) - return(TRUE) - - # try again to load - if (requireNamespace("renv", lib.loc = libpath, quietly = TRUE)) { - return(renv::load(project = getwd())) - } - - # failed to download or load renv; warn the user - msg <- c( - "Failed to find an renv installation: the project will not be loaded.", - "Use `renv::activate()` to re-initialize the project." - ) - - warning(paste(msg, collapse = "\n"), call. = FALSE) - - } - - renv_json_read <- function(file = NULL, text = NULL) { - - jlerr <- NULL - - # if jsonlite is loaded, use that instead - if ("jsonlite" %in% loadedNamespaces()) { - - json <- catch(renv_json_read_jsonlite(file, text)) - if (!inherits(json, "error")) - return(json) - - jlerr <- json - - } - - # otherwise, fall back to the default JSON reader - json <- catch(renv_json_read_default(file, text)) - if (!inherits(json, "error")) - return(json) - - # report an error - if (!is.null(jlerr)) - stop(jlerr) - else - stop(json) - - } - - renv_json_read_jsonlite <- function(file = NULL, text = NULL) { - text <- paste(text %||% read(file), collapse = "\n") - jsonlite::fromJSON(txt = text, simplifyVector = FALSE) - } - - renv_json_read_default <- function(file = NULL, text = NULL) { - - # find strings in the JSON - text <- paste(text %||% read(file), collapse = "\n") - pattern <- '["](?:(?:\\\\.)|(?:[^"\\\\]))*?["]' - locs <- gregexpr(pattern, text, perl = TRUE)[[1]] - - # if any are found, replace them with placeholders - replaced <- text - strings <- character() - replacements <- character() - - if (!identical(c(locs), -1L)) { - - # get the string values - starts <- locs - ends <- locs + attr(locs, "match.length") - 1L - strings <- substring(text, starts, ends) - - # only keep those requiring escaping - strings <- grep("[[\\]{}:]", strings, perl = TRUE, value = TRUE) - - # compute replacements - replacements <- sprintf('"\032%i\032"', seq_along(strings)) - - # replace the strings - mapply(function(string, replacement) { - replaced <<- sub(string, replacement, replaced, fixed = TRUE) - }, strings, replacements) - - } - - # transform the JSON into something the R parser understands - transformed <- replaced - transformed <- gsub("{}", "`names<-`(list(), character())", transformed, fixed = TRUE) - transformed <- gsub("[[{]", "list(", transformed, perl = TRUE) - transformed <- gsub("[]}]", ")", transformed, perl = TRUE) - transformed <- gsub(":", "=", transformed, fixed = TRUE) - text <- paste(transformed, collapse = "\n") - - # parse it - json <- parse(text = text, keep.source = FALSE, srcfile = NULL)[[1L]] - - # construct map between source strings, replaced strings - map <- as.character(parse(text = strings)) - names(map) <- as.character(parse(text = replacements)) - - # convert to list - map <- as.list(map) - - # remap strings in object - remapped <- renv_json_remap(json, map) - - # evaluate - eval(remapped, envir = baseenv()) - - } - - renv_json_remap <- function(json, map) { - - # fix names - if (!is.null(names(json))) { - lhs <- match(names(json), names(map), nomatch = 0L) - rhs <- match(names(map), names(json), nomatch = 0L) - names(json)[rhs] <- map[lhs] - } - - # fix values - if (is.character(json)) - return(map[[json]] %||% json) - - # handle true, false, null - if (is.name(json)) { - text <- as.character(json) - if (text == "true") - return(TRUE) - else if (text == "false") - return(FALSE) - else if (text == "null") - return(NULL) - } - - # recurse - if (is.recursive(json)) { - for (i in seq_along(json)) { - json[i] <- list(renv_json_remap(json[[i]], map)) - } - } - - json - - } - - # load the renv profile, if any - renv_bootstrap_profile_load(project) - - # construct path to library root - root <- renv_bootstrap_library_root(project) - - # construct library prefix for platform - prefix <- renv_bootstrap_platform_prefix() - - # construct full libpath - libpath <- file.path(root, prefix) - - # run bootstrap code - renv_bootstrap_exec(project, libpath, version) - - invisible() - -}) diff --git a/extras/TestModule1-0.0.1/renv/profiles/dev/renv.lock b/extras/TestModule1-0.0.1/renv/profiles/dev/renv.lock deleted file mode 100644 index aeb3539a..00000000 --- a/extras/TestModule1-0.0.1/renv/profiles/dev/renv.lock +++ /dev/null @@ -1,1093 +0,0 @@ -{ - "R": { - "Version": "4.2.3", - "Repositories": [ - { - "Name": "CRAN", - "URL": "https://packagemanager.posit.co/cran/latest" - } - ] - }, - "Packages": { - "CohortGenerator": { - "Package": "CohortGenerator", - "Version": "0.8.1", - "Source": "GitHub", - "RemoteType": "github", - "RemoteHost": "api.github.com", - "RemoteUsername": "OHDSI", - "RemoteRepo": "CohortGenerator", - "RemoteRef": "v0.8.1", - 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"R", - "Rcpp", - "methods", - "triebeard" - ], - "Hash": "e86a704261a105f4703f653e05defa3e" - }, - "utf8": { - "Package": "utf8", - "Version": "1.2.3", - "Source": "Repository", - "Repository": "CRAN", - "Requirements": [ - "R" - ], - "Hash": "1fe17157424bb09c48a8b3b550c753bc" - }, - "vctrs": { - "Package": "vctrs", - "Version": "0.6.3", - "Source": "Repository", - "Repository": "RSPM", - "Requirements": [ - "R", - "cli", - "glue", - "lifecycle", - "rlang" - ], - "Hash": "06eceb3a5d716fd0654cc23ca3d71a99" - }, - "vroom": { - "Package": "vroom", - "Version": "1.6.3", - "Source": "Repository", - "Repository": "CRAN", - "Requirements": [ - "R", - "bit64", - "cli", - "cpp11", - "crayon", - "glue", - "hms", - "lifecycle", - "methods", - "progress", - "rlang", - "stats", - "tibble", - "tidyselect", - "tzdb", - "vctrs", - "withr" - ], - "Hash": "7015a74373b83ffaef64023f4a0f5033" - }, - "waldo": { - "Package": "waldo", - "Version": "0.5.1", - "Source": "Repository", - "Repository": "CRAN", - "Requirements": [ - "cli", - "diffobj", - "fansi", - "glue", - "methods", - "rematch2", - "rlang", - "tibble" - ], - "Hash": "035fba89d0c86e2113120f93301b98ad" - }, - "withr": { - "Package": "withr", - "Version": "2.5.1", - "Source": "Repository", - "Repository": "CRAN", - "Requirements": [ - "R", - "grDevices", - "graphics", - "stats" - ], - "Hash": "c0e49a9760983e81e55cdd9be92e7182" - }, - "xml2": { - "Package": "xml2", - "Version": "1.3.5", - "Source": "Repository", - "Repository": "CRAN", - "Requirements": [ - "R", - "methods" - ], - "Hash": "40682ed6a969ea5abfd351eb67833adc" - }, - "yaml": { - "Package": "yaml", - "Version": "2.3.7", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "0d0056cc5383fbc240ccd0cb584bf436" - }, - "zip": { - "Package": "zip", - "Version": "2.3.0", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "d98c94dacb7e0efcf83b0a133a705504" - } - } -} diff --git a/extras/TestModule1-0.0.1/renv/profiles/dev/renv/.gitignore b/extras/TestModule1-0.0.1/renv/profiles/dev/renv/.gitignore deleted file mode 100644 index 0ec0cbba..00000000 --- a/extras/TestModule1-0.0.1/renv/profiles/dev/renv/.gitignore +++ /dev/null @@ -1,7 +0,0 @@ -library/ -local/ -cellar/ -lock/ -python/ -sandbox/ -staging/ diff --git a/extras/TestModule1-0.0.1/renv/profiles/dev/renv/settings.json b/extras/TestModule1-0.0.1/renv/profiles/dev/renv/settings.json deleted file mode 100644 index ffdbb320..00000000 --- a/extras/TestModule1-0.0.1/renv/profiles/dev/renv/settings.json +++ /dev/null @@ -1,19 +0,0 @@ -{ - "bioconductor.version": null, - "external.libraries": [], - "ignored.packages": [], - "package.dependency.fields": [ - "Imports", - "Depends", - "LinkingTo" - ], - "ppm.enabled": null, - "ppm.ignored.urls": [], - "r.version": null, - "snapshot.type": "implicit", - "use.cache": true, - "vcs.ignore.cellar": true, - "vcs.ignore.library": true, - "vcs.ignore.local": true, - "vcs.manage.ignores": true -} diff --git a/extras/TestModule1-0.0.1/renv/settings.json b/extras/TestModule1-0.0.1/renv/settings.json deleted file mode 100644 index ffdbb320..00000000 --- a/extras/TestModule1-0.0.1/renv/settings.json +++ /dev/null @@ -1,19 +0,0 @@ -{ - "bioconductor.version": null, - "external.libraries": [], - "ignored.packages": [], - "package.dependency.fields": [ - "Imports", - "Depends", - "LinkingTo" - ], - "ppm.enabled": null, - "ppm.ignored.urls": [], - "r.version": null, - "snapshot.type": "implicit", - "use.cache": true, - "vcs.ignore.cellar": true, - "vcs.ignore.library": true, - "vcs.ignore.local": true, - "vcs.manage.ignores": true -} diff --git a/extras/TestModule1-0.0.1/resultsDataModelSpecification.csv b/extras/TestModule1-0.0.1/resultsDataModelSpecification.csv deleted file mode 100644 index 38b8c8e3..00000000 --- a/extras/TestModule1-0.0.1/resultsDataModelSpecification.csv +++ /dev/null @@ -1,3 +0,0 @@ -table_name,column_name,data_type,is_required,primary_key,min_cell_count,description -unit_test,codeset_id,bigint,Yes,Yes,No,The codeset id -unit_test,concept_id,bigint,Yes,Yes,No,The concept id diff --git a/extras/TestModule1-0.0.1/tests/test-eunomia.R b/extras/TestModule1-0.0.1/tests/test-eunomia.R deleted file mode 100644 index 852af8ca..00000000 --- a/extras/TestModule1-0.0.1/tests/test-eunomia.R +++ /dev/null @@ -1,44 +0,0 @@ -# Use this profile when testing -#Sys.setenv(RENV_PROFILE = "dev") -#renv::restore(prompt = FALSE) -library(testthat) -library(Eunomia) -connectionDetails <- getEunomiaConnectionDetails() - -workFolder <- tempfile("work") -dir.create(workFolder) -resultsfolder <- tempfile("results") -dir.create(resultsfolder) -jobContext <- readRDS("tests/testJobContext.rds") -jobContext$moduleExecutionSettings$workSubFolder <- workFolder -jobContext$moduleExecutionSettings$resultsSubFolder <- resultsfolder -jobContext$moduleExecutionSettings$connectionDetails <- connectionDetails -jobContext$moduleExecutionSettings$resultsConnectionDetails <- connectionDetails -jobContext$moduleExecutionSettings$resultsDatabaseSchema <- jobContext$moduleExecutionSettings$workDatabaseSchema - -test_that("Test createDataModelSchema", { - source("Main.R") - createDataModelSchema(jobContext) - - # Verify that the table(s) are created - connection <- DatabaseConnector::connect( - connectionDetails = jobContext$moduleExecutionSettings$resultsConnectionDetails - ) - on.exit(DatabaseConnector::disconnect(connection)) - tableList <- DatabaseConnector::getTableNames( - connection = connection - ) - resultsTablesCreated <- tableList[grep(getModuleInfo()$TablePrefix, tableList)] - expect_true(length(resultsTablesCreated) > 0) -}) - -test_that("Run module", { - source("Main.R") - execute(jobContext) - resultsFiles <- list.files(resultsfolder) - expect_true("tm1_unit_test.csv" %in% resultsFiles) -}) - -unlink(workFolder) -unlink(resultsfolder) -unlink(connectionDetails$server()) diff --git a/extras/TestModule1-0.0.1/tests/testJobContext.rds b/extras/TestModule1-0.0.1/tests/testJobContext.rds deleted file mode 100644 index 0a515f82..00000000 Binary files a/extras/TestModule1-0.0.1/tests/testJobContext.rds and /dev/null differ diff --git a/extras/TestModule1-0.0.1/tests/testScript.R b/extras/TestModule1-0.0.1/tests/testScript.R deleted file mode 100644 index 02d8c189..00000000 --- a/extras/TestModule1-0.0.1/tests/testScript.R +++ /dev/null @@ -1,10 +0,0 @@ -library(testthat) - -testFiles <- list.files(file.path("tests"), "test-.*\\.R", full.names = TRUE) -for (testFile in testFiles) { - message(sprintf("*** Running tests in '%s' ***", testFile)) - source(testFile) -} - - -# Note: testthat default structure does not work for non-packages: https://github.com/r-lib/testthat/issues/1490 diff --git a/extras/ValidateModuleLockFiles.R b/extras/ValidateModuleLockFiles.R deleted file mode 100644 index f0033b2a..00000000 --- a/extras/ValidateModuleLockFiles.R +++ /dev/null @@ -1,24 +0,0 @@ -rootDir <- "C:/git/OHDSI" -moduleList <- c( - "Characterization", - "CohortDiagnostics", - "CohortGenerator", - "CohortIncidence", - "CohortMethod", - "EvidenceSynthesis", - "PatientLevelPrediction", - "SelfControlledCaseSeries" -) - -for (i in seq_along(moduleList)) { - repoPath <- file.path(rootDir, paste0(moduleList[i], "Module")) - if (dir.exists(repoPath)) { - cat("Checking ", repoPath, "\n") - cat(" -- Checking renv.lock file\n") - Strategus::validateLockFile(filename = file.path(repoPath, "renv.lock")) - cat(" -- Checking dev/renv.lock file\n") - Strategus::validateLockFile(filename = file.path(repoPath, "renv/profiles/dev/renv.lock")) - } else { - warning(paste0(repoPath, "NOT FOUND!!")) - } -} diff --git a/extras/rdms/SqlExtractor.java b/extras/rdms/SqlExtractor.java new file mode 100644 index 00000000..f92a8e70 --- /dev/null +++ b/extras/rdms/SqlExtractor.java @@ -0,0 +1,132 @@ +import java.io.*; +import java.nio.file.*; +import java.util.regex.*; +import java.util.List; +import java.util.ArrayList; + +public class SqlExtractor { + + // Method to scan a directory and process all .R files + public static void scanDirectory(String directoryPath, String outputCsvPath) { + try { + // Collect all .R files in the directory + List rFiles = getRFiles(directoryPath); + + // Create a list to store SQL extractions + List extractedData = new ArrayList<>(); + int totalSqlExcerpts = 0; + + // Process each R file + for (File file : rFiles) { + List sqlQueries = extractSqlFromFile(file); + extractedData.addAll(sqlQueries); + totalSqlExcerpts += sqlQueries.size(); + // Output the number of SQL queries found in each file + System.out.println(file.getName() + " - " + sqlQueries.size() + " SQL statements found"); + } + + // Write extracted SQL to CSV + writeCsv(outputCsvPath, extractedData); + + System.out.println("Extraction complete. Total SQL excerpts extracted: " + totalSqlExcerpts); + System.out.println("Results saved to: " + outputCsvPath); + } catch (IOException e) { + e.printStackTrace(); + } + } + + // Method to get all .R files from a directory + private static List getRFiles(String directoryPath) throws IOException { + List rFiles = new ArrayList<>(); + Files.walk(Paths.get(directoryPath)) + .filter(Files::isRegularFile) + .filter(path -> path.toString().endsWith(".R")) + .forEach(path -> rFiles.add(path.toFile())); + return rFiles; + } + + // Method to extract SQL queries from a file, including start and end line numbers + private static List extractSqlFromFile(File file) throws IOException { + List sqlQueries = new ArrayList<>(); + BufferedReader reader = new BufferedReader(new FileReader(file)); + String line; + boolean capturingSql = false; + StringBuilder sqlBuilder = new StringBuilder(); + char quoteChar = 0; // To store the opening quote character (' or ") + int lineNumber = 0; + int startLineNumber = 0; + + // Regex to detect the start of the SQL query: `sql <- "..."` or `sql <- '...'` + Pattern startPattern = Pattern.compile("sql\\s*<-\\s*(['\"])(.*)"); // Detects start with either single or double quotes + + while ((line = reader.readLine()) != null) { + lineNumber++; // Increment the line number for each line read + if (capturingSql) { + // Continue capturing until the matching quote character is found + int closingQuoteIndex = line.indexOf(quoteChar); + if (closingQuoteIndex != -1) { + sqlBuilder.append(line, 0, closingQuoteIndex); // Capture the SQL until the closing quote + sqlQueries.add(new String[]{ + "\"" + file.getName() + "\"", + "\"" + startLineNumber + "\"", + "\"" + lineNumber + "\"", + "\"" + sqlBuilder.toString().trim() + "\"" + }); // Save the captured SQL + capturingSql = false; // Stop capturing + } else { + sqlBuilder.append(line.trim()).append(" "); // Continue capturing across lines + } + } else { + // Check if the line contains the start of the SQL query + Matcher startMatcher = startPattern.matcher(line); + if (startMatcher.find()) { + quoteChar = startMatcher.group(1).charAt(0); // Capture the opening quote character (either ' or ") + sqlBuilder.setLength(0); // Clear the builder + sqlBuilder.append(startMatcher.group(2)); // Start capturing after the opening quote + startLineNumber = lineNumber; // Set the line number where SQL starts + + // Check if the SQL ends on the same line + int closingQuoteIndex = sqlBuilder.indexOf(Character.toString(quoteChar)); + if (closingQuoteIndex != -1) { + sqlQueries.add(new String[]{ + "\"" + file.getName() + "\"", + "\"" + startLineNumber + "\"", + "\"" + lineNumber + "\"", + "\"" + sqlBuilder.substring(0, closingQuoteIndex).trim() + "\"" + }); // Capture the SQL before the closing quote + capturingSql = false; + } else { + capturingSql = true; // SQL spans multiple lines + } + } + } + } + reader.close(); + return sqlQueries; + } + + // Method to write the extracted SQL queries to a CSV file with start and end line numbers + private static void writeCsv(String csvPath, List data) throws IOException { + FileWriter csvWriter = new FileWriter(csvPath); + // Update column headings to exactly match your request + csvWriter.append("\"fileName\",\"startLine\",\"endLine\",\"sqlQuery\"\n"); + + for (String[] row : data) { + csvWriter.append(String.join(",", row)).append("\n"); + } + csvWriter.flush(); + csvWriter.close(); + } + + public static void main(String[] args) { + if (args.length < 2) { + System.out.println("Usage: java SqlExtractor "); + return; + } + + String directoryPath = args[0]; + String outputCsvPath = args[1]; + + scanDirectory(directoryPath, outputCsvPath); + } +} diff --git a/extras/rdms/SqlJoinRelationshipExtractor.java b/extras/rdms/SqlJoinRelationshipExtractor.java new file mode 100644 index 00000000..48e28d6a --- /dev/null +++ b/extras/rdms/SqlJoinRelationshipExtractor.java @@ -0,0 +1,92 @@ +import java.io.*; +import java.util.*; +import java.util.regex.*; + +public class SqlJoinRelationshipExtractor { + + // Method to analyze SQL queries and extract the FROM and JOIN relationships, including multiple conditions (AND/OR) + public static void extractSqlJoins(String inputCsvFilePath, String outputCsvFilePath) { + try { + BufferedReader csvReader = new BufferedReader(new FileReader(inputCsvFilePath)); + FileWriter csvWriter = new FileWriter(outputCsvFilePath); + + String row; + boolean isFirstRow = true; + + // Write the header of the output CSV + csvWriter.append("fileName,startLine,endLine,fromClause,joinRelationship\n"); + + // Pattern to match FROM clause + Pattern fromPattern = Pattern.compile("from\\s+([\\w.@]+)\\s+([\\w@]+)", Pattern.CASE_INSENSITIVE); + // Pattern to match JOIN clauses, including AND/OR conditions + Pattern joinPattern = Pattern.compile("join\\s+([\\w.@]+)\\s+([\\w@]+)\\s+on\\s+(.+?)(?=\\s+join|\\s+where|;|$)", Pattern.CASE_INSENSITIVE); + + // Process each row of the CSV (from SqlExtractor) + while ((row = csvReader.readLine()) != null) { + if (isFirstRow) { + isFirstRow = false; // Skip the header + continue; + } + + // Split the row into columns (fileName, startLine, endLine, sqlQuery) + String[] columns = row.split(",(?=(?:[^\"]*\"[^\"]*\")*[^\"]*$)"); + if (columns.length < 4) continue; // Ensure row has the necessary columns + + String fileName = columns[0].replace("\"", ""); // Extract fileName + String startLine = columns[1].replace("\"", ""); // Extract startLine + String endLine = columns[2].replace("\"", ""); // Extract endLine + String sqlQuery = columns[3].replace("\"", ""); // Extract the SQL query + + // Capture the FROM clause + String fromClause = ""; + Matcher fromMatcher = fromPattern.matcher(sqlQuery); + if (fromMatcher.find()) { + fromClause = "FROM " + fromMatcher.group(1) + " " + fromMatcher.group(2); + } + + // Extract JOIN clauses including AND/OR conditions + Matcher joinMatcher = joinPattern.matcher(sqlQuery); + while (joinMatcher.find()) { + // Capture the full JOIN clause + String fullJoinClause = "JOIN " + joinMatcher.group(1) + " " + joinMatcher.group(2) + " ON " + joinMatcher.group(3).trim(); + + // Split the join conditions by AND/OR (but keep AND/OR in the condition for clarity) + String[] joinConditions = joinMatcher.group(3).split("(?<=\\))\\s+(AND|OR)\\s+"); + + // For each condition in the JOIN clause, create a new row + for (String condition : joinConditions) { + String joinRelationship = "JOIN " + joinMatcher.group(1) + " " + joinMatcher.group(2) + " ON " + condition.trim(); + + // Write fileName, startLine, endLine, fromClause, and each joinRelationship to the CSV + csvWriter.append(fileName).append(",") + .append(startLine).append(",") + .append(endLine).append(",") + .append("\"").append(fromClause).append("\",") + .append("\"").append(joinRelationship).append("\"\n"); + } + } + } + + csvReader.close(); + csvWriter.flush(); + csvWriter.close(); + + System.out.println("SQL FROM and JOIN relationships extraction complete. Results saved to: " + outputCsvFilePath); + + } catch (IOException e) { + e.printStackTrace(); + } + } + + public static void main(String[] args) { + if (args.length < 2) { + System.out.println("Usage: java SqlJoinRelationshipExtractor "); + return; + } + + String inputCsvFilePath = args[0]; + String outputCsvFilePath = args[1]; + + extractSqlJoins(inputCsvFilePath, outputCsvFilePath); + } +} diff --git a/extras/rdms/full_data_model_ohdsi.sql b/extras/rdms/full_data_model_ohdsi.sql new file mode 100644 index 00000000..f68efe65 --- /dev/null +++ b/extras/rdms/full_data_model_ohdsi.sql @@ -0,0 +1,1677 @@ +-- Strategus Tables +{DEFAULT @table_prefix = ''} +{DEFAULT @database_meta_data = database_meta_data} + +CREATE TABLE @database_schema.@table_prefix@database_meta_data ( + cdm_source_name VARCHAR, + cdm_source_abbreviation VARCHAR, + cdm_holder VARCHAR, + source_description VARCHAR, + source_documentation_reference VARCHAR, + cdm_etl_reference VARCHAR, + source_release_date DATE, + cdm_release_date DATE, + cdm_version VARCHAR, + cdm_version_concept_id INT, + vocabulary_version VARCHAR, + database_id VARCHAR NOT NULL, + max_obs_period_end_date DATE, + PRIMARY KEY(database_id) +); +-- CharacterizationModule Tables +{DEFAULT @table_prefix = ''} +{DEFAULT @c_time_to_event = c_time_to_event} +{DEFAULT @c_rechallenge_fail_case_series = c_rechallenge_fail_case_series} +{DEFAULT @c_dechallenge_rechallenge = c_dechallenge_rechallenge} +{DEFAULT @c_analysis_ref = c_analysis_ref} +{DEFAULT @c_covariate_ref = c_covariate_ref} +{DEFAULT @c_covariates = c_covariates} +{DEFAULT @c_covariates_continuous = c_covariates_continuous} +{DEFAULT @c_settings = c_settings} +{DEFAULT @c_cohort_details = c_cohort_details} +{DEFAULT @c_cohort_counts = c_cohort_counts} + +CREATE TABLE @database_schema.@table_prefix@c_time_to_event ( + database_id VARCHAR(100) NOT NULL, + target_cohort_definition_id BIGINT NOT NULL, + outcome_cohort_definition_id BIGINT NOT NULL, + outcome_type VARCHAR(100) NOT NULL, + target_outcome_type VARCHAR(40) NOT NULL, + time_to_event INT NOT NULL, + num_events INT, + time_scale VARCHAR(20) NOT NULL, + PRIMARY KEY(database_id,target_cohort_definition_id,outcome_cohort_definition_id,outcome_type,target_outcome_type,time_to_event,time_scale) +); + +CREATE TABLE @database_schema.@table_prefix@c_rechallenge_fail_case_series ( + database_id VARCHAR(100) NOT NULL, + dechallenge_stop_interval INT NOT NULL, + dechallenge_evaluation_window INT NOT NULL, + target_cohort_definition_id BIGINT NOT NULL, + outcome_cohort_definition_id BIGINT NOT NULL, + person_key INT NOT NULL, + subject_id BIGINT, + dechallenge_exposure_number INT, + dechallenge_exposure_start_date_offset INT, + dechallenge_exposure_end_date_offset INT, + dechallenge_outcome_number INT, + dechallenge_outcome_start_date_offset INT, + rechallenge_exposure_number INT, + rechallenge_exposure_start_date_offset INT, + rechallenge_exposure_end_date_offset INT, + rechallenge_outcome_number INT, + rechallenge_outcome_start_date_offset INT, + PRIMARY KEY(database_id,dechallenge_stop_interval,dechallenge_evaluation_window,target_cohort_definition_id,outcome_cohort_definition_id,person_key) +); + +CREATE TABLE @database_schema.@table_prefix@c_dechallenge_rechallenge ( + database_id VARCHAR(100) NOT NULL, + dechallenge_stop_interval INT NOT NULL, + dechallenge_evaluation_window INT NOT NULL, + target_cohort_definition_id BIGINT NOT NULL, + outcome_cohort_definition_id BIGINT NOT NULL, + num_exposure_eras INT, + num_persons_exposed INT, + num_cases INT, + dechallenge_attempt INT, + dechallenge_fail INT, + dechallenge_success INT, + rechallenge_attempt INT, + rechallenge_fail INT, + rechallenge_success INT, + pct_dechallenge_attempt FLOAT, + pct_dechallenge_success FLOAT, + pct_dechallenge_fail FLOAT, + pct_rechallenge_attempt FLOAT, + pct_rechallenge_success FLOAT, + pct_rechallenge_fail FLOAT, + PRIMARY KEY(database_id,dechallenge_stop_interval,dechallenge_evaluation_window,target_cohort_definition_id,outcome_cohort_definition_id) +); + +CREATE TABLE @database_schema.@table_prefix@c_analysis_ref ( + database_id VARCHAR(100) NOT NULL, + setting_id VARCHAR(30) NOT NULL, + analysis_id INT NOT NULL, + analysis_name VARCHAR, + domain_id VARCHAR, + start_day INT, + end_day INT, + is_binary VARCHAR(1), + missing_means_zero VARCHAR(1), + PRIMARY KEY(database_id,setting_id,analysis_id) +); + +CREATE TABLE @database_schema.@table_prefix@c_covariate_ref ( + database_id VARCHAR(100) NOT NULL, + setting_id VARCHAR(30) NOT NULL, + covariate_id BIGINT NOT NULL, + covariate_name VARCHAR, + analysis_id INT, + concept_id BIGINT, + value_as_concept_id INT, + collisions INT, + PRIMARY KEY(database_id,setting_id,covariate_id) +); + +CREATE TABLE @database_schema.@table_prefix@c_covariates ( + database_id VARCHAR(100) NOT NULL, + setting_id VARCHAR(30) NOT NULL, + cohort_type VARCHAR(12) NOT NULL, + target_cohort_id INT NOT NULL, + outcome_cohort_id INT NOT NULL, + min_characterization_mean FLOAT NOT NULL, + covariate_id BIGINT NOT NULL, + sum_value INT, + average_value FLOAT, + PRIMARY KEY(database_id,setting_id,cohort_type,target_cohort_id,outcome_cohort_id,min_characterization_mean,covariate_id) +); + +CREATE TABLE @database_schema.@table_prefix@c_covariates_continuous ( + database_id VARCHAR(100) NOT NULL, + setting_id VARCHAR(30) NOT NULL, + cohort_type VARCHAR(12) NOT NULL, + target_cohort_id INT NOT NULL, + outcome_cohort_id INT NOT NULL, + covariate_id BIGINT NOT NULL, + count_value INT, + min_value FLOAT, + max_value FLOAT, + average_value FLOAT, + standard_deviation FLOAT, + median_value FLOAT, + p_10_value FLOAT, + p_25_value FLOAT, + p_75_value FLOAT, + p_90_value FLOAT, + PRIMARY KEY(database_id,setting_id,cohort_type,target_cohort_id,outcome_cohort_id,covariate_id) +); + +CREATE TABLE @database_schema.@table_prefix@c_settings ( + setting_id VARCHAR(30) NOT NULL, + database_id VARCHAR(100) NOT NULL, + covariate_setting_json VARCHAR, + case_covariate_setting_json VARCHAR, + min_prior_observation INT, + outcome_washout_days INT, + risk_window_start INT, + risk_window_end INT, + start_anchor VARCHAR(15), + end_anchor VARCHAR(15), + case_pre_target_duration INT, + case_post_outcome_duration INT, + PRIMARY KEY(setting_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@c_cohort_details ( + database_id VARCHAR(100) NOT NULL, + setting_id VARCHAR(30) NOT NULL, + cohort_type VARCHAR(12) NOT NULL, + target_cohort_id INT NOT NULL, + outcome_cohort_id INT NOT NULL, + PRIMARY KEY(database_id,setting_id,cohort_type,target_cohort_id,outcome_cohort_id) +); + +CREATE TABLE @database_schema.@table_prefix@c_cohort_counts ( + database_id VARCHAR(100), + cohort_type VARCHAR(12), + target_cohort_id INT, + outcome_cohort_id INT, + risk_window_start INT, + risk_window_end INT, + start_anchor VARCHAR(15), + end_anchor VARCHAR(15), + min_prior_observation INT, + outcome_washout_days INT, + row_count INT, + person_count INT, + min_exposure_time BIGINT, + mean_exposure_time BIGINT, + max_exposure_time BIGINT +); +-- CohortDiagnosticsModule Tables +{DEFAULT @table_prefix = ''} +{DEFAULT @cd_cohort = cd_cohort} +{DEFAULT @cd_subset_definition = cd_subset_definition} +{DEFAULT @cd_cohort_count = cd_cohort_count} +{DEFAULT @cd_cohort_inclusion = cd_cohort_inclusion} +{DEFAULT @cd_cohort_inc_result = cd_cohort_inc_result} +{DEFAULT @cd_cohort_inc_stats = cd_cohort_inc_stats} +{DEFAULT @cd_cohort_relationships = cd_cohort_relationships} +{DEFAULT @cd_cohort_summary_stats = cd_cohort_summary_stats} +{DEFAULT @cd_concept = cd_concept} +{DEFAULT @cd_concept_ancestor = cd_concept_ancestor} +{DEFAULT @cd_concept_relationship = cd_concept_relationship} +{DEFAULT @cd_concept_sets = cd_concept_sets} +{DEFAULT @cd_concept_synonym = cd_concept_synonym} +{DEFAULT @cd_database = cd_database} +{DEFAULT @cd_domain = cd_domain} +{DEFAULT @cd_incidence_rate = cd_incidence_rate} +{DEFAULT @cd_included_source_concept = cd_included_source_concept} +{DEFAULT @cd_index_event_breakdown = cd_index_event_breakdown} +{DEFAULT @cd_metadata = cd_metadata} +{DEFAULT @cd_orphan_concept = cd_orphan_concept} +{DEFAULT @cd_relationship = cd_relationship} +{DEFAULT @cd_resolved_concepts = cd_resolved_concepts} +{DEFAULT @cd_temporal_analysis_ref = cd_temporal_analysis_ref} +{DEFAULT @cd_temporal_covariate_ref = cd_temporal_covariate_ref} +{DEFAULT @cd_temporal_covariate_value = cd_temporal_covariate_value} +{DEFAULT @cd_temporal_covariate_value_dist = cd_temporal_covariate_value_dist} +{DEFAULT @cd_temporal_time_ref = cd_temporal_time_ref} +{DEFAULT @cd_time_series = cd_time_series} +{DEFAULT @cd_visit_context = cd_visit_context} +{DEFAULT @cd_vocabulary = cd_vocabulary} + +CREATE TABLE @database_schema.@table_prefix@cd_cohort ( + cohort_id BIGINT NOT NULL, + cohort_name VARCHAR, + metadata VARCHAR, + json VARCHAR, + sql VARCHAR, + subset_parent BIGINT, + subset_definition_id BIGINT, + is_subset INT, + PRIMARY KEY(cohort_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_subset_definition ( + subset_definition_id BIGINT NOT NULL, + json VARCHAR NOT NULL, + PRIMARY KEY(subset_definition_id,json) +); + +CREATE TABLE @database_schema.@table_prefix@cd_cohort_count ( + cohort_id BIGINT NOT NULL, + cohort_entries FLOAT, + cohort_subjects FLOAT, + database_id VARCHAR NOT NULL, + PRIMARY KEY(cohort_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_cohort_inclusion ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + rule_sequence BIGINT NOT NULL, + name VARCHAR, + description VARCHAR, + PRIMARY KEY(database_id,cohort_id,rule_sequence) +); + +CREATE TABLE @database_schema.@table_prefix@cd_cohort_inc_result ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + mode_id BIGINT NOT NULL, + inclusion_rule_mask BIGINT NOT NULL, + person_count FLOAT, + PRIMARY KEY(database_id,cohort_id,mode_id,inclusion_rule_mask) +); + +CREATE TABLE @database_schema.@table_prefix@cd_cohort_inc_stats ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + rule_sequence BIGINT NOT NULL, + mode_id BIGINT NOT NULL, + person_count FLOAT, + gain_count FLOAT, + person_total FLOAT, + PRIMARY KEY(database_id,cohort_id,rule_sequence,mode_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_cohort_relationships ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + comparator_cohort_id BIGINT NOT NULL, + start_day BIGINT NOT NULL, + end_day FLOAT NOT NULL, + subjects BIGINT, + sub_cs_before_ts BIGINT, + sub_cs_on_ts BIGINT, + sub_cs_after_ts BIGINT, + sub_cs_before_te BIGINT, + sub_cs_on_te BIGINT, + sub_cs_after_te BIGINT, + sub_cs_window_t BIGINT, + sub_ce_window_t BIGINT, + sub_cs_window_ts BIGINT, + sub_cs_window_te BIGINT, + sub_ce_window_ts BIGINT, + sub_ce_window_te BIGINT, + sub_c_within_t BIGINT, + c_days_before_ts BIGINT, + c_days_before_te BIGINT, + c_days_within_t_days BIGINT, + c_days_after_ts BIGINT, + c_days_after_te BIGINT, + t_days BIGINT, + c_days BIGINT, + PRIMARY KEY(database_id,cohort_id,comparator_cohort_id,start_day,end_day) +); + +CREATE TABLE @database_schema.@table_prefix@cd_cohort_summary_stats ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + mode_id BIGINT NOT NULL, + base_count FLOAT, + final_count FLOAT, + PRIMARY KEY(database_id,cohort_id,mode_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_concept ( + concept_id BIGINT NOT NULL, + concept_name VARCHAR(255), + domain_id VARCHAR(20), + vocabulary_id VARCHAR(50), + concept_class_id VARCHAR(20), + standard_concept VARCHAR(1), + concept_code VARCHAR(255), + valid_start_date DATE, + valid_end_date DATE, + invalid_reason VARCHAR, + PRIMARY KEY(concept_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_concept_ancestor ( + ancestor_concept_id BIGINT NOT NULL, + descendant_concept_id BIGINT NOT NULL, + min_levels_of_separation INT, + max_levels_of_separation INT, + PRIMARY KEY(ancestor_concept_id,descendant_concept_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_concept_relationship ( + concept_id_1 BIGINT NOT NULL, + concept_id_2 BIGINT NOT NULL, + relationship_id VARCHAR(20) NOT NULL, + valid_start_date DATE, + valid_end_date DATE, + invalid_reason VARCHAR(1), + PRIMARY KEY(concept_id_1,concept_id_2,relationship_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_concept_sets ( + cohort_id BIGINT NOT NULL, + concept_set_id INT NOT NULL, + concept_set_sql VARCHAR, + concept_set_name VARCHAR(255), + concept_set_expression VARCHAR, + PRIMARY KEY(cohort_id,concept_set_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_concept_synonym ( + concept_id BIGINT NOT NULL, + concept_synonym_name VARCHAR NOT NULL, + language_concept_id BIGINT NOT NULL, + PRIMARY KEY(concept_id,concept_synonym_name,language_concept_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_database ( + database_id VARCHAR NOT NULL, + database_name VARCHAR, + description VARCHAR, + is_meta_analysis VARCHAR(1), + vocabulary_version VARCHAR, + vocabulary_version_cdm VARCHAR, + PRIMARY KEY(database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_domain ( + domain_id VARCHAR(20) NOT NULL, + domain_name VARCHAR(255), + domain_concept_id BIGINT, + PRIMARY KEY(domain_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_incidence_rate ( + cohort_count FLOAT, + person_years FLOAT, + gender VARCHAR NOT NULL, + age_group VARCHAR NOT NULL, + calendar_year VARCHAR(4) NOT NULL, + incidence_rate FLOAT, + cohort_id BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + PRIMARY KEY(gender,age_group,calendar_year,cohort_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_included_source_concept ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + concept_set_id INT NOT NULL, + concept_id BIGINT NOT NULL, + source_concept_id BIGINT NOT NULL, + concept_subjects FLOAT, + concept_count FLOAT, + PRIMARY KEY(database_id,cohort_id,concept_set_id,concept_id,source_concept_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_index_event_breakdown ( + concept_id BIGINT NOT NULL, + concept_count FLOAT, + subject_count FLOAT, + cohort_id BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + domain_field VARCHAR NOT NULL, + domain_table VARCHAR NOT NULL, + PRIMARY KEY(concept_id,cohort_id,database_id,domain_field,domain_table) +); + +CREATE TABLE @database_schema.@table_prefix@cd_metadata ( + database_id VARCHAR NOT NULL, + start_time VARCHAR NOT NULL, + variable_field VARCHAR NOT NULL, + value_field VARCHAR, + PRIMARY KEY(database_id,start_time,variable_field) +); + +CREATE TABLE @database_schema.@table_prefix@cd_orphan_concept ( + cohort_id BIGINT NOT NULL, + concept_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + concept_id BIGINT NOT NULL, + concept_count FLOAT, + concept_subjects FLOAT, + PRIMARY KEY(cohort_id,concept_set_id,database_id,concept_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_relationship ( + relationship_id VARCHAR(20) NOT NULL, + relationship_name VARCHAR(255), + is_hierarchical VARCHAR(1), + defines_ancestry VARCHAR(1), + reverse_relationship_id VARCHAR(20) NOT NULL, + relationship_concept_id BIGINT NOT NULL, + PRIMARY KEY(relationship_id,reverse_relationship_id,relationship_concept_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_resolved_concepts ( + cohort_id BIGINT NOT NULL, + concept_set_id INT NOT NULL, + concept_id BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + PRIMARY KEY(cohort_id,concept_set_id,concept_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_temporal_analysis_ref ( + analysis_id INT NOT NULL, + analysis_name VARCHAR, + domain_id VARCHAR(20) NOT NULL, + is_binary VARCHAR(1), + missing_means_zero VARCHAR(1), + PRIMARY KEY(analysis_id,domain_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_temporal_covariate_ref ( + covariate_id BIGINT NOT NULL, + covariate_name VARCHAR, + analysis_id INT, + concept_id BIGINT, + PRIMARY KEY(covariate_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_temporal_covariate_value ( + cohort_id BIGINT NOT NULL, + time_id INT NOT NULL, + covariate_id BIGINT NOT NULL, + sum_value FLOAT, + mean FLOAT, + sd FLOAT, + database_id VARCHAR NOT NULL, + PRIMARY KEY(cohort_id,time_id,covariate_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_temporal_covariate_value_dist ( + cohort_id BIGINT NOT NULL, + time_id INT NOT NULL, + covariate_id BIGINT NOT NULL, + count_value FLOAT, + min_value FLOAT, + max_value FLOAT, + mean FLOAT, + sd FLOAT, + median_value FLOAT, + p_10_value FLOAT, + p_25_value FLOAT, + p_75_value FLOAT, + p_90_value FLOAT, + database_id VARCHAR NOT NULL, + PRIMARY KEY(cohort_id,time_id,covariate_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_temporal_time_ref ( + time_id INT NOT NULL, + start_day FLOAT, + end_day FLOAT, + PRIMARY KEY(time_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_time_series ( + cohort_id BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + period_begin DATE NOT NULL, + period_end DATE NOT NULL, + series_type VARCHAR NOT NULL, + calendar_interval VARCHAR NOT NULL, + gender VARCHAR NOT NULL, + age_group VARCHAR NOT NULL, + records BIGINT, + subjects BIGINT, + person_days BIGINT, + person_days_in BIGINT, + records_start BIGINT, + subjects_start BIGINT, + subjects_start_in BIGINT, + records_end BIGINT, + subjects_end BIGINT, + subjects_end_in BIGINT, + PRIMARY KEY(cohort_id,database_id,period_begin,period_end,series_type,calendar_interval,gender,age_group) +); + +CREATE TABLE @database_schema.@table_prefix@cd_visit_context ( + cohort_id BIGINT NOT NULL, + visit_concept_id BIGINT NOT NULL, + visit_context VARCHAR NOT NULL, + subjects FLOAT, + database_id VARCHAR NOT NULL, + PRIMARY KEY(cohort_id,visit_concept_id,visit_context,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cd_vocabulary ( + vocabulary_id VARCHAR(50), + vocabulary_name VARCHAR(255), + vocabulary_reference VARCHAR, + vocabulary_version VARCHAR, + vocabulary_concept_id BIGINT +); +-- CohortGeneratorModule Tables +{DEFAULT @table_prefix = ''} +{DEFAULT @cg_cohort_definition = cg_cohort_definition} +{DEFAULT @cg_cohort_generation = cg_cohort_generation} +{DEFAULT @cg_cohort_inclusion = cg_cohort_inclusion} +{DEFAULT @cg_cohort_inc_result = cg_cohort_inc_result} +{DEFAULT @cg_cohort_inc_stats = cg_cohort_inc_stats} +{DEFAULT @cg_cohort_summary_stats = cg_cohort_summary_stats} +{DEFAULT @cg_cohort_censor_stats = cg_cohort_censor_stats} +{DEFAULT @cg_cohort_count = cg_cohort_count} +{DEFAULT @cg_cohort_count_neg_ctrl = cg_cohort_count_neg_ctrl} +{DEFAULT @cg_cohort_subset_definition = cg_cohort_subset_definition} +{DEFAULT @cg_cohort_definition_neg_ctrl = cg_cohort_definition_neg_ctrl} + +CREATE TABLE @database_schema.@table_prefix@cg_cohort_definition ( + cohort_definition_id BIGINT NOT NULL, + cohort_name VARCHAR, + description VARCHAR, + json TEXT, + sql_command TEXT, + subset_parent BIGINT, + is_subset INT, + subset_definition_id BIGINT, + PRIMARY KEY(cohort_definition_id) +); + +CREATE TABLE @database_schema.@table_prefix@cg_cohort_generation ( + cohort_id BIGINT NOT NULL, + cohort_name VARCHAR, + generation_status VARCHAR, + start_time TIMESTAMP, + end_time TIMESTAMP, + database_id VARCHAR NOT NULL, + PRIMARY KEY(cohort_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cg_cohort_inclusion ( + cohort_definition_id BIGINT NOT NULL, + rule_sequence INT NOT NULL, + name VARCHAR NOT NULL, + description VARCHAR, + PRIMARY KEY(cohort_definition_id,rule_sequence,name) +); + +CREATE TABLE @database_schema.@table_prefix@cg_cohort_inc_result ( + database_id VARCHAR NOT NULL, + cohort_definition_id BIGINT NOT NULL, + inclusion_rule_mask INT NOT NULL, + person_count BIGINT NOT NULL, + mode_id INT NOT NULL, + PRIMARY KEY(database_id,cohort_definition_id,inclusion_rule_mask,person_count,mode_id) +); + +CREATE TABLE @database_schema.@table_prefix@cg_cohort_inc_stats ( + database_id VARCHAR NOT NULL, + cohort_definition_id BIGINT NOT NULL, + rule_sequence INT NOT NULL, + person_count BIGINT NOT NULL, + gain_count BIGINT NOT NULL, + person_total BIGINT NOT NULL, + mode_id INT NOT NULL, + PRIMARY KEY(database_id,cohort_definition_id,rule_sequence,person_count,gain_count,person_total,mode_id) +); + +CREATE TABLE @database_schema.@table_prefix@cg_cohort_summary_stats ( + database_id VARCHAR NOT NULL, + cohort_definition_id BIGINT NOT NULL, + base_count BIGINT NOT NULL, + final_count BIGINT NOT NULL, + mode_id INT NOT NULL, + PRIMARY KEY(database_id,cohort_definition_id,base_count,final_count,mode_id) +); + +CREATE TABLE @database_schema.@table_prefix@cg_cohort_censor_stats ( + cohort_definition_id BIGINT NOT NULL, + lost_count BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + PRIMARY KEY(cohort_definition_id,lost_count,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cg_cohort_count ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + cohort_entries BIGINT NOT NULL, + cohort_subjects BIGINT NOT NULL, + PRIMARY KEY(database_id,cohort_id,cohort_entries,cohort_subjects) +); + +CREATE TABLE @database_schema.@table_prefix@cg_cohort_count_neg_ctrl ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + cohort_entries BIGINT NOT NULL, + cohort_subjects BIGINT NOT NULL, + PRIMARY KEY(database_id,cohort_id,cohort_entries,cohort_subjects) +); + +CREATE TABLE @database_schema.@table_prefix@cg_cohort_subset_definition ( + subset_definition_id BIGINT NOT NULL, + json TEXT, + PRIMARY KEY(subset_definition_id) +); + +CREATE TABLE @database_schema.@table_prefix@cg_cohort_definition_neg_ctrl ( + cohort_id BIGINT NOT NULL, + outcome_concept_id BIGINT, + cohort_name VARCHAR, + occurrence_type VARCHAR, + detect_on_descendants INT, + PRIMARY KEY(cohort_id) +); +-- CohortIncidenceModule Tables +{DEFAULT @table_prefix = ''} +{DEFAULT @ci_incidence_summary = ci_incidence_summary} +{DEFAULT @ci_target_def = ci_target_def} +{DEFAULT @ci_outcome_def = ci_outcome_def} +{DEFAULT @ci_tar_def = ci_tar_def} +{DEFAULT @ci_age_group_def = ci_age_group_def} +{DEFAULT @ci_subgroup_def = ci_subgroup_def} +{DEFAULT @ci_target_outcome_ref = ci_target_outcome_ref} + +CREATE TABLE @database_schema.@table_prefix@ci_incidence_summary ( + ref_id INT, + database_id VARCHAR(255), + source_name VARCHAR(255), + target_cohort_definition_id BIGINT, + tar_id BIGINT, + subgroup_id BIGINT, + outcome_id BIGINT, + age_group_id INT, + gender_id INT, + gender_name VARCHAR(255), + start_year INT, + persons_at_risk_pe BIGINT, + persons_at_risk BIGINT, + person_days_pe BIGINT, + person_days BIGINT, + person_outcomes_pe BIGINT, + person_outcomes BIGINT, + outcomes_pe BIGINT, + outcomes BIGINT, + incidence_proportion_p100p FLOAT, + incidence_rate_p100py FLOAT +); + +CREATE TABLE @database_schema.@table_prefix@ci_target_def ( + ref_id INT NOT NULL, + target_cohort_definition_id BIGINT NOT NULL, + target_name VARCHAR(255), + PRIMARY KEY(ref_id,target_cohort_definition_id) +); + +CREATE TABLE @database_schema.@table_prefix@ci_outcome_def ( + ref_id INT NOT NULL, + outcome_id BIGINT NOT NULL, + outcome_cohort_definition_id BIGINT, + outcome_name VARCHAR(255), + clean_window BIGINT, + excluded_cohort_definition_id BIGINT, + PRIMARY KEY(ref_id,outcome_id) +); + +CREATE TABLE @database_schema.@table_prefix@ci_tar_def ( + ref_id INT NOT NULL, + tar_id BIGINT NOT NULL, + tar_start_with VARCHAR(10), + tar_start_offset BIGINT, + tar_end_with VARCHAR(10), + tar_end_offset BIGINT, + PRIMARY KEY(ref_id,tar_id) +); + +CREATE TABLE @database_schema.@table_prefix@ci_age_group_def ( + ref_id INT NOT NULL, + age_group_id INT NOT NULL, + age_group_name VARCHAR(255), + min_age INT, + max_age INT, + PRIMARY KEY(ref_id,age_group_id) +); + +CREATE TABLE @database_schema.@table_prefix@ci_subgroup_def ( + ref_id INT NOT NULL, + subgroup_id BIGINT NOT NULL, + subgroup_name VARCHAR(255), + PRIMARY KEY(ref_id,subgroup_id) +); + +CREATE TABLE @database_schema.@table_prefix@ci_target_outcome_ref ( + ref_id INT NOT NULL, + target_cohort_id BIGINT NOT NULL, + outcome_cohort_id BIGINT NOT NULL, + PRIMARY KEY(ref_id,target_cohort_id,outcome_cohort_id) +); +-- CohortMethodModule Tables +{DEFAULT @table_prefix = ''} +{DEFAULT @cm_attrition = cm_attrition} +{DEFAULT @cm_follow_up_dist = cm_follow_up_dist} +{DEFAULT @cm_analysis = cm_analysis} +{DEFAULT @cm_result = cm_result} +{DEFAULT @cm_interaction_result = cm_interaction_result} +{DEFAULT @cm_covariate = cm_covariate} +{DEFAULT @cm_covariate_analysis = cm_covariate_analysis} +{DEFAULT @cm_covariate_balance = cm_covariate_balance} +{DEFAULT @cm_diagnostics_summary = cm_diagnostics_summary} +{DEFAULT @cm_target_comparator_outcome = cm_target_comparator_outcome} +{DEFAULT @cm_kaplan_meier_dist = cm_kaplan_meier_dist} +{DEFAULT @cm_likelihood_profile = cm_likelihood_profile} +{DEFAULT @cm_preference_score_dist = cm_preference_score_dist} +{DEFAULT @cm_propensity_model = cm_propensity_model} +{DEFAULT @cm_shared_covariate_balance = cm_shared_covariate_balance} + +CREATE TABLE @database_schema.@table_prefix@cm_attrition ( + sequence_number INT NOT NULL, + description VARCHAR, + subjects INT, + exposure_id BIGINT NOT NULL, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + analysis_id INT NOT NULL, + outcome_id BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + PRIMARY KEY(sequence_number,exposure_id,target_id,comparator_id,analysis_id,outcome_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cm_follow_up_dist ( + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + outcome_id BIGINT NOT NULL, + analysis_id INT NOT NULL, + target_min_days FLOAT, + target_p_10_days FLOAT, + target_p_25_days FLOAT, + target_median_days FLOAT, + target_p_75_days FLOAT, + target_p_90_days FLOAT, + target_max_days FLOAT, + comparator_min_days FLOAT, + comparator_p_10_days FLOAT, + comparator_p_25_days FLOAT, + comparator_median_days FLOAT, + comparator_p_75_days FLOAT, + comparator_p_90_days FLOAT, + comparator_max_days FLOAT, + target_min_date DATE, + target_max_date DATE, + comparator_min_date DATE, + comparator_max_date DATE, + database_id VARCHAR NOT NULL, + PRIMARY KEY(target_id,comparator_id,outcome_id,analysis_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cm_analysis ( + analysis_id INT NOT NULL, + description VARCHAR, + definition VARCHAR, + PRIMARY KEY(analysis_id) +); + +CREATE TABLE @database_schema.@table_prefix@cm_result ( + analysis_id INT NOT NULL, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + outcome_id BIGINT NOT NULL, + rr FLOAT, + ci_95_lb FLOAT, + ci_95_ub FLOAT, + p FLOAT, + one_sided_p FLOAT, + target_subjects INT, + comparator_subjects INT, + target_days INT, + comparator_days INT, + target_outcomes INT, + comparator_outcomes INT, + log_rr FLOAT, + se_log_rr FLOAT, + llr FLOAT, + calibrated_rr FLOAT, + calibrated_ci_95_lb FLOAT, + calibrated_ci_95_ub FLOAT, + calibrated_p FLOAT, + calibrated_one_sided_p FLOAT, + calibrated_log_rr FLOAT, + calibrated_se_log_rr FLOAT, + target_estimator VARCHAR, + database_id VARCHAR NOT NULL, + PRIMARY KEY(analysis_id,target_id,comparator_id,outcome_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cm_interaction_result ( + analysis_id INT NOT NULL, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + outcome_id BIGINT NOT NULL, + interaction_covariate_id INT NOT NULL, + rr FLOAT, + ci_95_lb FLOAT, + ci_95_ub FLOAT, + p FLOAT, + target_subjects INT, + comparator_subjects INT, + target_days INT, + comparator_days INT, + target_outcomes INT, + comparator_outcomes INT, + log_rr FLOAT, + se_log_rr FLOAT, + calibrated_rr FLOAT, + calibrated_ci_95_lb FLOAT, + calibrated_ci_95_ub FLOAT, + calibrated_p FLOAT, + calibrated_log_rr FLOAT, + calibrated_se_log_rr FLOAT, + target_estimator VARCHAR, + database_id VARCHAR NOT NULL, + PRIMARY KEY(analysis_id,target_id,comparator_id,outcome_id,interaction_covariate_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cm_covariate ( + covariate_id BIGINT NOT NULL, + covariate_name VARCHAR, + analysis_id INT NOT NULL, + covariate_analysis_id INT, + database_id VARCHAR NOT NULL, + PRIMARY KEY(covariate_id,analysis_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cm_covariate_analysis ( + covariate_analysis_id INT NOT NULL, + covariate_analysis_name VARCHAR, + analysis_id INT NOT NULL, + PRIMARY KEY(covariate_analysis_id,analysis_id) +); + +CREATE TABLE @database_schema.@table_prefix@cm_covariate_balance ( + database_id VARCHAR NOT NULL, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + outcome_id BIGINT NOT NULL, + analysis_id INT NOT NULL, + covariate_id BIGINT NOT NULL, + target_mean_before FLOAT, + comparator_mean_before FLOAT, + mean_before FLOAT, + std_diff_before FLOAT, + mean_after FLOAT, + target_mean_after FLOAT, + comparator_mean_after FLOAT, + std_diff_after FLOAT, + target_std_diff FLOAT, + comparator_std_diff FLOAT, + target_comparator_std_diff FLOAT, + PRIMARY KEY(database_id,target_id,comparator_id,outcome_id,analysis_id,covariate_id) +); + +CREATE TABLE @database_schema.@table_prefix@cm_diagnostics_summary ( + analysis_id INT NOT NULL, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + outcome_id BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + max_sdm FLOAT, + shared_max_sdm FLOAT, + equipoise FLOAT, + mdrr FLOAT, + attrition_fraction FLOAT, + generalizability_max_sdm FLOAT, + ease FLOAT, + balance_diagnostic VARCHAR(20), + shared_balance_diagnostic VARCHAR(20), + equipoise_diagnostic VARCHAR(20), + mdrr_diagnostic VARCHAR(20), + attrition_diagnostic VARCHAR(20), + generalizability_diagnostic VARCHAR(20), + ease_diagnostic VARCHAR(20), + unblind INT, + unblind_for_evidence_synthesis INT, + PRIMARY KEY(analysis_id,target_id,comparator_id,outcome_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cm_target_comparator_outcome ( + outcome_id BIGINT NOT NULL, + outcome_of_interest INT, + true_effect_size FLOAT, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + PRIMARY KEY(outcome_id,target_id,comparator_id) +); + +CREATE TABLE @database_schema.@table_prefix@cm_kaplan_meier_dist ( + time_day INT NOT NULL, + target_survival FLOAT, + target_survival_lb FLOAT, + target_survival_ub FLOAT, + comparator_survival FLOAT, + comparator_survival_lb FLOAT, + comparator_survival_ub FLOAT, + target_at_risk INT, + comparator_at_risk INT, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + outcome_id BIGINT NOT NULL, + analysis_id INT NOT NULL, + database_id VARCHAR NOT NULL, + PRIMARY KEY(time_day,target_id,comparator_id,outcome_id,analysis_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cm_likelihood_profile ( + log_rr FLOAT NOT NULL, + log_likelihood FLOAT, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + outcome_id BIGINT NOT NULL, + analysis_id INT NOT NULL, + database_id VARCHAR NOT NULL, + PRIMARY KEY(log_rr,target_id,comparator_id,outcome_id,analysis_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@cm_preference_score_dist ( + analysis_id INT NOT NULL, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + preference_score FLOAT NOT NULL, + target_density FLOAT, + comparator_density FLOAT, + PRIMARY KEY(analysis_id,target_id,comparator_id,database_id,preference_score) +); + +CREATE TABLE @database_schema.@table_prefix@cm_propensity_model ( + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + analysis_id INT NOT NULL, + database_id VARCHAR NOT NULL, + covariate_id BIGINT NOT NULL, + coefficient FLOAT, + PRIMARY KEY(target_id,comparator_id,analysis_id,database_id,covariate_id) +); + +CREATE TABLE @database_schema.@table_prefix@cm_shared_covariate_balance ( + database_id VARCHAR NOT NULL, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + analysis_id INT NOT NULL, + covariate_id BIGINT NOT NULL, + mean_before FLOAT, + target_mean_before FLOAT, + comparator_mean_before FLOAT, + std_diff_before FLOAT, + mean_after FLOAT, + target_mean_after FLOAT, + comparator_mean_after FLOAT, + std_diff_after FLOAT, + target_std_diff FLOAT, + comparator_std_diff FLOAT, + target_comparator_std_diff FLOAT, + PRIMARY KEY(database_id,target_id,comparator_id,analysis_id,covariate_id) +); +-- EvidenceSynthesisModule Tables +{DEFAULT @table_prefix = ''} +{DEFAULT @es_analysis = es_analysis} +{DEFAULT @es_cm_diagnostics_summary = es_cm_diagnostics_summary} +{DEFAULT @es_cm_result = es_cm_result} +{DEFAULT @es_sccs_diagnostics_summary = es_sccs_diagnostics_summary} +{DEFAULT @es_sccs_result = es_sccs_result} + +CREATE TABLE @database_schema.@table_prefix@es_analysis ( + evidence_synthesis_analysis_id INT NOT NULL, + evidence_synthesis_description VARCHAR(255), + source_method VARCHAR(100), + definition VARCHAR, + PRIMARY KEY(evidence_synthesis_analysis_id) +); + +CREATE TABLE @database_schema.@table_prefix@es_cm_diagnostics_summary ( + target_id INT NOT NULL, + comparator_id INT NOT NULL, + outcome_id INT NOT NULL, + analysis_id INT NOT NULL, + evidence_synthesis_analysis_id INT NOT NULL, + mdrr FLOAT, + i_2 FLOAT, + tau FLOAT, + ease FLOAT, + mdrr_diagnostic VARCHAR(13), + i_2_diagnostic VARCHAR(13), + tau_diagnostic VARCHAR(13), + ease_diagnostic VARCHAR(13), + unblind INT, + PRIMARY KEY(target_id,comparator_id,outcome_id,analysis_id,evidence_synthesis_analysis_id) +); + +CREATE TABLE @database_schema.@table_prefix@es_cm_result ( + target_id INT NOT NULL, + comparator_id INT NOT NULL, + outcome_id INT NOT NULL, + analysis_id INT NOT NULL, + evidence_synthesis_analysis_id INT NOT NULL, + rr FLOAT, + ci_95_lb FLOAT, + ci_95_ub FLOAT, + p FLOAT, + one_sided_p FLOAT, + log_rr FLOAT, + se_log_rr FLOAT, + target_subjects INT, + comparator_subjects INT, + target_days INT, + comparator_days INT, + target_outcomes INT, + comparator_outcomes INT, + n_databases INT, + calibrated_rr FLOAT, + calibrated_ci_95_lb FLOAT, + calibrated_ci_95_ub FLOAT, + calibrated_p FLOAT, + calibrated_one_sided_p FLOAT, + calibrated_log_rr FLOAT, + calibrated_se_log_rr FLOAT, + PRIMARY KEY(target_id,comparator_id,outcome_id,analysis_id,evidence_synthesis_analysis_id) +); + +CREATE TABLE @database_schema.@table_prefix@es_sccs_diagnostics_summary ( + exposures_outcome_set_id INT NOT NULL, + covariate_id INT NOT NULL, + analysis_id INT NOT NULL, + evidence_synthesis_analysis_id INT NOT NULL, + mdrr FLOAT, + i_2 FLOAT, + tau FLOAT, + ease FLOAT, + mdrr_diagnostic VARCHAR(13), + i_2_diagnostic VARCHAR(13), + tau_diagnostic VARCHAR(13), + ease_diagnostic VARCHAR(13), + unblind INT, + PRIMARY KEY(exposures_outcome_set_id,covariate_id,analysis_id,evidence_synthesis_analysis_id) +); + +CREATE TABLE @database_schema.@table_prefix@es_sccs_result ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + covariate_id INT NOT NULL, + evidence_synthesis_analysis_id INT NOT NULL, + rr FLOAT, + ci_95_lb FLOAT, + ci_95_ub FLOAT, + p FLOAT, + one_sided_p FLOAT, + outcome_subjects INT, + outcome_events INT, + outcome_observation_periods INT, + covariate_subjects INT, + covariate_days INT, + covariate_eras INT, + covariate_outcomes INT, + observed_days INT, + n_databases INT, + log_rr FLOAT, + se_log_rr FLOAT, + calibrated_rr FLOAT, + calibrated_ci_95_lb FLOAT, + calibrated_ci_95_ub FLOAT, + calibrated_p FLOAT, + calibrated_one_sided_p FLOAT, + calibrated_log_rr FLOAT, + calibrated_se_log_rr FLOAT, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,covariate_id,evidence_synthesis_analysis_id) +); +-- PatientLevelPredictionModule Tables +{DEFAULT @table_prefix = ''} +{DEFAULT @plp_cohorts = plp_cohorts} +{DEFAULT @plp_cohort_definition = plp_cohort_definition} +{DEFAULT @plp_database_meta_data = plp_database_meta_data} +{DEFAULT @plp_database_details = plp_database_details} +{DEFAULT @plp_tars = plp_tars} +{DEFAULT @plp_population_settings = plp_population_settings} +{DEFAULT @plp_covariate_settings = plp_covariate_settings} +{DEFAULT @plp_model_settings = plp_model_settings} +{DEFAULT @plp_split_settings = plp_split_settings} +{DEFAULT @plp_plp_data_settings = plp_plp_data_settings} +{DEFAULT @plp_feature_engineering_settings = plp_feature_engineering_settings} +{DEFAULT @plp_tidy_covariates_settings = plp_tidy_covariates_settings} +{DEFAULT @plp_sample_settings = plp_sample_settings} +{DEFAULT @plp_model_designs = plp_model_designs} +{DEFAULT @plp_diagnostics = plp_diagnostics} +{DEFAULT @plp_diagnostic_summary = plp_diagnostic_summary} +{DEFAULT @plp_diagnostic_predictors = plp_diagnostic_predictors} +{DEFAULT @plp_diagnostic_participants = plp_diagnostic_participants} +{DEFAULT @plp_diagnostic_outcomes = plp_diagnostic_outcomes} +{DEFAULT @plp_diagnostic_designs = plp_diagnostic_designs} +{DEFAULT @plp_models = plp_models} +{DEFAULT @plp_recalibrations = plp_recalibrations} +{DEFAULT @plp_performances = plp_performances} +{DEFAULT @plp_attrition = plp_attrition} +{DEFAULT @plp_prediction_distribution = plp_prediction_distribution} +{DEFAULT @plp_covariate_summary = plp_covariate_summary} +{DEFAULT @plp_threshold_summary = plp_threshold_summary} +{DEFAULT @plp_calibration_summary = plp_calibration_summary} +{DEFAULT @plp_evaluation_statistics = plp_evaluation_statistics} +{DEFAULT @plp_demographic_summary = plp_demographic_summary} + +CREATE TABLE @database_schema.@table_prefix@plp_cohorts ( + cohort_id INT NOT NULL, + cohort_definition_id BIGINT, + cohort_name VARCHAR, + PRIMARY KEY(cohort_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_cohort_definition ( + cohort_definition_id BIGINT, + cohort_name VARCHAR, + description TEXT, + json TEXT, + sql_command TEXT +); + +CREATE TABLE @database_schema.@table_prefix@plp_database_meta_data ( + database_id VARCHAR NOT NULL, + cdm_source_name VARCHAR, + cdm_source_abbreviation VARCHAR, + cdm_holder VARCHAR, + source_description TEXT, + source_documentation_reference VARCHAR, + cdm_etl_reference VARCHAR, + source_release_date VARCHAR, + cdm_release_date VARCHAR, + cdm_version VARCHAR, + vocabulary_version VARCHAR, + max_obs_period_end_date VARCHAR, + PRIMARY KEY(database_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_database_details ( + database_id INT NOT NULL, + database_meta_data_id VARCHAR, + PRIMARY KEY(database_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_tars ( + tar_id INT NOT NULL, + tar_start_day INT, + tar_start_anchor VARCHAR, + tar_end_day INT, + tar_end_anchor VARCHAR, + PRIMARY KEY(tar_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_population_settings ( + population_setting_id INT NOT NULL, + population_settings_json TEXT, + PRIMARY KEY(population_setting_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_covariate_settings ( + covariate_setting_id INT NOT NULL, + covariate_settings_json TEXT, + PRIMARY KEY(covariate_setting_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_model_settings ( + model_setting_id INT NOT NULL, + model_type VARCHAR, + model_settings_json VARCHAR, + PRIMARY KEY(model_setting_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_split_settings ( + split_setting_id INT NOT NULL, + split_settings_json TEXT, + PRIMARY KEY(split_setting_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_plp_data_settings ( + plp_data_setting_id INT NOT NULL, + plp_data_settings_json TEXT, + PRIMARY KEY(plp_data_setting_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_feature_engineering_settings ( + feature_engineering_setting_id INT NOT NULL, + feature_engineering_settings_json TEXT, + PRIMARY KEY(feature_engineering_setting_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_tidy_covariates_settings ( + tidy_covariates_setting_id INT NOT NULL, + tidy_covariates_settings_json TEXT, + PRIMARY KEY(tidy_covariates_setting_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_sample_settings ( + sample_setting_id INT NOT NULL, + sample_settings_json TEXT, + PRIMARY KEY(sample_setting_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_model_designs ( + model_design_id INT NOT NULL, + target_id INT, + outcome_id INT, + tar_id INT, + plp_data_setting_id INT, + population_setting_id INT, + model_setting_id INT, + covariate_setting_id INT, + sample_setting_id INT, + split_setting_id INT, + feature_engineering_setting_id INT, + tidy_covariates_setting_id INT, + PRIMARY KEY(model_design_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_diagnostics ( + diagnostic_id INT NOT NULL, + model_design_id INT, + database_id INT, + execution_date_time VARCHAR, + PRIMARY KEY(diagnostic_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_diagnostic_summary ( + diagnostic_id INT, + probast_id VARCHAR, + result_value VARCHAR +); + +CREATE TABLE @database_schema.@table_prefix@plp_diagnostic_predictors ( + diagnostic_id INT, + days_to_event INT, + outcome_at_time INT, + observed_at_start_of_day BIGINT, + input_type VARCHAR +); + +CREATE TABLE @database_schema.@table_prefix@plp_diagnostic_participants ( + diagnostic_id INT, + design VARCHAR, + metric VARCHAR, + value FLOAT, + probast_id VARCHAR +); + +CREATE TABLE @database_schema.@table_prefix@plp_diagnostic_outcomes ( + diagnostic_id INT, + xvalue INT, + outcome_percent FLOAT, + aggregation VARCHAR, + probast_id VARCHAR, + input_type VARCHAR +); + +CREATE TABLE @database_schema.@table_prefix@plp_diagnostic_designs ( + diagnostic_id INT NOT NULL, + probast_id VARCHAR, + value VARCHAR, + PRIMARY KEY(diagnostic_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_models ( + model_id INT NOT NULL, + analysis_id VARCHAR, + model_design_id INT, + database_id INT, + model_type VARCHAR, + plp_model_file TEXT, + train_details TEXT, + preprocessing TEXT, + execution_date_time VARCHAR, + training_time VARCHAR, + intercept FLOAT, + PRIMARY KEY(model_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_recalibrations ( + recalibration_id INT NOT NULL, + original_model_id INT, + recalibrated_model_id INT, + recalibration_type VARCHAR, + recalibration_json VARCHAR, + PRIMARY KEY(recalibration_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_performances ( + performance_id INT NOT NULL, + model_design_id INT, + development_database_id INT, + validation_database_id INT, + target_id INT, + outcome_id INT, + tar_id INT, + plp_data_setting_id INT, + population_setting_id INT, + model_development INT, + execution_date_time VARCHAR, + plp_version VARCHAR, + PRIMARY KEY(performance_id) +); + +CREATE TABLE @database_schema.@table_prefix@plp_attrition ( + performance_id INT, + outcome_id INT, + description VARCHAR, + target_count INT, + unique_people INT, + outcomes INT +); + +CREATE TABLE @database_schema.@table_prefix@plp_prediction_distribution ( + performance_id INT, + evaluation VARCHAR, + class_label INT, + person_count INT, + average_predicted_probability FLOAT, + st_dev_predicted_probability FLOAT, + min_predicted_probability FLOAT, + p_05_predicted_probability FLOAT, + p_25_predicted_probability FLOAT, + median_predicted_probability FLOAT, + p_75_predicted_probability FLOAT, + p_95_predicted_probability FLOAT, + max_predicted_probability FLOAT +); + +CREATE TABLE @database_schema.@table_prefix@plp_covariate_summary ( + performance_id INT, + covariate_id BIGINT, + covariate_name VARCHAR, + concept_id FLOAT, + covariate_value FLOAT, + covariate_count INT, + covariate_mean FLOAT, + covariate_st_dev FLOAT, + with_no_outcome_covariate_count INT, + with_no_outcome_covariate_mean FLOAT, + with_no_outcome_covariate_st_dev FLOAT, + with_outcome_covariate_count INT, + with_outcome_covariate_mean FLOAT, + with_outcome_covariate_st_dev FLOAT, + standardized_mean_diff FLOAT +); + +CREATE TABLE @database_schema.@table_prefix@plp_threshold_summary ( + performance_id INT, + evaluation VARCHAR, + prediction_threshold FLOAT, + preference_threshold FLOAT, + positive_count INT, + negative_count INT, + true_count INT, + false_count INT, + true_positive_count INT, + true_negative_count INT, + false_positive_count INT, + false_negative_count INT, + f_1_score FLOAT, + accuracy FLOAT, + sensitivity FLOAT, + false_negative_rate FLOAT, + false_positive_rate FLOAT, + specificity FLOAT, + positive_predictive_value FLOAT, + false_discovery_rate FLOAT, + negative_predictive_value FLOAT, + false_omission_rate FLOAT, + positive_likelihood_ratio FLOAT, + negative_likelihood_ratio FLOAT, + diagnostic_odds_ratio FLOAT +); + +CREATE TABLE @database_schema.@table_prefix@plp_calibration_summary ( + performance_id INT, + evaluation VARCHAR, + prediction_threshold FLOAT, + person_count_at_risk INT, + person_count_with_outcome INT, + average_predicted_probability FLOAT, + st_dev_predicted_probability FLOAT, + min_predicted_probability FLOAT, + p_25_predicted_probability FLOAT, + median_predicted_probability FLOAT, + p_75_predicted_probability FLOAT, + max_predicted_probability FLOAT, + observed_incidence FLOAT +); + +CREATE TABLE @database_schema.@table_prefix@plp_evaluation_statistics ( + performance_id INT, + evaluation VARCHAR, + metric VARCHAR, + value FLOAT +); + +CREATE TABLE @database_schema.@table_prefix@plp_demographic_summary ( + performance_id INT, + evaluation VARCHAR, + age_group VARCHAR, + gen_group VARCHAR, + person_count_at_risk INT, + person_count_with_outcome INT, + average_predicted_probability FLOAT, + st_dev_predicted_probability FLOAT, + min_predicted_probability FLOAT, + p_25_predicted_probability FLOAT, + p_50_predicted_probability FLOAT, + p_75_predicted_probability FLOAT, + max_predicted_probability FLOAT +); +-- SelfControlledCaseSeriesModule Tables +{DEFAULT @table_prefix = ''} +{DEFAULT @sccs_analysis = sccs_analysis} +{DEFAULT @sccs_covariate_analysis = sccs_covariate_analysis} +{DEFAULT @sccs_covariate = sccs_covariate} +{DEFAULT @sccs_era = sccs_era} +{DEFAULT @sccs_exposures_outcome_set = sccs_exposures_outcome_set} +{DEFAULT @sccs_exposure = sccs_exposure} +{DEFAULT @sccs_spline = sccs_spline} +{DEFAULT @sccs_censor_model = sccs_censor_model} +{DEFAULT @sccs_result = sccs_result} +{DEFAULT @sccs_covariate_result = sccs_covariate_result} +{DEFAULT @sccs_attrition = sccs_attrition} +{DEFAULT @sccs_likelihood_profile = sccs_likelihood_profile} +{DEFAULT @sccs_time_trend = sccs_time_trend} +{DEFAULT @sccs_time_to_event = sccs_time_to_event} +{DEFAULT @sccs_age_spanning = sccs_age_spanning} +{DEFAULT @sccs_calendar_time_spanning = sccs_calendar_time_spanning} +{DEFAULT @sccs_event_dep_observation = sccs_event_dep_observation} +{DEFAULT @sccs_diagnostics_summary = sccs_diagnostics_summary} + +CREATE TABLE @database_schema.@table_prefix@sccs_analysis ( + analysis_id INT NOT NULL, + description VARCHAR, + definition VARCHAR, + PRIMARY KEY(analysis_id) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_covariate_analysis ( + analysis_id INT NOT NULL, + covariate_analysis_id INT NOT NULL, + covariate_analysis_name VARCHAR, + variable_of_interest INT, + PRIMARY KEY(analysis_id,covariate_analysis_id) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_covariate ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + covariate_id INT NOT NULL, + covariate_name VARCHAR, + era_id INT, + covariate_analysis_id INT, + database_id VARCHAR NOT NULL, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,covariate_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_era ( + exposures_outcome_set_id INT NOT NULL, + analysis_id INT NOT NULL, + era_type VARCHAR NOT NULL, + era_id INT NOT NULL, + era_name VARCHAR, + database_id VARCHAR NOT NULL, + PRIMARY KEY(exposures_outcome_set_id,analysis_id,era_type,era_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_exposures_outcome_set ( + exposures_outcome_set_id INT NOT NULL, + outcome_id INT, + nesting_cohort_id INT, + PRIMARY KEY(exposures_outcome_set_id) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_exposure ( + exposures_outcome_set_id INT NOT NULL, + era_id INT NOT NULL, + true_effect_size FLOAT, + PRIMARY KEY(exposures_outcome_set_id,era_id) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_spline ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + spline_type VARCHAR NOT NULL, + knot_month FLOAT NOT NULL, + rr FLOAT, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,spline_type,knot_month) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_censor_model ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + parameter_id INT NOT NULL, + parameter_value FLOAT, + model_type VARCHAR, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,parameter_id) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_result ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + covariate_id INT NOT NULL, + rr FLOAT, + ci_95_lb FLOAT, + ci_95_ub FLOAT, + p FLOAT, + one_sided_p FLOAT, + outcome_subjects INT, + outcome_events INT, + outcome_observation_periods INT, + covariate_subjects INT, + covariate_days INT, + covariate_eras INT, + covariate_outcomes INT, + observed_days BIGINT, + log_rr FLOAT, + se_log_rr FLOAT, + llr FLOAT, + calibrated_rr FLOAT, + calibrated_ci_95_lb FLOAT, + calibrated_ci_95_ub FLOAT, + calibrated_p FLOAT, + calibrated_one_sided_p FLOAT, + calibrated_log_rr FLOAT, + calibrated_se_log_rr FLOAT, + database_id VARCHAR NOT NULL, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,covariate_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_covariate_result ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + covariate_id INT NOT NULL, + rr FLOAT, + ci_95_lb FLOAT, + ci_95_ub FLOAT, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,covariate_id) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_attrition ( + sequence_number INT NOT NULL, + description VARCHAR, + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + covariate_id INT NOT NULL, + database_id VARCHAR NOT NULL, + outcome_subjects INT, + outcome_events INT, + outcome_observation_periods INT, + observed_days BIGINT, + PRIMARY KEY(sequence_number,analysis_id,exposures_outcome_set_id,covariate_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_likelihood_profile ( + log_rr FLOAT NOT NULL, + log_likelihood FLOAT, + covariate_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + analysis_id INT NOT NULL, + database_id VARCHAR NOT NULL, + PRIMARY KEY(log_rr,covariate_id,exposures_outcome_set_id,analysis_id,database_id) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_time_trend ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + calendar_year INT NOT NULL, + calendar_month INT NOT NULL, + observed_subjects INT, + ratio FLOAT, + adjusted_ratio FLOAT, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,calendar_year,calendar_month) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_time_to_event ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + era_id INT NOT NULL, + week INT NOT NULL, + observed_subjects INT, + outcomes INT, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,era_id,week) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_age_spanning ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + age_month INT NOT NULL, + cover_before_after_subjects INT, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,age_month) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_calendar_time_spanning ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + calendar_year INT NOT NULL, + calendar_month INT NOT NULL, + cover_before_after_subjects INT, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,calendar_year,calendar_month) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_event_dep_observation ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + months_to_end INT NOT NULL, + censored INT NOT NULL, + outcomes INT, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,months_to_end,censored) +); + +CREATE TABLE @database_schema.@table_prefix@sccs_diagnostics_summary ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + covariate_id INT NOT NULL, + database_id VARCHAR NOT NULL, + mdrr FLOAT, + ease FLOAT, + time_trend_p FLOAT, + pre_exposure_p FLOAT, + mdrr_diagnostic VARCHAR(20), + ease_diagnostic VARCHAR(20), + time_trend_diagnostic VARCHAR(20), + pre_exposure_diagnostic VARCHAR(20), + unblind INT, + unblind_for_evidence_synthesis INT, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,covariate_id,database_id) +); diff --git a/extras/rdms/full_data_model_pg.sql b/extras/rdms/full_data_model_pg.sql new file mode 100644 index 00000000..1f5df959 --- /dev/null +++ b/extras/rdms/full_data_model_pg.sql @@ -0,0 +1,1414 @@ +-- Strategus Tables +CREATE TABLE results.database_meta_data ( + cdm_source_name VARCHAR, + cdm_source_abbreviation VARCHAR, + cdm_holder VARCHAR, + source_description VARCHAR, + source_documentation_reference VARCHAR, + cdm_etl_reference VARCHAR, + source_release_date DATE, + cdm_release_date DATE, + cdm_version VARCHAR, + cdm_version_concept_id INT, + vocabulary_version VARCHAR, + database_id VARCHAR NOT NULL, + max_obs_period_end_date DATE, + PRIMARY KEY(database_id) +); +-- CharacterizationModule Tables +CREATE TABLE results.c_time_to_event ( + database_id VARCHAR(100) NOT NULL, + target_cohort_definition_id BIGINT NOT NULL, + outcome_cohort_definition_id BIGINT NOT NULL, + outcome_type VARCHAR(100) NOT NULL, + target_outcome_type VARCHAR(40) NOT NULL, + time_to_event INT NOT NULL, + num_events INT, + time_scale VARCHAR(20) NOT NULL, + PRIMARY KEY(database_id,target_cohort_definition_id,outcome_cohort_definition_id,outcome_type,target_outcome_type,time_to_event,time_scale) +); +CREATE TABLE results.c_rechallenge_fail_case_series ( + database_id VARCHAR(100) NOT NULL, + dechallenge_stop_interval INT NOT NULL, + dechallenge_evaluation_window INT NOT NULL, + target_cohort_definition_id BIGINT NOT NULL, + outcome_cohort_definition_id BIGINT NOT NULL, + person_key INT NOT NULL, + subject_id BIGINT, + dechallenge_exposure_number INT, + dechallenge_exposure_start_date_offset INT, + dechallenge_exposure_end_date_offset INT, + dechallenge_outcome_number INT, + dechallenge_outcome_start_date_offset INT, + rechallenge_exposure_number INT, + rechallenge_exposure_start_date_offset INT, + rechallenge_exposure_end_date_offset INT, + rechallenge_outcome_number INT, + rechallenge_outcome_start_date_offset INT, + PRIMARY KEY(database_id,dechallenge_stop_interval,dechallenge_evaluation_window,target_cohort_definition_id,outcome_cohort_definition_id,person_key) +); +CREATE TABLE results.c_dechallenge_rechallenge ( + database_id VARCHAR(100) NOT NULL, + dechallenge_stop_interval INT NOT NULL, + dechallenge_evaluation_window INT NOT NULL, + target_cohort_definition_id BIGINT NOT NULL, + outcome_cohort_definition_id BIGINT NOT NULL, + num_exposure_eras INT, + num_persons_exposed INT, + num_cases INT, + dechallenge_attempt INT, + dechallenge_fail INT, + dechallenge_success INT, + rechallenge_attempt INT, + rechallenge_fail INT, + rechallenge_success INT, + pct_dechallenge_attempt NUMERIC, + pct_dechallenge_success NUMERIC, + pct_dechallenge_fail NUMERIC, + pct_rechallenge_attempt NUMERIC, + pct_rechallenge_success NUMERIC, + pct_rechallenge_fail NUMERIC, + PRIMARY KEY(database_id,dechallenge_stop_interval,dechallenge_evaluation_window,target_cohort_definition_id,outcome_cohort_definition_id) +); +CREATE TABLE results.c_analysis_ref ( + database_id VARCHAR(100) NOT NULL, + setting_id VARCHAR(30) NOT NULL, + analysis_id INT NOT NULL, + analysis_name VARCHAR, + domain_id VARCHAR, + start_day INT, + end_day INT, + is_binary VARCHAR(1), + missing_means_zero VARCHAR(1), + PRIMARY KEY(database_id,setting_id,analysis_id) +); +CREATE TABLE results.c_covariate_ref ( + database_id VARCHAR(100) NOT NULL, + setting_id VARCHAR(30) NOT NULL, + covariate_id BIGINT NOT NULL, + covariate_name VARCHAR, + analysis_id INT, + concept_id BIGINT, + value_as_concept_id INT, + collisions INT, + PRIMARY KEY(database_id,setting_id,covariate_id) +); +CREATE TABLE results.c_covariates ( + database_id VARCHAR(100) NOT NULL, + setting_id VARCHAR(30) NOT NULL, + cohort_type VARCHAR(12) NOT NULL, + target_cohort_id INT NOT NULL, + outcome_cohort_id INT NOT NULL, + min_characterization_mean NUMERIC NOT NULL, + covariate_id BIGINT NOT NULL, + sum_value INT, + average_value NUMERIC, + PRIMARY KEY(database_id,setting_id,cohort_type,target_cohort_id,outcome_cohort_id,min_characterization_mean,covariate_id) +); +CREATE TABLE results.c_covariates_continuous ( + database_id VARCHAR(100) NOT NULL, + setting_id VARCHAR(30) NOT NULL, + cohort_type VARCHAR(12) NOT NULL, + target_cohort_id INT NOT NULL, + outcome_cohort_id INT NOT NULL, + covariate_id BIGINT NOT NULL, + count_value INT, + min_value NUMERIC, + max_value NUMERIC, + average_value NUMERIC, + standard_deviation NUMERIC, + median_value NUMERIC, + p_10_value NUMERIC, + p_25_value NUMERIC, + p_75_value NUMERIC, + p_90_value NUMERIC, + PRIMARY KEY(database_id,setting_id,cohort_type,target_cohort_id,outcome_cohort_id,covariate_id) +); +CREATE TABLE results.c_settings ( + setting_id VARCHAR(30) NOT NULL, + database_id VARCHAR(100) NOT NULL, + covariate_setting_json VARCHAR, + case_covariate_setting_json VARCHAR, + min_prior_observation INT, + outcome_washout_days INT, + risk_window_start INT, + risk_window_end INT, + start_anchor VARCHAR(15), + end_anchor VARCHAR(15), + case_pre_target_duration INT, + case_post_outcome_duration INT, + PRIMARY KEY(setting_id,database_id) +); +CREATE TABLE results.c_cohort_details ( + database_id VARCHAR(100) NOT NULL, + setting_id VARCHAR(30) NOT NULL, + cohort_type VARCHAR(12) NOT NULL, + target_cohort_id INT NOT NULL, + outcome_cohort_id INT NOT NULL, + PRIMARY KEY(database_id,setting_id,cohort_type,target_cohort_id,outcome_cohort_id) +); +CREATE TABLE results.c_cohort_counts ( + database_id VARCHAR(100), + cohort_type VARCHAR(12), + target_cohort_id INT, + outcome_cohort_id INT, + risk_window_start INT, + risk_window_end INT, + start_anchor VARCHAR(15), + end_anchor VARCHAR(15), + min_prior_observation INT, + outcome_washout_days INT, + row_count INT, + person_count INT, + min_exposure_time BIGINT, + mean_exposure_time BIGINT, + max_exposure_time BIGINT +); +-- CohortDiagnosticsModule Tables +CREATE TABLE results.cd_cohort ( + cohort_id BIGINT NOT NULL, + cohort_name VARCHAR, + metadata VARCHAR, + json VARCHAR, + sql VARCHAR, + subset_parent BIGINT, + subset_definition_id BIGINT, + is_subset INT, + PRIMARY KEY(cohort_id) +); +CREATE TABLE results.cd_subset_definition ( + subset_definition_id BIGINT NOT NULL, + json VARCHAR NOT NULL, + PRIMARY KEY(subset_definition_id,json) +); +CREATE TABLE results.cd_cohort_count ( + cohort_id BIGINT NOT NULL, + cohort_entries NUMERIC, + cohort_subjects NUMERIC, + database_id VARCHAR NOT NULL, + PRIMARY KEY(cohort_id,database_id) +); +CREATE TABLE results.cd_cohort_inclusion ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + rule_sequence BIGINT NOT NULL, + name VARCHAR, + description VARCHAR, + PRIMARY KEY(database_id,cohort_id,rule_sequence) +); +CREATE TABLE results.cd_cohort_inc_result ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + mode_id BIGINT NOT NULL, + inclusion_rule_mask BIGINT NOT NULL, + person_count NUMERIC, + PRIMARY KEY(database_id,cohort_id,mode_id,inclusion_rule_mask) +); +CREATE TABLE results.cd_cohort_inc_stats ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + rule_sequence BIGINT NOT NULL, + mode_id BIGINT NOT NULL, + person_count NUMERIC, + gain_count NUMERIC, + person_total NUMERIC, + PRIMARY KEY(database_id,cohort_id,rule_sequence,mode_id) +); +CREATE TABLE results.cd_cohort_relationships ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + comparator_cohort_id BIGINT NOT NULL, + start_day BIGINT NOT NULL, + end_day NUMERIC NOT NULL, + subjects BIGINT, + sub_cs_before_ts BIGINT, + sub_cs_on_ts BIGINT, + sub_cs_after_ts BIGINT, + sub_cs_before_te BIGINT, + sub_cs_on_te BIGINT, + sub_cs_after_te BIGINT, + sub_cs_window_t BIGINT, + sub_ce_window_t BIGINT, + sub_cs_window_ts BIGINT, + sub_cs_window_te BIGINT, + sub_ce_window_ts BIGINT, + sub_ce_window_te BIGINT, + sub_c_within_t BIGINT, + c_days_before_ts BIGINT, + c_days_before_te BIGINT, + c_days_within_t_days BIGINT, + c_days_after_ts BIGINT, + c_days_after_te BIGINT, + t_days BIGINT, + c_days BIGINT, + PRIMARY KEY(database_id,cohort_id,comparator_cohort_id,start_day,end_day) +); +CREATE TABLE results.cd_cohort_summary_stats ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + mode_id BIGINT NOT NULL, + base_count NUMERIC, + final_count NUMERIC, + PRIMARY KEY(database_id,cohort_id,mode_id) +); +CREATE TABLE results.cd_concept ( + concept_id BIGINT NOT NULL, + concept_name VARCHAR(255), + domain_id VARCHAR(20), + vocabulary_id VARCHAR(50), + concept_class_id VARCHAR(20), + standard_concept VARCHAR(1), + concept_code VARCHAR(255), + valid_start_date DATE, + valid_end_date DATE, + invalid_reason VARCHAR, + PRIMARY KEY(concept_id) +); +CREATE TABLE results.cd_concept_ancestor ( + ancestor_concept_id BIGINT NOT NULL, + descendant_concept_id BIGINT NOT NULL, + min_levels_of_separation INT, + max_levels_of_separation INT, + PRIMARY KEY(ancestor_concept_id,descendant_concept_id) +); +CREATE TABLE results.cd_concept_relationship ( + concept_id_1 BIGINT NOT NULL, + concept_id_2 BIGINT NOT NULL, + relationship_id VARCHAR(20) NOT NULL, + valid_start_date DATE, + valid_end_date DATE, + invalid_reason VARCHAR(1), + PRIMARY KEY(concept_id_1,concept_id_2,relationship_id) +); +CREATE TABLE results.cd_concept_sets ( + cohort_id BIGINT NOT NULL, + concept_set_id INT NOT NULL, + concept_set_sql VARCHAR, + concept_set_name VARCHAR(255), + concept_set_expression VARCHAR, + PRIMARY KEY(cohort_id,concept_set_id) +); +CREATE TABLE results.cd_concept_synonym ( + concept_id BIGINT NOT NULL, + concept_synonym_name VARCHAR NOT NULL, + language_concept_id BIGINT NOT NULL, + PRIMARY KEY(concept_id,concept_synonym_name,language_concept_id) +); +CREATE TABLE results.cd_database ( + database_id VARCHAR NOT NULL, + database_name VARCHAR, + description VARCHAR, + is_meta_analysis VARCHAR(1), + vocabulary_version VARCHAR, + vocabulary_version_cdm VARCHAR, + PRIMARY KEY(database_id) +); +CREATE TABLE results.cd_domain ( + domain_id VARCHAR(20) NOT NULL, + domain_name VARCHAR(255), + domain_concept_id BIGINT, + PRIMARY KEY(domain_id) +); +CREATE TABLE results.cd_incidence_rate ( + cohort_count NUMERIC, + person_years NUMERIC, + gender VARCHAR NOT NULL, + age_group VARCHAR NOT NULL, + calendar_year VARCHAR(4) NOT NULL, + incidence_rate NUMERIC, + cohort_id BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + PRIMARY KEY(gender,age_group,calendar_year,cohort_id,database_id) +); +CREATE TABLE results.cd_included_source_concept ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + concept_set_id INT NOT NULL, + concept_id BIGINT NOT NULL, + source_concept_id BIGINT NOT NULL, + concept_subjects NUMERIC, + concept_count NUMERIC, + PRIMARY KEY(database_id,cohort_id,concept_set_id,concept_id,source_concept_id) +); +CREATE TABLE results.cd_index_event_breakdown ( + concept_id BIGINT NOT NULL, + concept_count NUMERIC, + subject_count NUMERIC, + cohort_id BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + domain_field VARCHAR NOT NULL, + domain_table VARCHAR NOT NULL, + PRIMARY KEY(concept_id,cohort_id,database_id,domain_field,domain_table) +); +CREATE TABLE results.cd_metadata ( + database_id VARCHAR NOT NULL, + start_time VARCHAR NOT NULL, + variable_field VARCHAR NOT NULL, + value_field VARCHAR, + PRIMARY KEY(database_id,start_time,variable_field) +); +CREATE TABLE results.cd_orphan_concept ( + cohort_id BIGINT NOT NULL, + concept_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + concept_id BIGINT NOT NULL, + concept_count NUMERIC, + concept_subjects NUMERIC, + PRIMARY KEY(cohort_id,concept_set_id,database_id,concept_id) +); +CREATE TABLE results.cd_relationship ( + relationship_id VARCHAR(20) NOT NULL, + relationship_name VARCHAR(255), + is_hierarchical VARCHAR(1), + defines_ancestry VARCHAR(1), + reverse_relationship_id VARCHAR(20) NOT NULL, + relationship_concept_id BIGINT NOT NULL, + PRIMARY KEY(relationship_id,reverse_relationship_id,relationship_concept_id) +); +CREATE TABLE results.cd_resolved_concepts ( + cohort_id BIGINT NOT NULL, + concept_set_id INT NOT NULL, + concept_id BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + PRIMARY KEY(cohort_id,concept_set_id,concept_id,database_id) +); +CREATE TABLE results.cd_temporal_analysis_ref ( + analysis_id INT NOT NULL, + analysis_name VARCHAR, + domain_id VARCHAR(20) NOT NULL, + is_binary VARCHAR(1), + missing_means_zero VARCHAR(1), + PRIMARY KEY(analysis_id,domain_id) +); +CREATE TABLE results.cd_temporal_covariate_ref ( + covariate_id BIGINT NOT NULL, + covariate_name VARCHAR, + analysis_id INT, + concept_id BIGINT, + PRIMARY KEY(covariate_id) +); +CREATE TABLE results.cd_temporal_covariate_value ( + cohort_id BIGINT NOT NULL, + time_id INT NOT NULL, + covariate_id BIGINT NOT NULL, + sum_value NUMERIC, + mean NUMERIC, + sd NUMERIC, + database_id VARCHAR NOT NULL, + PRIMARY KEY(cohort_id,time_id,covariate_id,database_id) +); +CREATE TABLE results.cd_temporal_covariate_value_dist ( + cohort_id BIGINT NOT NULL, + time_id INT NOT NULL, + covariate_id BIGINT NOT NULL, + count_value NUMERIC, + min_value NUMERIC, + max_value NUMERIC, + mean NUMERIC, + sd NUMERIC, + median_value NUMERIC, + p_10_value NUMERIC, + p_25_value NUMERIC, + p_75_value NUMERIC, + p_90_value NUMERIC, + database_id VARCHAR NOT NULL, + PRIMARY KEY(cohort_id,time_id,covariate_id,database_id) +); +CREATE TABLE results.cd_temporal_time_ref ( + time_id INT NOT NULL, + start_day NUMERIC, + end_day NUMERIC, + PRIMARY KEY(time_id) +); +CREATE TABLE results.cd_time_series ( + cohort_id BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + period_begin DATE NOT NULL, + period_end DATE NOT NULL, + series_type VARCHAR NOT NULL, + calendar_interval VARCHAR NOT NULL, + gender VARCHAR NOT NULL, + age_group VARCHAR NOT NULL, + records BIGINT, + subjects BIGINT, + person_days BIGINT, + person_days_in BIGINT, + records_start BIGINT, + subjects_start BIGINT, + subjects_start_in BIGINT, + records_end BIGINT, + subjects_end BIGINT, + subjects_end_in BIGINT, + PRIMARY KEY(cohort_id,database_id,period_begin,period_end,series_type,calendar_interval,gender,age_group) +); +CREATE TABLE results.cd_visit_context ( + cohort_id BIGINT NOT NULL, + visit_concept_id BIGINT NOT NULL, + visit_context VARCHAR NOT NULL, + subjects NUMERIC, + database_id VARCHAR NOT NULL, + PRIMARY KEY(cohort_id,visit_concept_id,visit_context,database_id) +); +CREATE TABLE results.cd_vocabulary ( + vocabulary_id VARCHAR(50), + vocabulary_name VARCHAR(255), + vocabulary_reference VARCHAR, + vocabulary_version VARCHAR, + vocabulary_concept_id BIGINT +); +-- CohortGeneratorModule Tables +CREATE TABLE results.cg_cohort_definition ( + cohort_definition_id BIGINT NOT NULL, + cohort_name VARCHAR, + description VARCHAR, + json TEXT, + sql_command TEXT, + subset_parent BIGINT, + is_subset INT, + subset_definition_id BIGINT, + PRIMARY KEY(cohort_definition_id) +); +CREATE TABLE results.cg_cohort_generation ( + cohort_id BIGINT NOT NULL, + cohort_name VARCHAR, + generation_status VARCHAR, + start_time TIMESTAMP, + end_time TIMESTAMP, + database_id VARCHAR NOT NULL, + PRIMARY KEY(cohort_id,database_id) +); +CREATE TABLE results.cg_cohort_inclusion ( + cohort_definition_id BIGINT NOT NULL, + rule_sequence INT NOT NULL, + name VARCHAR NOT NULL, + description VARCHAR, + PRIMARY KEY(cohort_definition_id,rule_sequence,name) +); +CREATE TABLE results.cg_cohort_inc_result ( + database_id VARCHAR NOT NULL, + cohort_definition_id BIGINT NOT NULL, + inclusion_rule_mask INT NOT NULL, + person_count BIGINT NOT NULL, + mode_id INT NOT NULL, + PRIMARY KEY(database_id,cohort_definition_id,inclusion_rule_mask,person_count,mode_id) +); +CREATE TABLE results.cg_cohort_inc_stats ( + database_id VARCHAR NOT NULL, + cohort_definition_id BIGINT NOT NULL, + rule_sequence INT NOT NULL, + person_count BIGINT NOT NULL, + gain_count BIGINT NOT NULL, + person_total BIGINT NOT NULL, + mode_id INT NOT NULL, + PRIMARY KEY(database_id,cohort_definition_id,rule_sequence,person_count,gain_count,person_total,mode_id) +); +CREATE TABLE results.cg_cohort_summary_stats ( + database_id VARCHAR NOT NULL, + cohort_definition_id BIGINT NOT NULL, + base_count BIGINT NOT NULL, + final_count BIGINT NOT NULL, + mode_id INT NOT NULL, + PRIMARY KEY(database_id,cohort_definition_id,base_count,final_count,mode_id) +); +CREATE TABLE results.cg_cohort_censor_stats ( + cohort_definition_id BIGINT NOT NULL, + lost_count BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + PRIMARY KEY(cohort_definition_id,lost_count,database_id) +); +CREATE TABLE results.cg_cohort_count ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + cohort_entries BIGINT NOT NULL, + cohort_subjects BIGINT NOT NULL, + PRIMARY KEY(database_id,cohort_id,cohort_entries,cohort_subjects) +); +CREATE TABLE results.cg_cohort_count_neg_ctrl ( + database_id VARCHAR NOT NULL, + cohort_id BIGINT NOT NULL, + cohort_entries BIGINT NOT NULL, + cohort_subjects BIGINT NOT NULL, + PRIMARY KEY(database_id,cohort_id,cohort_entries,cohort_subjects) +); +CREATE TABLE results.cg_cohort_subset_definition ( + subset_definition_id BIGINT NOT NULL, + json TEXT, + PRIMARY KEY(subset_definition_id) +); +CREATE TABLE results.cg_cohort_definition_neg_ctrl ( + cohort_id BIGINT NOT NULL, + outcome_concept_id BIGINT, + cohort_name VARCHAR, + occurrence_type VARCHAR, + detect_on_descendants INT, + PRIMARY KEY(cohort_id) +); +-- CohortIncidenceModule Tables +CREATE TABLE results.ci_incidence_summary ( + ref_id INT, + database_id VARCHAR(255), + source_name VARCHAR(255), + target_cohort_definition_id BIGINT, + tar_id BIGINT, + subgroup_id BIGINT, + outcome_id BIGINT, + age_group_id INT, + gender_id INT, + gender_name VARCHAR(255), + start_year INT, + persons_at_risk_pe BIGINT, + persons_at_risk BIGINT, + person_days_pe BIGINT, + person_days BIGINT, + person_outcomes_pe BIGINT, + person_outcomes BIGINT, + outcomes_pe BIGINT, + outcomes BIGINT, + incidence_proportion_p100p NUMERIC, + incidence_rate_p100py NUMERIC +); +CREATE TABLE results.ci_target_def ( + ref_id INT NOT NULL, + target_cohort_definition_id BIGINT NOT NULL, + target_name VARCHAR(255), + PRIMARY KEY(ref_id,target_cohort_definition_id) +); +CREATE TABLE results.ci_outcome_def ( + ref_id INT NOT NULL, + outcome_id BIGINT NOT NULL, + outcome_cohort_definition_id BIGINT, + outcome_name VARCHAR(255), + clean_window BIGINT, + excluded_cohort_definition_id BIGINT, + PRIMARY KEY(ref_id,outcome_id) +); +CREATE TABLE results.ci_tar_def ( + ref_id INT NOT NULL, + tar_id BIGINT NOT NULL, + tar_start_with VARCHAR(10), + tar_start_offset BIGINT, + tar_end_with VARCHAR(10), + tar_end_offset BIGINT, + PRIMARY KEY(ref_id,tar_id) +); +CREATE TABLE results.ci_age_group_def ( + ref_id INT NOT NULL, + age_group_id INT NOT NULL, + age_group_name VARCHAR(255), + min_age INT, + max_age INT, + PRIMARY KEY(ref_id,age_group_id) +); +CREATE TABLE results.ci_subgroup_def ( + ref_id INT NOT NULL, + subgroup_id BIGINT NOT NULL, + subgroup_name VARCHAR(255), + PRIMARY KEY(ref_id,subgroup_id) +); +CREATE TABLE results.ci_target_outcome_ref ( + ref_id INT NOT NULL, + target_cohort_id BIGINT NOT NULL, + outcome_cohort_id BIGINT NOT NULL, + PRIMARY KEY(ref_id,target_cohort_id,outcome_cohort_id) +); +-- CohortMethodModule Tables +CREATE TABLE results.cm_attrition ( + sequence_number INT NOT NULL, + description VARCHAR, + subjects INT, + exposure_id BIGINT NOT NULL, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + analysis_id INT NOT NULL, + outcome_id BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + PRIMARY KEY(sequence_number,exposure_id,target_id,comparator_id,analysis_id,outcome_id,database_id) +); +CREATE TABLE results.cm_follow_up_dist ( + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + outcome_id BIGINT NOT NULL, + analysis_id INT NOT NULL, + target_min_days NUMERIC, + target_p_10_days NUMERIC, + target_p_25_days NUMERIC, + target_median_days NUMERIC, + target_p_75_days NUMERIC, + target_p_90_days NUMERIC, + target_max_days NUMERIC, + comparator_min_days NUMERIC, + comparator_p_10_days NUMERIC, + comparator_p_25_days NUMERIC, + comparator_median_days NUMERIC, + comparator_p_75_days NUMERIC, + comparator_p_90_days NUMERIC, + comparator_max_days NUMERIC, + target_min_date DATE, + target_max_date DATE, + comparator_min_date DATE, + comparator_max_date DATE, + database_id VARCHAR NOT NULL, + PRIMARY KEY(target_id,comparator_id,outcome_id,analysis_id,database_id) +); +CREATE TABLE results.cm_analysis ( + analysis_id INT NOT NULL, + description VARCHAR, + definition VARCHAR, + PRIMARY KEY(analysis_id) +); +CREATE TABLE results.cm_result ( + analysis_id INT NOT NULL, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + outcome_id BIGINT NOT NULL, + rr NUMERIC, + ci_95_lb NUMERIC, + ci_95_ub NUMERIC, + p NUMERIC, + one_sided_p NUMERIC, + target_subjects INT, + comparator_subjects INT, + target_days INT, + comparator_days INT, + target_outcomes INT, + comparator_outcomes INT, + log_rr NUMERIC, + se_log_rr NUMERIC, + llr NUMERIC, + calibrated_rr NUMERIC, + calibrated_ci_95_lb NUMERIC, + calibrated_ci_95_ub NUMERIC, + calibrated_p NUMERIC, + calibrated_one_sided_p NUMERIC, + calibrated_log_rr NUMERIC, + calibrated_se_log_rr NUMERIC, + target_estimator VARCHAR, + database_id VARCHAR NOT NULL, + PRIMARY KEY(analysis_id,target_id,comparator_id,outcome_id,database_id) +); +CREATE TABLE results.cm_interaction_result ( + analysis_id INT NOT NULL, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + outcome_id BIGINT NOT NULL, + interaction_covariate_id INT NOT NULL, + rr NUMERIC, + ci_95_lb NUMERIC, + ci_95_ub NUMERIC, + p NUMERIC, + target_subjects INT, + comparator_subjects INT, + target_days INT, + comparator_days INT, + target_outcomes INT, + comparator_outcomes INT, + log_rr NUMERIC, + se_log_rr NUMERIC, + calibrated_rr NUMERIC, + calibrated_ci_95_lb NUMERIC, + calibrated_ci_95_ub NUMERIC, + calibrated_p NUMERIC, + calibrated_log_rr NUMERIC, + calibrated_se_log_rr NUMERIC, + target_estimator VARCHAR, + database_id VARCHAR NOT NULL, + PRIMARY KEY(analysis_id,target_id,comparator_id,outcome_id,interaction_covariate_id,database_id) +); +CREATE TABLE results.cm_covariate ( + covariate_id BIGINT NOT NULL, + covariate_name VARCHAR, + analysis_id INT NOT NULL, + covariate_analysis_id INT, + database_id VARCHAR NOT NULL, + PRIMARY KEY(covariate_id,analysis_id,database_id) +); +CREATE TABLE results.cm_covariate_analysis ( + covariate_analysis_id INT NOT NULL, + covariate_analysis_name VARCHAR, + analysis_id INT NOT NULL, + PRIMARY KEY(covariate_analysis_id,analysis_id) +); +CREATE TABLE results.cm_covariate_balance ( + database_id VARCHAR NOT NULL, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + outcome_id BIGINT NOT NULL, + analysis_id INT NOT NULL, + covariate_id BIGINT NOT NULL, + target_mean_before NUMERIC, + comparator_mean_before NUMERIC, + mean_before NUMERIC, + std_diff_before NUMERIC, + mean_after NUMERIC, + target_mean_after NUMERIC, + comparator_mean_after NUMERIC, + std_diff_after NUMERIC, + target_std_diff NUMERIC, + comparator_std_diff NUMERIC, + target_comparator_std_diff NUMERIC, + PRIMARY KEY(database_id,target_id,comparator_id,outcome_id,analysis_id,covariate_id) +); +CREATE TABLE results.cm_diagnostics_summary ( + analysis_id INT NOT NULL, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + outcome_id BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + max_sdm NUMERIC, + shared_max_sdm NUMERIC, + equipoise NUMERIC, + mdrr NUMERIC, + attrition_fraction NUMERIC, + generalizability_max_sdm NUMERIC, + ease NUMERIC, + balance_diagnostic VARCHAR(20), + shared_balance_diagnostic VARCHAR(20), + equipoise_diagnostic VARCHAR(20), + mdrr_diagnostic VARCHAR(20), + attrition_diagnostic VARCHAR(20), + generalizability_diagnostic VARCHAR(20), + ease_diagnostic VARCHAR(20), + unblind INT, + unblind_for_evidence_synthesis INT, + PRIMARY KEY(analysis_id,target_id,comparator_id,outcome_id,database_id) +); +CREATE TABLE results.cm_target_comparator_outcome ( + outcome_id BIGINT NOT NULL, + outcome_of_interest INT, + true_effect_size NUMERIC, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + PRIMARY KEY(outcome_id,target_id,comparator_id) +); +CREATE TABLE results.cm_kaplan_meier_dist ( + time_day INT NOT NULL, + target_survival NUMERIC, + target_survival_lb NUMERIC, + target_survival_ub NUMERIC, + comparator_survival NUMERIC, + comparator_survival_lb NUMERIC, + comparator_survival_ub NUMERIC, + target_at_risk INT, + comparator_at_risk INT, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + outcome_id BIGINT NOT NULL, + analysis_id INT NOT NULL, + database_id VARCHAR NOT NULL, + PRIMARY KEY(time_day,target_id,comparator_id,outcome_id,analysis_id,database_id) +); +CREATE TABLE results.cm_likelihood_profile ( + log_rr NUMERIC NOT NULL, + log_likelihood NUMERIC, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + outcome_id BIGINT NOT NULL, + analysis_id INT NOT NULL, + database_id VARCHAR NOT NULL, + PRIMARY KEY(log_rr,target_id,comparator_id,outcome_id,analysis_id,database_id) +); +CREATE TABLE results.cm_preference_score_dist ( + analysis_id INT NOT NULL, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + database_id VARCHAR NOT NULL, + preference_score NUMERIC NOT NULL, + target_density NUMERIC, + comparator_density NUMERIC, + PRIMARY KEY(analysis_id,target_id,comparator_id,database_id,preference_score) +); +CREATE TABLE results.cm_propensity_model ( + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + analysis_id INT NOT NULL, + database_id VARCHAR NOT NULL, + covariate_id BIGINT NOT NULL, + coefficient NUMERIC, + PRIMARY KEY(target_id,comparator_id,analysis_id,database_id,covariate_id) +); +CREATE TABLE results.cm_shared_covariate_balance ( + database_id VARCHAR NOT NULL, + target_id BIGINT NOT NULL, + comparator_id BIGINT NOT NULL, + analysis_id INT NOT NULL, + covariate_id BIGINT NOT NULL, + mean_before NUMERIC, + target_mean_before NUMERIC, + comparator_mean_before NUMERIC, + std_diff_before NUMERIC, + mean_after NUMERIC, + target_mean_after NUMERIC, + comparator_mean_after NUMERIC, + std_diff_after NUMERIC, + target_std_diff NUMERIC, + comparator_std_diff NUMERIC, + target_comparator_std_diff NUMERIC, + PRIMARY KEY(database_id,target_id,comparator_id,analysis_id,covariate_id) +); +-- EvidenceSynthesisModule Tables +CREATE TABLE results.es_analysis ( + evidence_synthesis_analysis_id INT NOT NULL, + evidence_synthesis_description VARCHAR(255), + source_method VARCHAR(100), + definition VARCHAR, + PRIMARY KEY(evidence_synthesis_analysis_id) +); +CREATE TABLE results.es_cm_diagnostics_summary ( + target_id INT NOT NULL, + comparator_id INT NOT NULL, + outcome_id INT NOT NULL, + analysis_id INT NOT NULL, + evidence_synthesis_analysis_id INT NOT NULL, + mdrr NUMERIC, + i_2 NUMERIC, + tau NUMERIC, + ease NUMERIC, + mdrr_diagnostic VARCHAR(13), + i_2_diagnostic VARCHAR(13), + tau_diagnostic VARCHAR(13), + ease_diagnostic VARCHAR(13), + unblind INT, + PRIMARY KEY(target_id,comparator_id,outcome_id,analysis_id,evidence_synthesis_analysis_id) +); +CREATE TABLE results.es_cm_result ( + target_id INT NOT NULL, + comparator_id INT NOT NULL, + outcome_id INT NOT NULL, + analysis_id INT NOT NULL, + evidence_synthesis_analysis_id INT NOT NULL, + rr NUMERIC, + ci_95_lb NUMERIC, + ci_95_ub NUMERIC, + p NUMERIC, + one_sided_p NUMERIC, + log_rr NUMERIC, + se_log_rr NUMERIC, + target_subjects INT, + comparator_subjects INT, + target_days INT, + comparator_days INT, + target_outcomes INT, + comparator_outcomes INT, + n_databases INT, + calibrated_rr NUMERIC, + calibrated_ci_95_lb NUMERIC, + calibrated_ci_95_ub NUMERIC, + calibrated_p NUMERIC, + calibrated_one_sided_p NUMERIC, + calibrated_log_rr NUMERIC, + calibrated_se_log_rr NUMERIC, + PRIMARY KEY(target_id,comparator_id,outcome_id,analysis_id,evidence_synthesis_analysis_id) +); +CREATE TABLE results.es_sccs_diagnostics_summary ( + exposures_outcome_set_id INT NOT NULL, + covariate_id INT NOT NULL, + analysis_id INT NOT NULL, + evidence_synthesis_analysis_id INT NOT NULL, + mdrr NUMERIC, + i_2 NUMERIC, + tau NUMERIC, + ease NUMERIC, + mdrr_diagnostic VARCHAR(13), + i_2_diagnostic VARCHAR(13), + tau_diagnostic VARCHAR(13), + ease_diagnostic VARCHAR(13), + unblind INT, + PRIMARY KEY(exposures_outcome_set_id,covariate_id,analysis_id,evidence_synthesis_analysis_id) +); +CREATE TABLE results.es_sccs_result ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + covariate_id INT NOT NULL, + evidence_synthesis_analysis_id INT NOT NULL, + rr NUMERIC, + ci_95_lb NUMERIC, + ci_95_ub NUMERIC, + p NUMERIC, + one_sided_p NUMERIC, + outcome_subjects INT, + outcome_events INT, + outcome_observation_periods INT, + covariate_subjects INT, + covariate_days INT, + covariate_eras INT, + covariate_outcomes INT, + observed_days INT, + n_databases INT, + log_rr NUMERIC, + se_log_rr NUMERIC, + calibrated_rr NUMERIC, + calibrated_ci_95_lb NUMERIC, + calibrated_ci_95_ub NUMERIC, + calibrated_p NUMERIC, + calibrated_one_sided_p NUMERIC, + calibrated_log_rr NUMERIC, + calibrated_se_log_rr NUMERIC, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,covariate_id,evidence_synthesis_analysis_id) +); +-- PatientLevelPredictionModule Tables +CREATE TABLE results.plp_cohorts ( + cohort_id INT NOT NULL, + cohort_definition_id BIGINT, + cohort_name VARCHAR, + PRIMARY KEY(cohort_id) +); +CREATE TABLE results.plp_cohort_definition ( + cohort_definition_id BIGINT, + cohort_name VARCHAR, + description TEXT, + json TEXT, + sql_command TEXT +); +CREATE TABLE results.plp_database_meta_data ( + database_id VARCHAR NOT NULL, + cdm_source_name VARCHAR, + cdm_source_abbreviation VARCHAR, + cdm_holder VARCHAR, + source_description TEXT, + source_documentation_reference VARCHAR, + cdm_etl_reference VARCHAR, + source_release_date VARCHAR, + cdm_release_date VARCHAR, + cdm_version VARCHAR, + vocabulary_version VARCHAR, + max_obs_period_end_date VARCHAR, + PRIMARY KEY(database_id) +); +CREATE TABLE results.plp_database_details ( + database_id INT NOT NULL, + database_meta_data_id VARCHAR, + PRIMARY KEY(database_id) +); +CREATE TABLE results.plp_tars ( + tar_id INT NOT NULL, + tar_start_day INT, + tar_start_anchor VARCHAR, + tar_end_day INT, + tar_end_anchor VARCHAR, + PRIMARY KEY(tar_id) +); +CREATE TABLE results.plp_population_settings ( + population_setting_id INT NOT NULL, + population_settings_json TEXT, + PRIMARY KEY(population_setting_id) +); +CREATE TABLE results.plp_covariate_settings ( + covariate_setting_id INT NOT NULL, + covariate_settings_json TEXT, + PRIMARY KEY(covariate_setting_id) +); +CREATE TABLE results.plp_model_settings ( + model_setting_id INT NOT NULL, + model_type VARCHAR, + model_settings_json VARCHAR, + PRIMARY KEY(model_setting_id) +); +CREATE TABLE results.plp_split_settings ( + split_setting_id INT NOT NULL, + split_settings_json TEXT, + PRIMARY KEY(split_setting_id) +); +CREATE TABLE results.plp_plp_data_settings ( + plp_data_setting_id INT NOT NULL, + plp_data_settings_json TEXT, + PRIMARY KEY(plp_data_setting_id) +); +CREATE TABLE results.plp_feature_engineering_settings ( + feature_engineering_setting_id INT NOT NULL, + feature_engineering_settings_json TEXT, + PRIMARY KEY(feature_engineering_setting_id) +); +CREATE TABLE results.plp_tidy_covariates_settings ( + tidy_covariates_setting_id INT NOT NULL, + tidy_covariates_settings_json TEXT, + PRIMARY KEY(tidy_covariates_setting_id) +); +CREATE TABLE results.plp_sample_settings ( + sample_setting_id INT NOT NULL, + sample_settings_json TEXT, + PRIMARY KEY(sample_setting_id) +); +CREATE TABLE results.plp_model_designs ( + model_design_id INT NOT NULL, + target_id INT, + outcome_id INT, + tar_id INT, + plp_data_setting_id INT, + population_setting_id INT, + model_setting_id INT, + covariate_setting_id INT, + sample_setting_id INT, + split_setting_id INT, + feature_engineering_setting_id INT, + tidy_covariates_setting_id INT, + PRIMARY KEY(model_design_id) +); +CREATE TABLE results.plp_diagnostics ( + diagnostic_id INT NOT NULL, + model_design_id INT, + database_id INT, + execution_date_time VARCHAR, + PRIMARY KEY(diagnostic_id) +); +CREATE TABLE results.plp_diagnostic_summary ( + diagnostic_id INT, + probast_id VARCHAR, + result_value VARCHAR +); +CREATE TABLE results.plp_diagnostic_predictors ( + diagnostic_id INT, + days_to_event INT, + outcome_at_time INT, + observed_at_start_of_day BIGINT, + input_type VARCHAR +); +CREATE TABLE results.plp_diagnostic_participants ( + diagnostic_id INT, + design VARCHAR, + metric VARCHAR, + value NUMERIC, + probast_id VARCHAR +); +CREATE TABLE results.plp_diagnostic_outcomes ( + diagnostic_id INT, + xvalue INT, + outcome_percent NUMERIC, + aggregation VARCHAR, + probast_id VARCHAR, + input_type VARCHAR +); +CREATE TABLE results.plp_diagnostic_designs ( + diagnostic_id INT NOT NULL, + probast_id VARCHAR, + value VARCHAR, + PRIMARY KEY(diagnostic_id) +); +CREATE TABLE results.plp_models ( + model_id INT NOT NULL, + analysis_id VARCHAR, + model_design_id INT, + database_id INT, + model_type VARCHAR, + plp_model_file TEXT, + train_details TEXT, + preprocessing TEXT, + execution_date_time VARCHAR, + training_time VARCHAR, + intercept NUMERIC, + PRIMARY KEY(model_id) +); +CREATE TABLE results.plp_recalibrations ( + recalibration_id INT NOT NULL, + original_model_id INT, + recalibrated_model_id INT, + recalibration_type VARCHAR, + recalibration_json VARCHAR, + PRIMARY KEY(recalibration_id) +); +CREATE TABLE results.plp_performances ( + performance_id INT NOT NULL, + model_design_id INT, + development_database_id INT, + validation_database_id INT, + target_id INT, + outcome_id INT, + tar_id INT, + plp_data_setting_id INT, + population_setting_id INT, + model_development INT, + execution_date_time VARCHAR, + plp_version VARCHAR, + PRIMARY KEY(performance_id) +); +CREATE TABLE results.plp_attrition ( + performance_id INT, + outcome_id INT, + description VARCHAR, + target_count INT, + unique_people INT, + outcomes INT +); +CREATE TABLE results.plp_prediction_distribution ( + performance_id INT, + evaluation VARCHAR, + class_label INT, + person_count INT, + average_predicted_probability NUMERIC, + st_dev_predicted_probability NUMERIC, + min_predicted_probability NUMERIC, + p_05_predicted_probability NUMERIC, + p_25_predicted_probability NUMERIC, + median_predicted_probability NUMERIC, + p_75_predicted_probability NUMERIC, + p_95_predicted_probability NUMERIC, + max_predicted_probability NUMERIC +); +CREATE TABLE results.plp_covariate_summary ( + performance_id INT, + covariate_id BIGINT, + covariate_name VARCHAR, + concept_id NUMERIC, + covariate_value NUMERIC, + covariate_count INT, + covariate_mean NUMERIC, + covariate_st_dev NUMERIC, + with_no_outcome_covariate_count INT, + with_no_outcome_covariate_mean NUMERIC, + with_no_outcome_covariate_st_dev NUMERIC, + with_outcome_covariate_count INT, + with_outcome_covariate_mean NUMERIC, + with_outcome_covariate_st_dev NUMERIC, + standardized_mean_diff NUMERIC +); +CREATE TABLE results.plp_threshold_summary ( + performance_id INT, + evaluation VARCHAR, + prediction_threshold NUMERIC, + preference_threshold NUMERIC, + positive_count INT, + negative_count INT, + true_count INT, + false_count INT, + true_positive_count INT, + true_negative_count INT, + false_positive_count INT, + false_negative_count INT, + f_1_score NUMERIC, + accuracy NUMERIC, + sensitivity NUMERIC, + false_negative_rate NUMERIC, + false_positive_rate NUMERIC, + specificity NUMERIC, + positive_predictive_value NUMERIC, + false_discovery_rate NUMERIC, + negative_predictive_value NUMERIC, + false_omission_rate NUMERIC, + positive_likelihood_ratio NUMERIC, + negative_likelihood_ratio NUMERIC, + diagnostic_odds_ratio NUMERIC +); +CREATE TABLE results.plp_calibration_summary ( + performance_id INT, + evaluation VARCHAR, + prediction_threshold NUMERIC, + person_count_at_risk INT, + person_count_with_outcome INT, + average_predicted_probability NUMERIC, + st_dev_predicted_probability NUMERIC, + min_predicted_probability NUMERIC, + p_25_predicted_probability NUMERIC, + median_predicted_probability NUMERIC, + p_75_predicted_probability NUMERIC, + max_predicted_probability NUMERIC, + observed_incidence NUMERIC +); +CREATE TABLE results.plp_evaluation_statistics ( + performance_id INT, + evaluation VARCHAR, + metric VARCHAR, + value NUMERIC +); +CREATE TABLE results.plp_demographic_summary ( + performance_id INT, + evaluation VARCHAR, + age_group VARCHAR, + gen_group VARCHAR, + person_count_at_risk INT, + person_count_with_outcome INT, + average_predicted_probability NUMERIC, + st_dev_predicted_probability NUMERIC, + min_predicted_probability NUMERIC, + p_25_predicted_probability NUMERIC, + p_50_predicted_probability NUMERIC, + p_75_predicted_probability NUMERIC, + max_predicted_probability NUMERIC +); +-- SelfControlledCaseSeriesModule Tables +CREATE TABLE results.sccs_analysis ( + analysis_id INT NOT NULL, + description VARCHAR, + definition VARCHAR, + PRIMARY KEY(analysis_id) +); +CREATE TABLE results.sccs_covariate_analysis ( + analysis_id INT NOT NULL, + covariate_analysis_id INT NOT NULL, + covariate_analysis_name VARCHAR, + variable_of_interest INT, + PRIMARY KEY(analysis_id,covariate_analysis_id) +); +CREATE TABLE results.sccs_covariate ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + covariate_id INT NOT NULL, + covariate_name VARCHAR, + era_id INT, + covariate_analysis_id INT, + database_id VARCHAR NOT NULL, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,covariate_id,database_id) +); +CREATE TABLE results.sccs_era ( + exposures_outcome_set_id INT NOT NULL, + analysis_id INT NOT NULL, + era_type VARCHAR NOT NULL, + era_id INT NOT NULL, + era_name VARCHAR, + database_id VARCHAR NOT NULL, + PRIMARY KEY(exposures_outcome_set_id,analysis_id,era_type,era_id,database_id) +); +CREATE TABLE results.sccs_exposures_outcome_set ( + exposures_outcome_set_id INT NOT NULL, + outcome_id INT, + nesting_cohort_id INT, + PRIMARY KEY(exposures_outcome_set_id) +); +CREATE TABLE results.sccs_exposure ( + exposures_outcome_set_id INT NOT NULL, + era_id INT NOT NULL, + true_effect_size NUMERIC, + PRIMARY KEY(exposures_outcome_set_id,era_id) +); +CREATE TABLE results.sccs_spline ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + spline_type VARCHAR NOT NULL, + knot_month NUMERIC NOT NULL, + rr NUMERIC, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,spline_type,knot_month) +); +CREATE TABLE results.sccs_censor_model ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + parameter_id INT NOT NULL, + parameter_value NUMERIC, + model_type VARCHAR, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,parameter_id) +); +CREATE TABLE results.sccs_result ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + covariate_id INT NOT NULL, + rr NUMERIC, + ci_95_lb NUMERIC, + ci_95_ub NUMERIC, + p NUMERIC, + one_sided_p NUMERIC, + outcome_subjects INT, + outcome_events INT, + outcome_observation_periods INT, + covariate_subjects INT, + covariate_days INT, + covariate_eras INT, + covariate_outcomes INT, + observed_days BIGINT, + log_rr NUMERIC, + se_log_rr NUMERIC, + llr NUMERIC, + calibrated_rr NUMERIC, + calibrated_ci_95_lb NUMERIC, + calibrated_ci_95_ub NUMERIC, + calibrated_p NUMERIC, + calibrated_one_sided_p NUMERIC, + calibrated_log_rr NUMERIC, + calibrated_se_log_rr NUMERIC, + database_id VARCHAR NOT NULL, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,covariate_id,database_id) +); +CREATE TABLE results.sccs_covariate_result ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + covariate_id INT NOT NULL, + rr NUMERIC, + ci_95_lb NUMERIC, + ci_95_ub NUMERIC, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,covariate_id) +); +CREATE TABLE results.sccs_attrition ( + sequence_number INT NOT NULL, + description VARCHAR, + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + covariate_id INT NOT NULL, + database_id VARCHAR NOT NULL, + outcome_subjects INT, + outcome_events INT, + outcome_observation_periods INT, + observed_days BIGINT, + PRIMARY KEY(sequence_number,analysis_id,exposures_outcome_set_id,covariate_id,database_id) +); +CREATE TABLE results.sccs_likelihood_profile ( + log_rr NUMERIC NOT NULL, + log_likelihood NUMERIC, + covariate_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + analysis_id INT NOT NULL, + database_id VARCHAR NOT NULL, + PRIMARY KEY(log_rr,covariate_id,exposures_outcome_set_id,analysis_id,database_id) +); +CREATE TABLE results.sccs_time_trend ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + calendar_year INT NOT NULL, + calendar_month INT NOT NULL, + observed_subjects INT, + ratio NUMERIC, + adjusted_ratio NUMERIC, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,calendar_year,calendar_month) +); +CREATE TABLE results.sccs_time_to_event ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + era_id INT NOT NULL, + week INT NOT NULL, + observed_subjects INT, + outcomes INT, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,era_id,week) +); +CREATE TABLE results.sccs_age_spanning ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + age_month INT NOT NULL, + cover_before_after_subjects INT, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,age_month) +); +CREATE TABLE results.sccs_calendar_time_spanning ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + calendar_year INT NOT NULL, + calendar_month INT NOT NULL, + cover_before_after_subjects INT, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,calendar_year,calendar_month) +); +CREATE TABLE results.sccs_event_dep_observation ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + database_id VARCHAR NOT NULL, + months_to_end INT NOT NULL, + censored INT NOT NULL, + outcomes INT, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,database_id,months_to_end,censored) +); +CREATE TABLE results.sccs_diagnostics_summary ( + analysis_id INT NOT NULL, + exposures_outcome_set_id INT NOT NULL, + covariate_id INT NOT NULL, + database_id VARCHAR NOT NULL, + mdrr NUMERIC, + ease NUMERIC, + time_trend_p NUMERIC, + pre_exposure_p NUMERIC, + mdrr_diagnostic VARCHAR(20), + ease_diagnostic VARCHAR(20), + time_trend_diagnostic VARCHAR(20), + pre_exposure_diagnostic VARCHAR(20), + unblind INT, + unblind_for_evidence_synthesis INT, + PRIMARY KEY(analysis_id,exposures_outcome_set_id,covariate_id,database_id) +); diff --git a/extras/rdms/ohdsi_shiny_modules_sql_queries.csv b/extras/rdms/ohdsi_shiny_modules_sql_queries.csv new file mode 100644 index 00000000..04bec28e --- /dev/null +++ b/extras/rdms/ohdsi_shiny_modules_sql_queries.csv @@ -0,0 +1,136 @@ +"fileName","startLine","endLine","sqlQuery" +"characterization-caseSeries.R","195","224","SELECT distinct s.database_id, d.CDM_SOURCE_ABBREVIATION as database_name,s.setting_id, s.RISK_WINDOW_START, s.RISK_WINDOW_END, s.START_ANCHOR, s.END_ANCHOR, ct1.cohort_name as target_name, ct2.cohort_name as outcome_name from @schema.@c_table_prefixsettings s inner join @schema.@database_meta_table d on s.database_id = d.database_id inner join @schema.@c_table_prefixcohort_details cd on s.setting_id = cd.setting_id and s.database_id = cd.database_id and cd.target_cohort_id = @target_id and cd.outcome_cohort_id = @outcome_id and cd.cohort_type = 'Cases' inner join @schema.@cg_table_prefixcohort_definition ct1 on ct1.cohort_definition_id = cd.target_cohort_id inner join @schema.@cg_table_prefixcohort_definition ct2 on ct2.cohort_definition_id = cd.outcome_cohort_id ;" +"characterization-caseSeries.R","275","306","SELECT case when cov.cohort_type = 'CasesBefore' then 'Before' when cov.cohort_type = 'CasesBetween' then 'During' when cov.cohort_type = 'CaseAfter' then 'After' end as type, cr.covariate_name, s.min_prior_observation, s.outcome_washout_days, s.case_post_outcome_duration, s.case_pre_target_duration, cov.covariate_id, cov.sum_value, cov.average_value from @schema.@c_table_prefixcovariates cov inner join @schema.@c_table_prefixcovariate_ref cr on cov.setting_id = cr.setting_id and cov.database_id = cr.database_id and cov.covariate_id = cr.covariate_id inner join @schema.@c_table_prefixsettings s on cov.setting_id = s.setting_id and cov.database_id = s.database_id where cov.target_cohort_id = @target_id and cov.outcome_cohort_id = @outcome_id and cov.cohort_type in ('CasesBetween','CasesAfter','CasesBefore') --and cov.setting_id = @setting_id and s.risk_window_start = @risk_window_start and s.risk_window_end = @risk_window_end and s.start_anchor = '@start_anchor' and s.end_anchor = '@end_anchor' and cov.database_id = '@database_id' and cr.analysis_id in (109, 110, 217, 218, 305, 417, 418, 505, 605, 713, 805, 926, 927) ;" +"characterization-caseSeries.R","328","361","SELECTcase when cov.cohort_type = 'CasesBefore' then 'Before' when cov.cohort_type = 'CasesBetween' then 'During' when cov.cohort_type = 'CasesAfter' then 'After' end as type, cr.covariate_name, s.min_prior_observation, s.outcome_washout_days, s.case_post_outcome_duration, s.case_pre_target_duration, cov.covariate_id, cov.count_value, cov.min_value, cov.max_value, cov.average_value, cov.standard_deviation, cov.median_value, cov.p_10_value, cov.p_25_value, cov.p_75_value, cov.p_90_value from @schema.@c_table_prefixcovariates_continuous cov inner join @schema.@c_table_prefixcovariate_ref cr on cov.setting_id = cr.setting_id and cov.database_id = cr.database_id and cov.covariate_id = cr.covariate_id inner join @schema.@c_table_prefixsettings s on cov.setting_id = s.setting_id and cov.database_id = s.database_id where cov.target_cohort_id = @target_id and cov.outcome_cohort_id = @outcome_id and cov.cohort_type in ('CasesBetween','CasesAfter','CasesBefore') and s.risk_window_start = @risk_window_start and s.risk_window_end = @risk_window_end and s.start_anchor = '@start_anchor' and s.end_anchor = '@end_anchor' and cov.database_id = '@database_id' and cr.analysis_id in (109, 110, 217, 218, 305, 417, 418, 505, 605, 713, 805, 926, 927) ;" +"characterization-cohorts.R","791","810","select ref.covariate_name, s.min_prior_observation, cov.target_cohort_id as cohort_definition_id, cov.* from @schema.@c_table_prefixCOVARIATES cov inner join @schema.@c_table_prefixcovariate_ref ref on cov.covariate_id = ref.covariate_id and cov.setting_id = ref.setting_id and cov.database_id = ref.database_id inner join @schema.@c_table_prefixsettings s on s.database_id = cov.database_id and s.setting_id = cov.setting_id where cov.target_cohort_id in (@target_ids) and cov.cohort_type = 'Target' AND cov.database_id in (@database_ids) AND cov.average_value >= @min_threshold;" +"characterization-cohorts.R","902","925","select ref.covariate_name, s.min_prior_observation, cov.target_cohort_id as cohort_definition_id, cov.*, d.CDM_SOURCE_ABBREVIATION as database_name from @schema.@c_table_prefixCOVARIATES_continuous cov inner join @schema.@c_table_prefixcovariate_ref ref on cov.covariate_id = ref.covariate_id and cov.setting_id = ref.setting_id and cov.database_id = ref.database_id inner join @schema.@c_table_prefixsettings s on cov.setting_id = s.setting_id and cov.database_id = s.database_id inner join @schema.@database_meta_table d on s.database_id = d.database_id where cov.target_cohort_id in (@target_ids) and cov.cohort_type = 'Target' AND cov.database_id in (@database_ids);" +"characterization-cohorts.R","990","999","select distinct d.database_id, d.cdm_source_abbreviation as database_name from @schema.@database_table d inner join @schema.@c_table_prefixcohort_details cd on d.database_id = cd.database_id where cd.target_cohort_id = @target_id and cd.cohort_type = 'Target' ;" +"characterization-dechallengeRechallenge.R","329","337","SELECT DISTINCT t.COHORT_NAME as target, dr.TARGET_COHORT_DEFINITION_ID, o.COHORT_NAME as outcome, dr.OUTCOME_COHORT_DEFINITION_ID FROM @schema.@c_table_prefixDECHALLENGE_RECHALLENGE dr inner join @schema.@cg_table_prefixCOHORT_DEFINITION t on dr.TARGET_COHORT_DEFINITION_ID = t.COHORT_DEFINITION_ID inner join @schema.@cg_table_prefixCOHORT_DEFINITION o on dr.OUTCOME_COHORT_DEFINITION_ID = o.COHORT_DEFINITION_ID ;" +"characterization-dechallengeRechallenge.R","390","395","SELECT distinct d.CDM_SOURCE_ABBREVIATION as database_name, dr.*FROM @schema.@c_table_prefixDECHALLENGE_RECHALLENGE dr inner join @schema.@database_table d on dr.database_id = d.database_id where dr.TARGET_COHORT_DEFINITION_ID = @target_id and dr.OUTCOME_COHORT_DEFINITION_ID = @outcome_id;" +"characterization-dechallengeRechallenge.R","433","438","SELECT * FROM @schema.@c_table_prefixRECHALLENGE_FAIL_CASE_SERIES where TARGET_COHORT_DEFINITION_ID = @target_id and OUTCOME_COHORT_DEFINITION_ID = @outcome_id and DATABASE_ID = '@database_id' and DECHALLENGE_STOP_INTERVAL = @dechallenge_stop_interval and DECHALLENGE_EVALUATION_WINDOW = @dechallenge_evaluation_window;" +"characterization-dechallengeRechallenge.R","476","480","SELECT cc.database_id, cc.cohort_id, cc.cohort_entries, cc.cohort_subjects FROM @schema.@cg_table_prefixCOHORT_COUNT cc where cc.cohort_id = @cohort_id ;" +"characterization-incidence.R","1702","1724","select d.cdm_source_abbreviation, i.*, ct1.cohort_name as target_name, ct2.cohort_name as outcome_namefrom ( select od.outcome_cohort_definition_id, od.clean_window, agd.age_group_name, tad.tar_start_with, tad.tar_start_offset, tad.tar_end_with, tad.tar_end_offset, sd.subgroup_name, i.* from @result_schema.@incidence_table_prefixINCIDENCE_SUMMARY i join @result_schema.@incidence_table_prefixOUTCOME_DEF od on i.outcome_id = od.outcome_id and i.ref_id = od.ref_id join @result_schema.@incidence_table_prefixTAR_DEF tad on i.tar_id = tad.tar_id and i.ref_id = tad.ref_id join @result_schema.@incidence_table_prefixSUBGROUP_DEF sd on i.subgroup_id = sd.subgroup_id and i.ref_id = sd.ref_id left join @result_schema.@incidence_table_prefixAGE_GROUP_DEF agd on i.age_group_id = agd.age_group_id and i.ref_id = agd.ref_id ) i inner join @result_schema.@database_table_name d on d.database_id = i.database_id inner join @result_schema.@cg_table_prefixcohort_definition ct1 on ct1.cohort_definition_id = i.target_cohort_definition_id inner join @result_schema.@cg_table_prefixcohort_definition ct2 on ct2.cohort_definition_id = i.outcome_cohort_definition_id where i.target_cohort_definition_id in (@target_ids) and i.outcome_cohort_definition_id in (@outcome_ids);" +"characterization-incidence.R","1800","1803","select outcome_id, outcome_name from @result_schema.@incidence_table_prefixOUTCOME_DEF" +"characterization-incidence.R","1879","1881","SELECT TAR_ID, TAR_START_WITH, TAR_START_OFFSET,TAR_END_WITH, TAR_END_OFFSET from @schema.@ci_table_prefixtar_def;" +"characterization-riskFactors.R","208","225","SELECT cohort_type, min_prior_observation, outcome_washout_days, row_count, person_count from @schema.@c_table_prefixcohort_counts where database_id = '@database_id' and target_cohort_id = @target_id and outcome_cohort_id in (@outcome_id, 0) and (risk_window_start = @risk_window_start OR risk_window_start is NULL) and (risk_window_end = @risk_window_end OR risk_window_end is NULL) and (start_anchor = '@start_anchor' OR start_anchor is NULL) and (end_anchor = '@end_anchor' OR end_anchor is NULL) and cohort_type in ('Cases','Exclude','Target') ;" +"characterization-riskFactors.R","256","272","SELECT distinct setting_idfrom @schema.@c_table_prefixsettings where database_id = '@database_id' and risk_window_start = @risk_window_start and risk_window_end = @risk_window_end and start_anchor = '@start_anchor' and end_anchor = '@end_anchor' union SELECT distinct setting_id from @schema.@c_table_prefixsettings where database_id = '@database_id' and risk_window_start is NULL ;" +"characterization-riskFactors.R","287","308","SELECT distinct cov.cohort_type, cr.covariate_name, s.min_prior_observation, s.outcome_washout_days, cov.covariate_id, cov.sum_value, cov.average_value from @schema.@c_table_prefixcovariates cov inner join @schema.@c_table_prefixcovariate_ref cr on cov.setting_id = cr.setting_id and cov.database_id = cr.database_id and cov.covariate_id = cr.covariate_id inner join @schema.@c_table_prefixsettings s on cov.setting_id = s.setting_id and cov.database_id = s.database_id where cov.target_cohort_id = @target_id and cov.outcome_cohort_id in (0,@outcome_id) and cov.cohort_type in ('Target','Cases', 'Exclude') and cov.database_id = '@database_id' and cov.setting_id in (@setting_ids) and cr.analysis_id not in (109, 110, 217, 218, 305, 417, 418, 505, 605, 713, 805, 926, 927) ;" +"characterization-riskFactors.R","328","350","SELECT distinct cov.cohort_type, cr.covariate_name, s.min_prior_observation, s.outcome_washout_days,cov.covariate_id, cov.count_value, cov.min_value, cov.max_value, cov.average_value, cov.standard_deviation, cov.median_value, cov.p_10_value, cov.p_25_value, cov.p_75_value, cov.p_90_value from @schema.@c_table_prefixcovariates_continuous cov inner join @schema.@c_table_prefixcovariate_ref cr on cov.setting_id = cr.setting_id and cov.database_id = cr.database_id and cov.covariate_id = cr.covariate_id inner join @schema.@c_table_prefixsettings s on cov.setting_id = s.setting_id and cov.database_id = s.database_id where cov.target_cohort_id = @target_id and cov.outcome_cohort_id in (0,@outcome_id) and cov.cohort_type in ('Target','Cases', 'Exclude') and cov.database_id = '@database_id' and cov.setting_id in (@setting_ids) and cr.analysis_id not in (109, 110, 217, 218, 305, 417, 418, 505, 605, 713, 805, 926, 927) ;" +"characterization-timeToEvent.R","265","270","SELECT tte.*, d.CDM_SOURCE_ABBREVIATION as database_name FROM @schema.@c_table_prefixTIME_TO_EVENT tte inner join @schema.@database_table d on tte.database_id = d.database_id where tte.TARGET_COHORT_DEFINITION_ID = @target_id and tte.OUTCOME_COHORT_DEFINITION_ID = @outcome_id;" +"cohort-diagnostics-characterization.R","923","933","SELECT @select_stament FROM @results_database_schema.@table_prefixtemporal_covariate_ref tcr INNER JOIN @results_database_schema.@table_prefixtemporal_analysis_ref tar ON tar.analysis_id = tcr.analysis_id LEFT JOIN @results_database_schema.@table_prefixtemporal_covariate_value tcv ON ( tcr.covariate_id = tcv.covariate_id ) LEFT JOIN @results_database_schema.@table_prefixtemporal_time_ref ttr ON ttr.time_id = tcv.time_id WHERE tcr.covariate_id IS NOT NULL" +"cohort-diagnostics-conceptsInDataSource.R","80","117","SELECT concepts.*,c.concept_name, c.vocabulary_id, c.domain_id, c.standard_concept, c.concept_code FROM ( SELECT isc.database_id, isc.cohort_id, isc.concept_id, 0 source_concept_id, max(concept_subjects) concept_subjects, sum(concept_count) concept_count FROM @schema.@table_name isc WHERE isc.cohort_id = @cohort_id AND isc.database_id IN (@database_ids) GROUP BY isc.database_id, isc.cohort_id, isc.concept_id UNION SELECT c.database_id, c.cohort_id, c.source_concept_id as concept_id, 1 source_concept_id, max(c.concept_subjects) concept_subjects, sum(c.concept_count) concept_count FROM @schema.@table_name c WHERE c.cohort_id = @cohort_id AND c.database_id IN (@database_ids) GROUP BY c.database_id, c.cohort_id, c.source_concept_id ) concepts INNER JOIN @schema.@concept_table c ON concepts.concept_id = c.concept_id WHERE c.invalid_reason IS NULL;" +"cohort-diagnostics-databaseInformation.R","61","63","SELECT *FROM @schema.@metadata WHERE database_id = @database_id;" +"cohort-diagnostics-definition.R","213","214","SELECT * FROM @schema.@cohort_table WHERE cohort_id IN (@cohort_ids)" +"cohort-diagnostics-definition.R","447","450","SELECT ics.*FROM @schema.@table_name ics WHERE ics.cohort_id = @cohort_id AND database_id in (@database_ids);" +"cohort-diagnostics-incidenceRates.R","20","20","SELECT DISTINCT age_group FROM @schema.@ir_table WHERE person_years >= @person_years" +"cohort-diagnostics-incidenceRates.R","31","31","SELECT DISTINCT calendar_year FROM @schema.@ir_table WHERE person_years >= @person_years" +"cohort-diagnostics-incidenceRates.R","45","45","SELECT DISTINCT gender FROM @schema.@ir_table WHERE person_years >= @person_years" +"cohort-diagnostics-incidenceRates.R","57","63","SELECTmin(incidence_rate) as min_ir, max(incidence_rate) as max_ir FROM @schema.@ir_table WHERE person_years >= @person_years AND incidence_rate > 0.0" +"cohort-diagnostics-incidenceRates.R","118","128","SELECT ir.*, cc.cohort_subjectsFROM @schema.@ir_table ir INNER JOIN @schema.@cc_table cc ON ( ir.database_id = cc.database_id AND ir.cohort_id = cc.cohort_id ) WHERE ir.cohort_id in (@cohort_ids) AND ir.database_id in (@database_ids) {@gender == TRUE} ? {AND ir.gender IS NOT NULL} : { AND ir.gender IS NULL} {@age_group == TRUE} ? {AND ir.age_group IS NOT NULL} : { AND ir.age_group IS NULL} {@calendar_year == TRUE} ? {AND ir.calendar_year IS NOT NULL} : { AND ir.calendar_year IS NULL} AND ir.person_years > @personYears;" +"cohort-diagnostics-indexEventBreakdown.R","99","109","SELECT index_event_breakdown.*,concept.concept_name, concept.domain_id, concept.vocabulary_id, concept.standard_concept, concept.concept_code FROM @schema.@table_name index_event_breakdown INNER JOIN @vocabulary_database_schema.@concept_table concept ON index_event_breakdown.concept_id = concept.concept_id WHERE database_id in (@database_id) AND cohort_id in (@cohort_ids);" +"cohort-diagnostics-main.R","19","19","SELECT table_name FROM information_schema.tables where table_schema = '@schema'" +"cohort-diagnostics-main.R","83","83","SELECT * FROM @schema.@table LIMIT 1" +"cohort-diagnostics-main.R","101","109","select c.relname as table_name from pg_class c inner join pg_namespace n on n.oid = c.relnamespace where c.relkind = 'r' and n.nspname not in ('information_schema','pg_catalog') and c.reltuples != 0 and n.nspname = '@schema'" +"cohort-diagnostics-main.R","366","367","SELECT * FROM @schema.@table_name;" +"cohort-diagnostics-orphanConcepts.R","129","153","SELECT c.concept_id, c.concept_name, c.vocabulary_id, c.concept_code, CASE WHEN c.standard_concept = 'S' THEN 'Standard' ELSE 'Non-standard' END as standard_concept %s FROM @schema.@orphan_table_name oc INNER JOIN @schema.@cs_table_name cs ON oc.cohort_id = cs.cohort_id AND oc.concept_set_id = cs.concept_set_id INNER JOIN @vocabulary_database_schema.@concept_table c ON oc.concept_id = c.concept_id WHERE oc.cohort_id = @cohort_id AND database_id in (@database_ids) {@search_str != ''} ? {AND lower(CONCAT(c.concept_id, c.concept_name, c.vocabulary_id, c.concept_code)) LIKE lower('%%@search_str%%')} {@use_concept_set_id} ? { AND oc.concept_set_id IN (@concept_set_id)} GROUP BY c.concept_id, c.concept_name, c.vocabulary_id, c.concept_code, c.standard_concept {@sort_by != \" +"cohort-diagnostics-shared.R","93","99","SELECT cc.*, db.database_name# FROM @schema.@table_name cc # INNER JOIN @schema.@database_table db ON db.database_id = cc.database_id # WHERE cc.cohort_id IS NOT NULL # {@use_database_ids} ? { AND cc.database_id in (@database_ids)} # {@cohort_ids != ''} ? { AND cc.cohort_id in (@cohort_ids)} # ;" +"cohort-diagnostics-shared.R","101","106","SELECT cc.*FROM @schema.@table_name cc WHERE cc.cohort_id IS NOT NULL {@use_database_ids} ? { AND cc.database_id in (@database_ids)} {@cohort_ids != ''} ? { AND cc.cohort_id in (@cohort_ids)} ;" +"cohort-diagnostics-shared.R","129","131","SELECT *FROM @schema.@database_table WHERE database_id in (@database_ids);" +"cohort-diagnostics-shared.R","986","990","SELECT *FROM @schema.@table_name WHERE database_id in (@database_id) {@cohort_ids != ''} ? { AND cohort_id in (@cohort_ids)} ;" +"cohort-diagnostics-visitContext.R","91","97","SELECT visit_context.*,standard_concept.concept_name AS visit_concept_name FROM @schema.@table_name visit_context INNER JOIN @vocabulary_database_schema.@concept_table standard_concept ON visit_context.visit_concept_id = standard_concept.concept_id WHERE database_id in (@database_id) AND cohort_id in (@cohort_ids);" +"cohort-generator-main.R","643","650","SELECT cc.cohort_id, cc.cohort_entries, cc.cohort_subjects,dt.cdm_source_name, cd.cohort_name FROM @schema.@cg_table_prefixCOHORT_COUNT cc join @schema.@database_table_prefix@database_table dt on cc.database_id = dt.database_id join @schema.@cg_table_prefixCOHORT_DEFINITION cd on cd.cohort_definition_id = cc.cohort_id ;" +"cohort-generator-main.R","667","672","SELECT cg.cohort_id, cg.cohort_name,cg.generation_status, cg.start_time, cg.end_time, dt.cdm_source_name from @schema.@cg_table_prefixCOHORT_GENERATION cg join @schema.@database_table_prefix@database_table dt on cg.database_id = dt.database_id ;" +"cohort-generator-main.R","708","715","SELECT css.cohort_definition_id, css.base_count, css.final_count, css.mode_id,dt.cdm_source_name, cd.cohort_name FROM @schema.@cg_table_prefixCOHORT_SUMMARY_STATS css join @schema.@database_table_prefix@database_table dt on css.database_id = dt.database_id join @schema.@cg_table_prefixCOHORT_DEFINITION cd on cd.cohort_definition_id = css.cohort_definition_id ;" +"cohort-generator-main.R","734","738","SELECT ci.cohort_definition_id, ci.rule_sequence, ci.name as rule_name,cd.cohort_name FROM @schema.@cg_table_prefixCOHORT_INCLUSION ci join @schema.@cg_table_prefixCOHORT_DEFINITION cd on cd.cohort_definition_id = ci.cohort_definition_id ;" +"cohort-generator-main.R","753","757","SELECT cir.database_id, cir.cohort_definition_id, cir.inclusion_rule_mask, cir.person_count, cir.mode_id,dt.cdm_source_name FROM @schema.@cg_table_prefixCOHORT_INC_RESULT cir join @schema.@database_table_prefix@database_table dt on cir.database_id = dt.database_id ;" +"data-diagnostic-drill.R","254","255","SELECT * FROM @schema.@dd_table_prefixdata_diagnostics_output WHERE analysis_name = '@analysis_name' and database_id = '@database_id';" +"data-diagnostic-drill.R","276","276","SELECT distinct database_id FROM @schema.@dd_table_prefixdata_diagnostics_summary;" +"data-diagnostic-drill.R","303","304","SELECT * FROM @schema.@dd_table_prefixdata_diagnostics_summary WHERE analysis_name in ('@analysis');" +"data-diagnostic-drill.R","333","334","SELECT distinct database_id FROM @schema.@dd_table_prefixdata_diagnostics_summary WHERE analysis_name in ('@analysis');" +"data-diagnostic-summary.R","145","146","SELECT distinct sum.analysis_name FROM @schema.@dd_table_prefixdata_diagnostics_summary as sum;" +"data-diagnostic-summary.R","169","176","SELECT distinct sum.analysis_id, sum.analysis_name, sum.database_id, sum.total_fails FROM @schema.@dd_table_prefixdata_diagnostics_summary as sum where sum.analysis_name in (@names);" +"datasources-main.R","192","193","SELECT * from @schema.@database_table ;" +"estimation-cohort-method-attrition.R","120","130","SELECT cmat.* FROM @schema.@cm_table_prefixattrition cmat WHERE cmat.target_id = @target_id AND cmat.comparator_id = @comparator_id AND cmat.outcome_id = @outcome_id AND cmat.analysis_id = @analysis_id AND cmat.database_id = '@database_id';" +"estimation-cohort-method-covariateBalance.R","330","334","select distinct d.cdm_source_abbreviation, i.database_id from @result_schema.@cm_table_prefixCOVARIATE_BALANCE i inner join @result_schema.@database_table_name d on d.database_id = i.database_id ;" +"estimation-cohort-method-covariateBalance.R","359","380","SELECT cmscb.database_id, cmc.covariate_name, --cmc.analysis_id analysis_id, cmscb.target_mean_before before_matching_mean_treated, cmscb.comparator_mean_before before_matching_mean_comparator, abs(cmscb.std_diff_before) abs_before_matching_std_diff, --absBeforeMatchingStdDiff cmscb.target_mean_after after_matching_mean_treated, cmscb.comparator_mean_after after_matching_mean_comparator, abs(cmscb.std_diff_after) abs_after_matching_std_diff FROM @results_schema.@cm_table_prefixshared_covariate_balance cmscb JOIN @results_schema.@cm_table_prefixcovariate cmc ON cmscb.covariate_id = cmc.covariate_id AND cmscb.analysis_id = cmc.analysis_id AND cmscb.database_id = cmc.database_id -- database_id optional -- JOIN @results_schema.@cm_table_prefixcovariate_analysis cmca ON cmca.analysis_id = cmc.analysis_id -- question: shouldn't we have a covariate_analysis_id in @table_prefixcovariate table? WHERE cmscb.target_id = @target_id AND cmscb.comparator_id = @comparator_id AND cmscb.analysis_id = @analysis_id --AND cmc.covariate_analysis_id = @covariate_analysis_id AND cmscb.database_id = '@database_id'" +"estimation-cohort-method-covariateBalance.R","601","602","select distinct covariate_analysis_id, covariate_analysis_name from @result_schema.@cm_table_prefixCOVARIATE_ANALYSIS;" +"estimation-cohort-method-covariateBalance.R","632","651","SELECT DISTINCT dmd.cdm_source_abbreviation database_name, cmds.analysis_id, cmds.target_id, cmds.comparator_id, cmds.outcome_id, cmds.max_sdm, cmds.ease FROM @schema.@cm_table_prefixdiagnostics_summary cmds INNER JOIN @schema.@database_table dmd ON dmd.database_id = cmds.database_id where cmds.target_id = @target_id and cmds.comparator_id = @comparator_id and cmds.outcome_id = @outcome_id and cmds.analysis_id = @analysis_id and cmds.database_id = '@database_id' ;" +"estimation-cohort-method-diagnostics.R","63","94","SELECT DISTINCT dmd.cdm_source_abbreviation database_name, cma.description analysis, cgcd1.cohort_name target, cgcd2.cohort_name comparator, cgcd3.cohort_name outcome, cmds.max_sdm, cmds.shared_max_sdm, cmds.equipoise, cmds.mdrr, cmds.ease, cmds.balance_diagnostic, cmds.shared_balance_diagnostic, -- added back cmds.equipoise_diagnostic, cmds.mdrr_diagnostic, cmds.ease_diagnostic, cmds.unblind FROM @schema.@cm_table_prefixdiagnostics_summary cmds INNER JOIN @schema.@cm_table_prefixanalysis cma ON cmds.analysis_id = cma.analysis_id INNER JOIN @schema.@database_table dmd ON dmd.database_id = cmds.database_id INNER JOIN @schema.@cg_table_prefixcohort_definition cgcd1 ON cmds.target_id = cgcd1.cohort_definition_id INNER JOIN @schema.@cg_table_prefixcohort_definition cgcd2 ON cmds.comparator_id = cgcd2.cohort_definition_id INNER JOIN @schema.@cg_table_prefixcohort_definition cgcd3 ON cmds.outcome_id = cgcd3.cohort_definition_id where cgcd1.cohort_definition_id in (@targets) {@use_comparators}?{and cgcd2.cohort_definition_id in (@comparators)} and cgcd3.cohort_definition_id in (@outcomes) {@use_analyses}?{and cma.analysis_id in (@analyses)} ;" +"estimation-cohort-method-kaplainMeier.R","144","155","SELECT * FROM @schema.@cm_table_prefixkaplan_meier_dist cmkmd WHERE cmkmd.target_id = @target_id AND cmkmd.comparator_id = @comparator_id AND cmkmd.outcome_id = @outcome_id AND cmkmd.analysis_id = @analysis_id AND cmkmd.database_id = '@database_id';" +"estimation-cohort-method-populationCharacteristics.R","176","202","SELECT cmcb.database_id, cmcb.covariate_id, cmc.covariate_name, cmc.covariate_analysis_id analysis_id, cmcb.target_mean_before before_ps_adjustment_mean_treated, cmcb.comparator_mean_before before_ps_adjustment_mean_comparator, abs(cmcb.std_diff_before) abs_before_ps_adjustment_std_diff, cmcb.target_mean_after after_ps_adjustment_mean_treated, cmcb.comparator_mean_after after_ps_adjustment_mean_comparator, abs(cmcb.std_diff_after) abs_after_ps_adjustment_std_diff FROM (select * from @schema.@cm_table_prefixcovariate_balance WHERE target_id = @target_id AND comparator_id = @comparator_id AND outcome_id = @outcome_id AND analysis_id = @analysis_id AND database_id = '@database_id' ) as cmcb INNER JOIN @schema.@cm_table_prefixcovariate cmc ON cmcb.covariate_id = cmc.covariate_id AND cmcb.analysis_id = cmc.analysis_id AND cmcb.database_id = cmc.database_id -- database_id optional" +"estimation-cohort-method-power.R","394","399","SELECT cma.* FROM @schema.@cm_table_prefixanalysis cma" +"estimation-cohort-method-power.R","423","433","SELECT * FROM @schema.@cm_table_prefixfollow_up_dist cmfud WHERE cmfud.target_id = @target_id AND cmfud.comparator_id = @comparator_id AND cmfud.outcome_id = @outcome_id AND cmfud.analysis_id = @analysis_id" +"estimation-cohort-method-propensityModel.R","145","171","SELECT cmc.covariate_id, cmc.covariate_name, cmpm.coefficient FROM ( SELECT covariate_id, covariate_name FROM @schema.@cm_table_prefixcovariate WHERE analysis_id = @analysis_id AND database_id = '@database_id' UNION SELECT 0 as covariate_id, 'intercept' as covariate_name) cmc JOIN @schema.@cm_table_prefixpropensity_model cmpm ON cmc.covariate_id = cmpm.covariate_id WHERE cmpm.target_id = @target_id AND cmpm.comparator_id = @comparator_id AND cmpm.analysis_id = @analysis_id AND cmpm.database_id = '@database_id'" +"estimation-cohort-method-propensityScoreDistribution.R","139","149","SELECT database_id, target_id, comparator_id, outcome_id, analysis_id, equipoise FROM @schema.@cm_table_prefixdiagnostics_summary cmpsd WHERE cmpsd.target_id = @target_id AND cmpsd.comparator_id = @comparator_id AND cmpsd.analysis_id = @analysis_id AND cmpsd.outcome_id = @outcome_id" +"estimation-cohort-method-propensityScoreDistribution.R","187","196","SELECT * FROM @schema.@cm_table_prefixpreference_score_dist cmpsd WHERE cmpsd.target_id = @target_id AND cmpsd.comparator_id = @comparator_id AND cmpsd.analysis_id = @analysis_id" +"estimation-cohort-method-results.R","297","356","SELECT cma.analysis_id, cma.description description, dmd.database_id database_id, dmd.cdm_source_abbreviation cdm_source_abbreviation, cmr.target_id, cg1.cohort_name as target, cmr.outcome_id, cg2.cohort_name as outcome, cmr.comparator_id, cg3.cohort_name as comparator, case when COALESCE(cmds.unblind, 0) = 0 then NULL else cmr.rr end rr, case when COALESCE(cmds.unblind, 0) = 0 then NULL else cmr.ci_95_lb end ci_95_lb, case when COALESCE(cmds.unblind, 0) = 0 then NULL else cmr.ci_95_ub end ci_95_ub, case when COALESCE(cmds.unblind, 0) = 0 then NULL else cmr.p end p, case when COALESCE(cmds.unblind, 0) = 0 then NULL else cmr.log_rr end log_rr, case when COALESCE(cmds.unblind, 0) = 0 then NULL else cmr.se_log_rr end se_log_rr, cmr.target_subjects, cmr.comparator_subjects, cmr.target_days, cmr.comparator_days, cmr.target_outcomes, cmr.comparator_outcomes, case when COALESCE(cmds.unblind, 0) = 0 then NULL else cmr.calibrated_rr end calibrated_rr, case when COALESCE(cmds.unblind, 0) = 0 then NULL else cmr.calibrated_ci_95_lb end calibrated_ci_95_lb, case when COALESCE(cmds.unblind, 0) = 0 then NULL else cmr.calibrated_ci_95_ub end calibrated_ci_95_ub, case when COALESCE(cmds.unblind, 0) = 0 then NULL else cmr.calibrated_p end calibrated_p, case when COALESCE(cmds.unblind, 0) = 0 then NULL else cmr.calibrated_log_rr end calibrated_log_rr, case when COALESCE(cmds.unblind, 0) = 0 then NULL else cmr.calibrated_se_log_rr end calibrated_se_log_rr, COALESCE(cmds.unblind, 0) unblind FROM @schema.@cm_table_prefixanalysis cma JOIN @schema.@cm_table_prefixresult cmr on cmr.analysis_id = cma.analysis_id JOIN @schema.@database_table dmd on dmd.database_id = cmr.database_id LEFT JOIN @schema.@cm_table_prefixdiagnostics_summary cmds on cmds.analysis_id = cmr.analysis_id AND cmds.target_id = cmr.target_id AND cmds.comparator_id = cmr.comparator_id AND cmds.outcome_id = cmr.outcome_id AND cmds.database_id = cmr.database_id inner join @schema.@cg_table_prefixcohort_definition cg1 on cg1.cohort_definition_id = cmr.target_id inner join @schema.@cg_table_prefixcohort_definition cg2 on cg2.cohort_definition_id = cmr.outcome_id inner join @schema.@cg_table_prefixcohort_definition cg3 on cg3.cohort_definition_id = cmr.comparator_id where cmr.target_id in (@targets) {@use_comparators}?{and cmr.comparator_id in (@comparators)} and cmr.outcome_id in (@outcomes) ;" +"estimation-cohort-method-results.R","386","461","select r.analysis_id, a.description, 0 as database_id, ev.evidence_synthesis_description as cdm_source_abbreviation, r.target_id, c1.cohort_name as target, r.outcome_id, c3.cohort_name as outcome, r.comparator_id, c2.cohort_name as comparator, NULL as rr, NULL as ci_95_lb, NULL as ci_95_ub, NULL as p, NULL as log_rr, NULL as se_log_rr, 0 as target_subjects, 0 as comparator_subjects, 0 as target_days, 0 as comparator_days, 0 as target_outcomes, 0 as comparator_outcomes, r.calibrated_rr, r.calibrated_ci_95_lb, r.calibrated_ci_95_ub, r.calibrated_p, r.calibrated_log_rr, r.calibrated_se_log_rr, 1 unblind from @schema.@es_table_prefixcm_result as r inner join @schema.@cm_table_prefixtarget_comparator_outcome as tco on r.target_id = tco.target_id and r.comparator_id = tco.comparator_id and r.outcome_id = tco.outcome_id inner join @schema.@es_table_prefixcm_diagnostics_summary as unblind on r.analysis_id = unblind.analysis_id and r.target_id = unblind.target_id and r.comparator_id = unblind.comparator_id and r.outcome_id = unblind.outcome_id inner join @schema.@cg_table_prefixcohort_definition as c1 on c1.cohort_definition_id = r.target_id inner join @schema.@cg_table_prefixcohort_definition as c2 on c2.cohort_definition_id = r.comparator_id inner join @schema.@cg_table_prefixcohort_definition as c3 on c3.cohort_definition_id = r.outcome_id inner join @schema.@cm_table_prefixanalysis as a on a.analysis_id = r.analysis_id inner join @schema.@es_table_prefixanalysis as ev on ev.evidence_synthesis_analysis_id = r.evidence_synthesis_analysis_id where r.calibrated_rr != 0 and tco.outcome_of_interest = 1 and unblind.unblind = 1 and r.target_id in (@target_ids) and r.outcome_id = @outcome_id ;" +"estimation-cohort-method-systematicError.R","161","174","SELECT cmr.*, cmtco.true_effect_size effect_size FROM @schema.@cm_table_prefixresult cmr JOIN @schema.@cm_table_prefixtarget_comparator_outcome cmtco ON cmr.target_id = cmtco.target_id AND cmr.comparator_id = cmtco.comparator_id AND cmr.outcome_id = cmtco.outcome_id WHERE cmtco.outcome_of_interest != 1 AND cmr.target_id = @target_id AND cmr.comparator_id = @comparator_id AND cmr.analysis_id = @analysis_id" +"estimation-cohort-method-systematicError.R","321","338","SELECT DISTINCT dmd.cdm_source_abbreviation database_name, cmds.analysis_id, cmds.target_id, cmds.comparator_id, cmds.max_sdm, cmds.ease FROM @schema.@cm_table_prefixdiagnostics_summary cmds INNER JOIN @schema.@database_table dmd ON dmd.database_id = cmds.database_id where cmds.target_id = @target_id and cmds.comparator_id = @comparator_id and cmds.analysis_id = @analysis_id and cmds.database_id = '@database_id' ;" +"estimation-sccs-diagnostics.R","57","102","SELECT d.cdm_source_abbreviation as database_name, a.description as analysis, c2.cohort_name as target, c3.cohort_name as indication, c.cohort_name as outcome, cov.covariate_name, ds.* FROM @schema.@sccs_table_prefixdiagnostics_summary ds inner join @schema.@sccs_table_prefixexposures_outcome_set eos on ds.exposures_outcome_set_id = eos.exposures_outcome_set_id inner join @schema.@cg_table_prefixcohort_definition as c on c.cohort_definition_id = eos.outcome_id INNER JOIN @schema.@database_table_prefix@database_table d on d.database_id = ds.database_id INNER JOIN @schema.@sccs_table_prefixanalysis a on a.analysis_id = ds.analysis_id INNER JOIN @schema.@sccs_table_prefixcovariate cov on cov.covariate_id = ds.covariate_id and cov.exposures_outcome_set_id = ds.exposures_outcome_set_id and cov.analysis_id = ds.analysis_id and cov.database_id = ds.database_id inner join @schema.@cg_table_prefixcohort_definition as c2 on cov.era_id = c2.cohort_definition_id left join @schema.@cg_table_prefixcohort_definition as c3 on eos.nesting_cohort_id = c3.cohort_definition_id where cov.era_id in (@target_ids) and eos.outcome_id in (@outcome_ids) ;" +"estimation-sccs-results-full.R","459","467","SELECT * FROM @schema.@sccs_table_prefixattrition WHERE database_id = '@database_id' AND analysis_id = @analysis_id AND exposures_outcome_set_id = @exposures_outcome_set_id AND covariate_id = @covariate_id" +"estimation-sccs-results-full.R","489","517","SELECT CASE WHEN era.era_name IS NULL THEN sc.covariate_name ELSE CONCAT(sc.covariate_name, ' : ', era.era_name) END as covariate_name, scr.covariate_id, scr.rr, scr.ci_95_lb, scr.ci_95_ub FROM @schema.@sccs_table_prefixcovariate_result scr INNER JOIN @schema.@sccs_table_prefixcovariate sc ON ( sc.exposures_outcome_set_id = scr.exposures_outcome_set_id AND sc.database_id = scr.database_id AND sc.analysis_id = scr.analysis_id AND sc.covariate_id = scr.covariate_id ) LEFT JOIN @schema.@cg_table_prefixcohort_definition cd ON cd.cohort_definition_id = sc.era_id LEFT JOIN @schema.@sccs_table_prefixera era ON ( era.exposures_outcome_set_id = scr.exposures_outcome_set_id AND era.database_id = scr.database_id AND era.analysis_id = scr.analysis_id AND era.era_id = sc.era_id ) WHERE scr.database_id = '@database_id' AND scr.analysis_id = @analysis_id --AND sc.era_id = @exposure_id --AND scr.rr IS NOT NULL AND scr.exposures_outcome_set_id = @exposures_outcome_set_id" +"estimation-sccs-results-full.R","539","545","SELECT * FROM @schema.@sccs_table_prefixtime_trend WHERE database_id = '@database_id' AND analysis_id = @analysis_id AND exposures_outcome_set_id = @exposures_outcome_set_id" +"estimation-sccs-results-full.R","567","575","SELECT pre_exposure_p FROM @schema.@sccs_table_prefixdiagnostics_summary WHERE database_id = '@database_id' AND covariate_id = @covariate_id AND analysis_id = @analysis_id AND exposures_outcome_set_id = @exposures_outcome_set_id" +"estimation-sccs-results-full.R","593","601","SELECT * , @p as p FROM @schema.@sccs_table_prefixtime_to_event WHERE database_id = '@database_id' AND era_id = @exposure_id AND analysis_id = @analysis_id AND exposures_outcome_set_id = @exposures_outcome_set_id;" +"estimation-sccs-results-full.R","627","634","SELECT * FROM @schema.@sccs_table_prefixevent_dep_observation WHERE database_id = '@database_id' AND analysis_id = @analysis_id AND exposures_outcome_set_id = @exposures_outcome_set_id;" +"estimation-sccs-results-full.R","654","661","SELECT * FROM @schema.@sccs_table_prefixage_spanning WHERE database_id = '@database_id' AND analysis_id = @analysis_id AND exposures_outcome_set_id = @exposures_outcome_set_id" +"estimation-sccs-results-full.R","680","687","SELECT * FROM @schema.@sccs_table_prefixcalendar_time_spanning WHERE database_id = '@database_id' AND analysis_id = @analysis_id AND exposures_outcome_set_id = @exposures_outcome_set_id" +"estimation-sccs-results-full.R","708","716","SELECT * FROM @schema.@sccs_table_prefixspline WHERE database_id = '@database_id' AND analysis_id = @analysis_id AND exposures_outcome_set_id = @exposures_outcome_set_id AND spline_type = '@spline_type';" +"estimation-sccs-results-full.R","740","766","SELECT r.ci_95_lb, r.ci_95_ub, r.log_rr, r.se_log_rr, r.calibrated_ci_95_lb, r.calibrated_ci_95_ub, r.calibrated_log_rr, r.calibrated_se_log_rr, r.exposures_outcome_set_id, e.true_effect_size, c.exposures_outcome_set_id FROM @schema.@sccs_table_prefixresult r INNER JOIN @schema.@sccs_table_prefixexposure e on r.exposures_outcome_set_id = e.exposures_outcome_set_id INNER JOIN @schema.@sccs_table_prefixcovariate c on e.era_id = c.era_id and e.exposures_outcome_set_id = c.exposures_outcome_set_id and c.database_id = r.database_id and c.analysis_id = r.analysis_id and c.covariate_id = r.covariate_id WHERE r.database_id = '@database_id' AND r.analysis_id = @analysis_id AND r.covariate_id = @covariate_id AND e.true_effect_size is not NULL -- AND e.era_id = @era_id ;" +"estimation-sccs-results-full.R","780","784","SELECT top 1 ds.easeFROM @schema.@sccs_table_prefixdiagnostics_summary ds WHERE ds.database_id = '@database_id' AND ds.analysis_id = @analysis_id AND ds.covariate_id = @covariate_id;" +"estimation-sccs-results.R","250","344","SELECT ds.cdm_source_abbreviation as database_name, sr.database_id, sc.covariate_id, sc.covariate_name, sc.era_id, sc.covariate_analysis_id, sr.analysis_id, a.description, eos.outcome_id, cg1.cohort_name as outcome, cg2.cohort_name as target, cg3.cohort_name as indication, eos.nesting_cohort_id as indication_id, eos.exposures_outcome_set_id, sr.outcome_subjects, sr.outcome_events, sr.outcome_observation_periods, sr.covariate_subjects, sr.covariate_days, sr.covariate_eras, sr.covariate_outcomes, sr.observed_days, case when COALESCE(sds.unblind, 0) = 0 then NULL else sr.rr end rr, case when COALESCE(sds.unblind, 0) = 0 then NULL else sr.ci_95_lb end ci_95_lb, case when COALESCE(sds.unblind, 0) = 0 then NULL else sr.ci_95_ub end ci_95_ub, case when COALESCE(sds.unblind, 0) = 0 then NULL else sr.p end p, case when COALESCE(sds.unblind, 0) = 0 then NULL else sr.log_rr end log_rr, case when COALESCE(sds.unblind, 0) = 0 then NULL else sr.se_log_rr end se_log_rr, case when COALESCE(sds.unblind, 0) = 0 then NULL else sr.calibrated_rr end calibrated_rr, case when COALESCE(sds.unblind, 0) = 0 then NULL else sr.calibrated_ci_95_lb end calibrated_ci_95_lb, case when COALESCE(sds.unblind, 0) = 0 then NULL else sr.calibrated_ci_95_ub end calibrated_ci_95_ub, case when COALESCE(sds.unblind, 0) = 0 then NULL else sr.calibrated_p end calibrated_p, case when COALESCE(sds.unblind, 0) = 0 then NULL else sr.calibrated_log_rr end calibrated_log_rr, case when COALESCE(sds.unblind, 0) = 0 then NULL else sr.calibrated_se_log_rr end calibrated_se_log_rr, case when COALESCE(sds.unblind, 0) = 0 then NULL else sr.llr end llr, sds.mdrr, --sds.ease, --sds.time_trend_p, --sds.pre_exposure_p, --sds.mdrr_diagnostic, --sds.ease_diagnostic, --sds.time_trend_diagnostic, --sds.pre_exposure_diagnostic, sds.unblind FROM @schema.@sccs_table_prefixresult sr INNER JOIN @schema.@database_table_prefix@database_table ds ON sr.database_id = ds.database_id INNER JOIN @schema.@sccs_table_prefixdiagnostics_summary sds ON ( sds.exposures_outcome_set_id = sr.exposures_outcome_set_id AND sds.database_id = sr.database_id AND sds.analysis_id = sr.analysis_id AND sds.covariate_id = sr.covariate_id ) INNER JOIN @schema.@sccs_table_prefixcovariate sc ON ( sc.exposures_outcome_set_id = sr.exposures_outcome_set_id AND sc.database_id = sr.database_id AND sc.analysis_id = sr.analysis_id AND sc.covariate_id = sr.covariate_id ) INNER JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON eos.exposures_outcome_set_id = sr.exposures_outcome_set_id INNER JOIN @schema.@sccs_table_prefixanalysis a on a.analysis_id = sr.analysis_id inner join @schema.@cg_table_prefixcohort_definition cg1 on cg1.cohort_definition_id = eos.outcome_id inner join @schema.@cg_table_prefixcohort_definition as cg2 on cg2.cohort_definition_id = sc.era_id left join @schema.@cg_table_prefixcohort_definition as cg3 on eos.nesting_cohort_id = cg3.cohort_definition_id WHERE eos.outcome_id IN (@outcome_ids) AND sc.era_id IN (@exposure_ids) ;" +"estimation-sccs-results.R","372","459","select distinctev.evidence_synthesis_description as database_name, 0 as database_id, cov.covariate_id, -- exists? cov.covariate_name, cov.era_id, 0 as covariate_analysis_id, esr.analysis_id, a.description, eos.outcome_id, c3.cohort_name as outcome, c1.cohort_name as target, c4.cohort_name as indication, eos.nesting_cohort_id as indication_id, eos.exposures_outcome_set_id, esr.outcome_subjects, esr.outcome_events, esr.outcome_observation_periods, esr.covariate_subjects, esr.covariate_days, esr.covariate_eras, esr.covariate_outcomes, esr.observed_days, esr.rr, esr.ci_95_lb, esr.ci_95_ub, esr.p, esr.log_rr, esr.se_log_rr, esr.calibrated_rr, esr.calibrated_ci_95_lb, esr.calibrated_ci_95_ub, esr.calibrated_p, esr.calibrated_log_rr, esr.calibrated_se_log_rr, NULL as llr, esd.mdrr, esd.unblind as unblind from @schema.@es_table_prefixsccs_result as esr inner join @schema.@sccs_table_prefixexposures_outcome_set as eos on esr.exposures_outcome_set_id = eos.exposures_outcome_set_id inner join @schema.@sccs_table_prefixcovariate as cov on esr.covariate_id = cov.covariate_id and esr.analysis_id = cov.analysis_id and esr.exposures_outcome_set_id = cov.exposures_outcome_set_id inner join @schema.@es_table_prefixsccs_diagnostics_summary as esd on esr.analysis_id = esd.analysis_id and esr.exposures_outcome_set_id = esd.exposures_outcome_set_id and esr.covariate_id = esd.covariate_id and esr.evidence_synthesis_analysis_id = esd.evidence_synthesis_analysis_id inner join @schema.@cg_table_prefixcohort_definition as c1 on c1.cohort_definition_id = cov.era_id inner join @schema.@cg_table_prefixcohort_definition as c3 on c3.cohort_definition_id = eos.outcome_id inner join @schema.@sccs_table_prefixanalysis as a on a.analysis_id = esr.analysis_id inner join @schema.@es_table_prefixanalysis as ev on ev.evidence_synthesis_analysis_id = esr.evidence_synthesis_analysis_id left join @schema.@cg_table_prefixcohort_definition as c4 on eos.nesting_cohort_id = c4.cohort_definition_id where esr.calibrated_rr != 0 and esd.unblind = 1 and cov.era_id in (@target_ids) and eos.outcome_id in (@outcome_id) ;" +"helpers-getPredictionResult.R","15","15","SELECT * FROM @schema.@table_name WHERE performance_id = @performance_id" +"helpers-sccsDataPulls.R","6","22","select distinct c.cohort_name as name, eos.outcome_id from @schema.@sccs_table_prefixexposures_outcome_set as eos inner join @schema.@cg_table_prefixcohort_definition as c on c.cohort_definition_id = eos.outcome_id inner join @schema.@sccs_table_prefixexposure as e on e.exposures_outcome_set_id = eos.exposures_outcome_set_id --where e.true_effect_size != 1 ;" +"helpers-sccsDataPulls.R","41","59","SELECTe.era_id AS exposure_id, c2.cohort_name as exposure_name, coalesce(c.cohort_definition_id, -1) as indication_id, coalesce(c.cohort_name, 'No indication') as indication_name FROM @schema.@sccs_table_prefixexposures_outcome_set eos LEFT JOIN @schema.@cg_table_prefixcohort_definition c on eos.nesting_cohort_id = c.cohort_definition_id INNER JOIN @schema.@sccs_table_prefixcovariate cov ON eos.exposures_outcome_set_id = cov.exposures_outcome_set_id INNER JOIN @schema.@sccs_table_prefixexposure e ON eos.exposures_outcome_set_id = e.exposures_outcome_set_id AND cov.era_id = e.era_id INNER JOIN @schema.@cg_table_prefixcohort_definition c2 on e.era_id = c2.cohort_definition_id GROUP BY c.cohort_definition_id, c.cohort_name, e.era_id, c2.cohort_name" +"helpers-sccsDataPulls.R","77","99","select distinct c1.cohort_name as name, e.era_id as exposure_id from @schema.@sccs_table_prefixresult r INNER JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON r.exposures_outcome_set_id = eos.exposures_outcome_set_id INNER JOIN @schema.@sccs_table_prefixcovariate cov ON r.exposures_outcome_set_id = cov.exposures_outcome_set_id AND r.analysis_id = cov.analysis_id AND r.covariate_id = cov.covariate_id INNER JOIN @schema.@sccs_table_prefixexposure e ON r.exposures_outcome_set_id = e.exposures_outcome_set_id AND cov.era_id = e.era_id INNER JOIN @schema.@cg_table_prefixcohort_definition as c1 on c1.cohort_definition_id = e.era_id WHERE e.true_effect_size IS NULL ;" +"helpers-sccsDataPulls.R","119","129","select distinct ds.cdm_source_abbreviation as database_name, r.database_id from @schema.@database_table_prefix@database_table ds inner join @schema.@sccs_table_prefixresult as r on r.database_id = ds.database_id;" +"helpers-sccsDataPulls.R","150","161","select distinct a.description as name, r.analysis_id from @schema.@sccs_table_prefixresult as r inner join @schema.@sccs_table_prefixanalysis as a on r.analysis_id = a.analysis_id ;" +"helpers-sccsDataPulls.R","186","217","SELECT CASE WHEN era.era_name IS NULL THEN sc.covariate_name ELSE CONCAT(sc.covariate_name, ' : ', era.era_name) END as covariate_name, scr.covariate_id, scr.rr, scr.ci_95_lb, scr.ci_95_ub FROM @schema.@sccs_table_prefixcovariate_result scr INNER JOIN @schema.@sccs_table_prefixcovariate sc ON ( sc.exposures_outcome_set_id = scr.exposures_outcome_set_id AND sc.database_id = scr.database_id AND sc.analysis_id = scr.analysis_id AND sc.covariate_id = scr.covariate_id ) LEFT JOIN @schema.@cg_table_prefixcohort_definition cd ON cd.cohort_definition_id = sc.era_id LEFT JOIN @schema.@sccs_table_prefixera era ON ( era.exposures_outcome_set_id = scr.exposures_outcome_set_id AND era.database_id = scr.database_id AND era.analysis_id = scr.analysis_id AND era.era_id = sc.era_id ) INNER JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON eos.exposures_outcome_set_id = scr.exposures_outcome_set_id WHERE scr.database_id = '@database_id' AND scr.analysis_id = @analysis_id AND eos.outcome_id = @outcome_id AND sc.era_id = @exposure_id AND scr.rr IS NOT NULL" +"helpers-sccsDataPulls.R","236","245","SELECT tt.* FROM @schema.@sccs_table_prefixtime_trend tt inner join @schema.@sccs_table_prefixexposures_outcome_set eos on tt.exposures_outcome_set_id = eos.exposures_outcome_set_id WHERE database_id = '@database_id' AND analysis_id = @analysis_id AND outcome_id = @outcome_id" +"helpers-sccsDataPulls.R","265","275","SELECT ds.pre_exposure_p FROM @schema.@sccs_table_prefixdiagnostics_summary ds inner join @schema.@sccs_table_prefixexposures_outcome_set eos on ds.exposures_outcome_set_id = eos.exposures_outcome_set_id WHERE ds.database_id = '@database_id' AND ds.covariate_id = @covariate_id AND ds.analysis_id = @analysis_id AND eos.outcome_id = @outcome_id" +"helpers-sccsDataPulls.R","288","298","SELECT tte.*, @p as p FROM @schema.@sccs_table_prefixtime_to_event tte inner join @schema.@sccs_table_prefixexposures_outcome_set eos on tte.exposures_outcome_set_id = eos.exposures_outcome_set_id WHERE tte.database_id = '@database_id' AND tte.era_id = @exposure_id AND tte.analysis_id = @analysis_id AND eos.outcome_id = @outcome_id" +"helpers-sccsDataPulls.R","324","335","SELECT a.* FROM @schema.@sccs_table_prefixattrition a inner join @schema.@sccs_table_prefixexposures_outcome_set eos on a.exposures_outcome_set_id = eos.exposures_outcome_set_id WHERE a.database_id = '@database_id' AND a.analysis_id = @analysis_id AND eos.outcome_id = @outcome_id AND a.covariate_id = @covariate_id" +"helpers-sccsDataPulls.R","351","361","SELECT o.* FROM @schema.@sccs_table_prefixevent_dep_observation o inner join @schema.@sccs_table_prefixexposures_outcome_set eos on o.exposures_outcome_set_id = eos.exposures_outcome_set_id WHERE o.database_id = '@database_id' AND o.analysis_id = @analysis_id AND eos.outcome_id = @outcome_id" +"helpers-sccsDataPulls.R","376","386","SELECT asp.* FROM @schema.@sccs_table_prefixage_spanning asp inner join @schema.@sccs_table_prefixexposures_outcome_set eos on asp.exposures_outcome_set_id = eos.exposures_outcome_set_id WHERE asp.database_id = '@database_id' AND asp.analysis_id = @analysis_id AND eos.outcome_id = @outcome_id" +"helpers-sccsDataPulls.R","401","411","SELECT ts.* FROM @schema.@sccs_table_prefixcalendar_time_spanning ts inner join @schema.@sccs_table_prefixexposures_outcome_set eos on ts.exposures_outcome_set_id = eos.exposures_outcome_set_id WHERE ts.database_id = '@database_id' AND ts.analysis_id = @analysis_id AND eos.outcome_id = @outcome_id" +"helpers-sccsDataPulls.R","428","439","SELECT s.* FROM @schema.@sccs_table_prefixspline s inner join @schema.@sccs_table_prefixexposures_outcome_set eos on s.exposures_outcome_set_id = eos.exposures_outcome_set_id WHERE s.database_id = '@database_id' AND s.analysis_id = @analysis_id AND eos.outcome_id = @outcome_id AND s.spline_type = '@spline_type';" +"helpers-sccsDataPulls.R","457","474","SELECT ci_95_lb, ci_95_ub, log_rr, se_log_rr, calibrated_ci_95_lb, calibrated_ci_95_ub, calibrated_log_rr, calibrated_se_log_rr, true_effect_size FROM @schema.@sccs_table_prefixresult sr INNER JOIN @schema.@sccs_table_prefixcovariate sc ON ( sc.exposures_outcome_set_id = sr.exposures_outcome_set_id AND sc.database_id = sr.database_id AND sc.analysis_id = sr.analysis_id AND sc.covariate_id = sr.covariate_id ) INNER JOIN @schema.@sccs_table_prefixexposure se ON ( se.exposures_outcome_set_id = sr.exposures_outcome_set_id AND se.era_id = sc.era_id ) WHERE sr.database_id = '@database_id' AND sr.analysis_id = @analysis_id AND sr.covariate_id = @covariate_id" +"helpers-sccsDataPulls.R","491","510","SELECT ds.* FROM @schema.@sccs_table_prefixdiagnostics_summary ds inner join @schema.@sccs_table_prefixexposures_outcome_set eos on ds.exposures_outcome_set_id = eos.exposures_outcome_set_id inner join @schema.@sccs_table_prefixcovariate cov on cov.covariate_id = ds.covariate_id and cov.exposures_outcome_set_id = ds.exposures_outcome_set_id and cov.analysis_id = ds.analysis_id and cov.database_id = ds.database_id WHERE ds.database_id = '@database_id' AND ds.analysis_id = @analysis_id AND ds.covariate_id = @covariate_id AND eos.outcome_id = @outcome_id AND cov.era_id = @exposure_id" +"patient-level-prediction-covariateSummary.R","286","287","SELECT train_details FROM @schema.@plp_table_prefixmodels WHERE database_id = @database_id and model_design_id = @model_design_id;" +"patient-level-prediction-covariateSummary.R","444","444","SELECT * FROM @schema.@plp_table_prefixcovariate_summary WHERE performance_id = @performance_id;" +"patient-level-prediction-covariateSummary.R","477","478","SELECT intercept FROM @schema.@plp_table_prefixmodels WHERE database_id = @database_id and model_design_id = @model_design_id" +"patient-level-prediction-designSummary.R","271","281","SELECT distinct cohorts.cohort_id, cohorts.cohort_name FROM @schema.@plp_table_prefixmodel_designs as model_designs inner join (SELECT c.cohort_id, cd.cohort_name FROM @schema.@plp_table_prefixcohorts c inner join @schema.@cg_table_prefixcohort_definition cd on c.cohort_definition_id = cd.cohort_definition_id ) AS cohorts ON model_designs.@type_id = cohorts.cohort_id ;" +"patient-level-prediction-designSummary.R","310","368","SELECT model_designs.model_design_id, model_settings.model_type AS model_type, targets.cohort_name AS target, outcomes.cohort_name AS outcome, tars.tar_start_day, tars.tar_start_anchor, tars.tar_end_day, tars.tar_end_anchor, COUNT(distinct diag.database_id) as diag_databases, COUNT(distinct d.database_id) dev_databases, MIN(p.value) min_AUROC, AVG(p.value) mean_AUROC, MAX(p.value) max_AUROC, COUNT(distinct v.database_id) val_databases FROM @schema.@plp_table_prefixmodel_designs as model_designs inner join @schema.@plp_table_prefixmodel_settings as model_settings on model_designs.model_setting_id = model_settings.model_setting_id LEFT JOIN @schema.@plp_table_prefixperformances AS results on model_designs.model_design_id = results.model_design_id LEFT JOIN (select * from @schema.@plp_table_prefixEVALUATION_STATISTICS where EVALUATION = 'Test' and METRIC = 'AUROC') p on p.performance_id = results.performance_id LEFT JOIN (SELECT c.cohort_id, cd.cohort_name FROM @schema.@plp_table_prefixcohorts c inner join @schema.@cg_table_prefixcohort_definition cd on c.cohort_definition_id = cd.cohort_definition_id ) AS targets ON model_designs.target_id = targets.cohort_id LEFT JOIN (SELECT c.cohort_id, cd.cohort_name FROM @schema.@plp_table_prefixcohorts c inner join @schema.@cg_table_prefixcohort_definition cd on c.cohort_definition_id = cd.cohort_definition_id ) AS outcomes ON model_designs.outcome_id = outcomes.cohort_id LEFT JOIN @schema.@plp_table_prefixtars AS tars ON model_designs.tar_id = tars.tar_id LEFT JOIN @schema.@plp_table_prefixdatabase_details AS d ON results.development_database_id = d.database_id LEFT JOIN @schema.@plp_table_prefixdatabase_details AS v ON results.validation_database_id = v.database_id LEFT JOIN @schema.@plp_table_prefixdiagnostics AS diag ON results.development_database_id = diag.database_id WHERE targets.cohort_id in (@target_ids) AND outcomes.cohort_id in (@outcome_ids) GROUP BY model_designs.model_design_id, model_settings.model_type, targets.cohort_name, outcomes.cohort_name, tars.tar_start_day, tars.tar_start_anchor, tars.tar_end_day, tars.tar_end_anchor;" +"patient-level-prediction-diagnostics.R","428","460","SELECT distinct design.MODEL_DESIGN_ID,diagnostics.diagnostic_id, database.DATABASE_NAME, cohortT.COHORT_NAME target_name, cohortO.COHORT_NAME outcome_name, summary.PROBAST_ID, summary.RESULT_VALUE from (select * from @schema.@plp_table_prefixDIAGNOSTICS where MODEL_DESIGN_ID = @model_design_id) as diagnostics inner join @schema.@plp_table_prefixMODEL_DESIGNS design on diagnostics.MODEL_DESIGN_ID = design.MODEL_DESIGN_ID inner join @schema.@plp_table_prefixDIAGNOSTIC_SUMMARY summary on diagnostics.DIAGNOSTIC_ID = summary.DIAGNOSTIC_ID inner join (select dd.database_id, md.cdm_source_abbreviation as database_name from @schema.@database_table_prefixdatabase_meta_data md inner join @schema.@plp_table_prefixdatabase_details dd on md.database_id = dd.database_meta_data_id) as database on database.database_id = diagnostics.database_id inner join @schema.@plp_table_prefixCOHORTS cohortT on cohortT.cohort_id = design.target_id inner join @schema.@plp_table_prefixCOHORTS cohortO on cohortO.cohort_id = design.outcome_id;" +"patient-level-prediction-diagnostics.R","505","505","SELECT * FROM @schema.@plp_table_prefix@table_name WHERE diagnostic_id = @diagnostic_id;" +"patient-level-prediction-diagnostics.R","538","538","SELECT * FROM @schema.@plp_table_prefix@table_name WHERE diagnostic_id = @diagnostic_id;" +"patient-level-prediction-diagnostics.R","557","557","SELECT * FROM @schema.@plp_table_prefix@table_name WHERE diagnostic_id = @diagnostic_id;" +"patient-level-prediction-modelSummary.R","224","224","SELECT * FROM @schema.@plp_table_prefixattrition WHERE performance_id = @performance_id;" +"patient-level-prediction-modelSummary.R","253","303","SELECT distinct results.performance_id, results.model_design_id, results.development_database_id, results.validation_database_id, d.database_acronym AS Dev, v.database_acronym AS Val, targets.cohort_name AS T, outcomes.cohort_name AS O, results.execution_date_time as time_stamp, tars.tar_start_day, tars.tar_start_anchor, tars.tar_end_day, tars.tar_end_anchor, ROUND(aucResult.auc, 3) as auroc, ROUND(auprcResult.auprc,4) as auprc, nResult.population_size, oResult.outcome_count, ROUND(nTest.test_size*100.0/nResult.population_size, 1) as eval_percent, ROUND(oResult.outcome_count*100.0/nResult.population_size,4) as outcome_percent, results.model_development FROM (select * from @schema.@plp_table_prefixperformances where model_design_id = @model_design_id) AS results inner join @schema.@plp_table_prefixmodel_designs as model_designs on model_designs.model_design_id = results.model_design_id LEFT JOIN (SELECT c.cohort_id, cd.cohort_name FROM @schema.@plp_table_prefixcohorts c inner join @schema.@cg_table_prefixcohort_definition cd on c.cohort_definition_id = cd.cohort_definition_id ) AS targets ON results.target_id = targets.cohort_id LEFT JOIN (SELECT c.cohort_id, cd.cohort_name FROM @schema.@plp_table_prefixcohorts c inner join @schema.@cg_table_prefixcohort_definition cd on c.cohort_definition_id = cd.cohort_definition_id ) AS outcomes ON results.outcome_id = outcomes.cohort_id LEFT JOIN (select dd.database_id, md.cdm_source_abbreviation database_acronym from @schema.@database_table_prefix@database_table md inner join @schema.@plp_table_prefixdatabase_details dd on md.database_id = dd.database_meta_data_id) AS d ON results.development_database_id = d.database_id LEFT JOIN (select dd.database_id, md.cdm_source_abbreviation database_acronym from @schema.@database_table_prefix@database_table md inner join @schema.@plp_table_prefixdatabase_details dd on md.database_id = dd.database_meta_data_id) AS v ON results.validation_database_id = v.database_id LEFT JOIN @schema.@plp_table_prefixtars AS tars ON results.tar_id = tars.tar_id LEFT JOIN (SELECT performance_id, value AS auc FROM @schema.@plp_table_prefixevaluation_statistics where metric = 'AUROC' and evaluation in ('Test','Validation') ) AS aucResult ON results.performance_id = aucResult.performance_id LEFT JOIN (SELECT performance_id, value AS auprc FROM @schema.@plp_table_prefixevaluation_statistics where metric = 'AUPRC' and evaluation in ('Test','Validation') ) AS auprcResult ON results.performance_id = auprcResult.performance_id LEFT JOIN (SELECT performance_id, sum(value) AS population_size FROM @schema.@plp_table_prefixevaluation_statistics where metric = 'populationSize' and evaluation in ('Train','Test','Validation') group by performance_id) AS nResult ON results.performance_id = nResult.performance_id LEFT JOIN (SELECT performance_id, sum(value) AS outcome_count FROM @schema.@plp_table_prefixevaluation_statistics where metric = 'outcomeCount' and evaluation in ('Train','Test','Validation') group by performance_id) AS oResult ON results.performance_id = oResult.performance_id LEFT JOIN (SELECT performance_id, value AS test_size FROM @schema.@plp_table_prefixevaluation_statistics where metric = 'populationSize' and evaluation in ('Test', 'Validation') ) AS nTest ON results.performance_id = nTest.performance_id;" +"patient-level-prediction-settings.R","350","380","SELECT tempD.dev_db, tempV.val_db FROM (select * from @schema.@plp_table_prefixperformances WHERE performance_id = @performance_id) perf inner join (select dd.database_id, dmd.cdm_source_name as dev_db from @schema.@plp_table_prefixdatabase_details as dd inner join @schema.@database_table_prefixdatabase_meta_data as dmd on dd.database_meta_data_id = dmd.database_id) tempD on tempD.database_id = perf.development_database_id inner join (select dd.database_id, dmd.cdm_source_name as val_db from @schema.@plp_table_prefixdatabase_details as dd inner join @schema.@database_table_prefixdatabase_meta_data dmd on dd.database_meta_data_id = dmd.database_id) tempV on tempV.database_id = perf.validation_database_id ;" +"patient-level-prediction-settings.R","412","414","SELECT * FROM @schema.@plp_table_prefixmodel_designs WHERE model_design_id = @model_design_id;" +"patient-level-prediction-settings.R","437","437","SELECT * FROM @schema.@plp_table_prefixmodel_settings WHERE model_setting_id = @model_setting_id;" +"patient-level-prediction-settings.R","452","452","SELECT * FROM @schema.@plp_table_prefixcovariate_settings WHERE covariate_setting_id = @setting_id;" +"patient-level-prediction-settings.R","467","467","SELECT * FROM @schema.@plp_table_prefixpopulation_settings WHERE population_setting_id = @setting_id;" +"patient-level-prediction-settings.R","482","482","SELECT * FROM @schema.@plp_table_prefixfeature_engineering_settings WHERE feature_engineering_setting_id = @setting_id;" +"patient-level-prediction-settings.R","494","494","SELECT * FROM @schema.@plp_table_prefixtidy_covariates_settings WHERE tidy_covariates_setting_id = @setting_id;" +"patient-level-prediction-settings.R","507","507","SELECT * FROM @schema.@plp_table_prefixplp_data_settings WHERE plp_data_setting_id = @setting_id;" +"patient-level-prediction-settings.R","520","520","SELECT * FROM @schema.@plp_table_prefixsample_settings WHERE sample_setting_id = @setting_id;" +"patient-level-prediction-settings.R","533","533","SELECT * FROM @schema.@plp_table_prefixsplit_settings WHERE split_setting_id = @setting_id;" +"patient-level-prediction-settings.R","546","550","SELECT c.*, cd.json as cohort_jsonFROM @schema.@plp_table_prefixcohorts c inner join @schema.@cg_table_prefixcohort_definition cd on c.cohort_definition_id = cd.cohort_definition_id WHERE c.cohort_id = @setting_id;" +"patient-level-prediction-settings.R","564","568","SELECT c.*, cd.json as cohort_jsonFROM @schema.@plp_table_prefixcohorts c inner join @schema.@cg_table_prefixcohort_definition cd on c.cohort_definition_id = cd.cohort_definition_id WHERE c.cohort_id = @setting_id;" +"patient-level-prediction-validation.R","256","311","SELECT results.performance_id, results.model_design_id, --databases.database_acronym AS Dev, d.database_acronym AS Val, targets.cohort_name AS target, outcomes.cohort_name AS outcome, results.population_setting_id, -- pop and plp_data settings? tars.tar_start_day, tars.tar_start_anchor, tars.tar_end_day, tars.tar_end_anchor, ROUND(aucResult.auc, 3) as auroc, ROUND(auclbResult.auclb, 3) as auroclb, ROUND(aucubResult.aucub, 3) as aurocub, ROUND(auprcResult.auprc,4) as auprc, nResult.population_size, oResult.outcome_count, ROUND(nTest.test_size*100.0/nResult.population_size, 1) as eval_percent, ROUND(oResult.outcome_count*100.0/nResult.population_size,4) as outcome_percent, ROUND(calibration_in_large, 3) as calibration_in_large FROM (SELECT * FROM @schema.@plp_table_appendperformances where model_design_id = @model_design_id and development_database_id = @development_database_id ) AS results LEFT JOIN (SELECT a.cohort_id, b.cohort_name FROM @schema.@plp_table_appendcohorts as a inner join @schema.@cg_table_appendcohort_definition as b on a.cohort_definition_id = b.cohort_definition_id) AS targets ON results.target_id = targets.cohort_id LEFT JOIN (SELECT a.cohort_id, b.cohort_name FROM @schema.@plp_table_appendcohorts as a inner join @schema.@cg_table_appendcohort_definition as b on a.cohort_definition_id = b.cohort_definition_id ) AS outcomes ON results.outcome_id = outcomes.cohort_id LEFT JOIN (select dd.database_id, md.cdm_source_abbreviation database_acronym from @schema.@database_table_appenddatabase_meta_data md inner join @schema.@plp_table_appenddatabase_details dd on md.database_id = dd.database_meta_data_id) AS d ON results.validation_database_id = d.database_id LEFT JOIN @schema.@plp_table_appendtars AS tars ON results.tar_id = tars.tar_id LEFT JOIN (SELECT performance_id, value AS auc FROM @schema.@plp_table_appendevaluation_statistics where metric = 'AUROC' and evaluation in ('Test','Validation') ) AS aucResult ON results.performance_id = aucResult.performance_id LEFT JOIN (SELECT performance_id, value AS auclb FROM @schema.@plp_table_appendevaluation_statistics where metric = '95% lower AUROC' and evaluation in ('Test','Validation') ) AS auclbResult ON results.performance_id = auclbResult.performance_id LEFT JOIN (SELECT performance_id, value AS aucub FROM @schema.@plp_table_appendevaluation_statistics where metric = '95% upper AUROC' and evaluation in ('Test','Validation') ) AS aucubResult ON results.performance_id = aucubResult.performance_id LEFT JOIN (SELECT performance_id, value AS auprc FROM @schema.@plp_table_appendevaluation_statistics where metric = 'AUPRC' and evaluation in ('Test','Validation') ) AS auprcResult ON results.performance_id = auprcResult.performance_id LEFT JOIN (SELECT performance_id, value AS calibration_in_large FROM @schema.@plp_table_appendevaluation_statistics where metric = 'calibrationInLarge intercept' and evaluation in ('Test','Validation') ) AS CalibrationInLargeResult ON results.performance_id = CalibrationInLargeResult.performance_id LEFT JOIN (SELECT performance_id, sum(value) AS population_size FROM @schema.@plp_table_appendevaluation_statistics where metric = 'populationSize' and evaluation in ('Test','Train','Validation') group by performance_id) AS nResult ON results.performance_id = nResult.performance_id LEFT JOIN (SELECT performance_id, sum(value) AS outcome_count FROM @schema.@plp_table_appendevaluation_statistics where metric = 'outcomeCount' and evaluation in ('Test','Train','Validation') group by performance_id) AS oResult ON results.performance_id = oResult.performance_id LEFT JOIN (SELECT performance_id, value AS test_size FROM @schema.@plp_table_appendevaluation_statistics where metric = 'populationSize' and evaluation in ('Test','Validation')) AS nTest ON results.performance_id = nTest.performance_id;" +"phevaluator-main.R","532","533","SELECT * FROM @schema.@pv_table_prefixALGORITHM_PERFORMANCE_RESULTS ;" +"phevaluator-main.R","560","561","SELECT * FROM @schema.@pv_table_prefixCOHORT_DEFINITION_SET ;" +"phevaluator-main.R","577","578","SELECT * FROM @schema.@pv_table_prefixDIAGNOSTICS ;" +"phevaluator-main.R","593","594","SELECT * FROM @schema.@pv_table_prefixEVALUATION_INPUT_PARAMETERS ;" +"phevaluator-main.R","609","610","SELECT * FROM @schema.@pv_table_prefixMODEL_COVARIATES ;" +"phevaluator-main.R","633","634","SELECT * FROM @schema.@pv_table_prefixMODEL_COVARIATE_SUMMARY ;" +"phevaluator-main.R","666","667","SELECT * FROM @schema.@pv_table_prefixMODEL_INPUT_PARAMETERS ;" +"phevaluator-main.R","682","683","SELECT * FROM @schema.@pv_table_prefixMODEL_PERFORMANCE ;" +"phevaluator-main.R","698","699","SELECT * FROM @schema.@pv_table_prefixTEST_SUBJECTS ;" +"phevaluator-main.R","714","715","SELECT * FROM @schema.@pv_table_prefixTEST_SUBJECTS_COVARIATES ;" +"report-main.R","772","772","select distinct * from @schema.@cg_table_prefixcohort_definition order by cohort_name;" +"report-main.R","843","911","select distinct tid, oid from ( {@characterization} ? { select distinct TARGET_COHORT_ID as tid, OUTCOME_COHORT_ID as oid from @schema.@c_table_prefixcohort_details where TARGET_COHORT_ID != 0 and OUTCOME_COHORT_ID != 0 } {@cohort_incidence} ? { {@characterization}?{union} select distinct TARGET_COHORT_DEFINITION_ID as tid, OUTCOME_COHORT_DEFINITION_ID as oid from @schema.@ci_table_prefixincidence_summary } {@cohort_method} ? { {@cohort_incidence | @characterization}?{union} select distinct TARGET_ID as tid, OUTCOME_ID as oid from @schema.@cm_table_prefixtarget_comparator_outcome where OUTCOME_OF_INTEREST = 1 } {@prediction} ? { {@cohort_method | @cohort_incidence | @characterization}?{union} select distinct c1.cohort_definition_id as tid, c2.cohort_definition_id as oid from @schema.@plp_table_prefixmodel_designs md inner join @schema.@plp_table_prefixcohorts c1 on c1.cohort_id = md.target_id inner join @schema.@plp_table_prefixcohorts c2 on c2.cohort_id = md.outcome_id } {@sccs} ? { {@cohort_method | @cohort_incidence | @characterization | @prediction}?{union} SELECT distinct cov.era_id as tid, eos.outcome_id as oid FROM @schema.@sccs_table_prefixdiagnostics_summary ds inner join @schema.@sccs_table_prefixexposures_outcome_set eos on ds.exposures_outcome_set_id = eos.exposures_outcome_set_id INNER JOIN @schema.@sccs_table_prefixcovariate cov on cov.covariate_id = ds.covariate_id and cov.exposures_outcome_set_id = ds.exposures_outcome_set_id and cov.analysis_id = ds.analysis_id and cov.database_id = ds.database_id -- adding code to remove the negative controls INNER JOIN @schema.@sccs_table_prefixexposure e ON e.exposures_outcome_set_id = ds.exposures_outcome_set_id AND e.era_id = cov.era_id where e.true_effect_size is NULL } ) temp_t_o ;" diff --git a/extras/rdms/ohdsi_shiny_modules_table_relationships.csv b/extras/rdms/ohdsi_shiny_modules_table_relationships.csv new file mode 100644 index 00000000..1c9929e2 --- /dev/null +++ b/extras/rdms/ohdsi_shiny_modules_table_relationships.csv @@ -0,0 +1,126 @@ +fileName,startLine,endLine,fromClause,joinRelationship +characterization-caseSeries.R,195,224,"FROM @schema.@c_table_prefixsettings s","JOIN @schema.@database_meta_table d ON s.database_id = d.database_id inner" +characterization-caseSeries.R,195,224,"FROM @schema.@c_table_prefixsettings s","JOIN @schema.@c_table_prefixcohort_details cd ON s.setting_id = cd.setting_id and s.database_id = cd.database_id and cd.target_cohort_id = @target_id and cd.outcome_cohort_id = @outcome_id and cd.cohort_type = 'Cases' inner" +characterization-caseSeries.R,195,224,"FROM @schema.@c_table_prefixsettings s","JOIN @schema.@cg_table_prefixcohort_definition ct1 ON ct1.cohort_definition_id = cd.target_cohort_id inner" +characterization-caseSeries.R,195,224,"FROM @schema.@c_table_prefixsettings s","JOIN @schema.@cg_table_prefixcohort_definition ct2 ON ct2.cohort_definition_id = cd.outcome_cohort_id" +characterization-caseSeries.R,275,306,"FROM @schema.@c_table_prefixcovariates cov","JOIN @schema.@c_table_prefixcovariate_ref cr ON cov.setting_id = cr.setting_id and cov.database_id = cr.database_id and cov.covariate_id = cr.covariate_id inner" +characterization-caseSeries.R,275,306,"FROM @schema.@c_table_prefixcovariates cov","JOIN @schema.@c_table_prefixsettings s ON cov.setting_id = s.setting_id and cov.database_id = s.database_id" +characterization-caseSeries.R,328,361,"FROM @schema.@c_table_prefixcovariates_continuous cov","JOIN @schema.@c_table_prefixcovariate_ref cr ON cov.setting_id = cr.setting_id and cov.database_id = cr.database_id and cov.covariate_id = cr.covariate_id inner" +characterization-caseSeries.R,328,361,"FROM @schema.@c_table_prefixcovariates_continuous cov","JOIN @schema.@c_table_prefixsettings s ON cov.setting_id = s.setting_id and cov.database_id = s.database_id" +characterization-cohorts.R,791,810,"FROM @schema.@c_table_prefixCOVARIATES cov","JOIN @schema.@c_table_prefixcovariate_ref ref ON cov.covariate_id = ref.covariate_id and cov.setting_id = ref.setting_id and cov.database_id = ref.database_id inner" +characterization-cohorts.R,791,810,"FROM @schema.@c_table_prefixCOVARIATES cov","JOIN @schema.@c_table_prefixsettings s ON s.database_id = cov.database_id and s.setting_id = cov.setting_id" +characterization-cohorts.R,902,925,"FROM @schema.@c_table_prefixCOVARIATES_continuous cov","JOIN @schema.@c_table_prefixcovariate_ref ref ON cov.covariate_id = ref.covariate_id and cov.setting_id = ref.setting_id and cov.database_id = ref.database_id inner" +characterization-cohorts.R,902,925,"FROM @schema.@c_table_prefixCOVARIATES_continuous cov","JOIN @schema.@c_table_prefixsettings s ON cov.setting_id = s.setting_id and cov.database_id = s.database_id inner" +characterization-cohorts.R,902,925,"FROM @schema.@c_table_prefixCOVARIATES_continuous cov","JOIN @schema.@database_meta_table d ON s.database_id = d.database_id" +characterization-cohorts.R,990,999,"FROM @schema.@database_table d","JOIN @schema.@c_table_prefixcohort_details cd ON d.database_id = cd.database_id" +characterization-dechallengeRechallenge.R,329,337,"FROM @schema.@c_table_prefixDECHALLENGE_RECHALLENGE dr","JOIN @schema.@cg_table_prefixCOHORT_DEFINITION t ON dr.TARGET_COHORT_DEFINITION_ID = t.COHORT_DEFINITION_ID inner" +characterization-dechallengeRechallenge.R,329,337,"FROM @schema.@c_table_prefixDECHALLENGE_RECHALLENGE dr","JOIN @schema.@cg_table_prefixCOHORT_DEFINITION o ON dr.OUTCOME_COHORT_DEFINITION_ID = o.COHORT_DEFINITION_ID" +characterization-dechallengeRechallenge.R,390,395,"FROM @schema.@c_table_prefixDECHALLENGE_RECHALLENGE dr","JOIN @schema.@database_table d ON dr.database_id = d.database_id" +characterization-incidence.R,1702,1724,"FROM @result_schema.@incidence_table_prefixINCIDENCE_SUMMARY i","JOIN @result_schema.@incidence_table_prefixOUTCOME_DEF od ON i.outcome_id = od.outcome_id and i.ref_id = od.ref_id" +characterization-incidence.R,1702,1724,"FROM @result_schema.@incidence_table_prefixINCIDENCE_SUMMARY i","JOIN @result_schema.@incidence_table_prefixTAR_DEF tad ON i.tar_id = tad.tar_id and i.ref_id = tad.ref_id" +characterization-incidence.R,1702,1724,"FROM @result_schema.@incidence_table_prefixINCIDENCE_SUMMARY i","JOIN @result_schema.@incidence_table_prefixSUBGROUP_DEF sd ON i.subgroup_id = sd.subgroup_id and i.ref_id = sd.ref_id left" +characterization-incidence.R,1702,1724,"FROM @result_schema.@incidence_table_prefixINCIDENCE_SUMMARY i","JOIN @result_schema.@incidence_table_prefixAGE_GROUP_DEF agd ON i.age_group_id = agd.age_group_id and i.ref_id = agd.ref_id ) i inner" +characterization-incidence.R,1702,1724,"FROM @result_schema.@incidence_table_prefixINCIDENCE_SUMMARY i","JOIN @result_schema.@database_table_name d ON d.database_id = i.database_id inner" +characterization-incidence.R,1702,1724,"FROM @result_schema.@incidence_table_prefixINCIDENCE_SUMMARY i","JOIN @result_schema.@cg_table_prefixcohort_definition ct1 ON ct1.cohort_definition_id = i.target_cohort_definition_id inner" +characterization-incidence.R,1702,1724,"FROM @result_schema.@incidence_table_prefixINCIDENCE_SUMMARY i","JOIN @result_schema.@cg_table_prefixcohort_definition ct2 ON ct2.cohort_definition_id = i.outcome_cohort_definition_id" +characterization-riskFactors.R,287,308,"FROM @schema.@c_table_prefixcovariates cov","JOIN @schema.@c_table_prefixcovariate_ref cr ON cov.setting_id = cr.setting_id and cov.database_id = cr.database_id and cov.covariate_id = cr.covariate_id inner" +characterization-riskFactors.R,287,308,"FROM @schema.@c_table_prefixcovariates cov","JOIN @schema.@c_table_prefixsettings s ON cov.setting_id = s.setting_id and cov.database_id = s.database_id" +characterization-riskFactors.R,328,350,"FROM @schema.@c_table_prefixcovariates_continuous cov","JOIN @schema.@c_table_prefixcovariate_ref cr ON cov.setting_id = cr.setting_id and cov.database_id = cr.database_id and cov.covariate_id = cr.covariate_id inner" +characterization-riskFactors.R,328,350,"FROM @schema.@c_table_prefixcovariates_continuous cov","JOIN @schema.@c_table_prefixsettings s ON cov.setting_id = s.setting_id and cov.database_id = s.database_id" +characterization-timeToEvent.R,265,270,"FROM @schema.@c_table_prefixTIME_TO_EVENT tte","JOIN @schema.@database_table d ON tte.database_id = d.database_id" +cohort-diagnostics-characterization.R,923,933,"FROM @results_database_schema.@table_prefixtemporal_covariate_ref tcr","JOIN @results_database_schema.@table_prefixtemporal_analysis_ref tar ON tar.analysis_id = tcr.analysis_id LEFT" +cohort-diagnostics-characterization.R,923,933,"FROM @results_database_schema.@table_prefixtemporal_covariate_ref tcr","JOIN @results_database_schema.@table_prefixtemporal_covariate_value tcv ON ( tcr.covariate_id = tcv.covariate_id ) LEFT" +cohort-diagnostics-characterization.R,923,933,"FROM @results_database_schema.@table_prefixtemporal_covariate_ref tcr","JOIN @results_database_schema.@table_prefixtemporal_time_ref ttr ON ttr.time_id = tcv.time_id" +cohort-diagnostics-conceptsInDataSource.R,80,117,"FROM @schema.@table_name isc","JOIN @schema.@concept_table c ON concepts.concept_id = c.concept_id" +cohort-diagnostics-incidenceRates.R,118,128,"FROM @schema.@ir_table ir","JOIN @schema.@cc_table cc ON ( ir.database_id = cc.database_id AND ir.cohort_id = cc.cohort_id )" +cohort-diagnostics-indexEventBreakdown.R,99,109,"FROM @schema.@table_name index_event_breakdown","JOIN @vocabulary_database_schema.@concept_table concept ON index_event_breakdown.concept_id = concept.concept_id" +cohort-diagnostics-main.R,101,109,"FROM pg_class c","JOIN pg_namespace n ON n.oid = c.relnamespace" +cohort-diagnostics-orphanConcepts.R,129,153,"FROM @schema.@orphan_table_name oc","JOIN @schema.@cs_table_name cs ON oc.cohort_id = cs.cohort_id AND oc.concept_set_id = cs.concept_set_id INNER" +cohort-diagnostics-orphanConcepts.R,129,153,"FROM @schema.@orphan_table_name oc","JOIN @vocabulary_database_schema.@concept_table c ON oc.concept_id = c.concept_id" +cohort-diagnostics-shared.R,93,99,"FROM @schema.@table_name cc","JOIN @schema.@database_table db ON db.database_id = cc.database_id #" +cohort-diagnostics-visitContext.R,91,97,"FROM @schema.@table_name visit_context","JOIN @vocabulary_database_schema.@concept_table standard_concept ON visit_context.visit_concept_id = standard_concept.concept_id" +cohort-generator-main.R,643,650,"FROM @schema.@cg_table_prefixCOHORT_COUNT cc","JOIN @schema.@database_table_prefix@database_table dt ON cc.database_id = dt.database_id" +cohort-generator-main.R,643,650,"FROM @schema.@cg_table_prefixCOHORT_COUNT cc","JOIN @schema.@cg_table_prefixCOHORT_DEFINITION cd ON cd.cohort_definition_id = cc.cohort_id" +cohort-generator-main.R,667,672,"FROM @schema.@cg_table_prefixCOHORT_GENERATION cg","JOIN @schema.@database_table_prefix@database_table dt ON cg.database_id = dt.database_id" +cohort-generator-main.R,708,715,"FROM @schema.@cg_table_prefixCOHORT_SUMMARY_STATS css","JOIN @schema.@database_table_prefix@database_table dt ON css.database_id = dt.database_id" +cohort-generator-main.R,708,715,"FROM @schema.@cg_table_prefixCOHORT_SUMMARY_STATS css","JOIN @schema.@cg_table_prefixCOHORT_DEFINITION cd ON cd.cohort_definition_id = css.cohort_definition_id" +cohort-generator-main.R,734,738,"FROM @schema.@cg_table_prefixCOHORT_INCLUSION ci","JOIN @schema.@cg_table_prefixCOHORT_DEFINITION cd ON cd.cohort_definition_id = ci.cohort_definition_id" +cohort-generator-main.R,753,757,"FROM @schema.@cg_table_prefixCOHORT_INC_RESULT cir","JOIN @schema.@database_table_prefix@database_table dt ON cir.database_id = dt.database_id" +estimation-cohort-method-covariateBalance.R,330,334,"FROM @result_schema.@cm_table_prefixCOVARIATE_BALANCE i","JOIN @result_schema.@database_table_name d ON d.database_id = i.database_id" +estimation-cohort-method-covariateBalance.R,359,380,"FROM @results_schema.@cm_table_prefixshared_covariate_balance cmscb","JOIN @results_schema.@cm_table_prefixcovariate cmc ON cmscb.covariate_id = cmc.covariate_id AND cmscb.analysis_id = cmc.analysis_id AND cmscb.database_id = cmc.database_id -- database_id optional --" +estimation-cohort-method-covariateBalance.R,359,380,"FROM @results_schema.@cm_table_prefixshared_covariate_balance cmscb","JOIN @results_schema.@cm_table_prefixcovariate_analysis cmca ON cmca.analysis_id = cmc.analysis_id -- question: shouldn't we have a covariate_analysis_id in @table_prefixcovariate table?" +estimation-cohort-method-covariateBalance.R,632,651,"FROM @schema.@cm_table_prefixdiagnostics_summary cmds","JOIN @schema.@database_table dmd ON dmd.database_id = cmds.database_id" +estimation-cohort-method-diagnostics.R,63,94,"FROM @schema.@cm_table_prefixdiagnostics_summary cmds","JOIN @schema.@cm_table_prefixanalysis cma ON cmds.analysis_id = cma.analysis_id INNER" +estimation-cohort-method-diagnostics.R,63,94,"FROM @schema.@cm_table_prefixdiagnostics_summary cmds","JOIN @schema.@database_table dmd ON dmd.database_id = cmds.database_id INNER" +estimation-cohort-method-diagnostics.R,63,94,"FROM @schema.@cm_table_prefixdiagnostics_summary cmds","JOIN @schema.@cg_table_prefixcohort_definition cgcd1 ON cmds.target_id = cgcd1.cohort_definition_id INNER" +estimation-cohort-method-diagnostics.R,63,94,"FROM @schema.@cm_table_prefixdiagnostics_summary cmds","JOIN @schema.@cg_table_prefixcohort_definition cgcd2 ON cmds.comparator_id = cgcd2.cohort_definition_id INNER" +estimation-cohort-method-diagnostics.R,63,94,"FROM @schema.@cm_table_prefixdiagnostics_summary cmds","JOIN @schema.@cg_table_prefixcohort_definition cgcd3 ON cmds.outcome_id = cgcd3.cohort_definition_id" +estimation-cohort-method-populationCharacteristics.R,176,202,"FROM @schema.@cm_table_prefixcovariate_balance WHERE","JOIN @schema.@cm_table_prefixcovariate cmc ON cmcb.covariate_id = cmc.covariate_id AND cmcb.analysis_id = cmc.analysis_id AND cmcb.database_id = cmc.database_id -- database_id optional" +estimation-cohort-method-propensityModel.R,145,171,"FROM @schema.@cm_table_prefixcovariate WHERE","JOIN @schema.@cm_table_prefixpropensity_model cmpm ON cmc.covariate_id = cmpm.covariate_id" +estimation-cohort-method-results.R,297,356,"FROM @schema.@cm_table_prefixanalysis cma","JOIN @schema.@cm_table_prefixresult cmr ON cmr.analysis_id = cma.analysis_id" +estimation-cohort-method-results.R,297,356,"FROM @schema.@cm_table_prefixanalysis cma","JOIN @schema.@database_table dmd ON dmd.database_id = cmr.database_id LEFT" +estimation-cohort-method-results.R,297,356,"FROM @schema.@cm_table_prefixanalysis cma","JOIN @schema.@cm_table_prefixdiagnostics_summary cmds ON cmds.analysis_id = cmr.analysis_id AND cmds.target_id = cmr.target_id AND cmds.comparator_id = cmr.comparator_id AND cmds.outcome_id = cmr.outcome_id AND cmds.database_id = cmr.database_id inner" +estimation-cohort-method-results.R,297,356,"FROM @schema.@cm_table_prefixanalysis cma","JOIN @schema.@cg_table_prefixcohort_definition cg1 ON cg1.cohort_definition_id = cmr.target_id inner" +estimation-cohort-method-results.R,297,356,"FROM @schema.@cm_table_prefixanalysis cma","JOIN @schema.@cg_table_prefixcohort_definition cg2 ON cg2.cohort_definition_id = cmr.outcome_id inner" +estimation-cohort-method-results.R,297,356,"FROM @schema.@cm_table_prefixanalysis cma","JOIN @schema.@cg_table_prefixcohort_definition cg3 ON cg3.cohort_definition_id = cmr.comparator_id" +estimation-cohort-method-systematicError.R,161,174,"FROM @schema.@cm_table_prefixresult cmr","JOIN @schema.@cm_table_prefixtarget_comparator_outcome cmtco ON cmr.target_id = cmtco.target_id AND cmr.comparator_id = cmtco.comparator_id AND cmr.outcome_id = cmtco.outcome_id" +estimation-cohort-method-systematicError.R,321,338,"FROM @schema.@cm_table_prefixdiagnostics_summary cmds","JOIN @schema.@database_table dmd ON dmd.database_id = cmds.database_id" +estimation-sccs-diagnostics.R,57,102,"FROM @schema.@sccs_table_prefixdiagnostics_summary ds","JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON ds.exposures_outcome_set_id = eos.exposures_outcome_set_id inner" +estimation-sccs-diagnostics.R,57,102,"FROM @schema.@sccs_table_prefixdiagnostics_summary ds","JOIN @schema.@database_table_prefix@database_table d ON d.database_id = ds.database_id INNER" +estimation-sccs-diagnostics.R,57,102,"FROM @schema.@sccs_table_prefixdiagnostics_summary ds","JOIN @schema.@sccs_table_prefixanalysis a ON a.analysis_id = ds.analysis_id INNER" +estimation-sccs-diagnostics.R,57,102,"FROM @schema.@sccs_table_prefixdiagnostics_summary ds","JOIN @schema.@sccs_table_prefixcovariate cov ON cov.covariate_id = ds.covariate_id and cov.exposures_outcome_set_id = ds.exposures_outcome_set_id and cov.analysis_id = ds.analysis_id and cov.database_id = ds.database_id inner" +estimation-sccs-results-full.R,489,517,"FROM @schema.@sccs_table_prefixcovariate_result scr","JOIN @schema.@sccs_table_prefixcovariate sc ON ( sc.exposures_outcome_set_id = scr.exposures_outcome_set_id AND sc.database_id = scr.database_id AND sc.analysis_id = scr.analysis_id AND sc.covariate_id = scr.covariate_id ) LEFT" +estimation-sccs-results-full.R,489,517,"FROM @schema.@sccs_table_prefixcovariate_result scr","JOIN @schema.@cg_table_prefixcohort_definition cd ON cd.cohort_definition_id = sc.era_id LEFT" +estimation-sccs-results-full.R,489,517,"FROM @schema.@sccs_table_prefixcovariate_result scr","JOIN @schema.@sccs_table_prefixera era ON ( era.exposures_outcome_set_id = scr.exposures_outcome_set_id AND era.database_id = scr.database_id AND era.analysis_id = scr.analysis_id AND era.era_id = sc.era_id )" +estimation-sccs-results-full.R,740,766,"FROM @schema.@sccs_table_prefixresult r","JOIN @schema.@sccs_table_prefixexposure e ON r.exposures_outcome_set_id = e.exposures_outcome_set_id INNER" +estimation-sccs-results-full.R,740,766,"FROM @schema.@sccs_table_prefixresult r","JOIN @schema.@sccs_table_prefixcovariate c ON e.era_id = c.era_id and e.exposures_outcome_set_id = c.exposures_outcome_set_id and c.database_id = r.database_id and c.analysis_id = r.analysis_id and c.covariate_id = r.covariate_id" +estimation-sccs-results.R,250,344,"FROM @schema.@sccs_table_prefixresult sr","JOIN @schema.@database_table_prefix@database_table ds ON sr.database_id = ds.database_id INNER" +estimation-sccs-results.R,250,344,"FROM @schema.@sccs_table_prefixresult sr","JOIN @schema.@sccs_table_prefixdiagnostics_summary sds ON ( sds.exposures_outcome_set_id = sr.exposures_outcome_set_id AND sds.database_id = sr.database_id AND sds.analysis_id = sr.analysis_id AND sds.covariate_id = sr.covariate_id ) INNER" +estimation-sccs-results.R,250,344,"FROM @schema.@sccs_table_prefixresult sr","JOIN @schema.@sccs_table_prefixcovariate sc ON ( sc.exposures_outcome_set_id = sr.exposures_outcome_set_id AND sc.database_id = sr.database_id AND sc.analysis_id = sr.analysis_id AND sc.covariate_id = sr.covariate_id ) INNER" +estimation-sccs-results.R,250,344,"FROM @schema.@sccs_table_prefixresult sr","JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON eos.exposures_outcome_set_id = sr.exposures_outcome_set_id INNER" +estimation-sccs-results.R,250,344,"FROM @schema.@sccs_table_prefixresult sr","JOIN @schema.@sccs_table_prefixanalysis a ON a.analysis_id = sr.analysis_id inner" +estimation-sccs-results.R,250,344,"FROM @schema.@sccs_table_prefixresult sr","JOIN @schema.@cg_table_prefixcohort_definition cg1 ON cg1.cohort_definition_id = eos.outcome_id inner" +helpers-sccsDataPulls.R,41,59,"FROM @schema.@sccs_table_prefixexposures_outcome_set eos","JOIN @schema.@cg_table_prefixcohort_definition c ON eos.nesting_cohort_id = c.cohort_definition_id INNER" +helpers-sccsDataPulls.R,41,59,"FROM @schema.@sccs_table_prefixexposures_outcome_set eos","JOIN @schema.@sccs_table_prefixcovariate cov ON eos.exposures_outcome_set_id = cov.exposures_outcome_set_id INNER" +helpers-sccsDataPulls.R,41,59,"FROM @schema.@sccs_table_prefixexposures_outcome_set eos","JOIN @schema.@sccs_table_prefixexposure e ON eos.exposures_outcome_set_id = e.exposures_outcome_set_id AND cov.era_id = e.era_id INNER" +helpers-sccsDataPulls.R,41,59,"FROM @schema.@sccs_table_prefixexposures_outcome_set eos","JOIN @schema.@cg_table_prefixcohort_definition c2 ON e.era_id = c2.cohort_definition_id GROUP BY c.cohort_definition_id, c.cohort_name, e.era_id, c2.cohort_name" +helpers-sccsDataPulls.R,77,99,"FROM @schema.@sccs_table_prefixresult r","JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON r.exposures_outcome_set_id = eos.exposures_outcome_set_id INNER" +helpers-sccsDataPulls.R,77,99,"FROM @schema.@sccs_table_prefixresult r","JOIN @schema.@sccs_table_prefixcovariate cov ON r.exposures_outcome_set_id = cov.exposures_outcome_set_id AND r.analysis_id = cov.analysis_id AND r.covariate_id = cov.covariate_id INNER" +helpers-sccsDataPulls.R,77,99,"FROM @schema.@sccs_table_prefixresult r","JOIN @schema.@sccs_table_prefixexposure e ON r.exposures_outcome_set_id = e.exposures_outcome_set_id AND cov.era_id = e.era_id INNER" +helpers-sccsDataPulls.R,186,217,"FROM @schema.@sccs_table_prefixcovariate_result scr","JOIN @schema.@sccs_table_prefixcovariate sc ON ( sc.exposures_outcome_set_id = scr.exposures_outcome_set_id AND sc.database_id = scr.database_id AND sc.analysis_id = scr.analysis_id AND sc.covariate_id = scr.covariate_id ) LEFT" +helpers-sccsDataPulls.R,186,217,"FROM @schema.@sccs_table_prefixcovariate_result scr","JOIN @schema.@cg_table_prefixcohort_definition cd ON cd.cohort_definition_id = sc.era_id LEFT" +helpers-sccsDataPulls.R,186,217,"FROM @schema.@sccs_table_prefixcovariate_result scr","JOIN @schema.@sccs_table_prefixera era ON ( era.exposures_outcome_set_id = scr.exposures_outcome_set_id AND era.database_id = scr.database_id AND era.analysis_id = scr.analysis_id AND era.era_id = sc.era_id ) INNER" +helpers-sccsDataPulls.R,186,217,"FROM @schema.@sccs_table_prefixcovariate_result scr","JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON eos.exposures_outcome_set_id = scr.exposures_outcome_set_id" +helpers-sccsDataPulls.R,236,245,"FROM @schema.@sccs_table_prefixtime_trend tt","JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON tt.exposures_outcome_set_id = eos.exposures_outcome_set_id" +helpers-sccsDataPulls.R,265,275,"FROM @schema.@sccs_table_prefixdiagnostics_summary ds","JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON ds.exposures_outcome_set_id = eos.exposures_outcome_set_id" +helpers-sccsDataPulls.R,288,298,"FROM @schema.@sccs_table_prefixtime_to_event tte","JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON tte.exposures_outcome_set_id = eos.exposures_outcome_set_id" +helpers-sccsDataPulls.R,324,335,"FROM @schema.@sccs_table_prefixattrition a","JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON a.exposures_outcome_set_id = eos.exposures_outcome_set_id" +helpers-sccsDataPulls.R,351,361,"FROM @schema.@sccs_table_prefixevent_dep_observation o","JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON o.exposures_outcome_set_id = eos.exposures_outcome_set_id" +helpers-sccsDataPulls.R,376,386,"FROM @schema.@sccs_table_prefixage_spanning asp","JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON asp.exposures_outcome_set_id = eos.exposures_outcome_set_id" +helpers-sccsDataPulls.R,401,411,"FROM @schema.@sccs_table_prefixcalendar_time_spanning ts","JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON ts.exposures_outcome_set_id = eos.exposures_outcome_set_id" +helpers-sccsDataPulls.R,428,439,"FROM @schema.@sccs_table_prefixspline s","JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON s.exposures_outcome_set_id = eos.exposures_outcome_set_id" +helpers-sccsDataPulls.R,457,474,"FROM @schema.@sccs_table_prefixresult sr","JOIN @schema.@sccs_table_prefixcovariate sc ON ( sc.exposures_outcome_set_id = sr.exposures_outcome_set_id AND sc.database_id = sr.database_id AND sc.analysis_id = sr.analysis_id AND sc.covariate_id = sr.covariate_id ) INNER" +helpers-sccsDataPulls.R,457,474,"FROM @schema.@sccs_table_prefixresult sr","JOIN @schema.@sccs_table_prefixexposure se ON ( se.exposures_outcome_set_id = sr.exposures_outcome_set_id AND se.era_id = sc.era_id )" +helpers-sccsDataPulls.R,491,510,"FROM @schema.@sccs_table_prefixdiagnostics_summary ds","JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON ds.exposures_outcome_set_id = eos.exposures_outcome_set_id inner" +helpers-sccsDataPulls.R,491,510,"FROM @schema.@sccs_table_prefixdiagnostics_summary ds","JOIN @schema.@sccs_table_prefixcovariate cov ON cov.covariate_id = ds.covariate_id and cov.exposures_outcome_set_id = ds.exposures_outcome_set_id and cov.analysis_id = ds.analysis_id and cov.database_id = ds.database_id" +patient-level-prediction-designSummary.R,271,281,"FROM @schema.@plp_table_prefixmodel_designs as","JOIN @schema.@cg_table_prefixcohort_definition cd ON c.cohort_definition_id = cd.cohort_definition_id ) AS cohorts ON model_designs.@type_id = cohorts.cohort_id" +patient-level-prediction-designSummary.R,310,368,"FROM @schema.@plp_table_prefixmodel_designs as","JOIN @schema.@cg_table_prefixcohort_definition cd ON c.cohort_definition_id = cd.cohort_definition_id ) AS targets ON model_designs.target_id = targets.cohort_id LEFT" +patient-level-prediction-designSummary.R,310,368,"FROM @schema.@plp_table_prefixmodel_designs as","JOIN @schema.@cg_table_prefixcohort_definition cd ON c.cohort_definition_id = cd.cohort_definition_id ) AS outcomes ON model_designs.outcome_id = outcomes.cohort_id LEFT" +patient-level-prediction-diagnostics.R,428,460,"FROM @schema.@plp_table_prefixDIAGNOSTICS where","JOIN @schema.@plp_table_prefixMODEL_DESIGNS design ON diagnostics.MODEL_DESIGN_ID = design.MODEL_DESIGN_ID inner" +patient-level-prediction-diagnostics.R,428,460,"FROM @schema.@plp_table_prefixDIAGNOSTICS where","JOIN @schema.@plp_table_prefixDIAGNOSTIC_SUMMARY summary ON diagnostics.DIAGNOSTIC_ID = summary.DIAGNOSTIC_ID inner" +patient-level-prediction-diagnostics.R,428,460,"FROM @schema.@plp_table_prefixDIAGNOSTICS where","JOIN @schema.@plp_table_prefixdatabase_details dd ON md.database_id = dd.database_meta_data_id) as database on database.database_id = diagnostics.database_id inner" +patient-level-prediction-diagnostics.R,428,460,"FROM @schema.@plp_table_prefixDIAGNOSTICS where","JOIN @schema.@plp_table_prefixCOHORTS cohortT ON cohortT.cohort_id = design.target_id inner" +patient-level-prediction-diagnostics.R,428,460,"FROM @schema.@plp_table_prefixDIAGNOSTICS where","JOIN @schema.@plp_table_prefixCOHORTS cohortO ON cohortO.cohort_id = design.outcome_id" +patient-level-prediction-modelSummary.R,253,303,"FROM @schema.@plp_table_prefixperformances where","JOIN @schema.@cg_table_prefixcohort_definition cd ON c.cohort_definition_id = cd.cohort_definition_id ) AS targets ON results.target_id = targets.cohort_id LEFT" +patient-level-prediction-modelSummary.R,253,303,"FROM @schema.@plp_table_prefixperformances where","JOIN @schema.@cg_table_prefixcohort_definition cd ON c.cohort_definition_id = cd.cohort_definition_id ) AS outcomes ON results.outcome_id = outcomes.cohort_id LEFT" +patient-level-prediction-modelSummary.R,253,303,"FROM @schema.@plp_table_prefixperformances where","JOIN @schema.@plp_table_prefixdatabase_details dd ON md.database_id = dd.database_meta_data_id) AS d ON results.development_database_id = d.database_id LEFT" +patient-level-prediction-modelSummary.R,253,303,"FROM @schema.@plp_table_prefixperformances where","JOIN @schema.@plp_table_prefixdatabase_details dd ON md.database_id = dd.database_meta_data_id) AS v ON results.validation_database_id = v.database_id LEFT" +patient-level-prediction-settings.R,350,380,"FROM @schema.@plp_table_prefixperformances WHERE","JOIN @schema.@database_table_prefixdatabase_meta_data dmd ON dd.database_meta_data_id = dmd.database_id) tempV on tempV.database_id = perf.validation_database_id" +patient-level-prediction-settings.R,546,550,"FROM @schema.@plp_table_prefixcohorts c","JOIN @schema.@cg_table_prefixcohort_definition cd ON c.cohort_definition_id = cd.cohort_definition_id" +patient-level-prediction-settings.R,564,568,"FROM @schema.@plp_table_prefixcohorts c","JOIN @schema.@cg_table_prefixcohort_definition cd ON c.cohort_definition_id = cd.cohort_definition_id" +patient-level-prediction-validation.R,256,311,"FROM @schema.@plp_table_appendperformances where","JOIN @schema.@plp_table_appenddatabase_details dd ON md.database_id = dd.database_meta_data_id) AS d ON results.validation_database_id = d.database_id LEFT" +report-main.R,843,911,"FROM @schema.@c_table_prefixcohort_details where","JOIN @schema.@plp_table_prefixcohorts c1 ON c1.cohort_id = md.target_id inner" +report-main.R,843,911,"FROM @schema.@c_table_prefixcohort_details where","JOIN @schema.@plp_table_prefixcohorts c2 ON c2.cohort_id = md.outcome_id } {@sccs} ? { {@cohort_method | @cohort_incidence | @characterization | @prediction}?{union} SELECT distinct cov.era_id as tid, eos.outcome_id as oid FROM @schema.@sccs_table_prefixdiagnostics_summary ds inner" +report-main.R,843,911,"FROM @schema.@c_table_prefixcohort_details where","JOIN @schema.@sccs_table_prefixexposures_outcome_set eos ON ds.exposures_outcome_set_id = eos.exposures_outcome_set_id INNER" +report-main.R,843,911,"FROM @schema.@c_table_prefixcohort_details where","JOIN @schema.@sccs_table_prefixcovariate cov ON cov.covariate_id = ds.covariate_id and cov.exposures_outcome_set_id = ds.exposures_outcome_set_id and cov.analysis_id = ds.analysis_id and cov.database_id = ds.database_id -- adding code to remove the negative controls INNER" +report-main.R,843,911,"FROM @schema.@c_table_prefixcohort_details where","JOIN @schema.@sccs_table_prefixexposure e ON e.exposures_outcome_set_id = ds.exposures_outcome_set_id AND e.era_id = cov.era_id" diff --git a/extras/rdms/results_table_relationships.csv b/extras/rdms/results_table_relationships.csv new file mode 100644 index 00000000..ae805e9b --- /dev/null +++ b/extras/rdms/results_table_relationships.csv @@ -0,0 +1,140 @@ +table_name,column_name,fk_table_name,fk_column_name +c_settings,database_id,database_meta_data,database_id +c_settings,setting_id,c_cohort_details,setting_id +c_settings,database_id,c_cohort_details,database_id +c_cohort_details,target_cohort_id,cg_cohort_definition,cohort_definition_id +c_cohort_details,outcome_cohort_id,cg_cohort_definition,cohort_definition_id +c_covariates,setting_id,c_covariate_ref,setting_id +c_covariates,database_id,c_covariate_ref,database_id +c_covariates,covariate_id,c_covariate_ref,covariate_id +c_covariates,setting_id,c_settings,setting_id +c_covariates,database_id,c_settings,database_id +c_covariates_continuous,setting_id,c_covariate_ref,setting_id +c_covariates_continuous,database_id,c_covariate_ref,database_id +c_covariates_continuous,setting_id,c_settings,setting_id +c_covariates,setting_id,c_settings,database_id +c_covariates,database_id,c_settings,setting_id +c_covariates_continuous,covariate_id,c_covariate_ref,covariate_id +c_covariates_continuous,database_id,c_settings,database_id +c_covariates_continuous,database_id,database_meta_data,database_id +database_meta_data,database_id,c_cohort_details,database_id +c_dechallenge_rechallenge,target_cohort_definition_id,cg_cohort_definition,cohort_definition_id +c_dechallenge_rechallenge,outcome_cohort_definition_id,cg_cohort_definition,cohort_definition_id +c_dechallenge_rechallenge,database_id,database_meta_data,database_id +ci_incidence_summary,outcome_id,ci_outcome_def,outcome_id +ci_incidence_summary,ref_id,ci_outcome_def,ref_id +ci_incidence_summary,ref_id,ci_tar_def,ref_id +ci_incidence_summary,tar_id,ci_tar_def,ref_id +ci_incidence_summary,subgroup_id,ci_subgroup_def,subgroup_id +ci_incidence_summary,ref_id,ci_subgroup_def,ref_id +ci_incidence_summary,age_group_id,ci_age_group_def,age_group_id +ci_incidence_summary,ref_id,ci_age_group_def,ref_id +ci_incidence_summary,database_id,database_meta_data,database_id +ci_incidence_summary,target_cohort_definition_id,cg_cohort_definition,cohort_definition_id +ci_incidence_summary,outcome_cohort_definition_id,cg_cohort_definition,cohort_definition_id +c_time_to_event,database_id,database_meta_data,database_id +cd_temporal_covariate_ref,analysis_id,cd_temporal_analysis_ref,analysis_id +cd_temporal_covariate_ref,covariate_id,cd_temporal_covariate_value,covariate_id +cd_temporal_covariate_ref,time_id,cd_temporal_time_ref,time_id +cd_included_source_concept,concept_id,cd_concept,concept_id +cd_incidence_rate,database_id,cd_cohort_count,database_id +cd_incidence_rate,cohort_id,cd_cohort_count,cohort_id +cd_index_event_breakdown,concept_id,cd_concept,concept_id +cd_orphan_concept,cohort_id,cd_concept_sets,cohort_id +cd_orphan_concept,concept_set_id,cd_concept_sets,concept_set_id +cd_orphan_concept,concept_id,cd_concept,concept_id +cd_cohort_count,database_id,database_meta_data,database_id +cd_visit_context,concept_id,cd_concept,concept_id +cg_cohort_count,database_id,database_meta_data,database_id +cg_cohort_count,cohort_id,cg_cohort_definition,cohort_definition_id +cg_cohort_generation,database_id,database_meta_data,database_id +cg_cohort_summary_stats,database_id,database_meta_data,database_id +cg_cohort_summary_stats,cohort_definition_id,cg_cohort_definition,cohort_definition_id +cg_cohort_inclusion,cohort_definition_id,cg_cohort_definition,cohort_definition_id +cg_cohort_inc_result,database_id,database_meta_data,database_id +cm_covariate_balance,database_id,database_meta_data,database_id +cm_shared_covariate_balance,covariate_id,cm_covariate,covariate_id +cm_shared_covariate_balance,analysis_id,cm_covariate,analysis_id +cm_shared_covariate_balance,database_id,cm_covariate,database_id +cm_shared_covariate_balance,analysis_id,cm_covariate_analysis,analysis_id +cm_diagnostics_summary,database_id,database_meta_data,database_id +cm_diagnostics_summary,analysis_id,cm_analysis,analysis_id +cm_diagnostics_summary,target_id,cg_cohort_definition,cohort_definition_id +cm_diagnostics_summary,comparator_id,cg_cohort_definition,cohort_definition_id +cm_diagnostics_summary,outcome_id,cg_cohort_definition,cohort_definition_id +cm_covariate_balance,covariate_id,cm_covariate,covariate_id +cm_covariate_balance,analysis_id,cm_covariate,analysis_id +cm_covariate_balance,database_id,cm_covariate,database_id +cm_covariate,covariate_id,cm_propensity_model,covariate_id +cm_analysis,analysis_id,cm_result,analysis_id +cm_analysis,database_id,database_meta_data,database_id +cm_analysis,analysis_id,cm_diagnostics_summary,analysis_id +cm_analysis,target_id,cm_diagnostics_summary,target_id +cm_analysis,comparator_id,cm_diagnostics_summary,comparator_id +cm_analysis,outcome_id,cm_diagnostics_summary,outcome_id +cm_analysis,database_id,cm_diagnostics_summary,database_id +cm_analysis,target_id,cg_cohort_definition,cohort_definition_id +cm_analysis,outcome_id,cg_cohort_definition,cohort_definition_id +cm_analysis,comparator_id,cg_cohort_definition,cohort_definition_id +cm_result,target_id,cm_target_comparator_outcome,target_id +cm_result,comparator_id,cm_target_comparator_outcome,comparator_id +cm_result,outcome_id,cm_target_comparator_outcome,outcome_id +sccs_diagnostics_summary,exposures_outcome_set_id,sccs_exposures_outcome_set,exposures_outcome_set_id +sccs_diagnostics_summary,database_id,database_meta_data,database_id +sccs_diagnostics_summary,analysis_id,sccs_analysis,analysis_id +sccs_diagnostics_summary,covariate_id,sccs_covariate,covariate_id +sccs_diagnostics_summary,exposures_outcome_set_id,sccs_covariate,exposures_outcome_set_id +sccs_diagnostics_summary,database_id,sccs_covariate,database_id +sccs_covariate_result,exposures_outcome_set_id,sccs_covariate,exposures_outcome_set_id +sccs_covariate_result,database_id,sccs_covariate,database_id +sccs_covariate_result,analysis_id,sccs_covariate,analysis_id +sccs_covariate_result,covariate_id,sccs_covariate,covariate_id +sccs_covariate_result,era_id,cg_cohort_definition,cohort_definition_id +sccs_covariate_result,exposures_outcome_set_id,sccs_era,exposures_outcome_set_id +sccs_covariate_result,database_id,sccs_era,database_id +sccs_covariate_result,analysis_id,sccs_era,analysis_id +sccs_covariate_result,era_id,sccs_era,era_id +sccs_result,exposures_outcome_set_id,sccs_exposure,exposures_outcome_set_id +sccs_result,era_id,sccs_covariate,era_id +sccs_result,exposures_outcome_set_id,sccs_covariate,exposures_outcome_set_id +sccs_result,database_id,sccs_covariate,database_id +sccs_result,covariate_id,sccs_covariate,covariate_id +sccs_result,database_id,database_meta_data,database_id +sccs_result,exposures_outcome_set_id,sccs_diagnostics_summary,exposures_outcome_set_id +sccs_result,database_id,sccs_diagnostics_summary,database_id +sccs_result,analysis_id,sccs_diagnostics_summary,analysis_id +sccs_result,covariate_id,sccs_diagnostics_summary,covariate_id +sccs_result,analysis_id,sccs_covariate,analysis_id +sccs_result,exposures_outcome_set_id,sccs_exposures_outcome_set,exposures_outcome_set_id +sccs_result,analysis_id,sccs_analysis,analysis_id +sccs_result,outcome_id,cg_cohort_definition,cohort_definition_id +sccs_exposures_outcome_set,nesting_cohort_id,cg_cohort_definition,cohort_definition_id +sccs_exposures_outcome_set,exposures_outcome_set_id,sccs_covariate,exposures_outcome_set_id +sccs_exposures_outcome_set,exposures_outcome_set_id,sccs_exposure,exposures_outcome_set_id +sccs_exposures_outcome_set,era_id,sccs_exposure,era_id +sccs_exposures_outcome_set,era_id,cg_cohort_definition,era_id +sccs_result,exposures_outcome_set_id,sccs_exposures_outcome_set,exposures_outcome_set_id +sccs_covariate_result,exposures_outcome_set_id,sccs_exposures_outcome_set,exposures_outcome_set_id +sccs_time_trend,exposures_outcome_set_id,sccs_exposures_outcome_set,exposures_outcome_set_id +sccs_diagnostics_summary,exposures_outcome_set_id,sccs_exposures_outcome_set,exposures_outcome_set_id +sccs_time_to_event,exposures_outcome_set_id,sccs_exposures_outcome_set,exposures_outcome_set_id +sccs_attrition,exposures_outcome_set_id,sccs_exposures_outcome_set,exposures_outcome_set_id +sccs_event_dep_observation,exposures_outcome_set_id,sccs_exposures_outcome_set,exposures_outcome_set_id +sccs_age_spanning,exposures_outcome_set_id,sccs_exposures_outcome_set,exposures_outcome_set_id +sccs_calendar_time_spanning,exposures_outcome_set_id,sccs_exposures_outcome_set,exposures_outcome_set_id +sccs_spline,exposures_outcome_set_id,sccs_exposures_outcome_set,exposures_outcome_set_id +sccs_diagnostics_summary,analysis_id,sccs_covariate,analysis_id +plp_model_designs,target_id,cg_cohort_definition,cohort_definition_id +plp_model_designs,outcome_id,cg_cohort_definition,cohort_definition_id +plp_diagnostics,model_design_id,plp_model_designs,model_design_id +plp_diagnostics,diagnostic_id,plp_diagnostic_summary,diagnostic_id +plp_diagnostics,database_id,database_meta_data,database_id +plp_diagnostics,target_id,plp_cohorts,cohort_id +plp_diagnostics,outcome_id,plp_cohorts,cohort_id +plp_performances,target_id,cg_cohort_definition,cohort_definition_id +plp_performances,outcome_id,cg_cohort_definition,cohort_definition_id +plp_performances,development_database_id,database_meta_data,database_id +plp_performances,validation_database_id,database_meta_data,database_id +plp_performances,database_id,database_meta_data,database_id +plp_cohorts,cohort_definition_id,cg_cohort_definition,cohort_definition_id +c_cohort_details,target_id,cg_cohort_definition,cohort_definition_id diff --git a/extras/rdms/results_table_relationships.xlsx b/extras/rdms/results_table_relationships.xlsx new file mode 100644 index 00000000..ea97eea1 Binary files /dev/null and b/extras/rdms/results_table_relationships.xlsx differ diff --git a/extras/rdms/run-local.txt b/extras/rdms/run-local.txt new file mode 100644 index 00000000..2405217c --- /dev/null +++ b/extras/rdms/run-local.txt @@ -0,0 +1 @@ +"E:\Program Files\Amazon Corretto\jdk17.0.12_7\bin\java.exe" -jar schemaspy-6.2.4.jar -vizjs -dp E:\jdbcDrivers -configFile schemaspy-config.properties -meta schema_meta.xml -desc "Results data model" -noTablePaging -noimplied diff --git a/extras/rdms/schema_meta.xml b/extras/rdms/schema_meta.xml new file mode 100644 index 00000000..8d1a4f91 --- /dev/null +++ b/extras/rdms/schema_meta.xml @@ -0,0 +1,1505 @@ + + + The tables in the results data model are grouped using a unique prefix for + each Strategus module. For example, the CharacterizationModule results tables + all start with "c_". + + + + + + + + + + + + + + + + + +
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    +     +     diff --git a/extras/rdms/schemaspy-6.2.4.jar b/extras/rdms/schemaspy-6.2.4.jar new file mode 100644 index 00000000..39a8b006 Binary files /dev/null and b/extras/rdms/schemaspy-6.2.4.jar differ diff --git a/extras/rdms/schemaspy-config.properties b/extras/rdms/schemaspy-config.properties new file mode 100644 index 00000000..a0d9ba45 --- /dev/null +++ b/extras/rdms/schemaspy-config.properties @@ -0,0 +1,10 @@ +schemaspy.t=pgsql + +schemaspy.host=127.0.0.1 +schemaspy.port=5432 +schemaspy.db=strategus +schemaspy.u=user +schemaspy.p=password + +schemaspy.o=./public +schemaspy.s=results diff --git a/extras/rdms/table_descriptions.csv b/extras/rdms/table_descriptions.csv new file mode 100644 index 00000000..646daf44 --- /dev/null +++ b/extras/rdms/table_descriptions.csv @@ -0,0 +1,129 @@ +table_defined_by,table_name,description +CharacterizationModule,c_analysis_ref,"Analysis reference" +CharacterizationModule,c_cohort_counts,"Cohort counts" +CharacterizationModule,c_cohort_details,"Cohort details" +CharacterizationModule,c_covariate_ref,"Covariate reference" +CharacterizationModule,c_covariates,"Binary covariates" +CharacterizationModule,c_covariates_continuous,"Continuous covariates" +CharacterizationModule,c_dechallenge_rechallenge,"Dechallenge rechallenge" +CharacterizationModule,c_rechallenge_fail_case_series,"Rechallenge fail case series" +CharacterizationModule,c_settings,"Settings" +CharacterizationModule,c_time_to_event,"Time to event" +CohortDiagnosticsModule,cd_cohort,"Cohort details" +CohortDiagnosticsModule,cd_cohort_count,"Cohort counts" +CohortDiagnosticsModule,cd_cohort_inc_result,"Cohort inclusion results" +CohortDiagnosticsModule,cd_cohort_inc_stats,"Cohort inclusion statstics" +CohortDiagnosticsModule,cd_cohort_inclusion,"Cohort inclusion info" +CohortDiagnosticsModule,cd_cohort_overlap,"Cohort overlap" +CohortDiagnosticsModule,cd_cohort_relationships,"Cohort relationships" +CohortDiagnosticsModule,cd_cohort_summary_stats,"Cohort summary stats" +CohortDiagnosticsModule,cd_concept,"Concept lookup table" +CohortDiagnosticsModule,cd_concept_ancestor,"Concept ancestor" +CohortDiagnosticsModule,cd_concept_relationship,"Concept Relationship" +CohortDiagnosticsModule,cd_concept_sets,"Concept sets" +CohortDiagnosticsModule,cd_concept_synonym,"Concept synonym" +CohortDiagnosticsModule,cd_database,"CDM database information for Cohort Diagnostics" +CohortDiagnosticsModule,cd_domain,"Domain from the vocabulary" +CohortDiagnosticsModule,cd_incidence_rate,"Incidence rate for Cohort Diagnostics" +CohortDiagnosticsModule,cd_included_source_concept,"Included source concepts" +CohortDiagnosticsModule,cd_index_event_breakdown,"Index event breakdown" +CohortDiagnosticsModule,cd_metadata,"Metadata for the database and runtime environment used for Cohort Diagnostics" +CohortDiagnosticsModule,cd_orphan_concept,"Orphan concept list" +CohortDiagnosticsModule,cd_relationship,"Relationships" +CohortDiagnosticsModule,cd_resolved_concepts,"Resolved concepts" +CohortDiagnosticsModule,cd_subset_definition,"Cohort subset definition" +CohortDiagnosticsModule,cd_temporal_analysis_ref,"Temporal analysis reference" +CohortDiagnosticsModule,cd_temporal_covariate_ref,"Covariate reference" +CohortDiagnosticsModule,cd_temporal_covariate_value,"Binary covariate values" +CohortDiagnosticsModule,cd_temporal_covariate_value_dist,"Continuous covariate values" +CohortDiagnosticsModule,cd_temporal_time_ref,"Temporal time reference" +CohortDiagnosticsModule,cd_time_series,"Time series information" +CohortDiagnosticsModule,cd_visit_context,"Visit context" +CohortDiagnosticsModule,cd_vocabulary,"Vocabulary information" +CohortGeneratorModule,cg_cohort_censor_stats,"Cohort censor statistics" +CohortGeneratorModule,cg_cohort_count,"Cohort counts" +CohortGeneratorModule,cg_cohort_count_neg_ctrl,"Negative control outcome cohort counts" +CohortGeneratorModule,cg_cohort_definition,"Cohort definitions" +CohortGeneratorModule,cg_cohort_definition_neg_ctrl,"Negative control outcome cohort definitions" +CohortGeneratorModule,cg_cohort_generation,"Cohort generation times" +CohortGeneratorModule,cg_cohort_inc_result,"Cohort inclusion results" +CohortGeneratorModule,cg_cohort_inc_stats,"Cohort inclusion statistics" +CohortGeneratorModule,cg_cohort_inclusion,"Cohort inclusion information" +CohortGeneratorModule,cg_cohort_subset_definition,"Cohort subset definitions" +CohortGeneratorModule,cg_cohort_summary_stats,"Cohort summary statistics" +CohortIncidenceModule,ci_age_group_def,"Age group definitions" +CohortIncidenceModule,ci_incidence_summary,"Incidence rate/proportion summary" +CohortIncidenceModule,ci_outcome_def,"Outcome cohort definitions" +CohortIncidenceModule,ci_subgroup_def,"Subgroup definitions" +CohortIncidenceModule,ci_tar_def,"Time-at-risk definitions" +CohortIncidenceModule,ci_target_def,"Target cohort definitions" +CohortIncidenceModule,ci_target_outcome_ref,"Target outcome cross reference" +CohortMethodModule,cm_analysis,"Analysis reference" +CohortMethodModule,cm_attrition,"Attrition table" +CohortMethodModule,cm_covariate,"Covariate reference" +CohortMethodModule,cm_covariate_analysis,"Covariate analysis reference" +CohortMethodModule,cm_covariate_balance,"Covariate balance" +CohortMethodModule,cm_diagnostics_summary,"Diagnostics summary" +CohortMethodModule,cm_follow_up_dist,"Follow up distribution" +CohortMethodModule,cm_interaction_result,"Study results for interaction effects" +CohortMethodModule,cm_kaplan_meier_dist,"Kaplan Meier distribution" +CohortMethodModule,cm_likelihood_profile,"Likelihood Profile" +CohortMethodModule,cm_preference_score_dist,"Preference score distribution" +CohortMethodModule,cm_propensity_model,"Propensity model" +CohortMethodModule,cm_result,"Study results for main effects" +CohortMethodModule,cm_shared_covariate_balance,"Shared covariate balance" +CohortMethodModule,cm_target_comparator_outcome,"Target comparator outcome reference" +Strategus,database_meta_data,"Metadata for each CDM database" +EvidenceSynthesisModule,es_analysis,"Analysis reference" +EvidenceSynthesisModule,es_cm_diagnostics_summary,"Cohort method diagnostics summary" +EvidenceSynthesisModule,es_cm_result,"Cohort method results" +EvidenceSynthesisModule,es_sccs_diagnostics_summary,"Self controlled case series diagnostics summary" +EvidenceSynthesisModule,es_sccs_result,"Self controlled case series results" +PatientLevelPredictionModule,plp_attrition,"Attrition information" +PatientLevelPredictionModule,plp_calibration_summary,"Calibration summary" +PatientLevelPredictionModule,plp_cohort_definition,"Cohort definitions" +PatientLevelPredictionModule,plp_cohorts,"Cohort identifier reference" +PatientLevelPredictionModule,plp_covariate_settings,"Covariate settings" +PatientLevelPredictionModule,plp_covariate_summary,"Covariate summary" +PatientLevelPredictionModule,plp_database_details,"CDM database details" +PatientLevelPredictionModule,plp_database_meta_data,"CDM database metadata" +PatientLevelPredictionModule,plp_demographic_summary,"Demographic summary" +PatientLevelPredictionModule,plp_diagnostic_designs,"Diagnostic designs" +PatientLevelPredictionModule,plp_diagnostic_outcomes,"Diagnostic outcomes" +PatientLevelPredictionModule,plp_diagnostic_participants,"Diagnostic participants" +PatientLevelPredictionModule,plp_diagnostic_predictors,"Diagnostic predictors" +PatientLevelPredictionModule,plp_diagnostic_summary,"Diagnostic summary" +PatientLevelPredictionModule,plp_diagnostics,"Diagnostics" +PatientLevelPredictionModule,plp_evaluation_statistics,"Evaluation statistics" +PatientLevelPredictionModule,plp_feature_engineering_settings,"Feature engineering settings" +PatientLevelPredictionModule,plp_model_designs,"Model designs" +PatientLevelPredictionModule,plp_model_settings,"Model settings" +PatientLevelPredictionModule,plp_models,"Models" +PatientLevelPredictionModule,plp_performances,"Model performance" +PatientLevelPredictionModule,plp_plp_data_settings,"PLP data settings" +PatientLevelPredictionModule,plp_population_settings,"Population settings" +PatientLevelPredictionModule,plp_prediction_distribution,"Prediction distribution" +PatientLevelPredictionModule,plp_recalibrations,"Recalibrations" +PatientLevelPredictionModule,plp_sample_settings,"Sample settings" +PatientLevelPredictionModule,plp_split_settings,"Split settings" +PatientLevelPredictionModule,plp_tars,"Time-at-risk settings" +PatientLevelPredictionModule,plp_threshold_summary,"Threshold summary" +PatientLevelPredictionModule,plp_tidy_covariates_settings,"Tidy covariate settings" +SelfControlledCaseSeriesModule,sccs_age_spanning,"Age spanning diagnostic" +SelfControlledCaseSeriesModule,sccs_analysis,"Analysis reference" +SelfControlledCaseSeriesModule,sccs_attrition,"Attrition table" +SelfControlledCaseSeriesModule,sccs_calendar_time_spanning,"Calendar time spanning diagnostic" +SelfControlledCaseSeriesModule,sccs_censor_model,"Event-dependent observation censoring model" +SelfControlledCaseSeriesModule,sccs_covariate,"Covariate reference" +SelfControlledCaseSeriesModule,sccs_covariate_analysis,"Covariate analysis" +SelfControlledCaseSeriesModule,sccs_covariate_result,"Covariate results" +SelfControlledCaseSeriesModule,sccs_diagnostics_summary,"Diagnostic summary" +SelfControlledCaseSeriesModule,sccs_era,"Era reference" +SelfControlledCaseSeriesModule,sccs_event_dep_observation,"Event-dependent observation diagnostic" +SelfControlledCaseSeriesModule,sccs_exposure,"Exposure reference" +SelfControlledCaseSeriesModule,sccs_exposures_outcome_set,"Exposure outcome set reference" +SelfControlledCaseSeriesModule,sccs_likelihood_profile,"Likelihood profile" +SelfControlledCaseSeriesModule,sccs_result,"Results" +SelfControlledCaseSeriesModule,sccs_spline,"Season, age, and calendar time splines" +SelfControlledCaseSeriesModule,sccs_time_to_event,"Time-to-event diagnostic" +SelfControlledCaseSeriesModule,sccs_time_trend,"Time trend diagnostic" diff --git a/extras/rdms/table_relationships.xml b/extras/rdms/table_relationships.xml new file mode 100644 index 00000000..ec43f7f8 --- /dev/null +++ b/extras/rdms/table_relationships.xml @@ -0,0 +1,21 @@ + + + + + + + + + + + + + +
    + + + + +
    +     +     \ No newline at end of file diff --git a/extras/testExecutionSettings.json b/extras/testExecutionSettings.json deleted file mode 100644 index fb1a9967..00000000 --- a/extras/testExecutionSettings.json +++ /dev/null @@ -1,17 +0,0 @@ -{ - "connectionDetailsReference": "prod-1-mdcd", - "workDatabaseSchema": "scratch_mschuemi", - "cdmDatabaseSchema": "cdm_truven_mdcd_v1978", - "cohortTableNames": { - "cohortTable": "strategus_test", - "cohortInclusionTable": "strategus_test_inclusion", - "cohortInclusionResultTable": "strategus_test_inclusion_result", - "cohortInclusionStatsTable": "strategus_test_inclusion_stats", - "cohortSummaryStatsTable": "strategus_test_summary_stats", - "cohortCensorStatsTable": "strategus_test_censor_stats" - }, - "workFolder": "c:/temp/strategusWork", - "resultsFolder": "c:/temp/strategusOutput", - "minCellCount": 5, - "attr_class": "ExecutionSettings" -} diff --git a/inst/csv/cohortIncidenceRdms.csv b/inst/csv/cohortIncidenceRdms.csv new file mode 100644 index 00000000..93b73049 --- /dev/null +++ b/inst/csv/cohortIncidenceRdms.csv @@ -0,0 +1,48 @@ +table_name,column_name,data_type,is_required,primary_key,description +incidence_summary,ref_id,int,no,no,The reference identifier for the analysis +incidence_summary,database_id,varchar(255),yes,no,The database identifier +incidence_summary,source_name,varchar(255),no,no,The source name for the database +incidence_summary,target_cohort_definition_id,bigint,no,no,Target cohort identifier +incidence_summary,tar_id,bigint,no,no,Time-at-risk identifier +incidence_summary,subgroup_id,bigint,no,no,Subgroup identifier +incidence_summary,outcome_id,bigint,no,no,Outcome cohort identifier +incidence_summary,age_group_id,int,no,no,Age group identifier +incidence_summary,gender_id,int,no,no,Gender identifier +incidence_summary,gender_name,varchar(255),no,no,Gender name +incidence_summary,start_year,int,no,no,Start year +incidence_summary,persons_at_risk_pe,bigint,no,no,Persons at risk pre-exclude (counts before excluding time at risk) +incidence_summary,persons_at_risk,bigint,no,no,Persons at risk +incidence_summary,person_days_pe,bigint,no,no,Person days pre-exclude (counts before excluding time at risk) +incidence_summary,person_days,bigint,no,no,Person days +incidence_summary,person_outcomes_pe,bigint,no,no,Person outcomes pre-exclude (counts before excluding time at risk) +incidence_summary,person_outcomes,bigint,no,no,Person outcomes +incidence_summary,outcomes_pe,bigint,no,no,Outcomes pre-exclude (counts before excluding time at risk) +incidence_summary,outcomes,bigint,no,no,Outcomes +incidence_summary,incidence_proportion_p100p,float,no,no,Incidence proportion (person_outcomes / persons_at_risk) per 100 people +incidence_summary,incidence_rate_p100py,float,no,no,Incidence rate (outcomes / time_at_risk) per 100 person years +target_def,ref_id,int,yes,yes,The reference identifier for the analysis +target_def,target_cohort_definition_id,bigint,yes,yes,Target cohort identifier +target_def,target_name,varchar(255),no,no,Target cohort name +outcome_def,ref_id,int,yes,yes,The reference identifier for the analysis +outcome_def,outcome_id,bigint,yes,yes,Outcome identifier +outcome_def,outcome_cohort_definition_id,bigint,no,no,Outcome cohort identifier +outcome_def,outcome_name,varchar(255),no,no,Outcome name +outcome_def,clean_window,bigint,no,no,Clean window +outcome_def,excluded_cohort_definition_id,bigint,no,no,Excluded cohort identifier +tar_def,ref_id,int,yes,yes,The reference identifier for the analysis +tar_def,tar_id,bigint,yes,yes,Time-at-risk identifier +tar_def,tar_start_with,varchar(10),no,no,Time-at-risk start anchor +tar_def,tar_start_offset,bigint,no,no,Time-at-risk start offset in days +tar_def,tar_end_with,varchar(10),no,no,Time-at-risk end anchor +tar_def,tar_end_offset,bigint,no,no,Time-at-risk end offset in days +age_group_def,ref_id,int,yes,yes,The reference identifier for the analysis +age_group_def,age_group_id,int,yes,yes,Age group identifier +age_group_def,age_group_name,varchar(255),yes,no,Age group name +age_group_def,min_age,int,no,no,Minimum age +age_group_def,max_age,int,no,no,Maximum age +subgroup_def,ref_id,int,yes,yes,The reference identifier for the analysis +subgroup_def,subgroup_id,bigint,no,yes,The subgroup identifier +subgroup_def,subgroup_name,varchar(255),no,no,The subgroup name +target_outcome_ref,ref_id,int,yes,yes,The reference identifier for the analysis +target_outcome_ref,target_cohort_id,bigint,yes,yes,The target cohort identifier +target_outcome_ref,outcome_cohort_id,bigint,yes,yes,The outcome cohort identifier diff --git a/inst/databaseMetaDataRdms.csv b/inst/csv/databaseMetaDataRdms.csv similarity index 100% rename from inst/databaseMetaDataRdms.csv rename to inst/csv/databaseMetaDataRdms.csv diff --git a/inst/csv/evidenceSynthesisRdms.csv b/inst/csv/evidenceSynthesisRdms.csv new file mode 100644 index 00000000..82e0f0d2 --- /dev/null +++ b/inst/csv/evidenceSynthesisRdms.csv @@ -0,0 +1,85 @@ +table_name,column_name,data_type,is_required,primary_key,min_cell_count,description +es_analysis,evidence_synthesis_analysis_id,int,Yes,Yes,No,A unique identifier for the evidence synthesis analysis. +es_analysis,evidence_synthesis_description,varchar(255),Yes,No,No,A description of the evidence synthesis analysis. +es_analysis,source_method,varchar(100),Yes,No,No,The method used to produce the source estimates (e.g. 'CohortMethod'). +es_analysis,definition,varchar,Yes,No,No,A JSON string representing the settings of the evidence synthesis analysis. +es_cm_diagnostics_summary,target_id,int,Yes,Yes,No,The identifier for the target cohort. +es_cm_diagnostics_summary,comparator_id,int,Yes,Yes,No,The identifier for the comparator cohort. +es_cm_diagnostics_summary,outcome_id,int,Yes,Yes,No,The identifier for the outcome cohort. +es_cm_diagnostics_summary,analysis_id,int,Yes,Yes,No,A unique identifier for the cohort method analysis. +es_cm_diagnostics_summary,evidence_synthesis_analysis_id,int,Yes,Yes,No,A foreign key referencing the es_analysis table. +es_cm_diagnostics_summary,mdrr,float,No,No,No,The minimum detectable relative risk. +es_cm_diagnostics_summary,i_2,float,No,No,No,The I2 statistics for heterogeneity. +es_cm_diagnostics_summary,tau,float,No,No,No,The estimated tau (standard deviation of the random-effects distribution). +es_cm_diagnostics_summary,ease,float,No,No,No,The expected absolute systematic error. +es_cm_diagnostics_summary,mdrr_diagnostic,varchar(13),Yes,No,No,PASS/ NOT EVALUATED / FAIL classification of the MDRR diagnostic. +es_cm_diagnostics_summary,i_2_diagnostic,varchar(13),Yes,No,No,PASS/ NOT EVALUATED / FAIL classification of the I2 diagnostic. +es_cm_diagnostics_summary,tau_diagnostic,varchar(13),Yes,No,No,PPASS/ NOT EVALUATED / FAIL classification of the tau diagnostic. +es_cm_diagnostics_summary,ease_diagnostic,varchar(13),Yes,No,No,PASS/ NOT EVALUATED / FAIL classification of the EASE diagnostic. +es_cm_diagnostics_summary,unblind,int,Yes,No,No,"Is unblinding the result recommended? (1 = yes, 0 = no)" +es_cm_result,target_id,int,Yes,Yes,No,The identifier for the target cohort. +es_cm_result,comparator_id,int,Yes,Yes,No,The identifier for the comparator cohort. +es_cm_result,outcome_id,int,Yes,Yes,No,The identifier for the outcome cohort. +es_cm_result,analysis_id,int,Yes,Yes,No,A unique identifier for the cohort method analysis. +es_cm_result,evidence_synthesis_analysis_id,int,Yes,Yes,No,A foreign key referencing the es_analysis table. +es_cm_result,rr,float,No,No,No,The estimated relative risk (e.g. the hazard ratio). +es_cm_result,ci_95_lb,float,No,No,No,The lower bound of the 95% confidence interval of the relative risk. +es_cm_result,ci_95_ub,float,No,No,No,The upper bound of the 95% confidence interval of the relative risk. +es_cm_result,p,float,No,No,No,The two-sided p-value considering the null hypothesis of no effect. +es_cm_result,one_sided_p,float,No,No,No,The one-sided p-value considering the null hypothesis of RR <= 1. +es_cm_result,log_rr,float,No,No,No,The log of the relative risk. +es_cm_result,se_log_rr,float,No,No,No,The standard error of the log of the relative risk. +es_cm_result,target_subjects,int,No,No,Yes,The number of subject in the target cohort. +es_cm_result,comparator_subjects,int,No,No,Yes,The number of subject in the comparator cohort. +es_cm_result,target_days,int,No,No,No,The number of days observed in the target cohort. +es_cm_result,comparator_days,int,No,No,No,The number of days observed in the comparator cohort. +es_cm_result,target_outcomes,int,No,No,Yes,The number of outcomes observed in the target cohort. +es_cm_result,comparator_outcomes,int,No,No,Yes,The number of outcomes observed in the comparator cohort. +es_cm_result,n_databases,int,Yes,No,No,The number of databases that contributed to the meta-analytic estimate. +es_cm_result,calibrated_rr,float,No,No,No,The calibrated relative risk. +es_cm_result,calibrated_ci_95_lb,float,No,No,No,The lower bound of the calibrated 95% confidence interval of the relative risk. +es_cm_result,calibrated_ci_95_ub,float,No,No,No,The upper bound of the calibrated 95% confidence interval of the relative risk. +es_cm_result,calibrated_p,float,No,No,No,The calibrated two-sided p-value. +es_cm_result,calibrated_one_sided_p,float,No,No,No,The calibrated one-sided p-value considering the null hypothesis of RR <= 1. +es_cm_result,calibrated_log_rr,float,No,No,No,The log of the calibrated relative risk. +es_cm_result,calibrated_se_log_rr,float,No,No,No,The standard error of the log of the calibrated relative risk. +es_sccs_diagnostics_summary,exposures_outcome_set_id,int,Yes,Yes,No,A foreign key referencing the sccs_exposures_outcome_set table. +es_sccs_diagnostics_summary,covariate_id,int,Yes,Yes,No,A foreign key referencing the sccs_covariate table. The identifier for the covariate of interest. +es_sccs_diagnostics_summary,analysis_id,int,Yes,Yes,No,A unique identifier for the cohort method analysis. +es_sccs_diagnostics_summary,evidence_synthesis_analysis_id,int,Yes,Yes,No,A foreign key referencing the es_analysis table. +es_sccs_diagnostics_summary,mdrr,float,No,No,No,The minimum detectable relative risk. +es_sccs_diagnostics_summary,i_2,float,No,No,No,The I2 statistics for heterogeneity. +es_sccs_diagnostics_summary,tau,float,No,No,No,The estimated tau (standard deviation of the random-effects distribution). +es_sccs_diagnostics_summary,ease,float,No,No,No,The expected absolute systematic error. +es_sccs_diagnostics_summary,mdrr_diagnostic,varchar(13),Yes,No,No,PASS/ NOT EVALUATED / FAIL classification of the MDRR diagnostic. +es_sccs_diagnostics_summary,i_2_diagnostic,varchar(13),Yes,No,No,Pass / warning / fail classification of the I2 diagnostic. +es_sccs_diagnostics_summary,tau_diagnostic,varchar(13),Yes,No,No,Pass / warning / fail classification of the tau diagnostic. +es_sccs_diagnostics_summary,ease_diagnostic,varchar(13),Yes,No,No,Pass / warning / fail classification of the EASE diagnostic. +es_sccs_diagnostics_summary,unblind,int,Yes,No,No,"Is unblinding the result recommended? (1 = yes, 0 = no)" +es_sccs_result,analysis_id,int,Yes,Yes,No,A foreign key referencing the sccs_analysis table. +es_sccs_result,exposures_outcome_set_id,int,Yes,Yes,No,A foreign key referencing the sccs_exposures_outcome_set table. +es_sccs_result,covariate_id,int,Yes,Yes,No,A foreign key referencing the sccs_covariate table. The identifier for the covariate of interest. +es_sccs_result,evidence_synthesis_analysis_id,int,Yes,Yes,No,A foreign key referencing the es_analysis table. +es_sccs_result,rr,float,No,No,No,The estimated relative risk (i.e. the incidence rate ratio). +es_sccs_result,ci_95_lb,float,No,No,No,The lower bound of the 95% confidence interval of the relative risk. +es_sccs_result,ci_95_ub,float,No,No,No,The upper bound of the 95% confidence interval of the relative risk. +es_sccs_result,p,float,No,No,No,The two-sided p-value considering the null hypothesis of no effect. +es_sccs_result,one_sided_p,float,No,No,No,The one-sided p-value considering the null hypothesis of RR <= 1. +es_sccs_result,outcome_subjects,int,Yes,No,Yes,The number of subjects with at least one outcome. +es_sccs_result,outcome_events,int,Yes,No,Yes,The number of outcome events. +es_sccs_result,outcome_observation_periods,int,Yes,No,Yes,The number of observation periods containing at least one outcome. +es_sccs_result,covariate_subjects,int,Yes,No,Yes,The number of subjects having the covariate. +es_sccs_result,covariate_days,int,Yes,No,Yes,The total covariate time in days. +es_sccs_result,covariate_eras,int,Yes,No,Yes,The number of continuous eras of the covariate. +es_sccs_result,covariate_outcomes,int,Yes,No,Yes,The number of outcomes observed during the covariate time. +es_sccs_result,observed_days,int,Yes,No,Yes,The number of days subjects were observed. +es_sccs_result,n_databases,int,Yes,No,No,The number of databases that contributed to the meta-analytic estimate. +es_sccs_result,log_rr,float,No,No,No,The log of the relative risk. +es_sccs_result,se_log_rr,float,No,No,No,The standard error of the log of the relative risk. +es_sccs_result,calibrated_rr,float,No,No,No,The calibrated relative risk. +es_sccs_result,calibrated_ci_95_lb,float,No,No,No,The lower bound of the calibrated 95% confidence interval of the relative risk. +es_sccs_result,calibrated_ci_95_ub,float,No,No,No,The upper bound of the calibrated 95% confidence interval of the relative risk. +es_sccs_result,calibrated_p,float,No,No,No,The calibrated two-sided p-value. +es_sccs_result,calibrated_one_sided_p,float,No,No,No,The calibrated one-sided p-value considering the null hypothesis of RR <= 1. +es_sccs_result,calibrated_log_rr,float,No,No,No,The log of the calibrated relative risk. +es_sccs_result,calibrated_se_log_rr,float,No,No,No,The standard error of the log of the calibrated relative risk. diff --git a/inst/csv/modules.csv b/inst/csv/modules.csv deleted file mode 100644 index 7b43cd44..00000000 --- a/inst/csv/modules.csv +++ /dev/null @@ -1,9 +0,0 @@ -module,version,remote_repo,remote_username,module_type,main_package,main_package_tag -CharacterizationModule,v0.6.0,github.com,OHDSI,cdm,Characterization,v0.2.0 -CohortDiagnosticsModule,v0.2.0,github.com,OHDSI,cdm,CohortDiagnostics,v3.2.5 -CohortGeneratorModule,v0.4.1,github.com,OHDSI,cdm,CohortGenerator,v0.9.0 -CohortIncidenceModule,v0.4.1,github.com,OHDSI,cdm,CohortIncidence,v3.3.0 -CohortMethodModule,v0.3.1,github.com,OHDSI,cdm,CohortMethod,v5.3.0 -PatientLevelPredictionModule,v0.3.0,github.com,OHDSI,cdm,PatientLevelPrediction,v6.3.6 -SelfControlledCaseSeriesModule,v0.5.0,github.com,OHDSI,cdm,SelfControlledCaseSeries,v5.2.0 -EvidenceSynthesisModule,v0.6.1,github.com,OHDSI,results,EvidenceSynthesis,v0.5.0 diff --git a/inst/doc/CreatingAnalysisSpecification.pdf b/inst/doc/CreatingAnalysisSpecification.pdf index e3d7dd2a..51fdd79b 100644 Binary files a/inst/doc/CreatingAnalysisSpecification.pdf and b/inst/doc/CreatingAnalysisSpecification.pdf differ diff --git a/inst/doc/CreatingModules.pdf b/inst/doc/CreatingModules.pdf deleted file mode 100644 index edeb8a32..00000000 Binary files a/inst/doc/CreatingModules.pdf and /dev/null differ diff --git a/inst/doc/ExecuteStrategus.pdf b/inst/doc/ExecuteStrategus.pdf index 666c055a..0bca1fd5 100644 Binary files a/inst/doc/ExecuteStrategus.pdf and b/inst/doc/ExecuteStrategus.pdf differ diff --git a/inst/doc/IntroductionToStrategus.pdf b/inst/doc/IntroductionToStrategus.pdf index 3ecbd02d..83893f4b 100644 Binary files a/inst/doc/IntroductionToStrategus.pdf and b/inst/doc/IntroductionToStrategus.pdf differ diff --git a/inst/doc/WorkingWithResults.pdf b/inst/doc/WorkingWithResults.pdf new file mode 100644 index 00000000..4815afbc Binary files /dev/null and b/inst/doc/WorkingWithResults.pdf differ diff --git a/inst/testdata/TestModule1_0.0.1.zip b/inst/testdata/TestModule1_0.0.1.zip deleted file mode 100644 index e93236a0..00000000 Binary files a/inst/testdata/TestModule1_0.0.1.zip and /dev/null differ diff --git a/inst/testdata/analysisSpecification.json b/inst/testdata/cdmModulesAnalysisSpecifications.json similarity index 82% rename from inst/testdata/analysisSpecification.json rename to inst/testdata/cdmModulesAnalysisSpecifications.json index 9c4557d0..801d99b4 100644 --- a/inst/testdata/analysisSpecification.json +++ b/inst/testdata/cdmModulesAnalysisSpecifications.json @@ -28,6 +28,36 @@ "cohortDefinition": "{\r\n\t\"cdmVersionRange\" : \">=5.0.0\",\r\n\t\"PrimaryCriteria\" : {\r\n\t\t\"CriteriaList\" : [\r\n\t\t\t{\r\n\t\t\t\t\"DrugEra\" : {\r\n\t\t\t\t\t\"CodesetId\" : 0\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t],\r\n\t\t\"ObservationWindow\" : {\r\n\t\t\t\"PriorDays\" : 0,\r\n\t\t\t\"PostDays\" : 0\r\n\t\t},\r\n\t\t\"PrimaryCriteriaLimit\" : {\r\n\t\t\t\"Type\" : \"First\"\r\n\t\t}\r\n\t},\r\n\t\"ConceptSets\" : [\r\n\t\t{\r\n\t\t\t\"id\" : 0,\r\n\t\t\t\"name\" : \"Diclofenac\",\r\n\t\t\t\"expression\" : {\r\n\t\t\t\t\"items\" : [\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\t\"concept\" : {\r\n\t\t\t\t\t\t\t\"CONCEPT_ID\" : 1124300,\r\n\t\t\t\t\t\t\t\"CONCEPT_NAME\" : \"diclofenac\",\r\n\t\t\t\t\t\t\t\"STANDARD_CONCEPT\" : \"S\",\r\n\t\t\t\t\t\t\t\"STANDARD_CONCEPT_CAPTION\" : \"Standard\",\r\n\t\t\t\t\t\t\t\"INVALID_REASON\" : \"V\",\r\n\t\t\t\t\t\t\t\"INVALID_REASON_CAPTION\" : \"Valid\",\r\n\t\t\t\t\t\t\t\"CONCEPT_CODE\" : \"3355\",\r\n\t\t\t\t\t\t\t\"DOMAIN_ID\" : \"Drug\",\r\n\t\t\t\t\t\t\t\"VOCABULARY_ID\" : \"RxNorm\",\r\n\t\t\t\t\t\t\t\"CONCEPT_CLASS_ID\" : \"Ingredient\"\r\n\t\t\t\t\t\t},\r\n\t\t\t\t\t\t\"isExcluded\" : false,\r\n\t\t\t\t\t\t\"includeDescendants\" : false,\r\n\t\t\t\t\t\t\"includeMapped\" : false\r\n\t\t\t\t\t}\r\n\t\t\t\t]\r\n\t\t\t}\r\n\t\t}\r\n\t],\r\n\t\"QualifiedLimit\" : {\r\n\t\t\"Type\" : \"First\"\r\n\t},\r\n\t\"ExpressionLimit\" : {\r\n\t\t\"Type\" : \"First\"\r\n\t},\r\n\t\"InclusionRules\" : [\r\n\t\t{\r\n\t\t\t\"name\" : \"Age >= 30\",\r\n\t\t\t\"expression\" : {\r\n\t\t\t\t\"Type\" : \"ALL\",\r\n\t\t\t\t\"CriteriaList\" : [],\r\n\t\t\t\t\"DemographicCriteriaList\" : [\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\t\"Age\" : {\r\n\t\t\t\t\t\t\t\"Value\" : 30,\r\n\t\t\t\t\t\t\t\"Op\" : \"gte\"\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t}\r\n\t\t\t\t],\r\n\t\t\t\t\"Groups\" : []\r\n\t\t\t}\r\n\t\t}\r\n\t],\r\n\t\"EndStrategy\" : {\r\n\t\t\"CustomEra\" : {\r\n\t\t\t\"DrugCodesetId\" : 0,\r\n\t\t\t\"GapDays\" : 30,\r\n\t\t\t\"Offset\" : 0\r\n\t\t}\r\n\t},\r\n\t\"CensoringCriteria\" : [],\r\n\t\"CollapseSettings\" : {\r\n\t\t\"CollapseType\" : \"ERA\",\r\n\t\t\"EraPad\" : 0\r\n\t},\r\n\t\"CensorWindow\" : {}\r\n}" } ], + "subsetDefs": [ + "{\n \"name\": \"test definition\",\n \"definitionId\": 1,\n \"subsetOperators\": [\n {\n \"name\": \"Demographic Criteria\",\n \"subsetType\": \"DemographicSubsetOperator\",\n \"ageMin\": 18,\n \"ageMax\": 64\n }\n ],\n \"packageVersion\": \"0.11.0\",\n \"identifierExpression\": \"targetId * 1000 + definitionId\",\n \"operatorNameConcatString\": \", \",\n \"subsetCohortNameTemplate\": \"@baseCohortName - @subsetDefinitionName @operatorNames\"\n}" + ], + "cohortSubsets": [ + { + "cohortId": 1001, + "subsetId": 1, + "targetCohortId": 1 + }, + { + "cohortId": 2001, + "subsetId": 1, + "targetCohortId": 2 + }, + { + "cohortId": 3001, + "subsetId": 1, + "targetCohortId": 3 + }, + { + "cohortId": 4001, + "subsetId": 1, + "targetCohortId": 4 + }, + { + "cohortId": 5001, + "subsetId": 1, + "targetCohortId": 5 + } + ], "attr_class": ["CohortDefinitionSharedResources", "SharedResources"] }, { @@ -214,7 +244,7 @@ "outcomeConceptId": " 197236" } ], - "occurrenceType": "all", + "occurrenceType": "first", "detectOnDescendants": true }, "attr_class": ["NegativeControlOutcomeSharedResources", "SharedResources"] @@ -222,21 +252,183 @@ ], "moduleSpecifications": [ { - "module": "CohortGeneratorModule", - "version": "0.3.0", - "remoteRepo": "github.com", - "remoteUsername": "ohdsi", + "module": "CharacterizationModule", "settings": { - "incremental": true, - "generateStats": true + "analysis": { + "timeToEventSettings": [ + { + "targetIds": [1, 2], + "outcomeIds": 3, + "attr_class": "timeToEventSettings" + } + ], + "dechallengeRechallengeSettings": [ + { + "targetCohortDefinitionIds": [1, 2], + "outcomeCohortDefinitionIds": 3, + "dechallengeStopInterval": 30, + "dechallengeEvaluationWindow": 30, + "attr_class": "dechallengeRechallengeSettings" + } + ], + "aggregateCovariateSettings": [ + { + "targetIds": [1, 2], + "minPriorObservation": 365, + "outcomeIds": 3, + "outcomeWashoutDays": 365, + "riskWindowStart": 1, + "startAnchor": "cohort start", + "riskWindowEnd": 0, + "endAnchor": "cohort end", + "covariateSettings": [ + { + "temporal": false, + "temporalSequence": false, + "DemographicsGender": true, + "DemographicsAge": true, + "DemographicsAgeGroup": true, + "DemographicsRace": true, + "DemographicsEthnicity": true, + "DemographicsIndexYear": true, + "DemographicsIndexMonth": true, + "DemographicsPriorObservationTime": true, + "DemographicsPostObservationTime": true, + "DemographicsTimeInCohort": true, + "ConditionGroupEraLongTerm": true, + "ConditionGroupEraShortTerm": true, + "DrugGroupEraLongTerm": true, + "DrugGroupEraShortTerm": true, + "DrugGroupEraOverlapping": true, + "ProcedureOccurrenceLongTerm": true, + "ProcedureOccurrenceShortTerm": true, + "DeviceExposureLongTerm": true, + "DeviceExposureShortTerm": true, + "MeasurementLongTerm": true, + "MeasurementShortTerm": true, + "ObservationLongTerm": true, + "ObservationShortTerm": true, + "VisitConceptCountLongTerm": true, + "VisitConceptCountShortTerm": true, + "longTermStartDays": -365, + "mediumTermStartDays": -180, + "shortTermStartDays": -30, + "endDays": 0, + "includedCovariateConceptIds": [], + "addDescendantsToInclude": false, + "excludedCovariateConceptIds": [], + "addDescendantsToExclude": false, + "includedCovariateIds": [], + "attr_class": "covariateSettings", + "attr_fun": "getDbDefaultCovariateData" + } + ], + "caseCovariateSettings": { + "temporal": false, + "temporalSequence": false, + "ConditionGroupEraDuring": true, + "DrugGroupEraDuring": true, + "ProcedureOccurrenceDuring": true, + "DeviceExposureDuring": true, + "MeasurementDuring": true, + "ObservationDuring": true, + "VisitConceptCountDuring": true, + "includedCovariateConceptIds": [], + "addDescendantsToInclude": false, + "excludedCovariateConceptIds": [], + "addDescendantsToExclude": false, + "includedCovariateIds": [], + "attr_class": "covariateSettings", + "attr_fun": "Characterization::getDbDuringCovariateData" + }, + "casePreTargetDuration": 365, + "casePostOutcomeDuration": 365, + "extractNonCaseCovariates": true, + "attr_class": "aggregateCovariateSettings" + }, + { + "targetIds": [1, 2], + "minPriorObservation": 365, + "outcomeIds": 3, + "outcomeWashoutDays": 365, + "riskWindowStart": 1, + "startAnchor": "cohort start", + "riskWindowEnd": 365, + "endAnchor": "cohort end", + "covariateSettings": [ + { + "temporal": false, + "temporalSequence": false, + "DemographicsGender": true, + "DemographicsAge": true, + "DemographicsAgeGroup": true, + "DemographicsRace": true, + "DemographicsEthnicity": true, + "DemographicsIndexYear": true, + "DemographicsIndexMonth": true, + "DemographicsPriorObservationTime": true, + "DemographicsPostObservationTime": true, + "DemographicsTimeInCohort": true, + "ConditionGroupEraLongTerm": true, + "ConditionGroupEraShortTerm": true, + "DrugGroupEraLongTerm": true, + "DrugGroupEraShortTerm": true, + "DrugGroupEraOverlapping": true, + "ProcedureOccurrenceLongTerm": true, + "ProcedureOccurrenceShortTerm": true, + "DeviceExposureLongTerm": true, + "DeviceExposureShortTerm": true, + "MeasurementLongTerm": true, + "MeasurementShortTerm": true, + "ObservationLongTerm": true, + "ObservationShortTerm": true, + "VisitConceptCountLongTerm": true, + "VisitConceptCountShortTerm": true, + "longTermStartDays": -365, + "mediumTermStartDays": -180, + "shortTermStartDays": -30, + "endDays": 0, + "includedCovariateConceptIds": [], + "addDescendantsToInclude": false, + "excludedCovariateConceptIds": [], + "addDescendantsToExclude": false, + "includedCovariateIds": [], + "attr_class": "covariateSettings", + "attr_fun": "getDbDefaultCovariateData" + } + ], + "caseCovariateSettings": { + "temporal": false, + "temporalSequence": false, + "ConditionGroupEraDuring": true, + "DrugGroupEraDuring": true, + "ProcedureOccurrenceDuring": true, + "DeviceExposureDuring": true, + "MeasurementDuring": true, + "ObservationDuring": true, + "VisitConceptCountDuring": true, + "includedCovariateConceptIds": [], + "addDescendantsToInclude": false, + "excludedCovariateConceptIds": [], + "addDescendantsToExclude": false, + "includedCovariateIds": [], + "attr_class": "covariateSettings", + "attr_fun": "Characterization::getDbDuringCovariateData" + }, + "casePreTargetDuration": 365, + "casePostOutcomeDuration": 365, + "extractNonCaseCovariates": true, + "attr_class": "aggregateCovariateSettings" + } + ], + "attr_class": "characterizationSettings" + }, + "minCharacterizationMean": 0.01 }, - "attr_class": ["CohortGeneratorModuleSpecifications", "ModuleSpecifications"] + "attr_class": ["ModuleSpecifications", "CharacterizationModuleSpecifications"] }, { "module": "CohortDiagnosticsModule", - "version": "0.2.0", - "remoteRepo": "github.com", - "remoteUsername": "ohdsi", "settings": { "runInclusionStatistics": true, "runIncludedSourceConcepts": true, @@ -286,16 +478,19 @@ "attr_fun": "getDbDefaultCovariateData" }, "minCharacterizationMean": 0.01, - "irWashoutPeriod": 0, - "incremental": false + "irWashoutPeriod": 0 + }, + "attr_class": ["ModuleSpecifications", "CohortDiagnosticsModuleSpecifications"] + }, + { + "module": "CohortGeneratorModule", + "settings": { + "generateStats": true }, - "attr_class": ["CohortDiagnosticsModuleSpecifications", "ModuleSpecifications"] + "attr_class": ["ModuleSpecifications", "CohortGeneratorModuleSpecifications"] }, { "module": "CohortIncidenceModule", - "version": "0.4.0", - "remoteRepo": "github.com", - "remoteUsername": "ohdsi", "settings": { "irDesign": { "targetDefs": [ @@ -362,139 +557,10 @@ } } }, - "attr_class": ["CohortIncidenceModuleSpecifications", "ModuleSpecifications"] - }, - { - "module": "CharacterizationModule", - "version": "0.5.0", - "remoteRepo": "github.com", - "remoteUsername": "ohdsi", - "settings": { - "timeToEventSettings": [ - { - "targetIds": [1, 2], - "outcomeIds": 3, - "attr_class": "timeToEventSettings" - } - ], - "dechallengeRechallengeSettings": [ - { - "targetCohortDefinitionIds": [1, 2], - "outcomeCohortDefinitionIds": 3, - "dechallengeStopInterval": 30, - "dechallengeEvaluationWindow": 30, - "attr_class": "dechallengeRechallengeSettings" - } - ], - "aggregateCovariateSettings": [ - { - "targetIds": [1, 2], - "outcomeIds": 3, - "minPriorObservation": 0, - "riskWindowStart": 1, - "startAnchor": "cohort start", - "riskWindowEnd": 0, - "endAnchor": "cohort end", - "covariateSettings": { - "temporal": false, - "temporalSequence": false, - "DemographicsGender": true, - "DemographicsAgeGroup": true, - "DemographicsRace": true, - "DemographicsEthnicity": true, - "DemographicsIndexYear": true, - "DemographicsIndexMonth": true, - "ConditionGroupEraLongTerm": true, - "ConditionGroupEraShortTerm": true, - "DrugGroupEraLongTerm": true, - "DrugGroupEraShortTerm": true, - "DrugGroupEraOverlapping": true, - "ProcedureOccurrenceLongTerm": true, - "ProcedureOccurrenceShortTerm": true, - "DeviceExposureLongTerm": true, - "DeviceExposureShortTerm": true, - "MeasurementLongTerm": true, - "MeasurementShortTerm": true, - "MeasurementRangeGroupLongTerm": true, - "ObservationLongTerm": true, - "ObservationShortTerm": true, - "CharlsonIndex": true, - "Dcsi": true, - "Chads2": true, - "Chads2Vasc": true, - "includedCovariateConceptIds": [], - "includedCovariateIds": [], - "addDescendantsToInclude": false, - "excludedCovariateConceptIds": [], - "addDescendantsToExclude": false, - "shortTermStartDays": -30, - "mediumTermStartDays": -180, - "endDays": 0, - "longTermStartDays": -365, - "attr_class": "covariateSettings", - "attr_fun": "getDbDefaultCovariateData" - }, - "attr_class": "aggregateCovariateSettings" - }, - { - "targetIds": [1, 2], - "outcomeIds": 3, - "minPriorObservation": 0, - "riskWindowStart": 1, - "startAnchor": "cohort start", - "riskWindowEnd": 365, - "endAnchor": "cohort end", - "covariateSettings": { - "temporal": false, - "temporalSequence": false, - "DemographicsGender": true, - "DemographicsAgeGroup": true, - "DemographicsRace": true, - "DemographicsEthnicity": true, - "DemographicsIndexYear": true, - "DemographicsIndexMonth": true, - "ConditionGroupEraLongTerm": true, - "ConditionGroupEraShortTerm": true, - "DrugGroupEraLongTerm": true, - "DrugGroupEraShortTerm": true, - "DrugGroupEraOverlapping": true, - "ProcedureOccurrenceLongTerm": true, - "ProcedureOccurrenceShortTerm": true, - "DeviceExposureLongTerm": true, - "DeviceExposureShortTerm": true, - "MeasurementLongTerm": true, - "MeasurementShortTerm": true, - "MeasurementRangeGroupLongTerm": true, - "ObservationLongTerm": true, - "ObservationShortTerm": true, - "CharlsonIndex": true, - "Dcsi": true, - "Chads2": true, - "Chads2Vasc": true, - "includedCovariateConceptIds": [], - "includedCovariateIds": [], - "addDescendantsToInclude": false, - "excludedCovariateConceptIds": [], - "addDescendantsToExclude": false, - "shortTermStartDays": -30, - "mediumTermStartDays": -180, - "endDays": 0, - "longTermStartDays": -365, - "attr_class": "covariateSettings", - "attr_fun": "getDbDefaultCovariateData" - }, - "attr_class": "aggregateCovariateSettings" - } - ], - "attr_class": "characterizationSettings" - }, - "attr_class": ["CharacterizationModuleSpecifications", "ModuleSpecifications"] + "attr_class": ["ModuleSpecifications", "CohortIncidenceModuleSpecifications"] }, { "module": "CohortMethodModule", - "version": "0.3.0", - "remoteRepo": "github.com", - "remoteUsername": "ohdsi", "settings": { "cmAnalysisList": [ { @@ -529,8 +595,13 @@ "MeasurementLongTerm": true, "MeasurementShortTerm": true, "MeasurementRangeGroupLongTerm": true, + "MeasurementRangeGroupShortTerm": true, + "MeasurementValueAsConceptLongTerm": true, + "MeasurementValueAsConceptShortTerm": true, "ObservationLongTerm": true, "ObservationShortTerm": true, + "ObservationValueAsConceptLongTerm": true, + "ObservationValueAsConceptShortTerm": true, "CharlsonIndex": true, "Dcsi": true, "Chads2": true, @@ -603,6 +674,8 @@ "initialBound": 2, "maxBoundCount": 5, "algorithm": "ccd", + "doItAll": true, + "syncCV": false, "attr_class": "cyclopsControl" }, "attr_class": "args" @@ -641,8 +714,13 @@ "MeasurementLongTerm": true, "MeasurementShortTerm": true, "MeasurementRangeGroupLongTerm": true, + "MeasurementRangeGroupShortTerm": true, + "MeasurementValueAsConceptLongTerm": true, + "MeasurementValueAsConceptShortTerm": true, "ObservationLongTerm": true, "ObservationShortTerm": true, + "ObservationValueAsConceptLongTerm": true, + "ObservationValueAsConceptShortTerm": true, "CharlsonIndex": true, "Dcsi": true, "Chads2": true, @@ -713,6 +791,8 @@ "initialBound": 2, "maxBoundCount": 5, "algorithm": "ccd", + "doItAll": true, + "syncCV": false, "attr_class": "cyclopsControl" }, "estimator": "att", @@ -744,9 +824,8 @@ "covariateIds": [] }, "default": [], - "delim": "," - }, - "attr_problems": {} + "skip": 1 + } }, "attr_class": "args" }, @@ -788,6 +867,8 @@ "initialBound": 2, "maxBoundCount": 5, "algorithm": "ccd", + "doItAll": true, + "syncCV": false, "attr_class": "cyclopsControl" }, "attr_class": "args" @@ -1340,13 +1421,10 @@ "attr_class": "CmDiagnosticThresholds" } }, - "attr_class": ["CohortMethodModuleSpecifications", "ModuleSpecifications"] + "attr_class": ["ModuleSpecifications", "CohortMethodModuleSpecifications"] }, { "module": "SelfControlledCaseSeriesModule", - "version": "0.4.1", - "remoteRepo": "github.com", - "remoteUsername": "ohdsi", "settings": { "sccsAnalysisList": [ { @@ -1452,6 +1530,8 @@ "initialBound": 2, "maxBoundCount": 5, "algorithm": "ccd", + "doItAll": true, + "syncCV": false, "attr_class": "cyclopsControl" }, "profileBounds": [-2.3026, 2.3026], @@ -2359,290 +2439,299 @@ "attr_class": "SccsDiagnosticThresholds" } }, - "attr_class": ["SelfControlledCaseSeriesModuleSpecifications", "ModuleSpecifications"] + "attr_class": ["ModuleSpecifications", "SelfControlledCaseSeriesModuleSpecifications"] }, { "module": "PatientLevelPredictionModule", - "version": "0.3.0", - "remoteRepo": "github.com", - "remoteUsername": "ohdsi", - "settings": [ - { - "targetId": 1, - "outcomeId": 3, - "restrictPlpDataSettings": { - "studyStartDate": "", - "studyEndDate": "", - "firstExposureOnly": false, - "washoutPeriod": 0, - "sampleSize": null, - "attr_class": "restrictPlpDataSettings" - }, - "covariateSettings": { - "temporal": false, - "temporalSequence": false, - "DemographicsGender": true, - "DemographicsAgeGroup": true, - "DemographicsRace": true, - "DemographicsEthnicity": true, - "DemographicsIndexYear": true, - "DemographicsIndexMonth": true, - "ConditionGroupEraLongTerm": true, - "ConditionGroupEraShortTerm": true, - "DrugGroupEraLongTerm": true, - "DrugGroupEraShortTerm": true, - "DrugGroupEraOverlapping": true, - "ProcedureOccurrenceLongTerm": true, - "ProcedureOccurrenceShortTerm": true, - "DeviceExposureLongTerm": true, - "DeviceExposureShortTerm": true, - "MeasurementLongTerm": true, - "MeasurementShortTerm": true, - "MeasurementRangeGroupLongTerm": true, - "ObservationLongTerm": true, - "ObservationShortTerm": true, - "CharlsonIndex": true, - "Dcsi": true, - "Chads2": true, - "Chads2Vasc": true, - "includedCovariateConceptIds": [], - "includedCovariateIds": [], - "addDescendantsToInclude": false, - "excludedCovariateConceptIds": [], - "addDescendantsToExclude": false, - "shortTermStartDays": -30, - "mediumTermStartDays": -180, - "endDays": 0, - "longTermStartDays": -365, - "attr_class": "covariateSettings", - "attr_fun": "getDbDefaultCovariateData" - }, - "populationSettings": { - "binary": true, - "includeAllOutcomes": true, - "firstExposureOnly": false, - "washoutPeriod": 0, - "removeSubjectsWithPriorOutcome": true, - "priorOutcomeLookback": 99999, - "requireTimeAtRisk": true, - "minTimeAtRisk": 1, - "riskWindowStart": 1, - "startAnchor": "cohort start", - "riskWindowEnd": 365, - "endAnchor": "cohort start", - "restrictTarToCohortEnd": false, - "attr_class": "populationSettings" - }, - "sampleSettings": [ - { - "numberOutcomestoNonOutcomes": 1, - "sampleSeed": 1, - "attr_class": "sampleSettings", - "attr_fun": "sameData" - } - ], - "featureEngineeringSettings": [ - { - "attr_class": "featureEngineeringSettings", - "attr_fun": "sameData" - } - ], - "preprocessSettings": { - "minFraction": 0.001, - "normalize": true, - "removeRedundancy": true, - "attr_class": "preprocessSettings" - }, - "modelSettings": { - "fitFunction": "fitCyclopsModel", - "param": { - "priorParams": { - "priorType": "laplace", - "forceIntercept": false, - "variance": 0.01, - "exclude": 0 - }, - "includeCovariateIds": null, - "upperLimit": 20, - "lowerLimit": 0.01, - "priorCoefs": null, - "attr_settings": { - "priorfunction": "Cyclops::createPrior", - "selectorType": "byPid", - "crossValidationInPrior": true, - "modelType": "logistic", - "addIntercept": true, - "useControl": true, - "seed": 15721621, - "name": "Lasso Logistic Regression", - "threads": -1, - "tolerance": 2e-06, - "cvRepetitions": 1, - "maxIterations": 3000 + "settings": { + "modelDesignList": [ + { + "targetId": 1, + "outcomeId": 3, + "restrictPlpDataSettings": { + "studyStartDate": "", + "studyEndDate": "", + "firstExposureOnly": false, + "washoutPeriod": 0, + "sampleSize": null, + "attr_class": "restrictPlpDataSettings" + }, + "covariateSettings": { + "temporal": false, + "temporalSequence": false, + "DemographicsGender": true, + "DemographicsAgeGroup": true, + "DemographicsRace": true, + "DemographicsEthnicity": true, + "DemographicsIndexYear": true, + "DemographicsIndexMonth": true, + "ConditionGroupEraLongTerm": true, + "ConditionGroupEraShortTerm": true, + "DrugGroupEraLongTerm": true, + "DrugGroupEraShortTerm": true, + "DrugGroupEraOverlapping": true, + "ProcedureOccurrenceLongTerm": true, + "ProcedureOccurrenceShortTerm": true, + "DeviceExposureLongTerm": true, + "DeviceExposureShortTerm": true, + "MeasurementLongTerm": true, + "MeasurementShortTerm": true, + "MeasurementRangeGroupLongTerm": true, + "MeasurementRangeGroupShortTerm": true, + "MeasurementValueAsConceptLongTerm": true, + "MeasurementValueAsConceptShortTerm": true, + "ObservationLongTerm": true, + "ObservationShortTerm": true, + "ObservationValueAsConceptLongTerm": true, + "ObservationValueAsConceptShortTerm": true, + "CharlsonIndex": true, + "Dcsi": true, + "Chads2": true, + "Chads2Vasc": true, + "includedCovariateConceptIds": [], + "includedCovariateIds": [], + "addDescendantsToInclude": false, + "excludedCovariateConceptIds": [], + "addDescendantsToExclude": false, + "shortTermStartDays": -30, + "mediumTermStartDays": -180, + "endDays": 0, + "longTermStartDays": -365, + "attr_class": "covariateSettings", + "attr_fun": "getDbDefaultCovariateData" + }, + "populationSettings": { + "binary": true, + "includeAllOutcomes": true, + "firstExposureOnly": false, + "washoutPeriod": 0, + "removeSubjectsWithPriorOutcome": true, + "priorOutcomeLookback": 99999, + "requireTimeAtRisk": true, + "minTimeAtRisk": 1, + "riskWindowStart": 1, + "startAnchor": "cohort start", + "riskWindowEnd": 365, + "endAnchor": "cohort start", + "restrictTarToCohortEnd": false, + "attr_class": "populationSettings" + }, + "sampleSettings": [ + { + "numberOutcomestoNonOutcomes": 1, + "sampleSeed": 1, + "attr_class": "sampleSettings", + "attr_fun": "sameData" + } + ], + "featureEngineeringSettings": [ + { + "attr_class": "featureEngineeringSettings", + "attr_fun": "sameData" + } + ], + "preprocessSettings": { + "minFraction": 0.001, + "normalize": true, + "removeRedundancy": true, + "attr_class": "preprocessSettings" + }, + "modelSettings": { + "fitFunction": "fitCyclopsModel", + "param": { + "priorParams": { + "priorType": "laplace", + "forceIntercept": false, + "variance": 0.01, + "exclude": 0 + }, + "includeCovariateIds": null, + "upperLimit": 20, + "lowerLimit": 0.01, + "priorCoefs": null, + "attr_settings": { + "priorfunction": "Cyclops::createPrior", + "selectorType": "byPid", + "crossValidationInPrior": true, + "modelType": "logistic", + "addIntercept": true, + "useControl": true, + "seed": 59989126, + "name": "Lasso Logistic Regression", + "threads": -1, + "tolerance": 2e-06, + "cvRepetitions": 1, + "maxIterations": 3000 + }, + "attr_modelType": "binary", + "attr_saveType": "RtoJson" }, - "attr_modelType": "binary", - "attr_saveType": "RtoJson" + "attr_class": "modelSettings" }, - "attr_class": "modelSettings" - }, - "splitSettings": { - "test": 0.25, - "train": 0.75, - "seed": 78595, - "nfold": 3, - "attr_class": "splitSettings", - "attr_fun": "randomSplitter" - }, - "executeSettings": { - "runSplitData": true, - "runSampleData": false, - "runfeatureEngineering": false, - "runPreprocessData": true, - 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"evidenceSynthesisDescription": "Bayesian random-effects alpha 0.05 - adaptive grid", + "evidenceSynthesisSource": { + "sourceMethod": "CohortMethod", + "likelihoodApproximation": "adaptive grid", + "attr_class": "EvidenceSynthesisSource" + }, + "controlType": "outcome", + "attr_class": ["BayesianMetaAnalysis", "EvidenceSynthesisAnalysis"] + }, + { + "chainLength": 1100000, + "burnIn": 100000, + "subSampleFrequency": 100, + "priorSd": [2, 0.5], + "alpha": 0.05, + "robust": false, + "df": 4, + "seed": 1, + "evidenceSynthesisAnalysisId": 2, + "evidenceSynthesisDescription": "Bayesian random-effects alpha 0.05 - adaptive grid", + "evidenceSynthesisSource": { + "sourceMethod": "SelfControlledCaseSeries", + "likelihoodApproximation": "adaptive grid", + "attr_class": "EvidenceSynthesisSource" + }, + "controlType": "outcome", + "attr_class": ["BayesianMetaAnalysis", "EvidenceSynthesisAnalysis"] + } + ], + "esDiagnosticThresholds": { + "mdrrThreshold": 10, + "easeThreshold": 0.25, + "i2Threshold": 0.4, + "tauThreshold": 0.6931, + "attr_class": "EsDiagnosticThresholds" + } + }, + "attr_class": ["ModuleSpecifications", "EvidenceSynthesisModuleSpecifications"] + } + ], + "attr_class": "AnalysisSpecifications" +} diff --git a/inst/testdata/unitTestAnalysisSpecification.json b/inst/testdata/unitTestAnalysisSpecification.json deleted file mode 100644 index e6b5af7e..00000000 --- a/inst/testdata/unitTestAnalysisSpecification.json +++ /dev/null @@ -1,12 +0,0 @@ -{ - "sharedResources": [], - "moduleSpecifications": [ - { - "module": "TestModule1", - "version": "0.0.1", - "settings": [], - "attr_class": ["TestModule1Specifications", "ModuleSpecifications"] - } - ], - "attr_class": "AnalysisSpecifications" -} diff --git a/man-roxygen/connectionDetails.R b/man-roxygen/connectionDetails.R new file mode 100644 index 00000000..07304da8 --- /dev/null +++ b/man-roxygen/connectionDetails.R @@ -0,0 +1,2 @@ +#' @param connectionDetails An object of class `connectionDetails` as created by the +#' [DatabaseConnector::createConnectionDetails()] function. diff --git a/man-roxygen/enforceModuleDependencies.R b/man-roxygen/enforceModuleDependencies.R deleted file mode 100644 index 92393bc8..00000000 --- a/man-roxygen/enforceModuleDependencies.R +++ /dev/null @@ -1,8 +0,0 @@ -#' @param enforceModuleDependencies When set to TRUE, Strategus will enforce -#' module dependencies that are declared by each module. For example, the -#' CohortDiagnostics module declares a dependency on the CohortGenerator module -#' and Strategus will require that an analysis specification declare that both -#' modules must exist in order to execute the analysis. When set to FALSE, -#' Strategus will not enforce these module dependencies which assumes you have -#' properly run all module dependencies yourself. Setting this to FALSE is not -#' recommended since it is potentially unsafe. diff --git a/man-roxygen/forceVerification.R b/man-roxygen/forceVerification.R deleted file mode 100644 index 540cf869..00000000 --- a/man-roxygen/forceVerification.R +++ /dev/null @@ -1,5 +0,0 @@ -#' @param forceVerification When set to TRUE, the verification process is forced -#' to re-evaluate if a module is properly installed. The default is FALSE -#' since if a module is successfully validated, the module will contain -#' the hash value of the module's renv.lock file in the file system so it can -#' by-pass running this check every time. diff --git a/man-roxygen/keyringName.R b/man-roxygen/keyringName.R deleted file mode 100644 index 13737125..00000000 --- a/man-roxygen/keyringName.R +++ /dev/null @@ -1,7 +0,0 @@ -#' @param keyringName The name of the keyring to operate on. This function assumes you have -#' created the keyring before calling this function. It defaults to -#' NULL to select the default keyring. If the keyring is password -#' protected, the password must be stored in the environment variable -#' STRATEGUS_KEYRING_PASSWORD so it is retrieved using the command -#' Sys.getenv("STRATEGUS_KEYRING_PASSWORD") - diff --git a/man-roxygen/moduleSpecifications.R b/man-roxygen/moduleSpecifications.R new file mode 100644 index 00000000..a793e24f --- /dev/null +++ b/man-roxygen/moduleSpecifications.R @@ -0,0 +1 @@ +#' @param moduleSpecifications An object of type `ModuleSpecifications` diff --git a/man-roxygen/resultsConnectionDetails.R b/man-roxygen/resultsConnectionDetails.R new file mode 100644 index 00000000..80a0bd23 --- /dev/null +++ b/man-roxygen/resultsConnectionDetails.R @@ -0,0 +1,3 @@ +#' @param resultsConnectionDetails The connection details to the results database which +#' is an object of class `connectionDetails` as created by the +#' [DatabaseConnector::createConnectionDetails()] function. diff --git a/man-roxygen/resultsDataModelSettings.R b/man-roxygen/resultsDataModelSettings.R new file mode 100644 index 00000000..3c13d0c0 --- /dev/null +++ b/man-roxygen/resultsDataModelSettings.R @@ -0,0 +1 @@ +#' @param resultsDataModelSettings The results data model settings as created using [@seealso [createResultsDataModelSettings()]] diff --git a/man-roxygen/resultsDatabaseSchema.R b/man-roxygen/resultsDatabaseSchema.R new file mode 100644 index 00000000..82177a74 --- /dev/null +++ b/man-roxygen/resultsDatabaseSchema.R @@ -0,0 +1 @@ +#' @param resultsDatabaseSchema The schema in the results database that holds the results data model. diff --git a/man-roxygen/resultsFolder.R b/man-roxygen/resultsFolder.R new file mode 100644 index 00000000..ff7d1fbc --- /dev/null +++ b/man-roxygen/resultsFolder.R @@ -0,0 +1 @@ +#' @param resultsFolder The root folder holding the study results. diff --git a/man-roxygen/tablePrefix.R b/man-roxygen/tablePrefix.R new file mode 100644 index 00000000..b20d050e --- /dev/null +++ b/man-roxygen/tablePrefix.R @@ -0,0 +1 @@ +#' @param tablePrefix A prefix to apply to the database table names (optional). diff --git a/man/CharacterizationModule.Rd b/man/CharacterizationModule.Rd new file mode 100644 index 00000000..09120dbd --- /dev/null +++ b/man/CharacterizationModule.Rd @@ -0,0 +1,264 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Module-Characterization.R +\name{CharacterizationModule} +\alias{CharacterizationModule} +\title{Characterize cohorts with the \href{https://ohdsi.github.io/Characterization/}{HADES Characterization Package}} +\description{ +Computes cohort characterization information against +the OMOP Common Data Model +} +\section{Super class}{ +\code{\link[Strategus:StrategusModule]{Strategus::StrategusModule}} -> \code{CharacterizationModule} +} +\section{Public fields}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{tablePrefix}}{The table prefix to append to the results tables} +} +\if{html}{\out{
    }} +} +\section{Methods}{ +\subsection{Public methods}{ +\itemize{ +\item \href{#method-CharacterizationModule-new}{\code{CharacterizationModule$new()}} +\item \href{#method-CharacterizationModule-execute}{\code{CharacterizationModule$execute()}} +\item \href{#method-CharacterizationModule-createResultsDataModel}{\code{CharacterizationModule$createResultsDataModel()}} +\item \href{#method-CharacterizationModule-getResultsDataModelSpecification}{\code{CharacterizationModule$getResultsDataModelSpecification()}} +\item \href{#method-CharacterizationModule-uploadResults}{\code{CharacterizationModule$uploadResults()}} +\item \href{#method-CharacterizationModule-createModuleSpecifications}{\code{CharacterizationModule$createModuleSpecifications()}} +\item \href{#method-CharacterizationModule-clone}{\code{CharacterizationModule$clone()}} +} +} +\if{html}{\out{ +
    Inherited methods + +
    +}} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CharacterizationModule-new}{}}} +\subsection{Method \code{new()}}{ +Initialize the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CharacterizationModule$new()}\if{html}{\out{
    }} +} + +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CharacterizationModule-execute}{}}} +\subsection{Method \code{execute()}}{ +Execute characterization +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CharacterizationModule$execute( + connectionDetails, + analysisSpecifications, + executionSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{connectionDetails}}{An object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{executionSettings}}{An object of type \code{ExecutionSettings} as created +by \code{\link[=createCdmExecutionSettings]{createCdmExecutionSettings()}} or \code{\link[=createResultsExecutionSettings]{createResultsExecutionSettings()}}.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CharacterizationModule-createResultsDataModel}{}}} +\subsection{Method \code{createResultsDataModel()}}{ +Create the results data model for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CharacterizationModule$createResultsDataModel( + resultsConnectionDetails, + resultsDatabaseSchema, + tablePrefix = self$tablePrefix +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsDatabaseSchema}}{The schema in the results database that holds the results data model.} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CharacterizationModule-getResultsDataModelSpecification}{}}} +\subsection{Method \code{getResultsDataModelSpecification()}}{ +Get the results data model specification for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CharacterizationModule$getResultsDataModelSpecification(tablePrefix = "")}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CharacterizationModule-uploadResults}{}}} +\subsection{Method \code{uploadResults()}}{ +Upload the results for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CharacterizationModule$uploadResults( + resultsConnectionDetails, + analysisSpecifications, + resultsDataModelSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{resultsDataModelSettings}}{The results data model settings as created using [@seealso \code{\link[=createResultsDataModelSettings]{createResultsDataModelSettings()}}]} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CharacterizationModule-createModuleSpecifications}{}}} +\subsection{Method \code{createModuleSpecifications()}}{ +Creates the CharacterizationModule Specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CharacterizationModule$createModuleSpecifications( + targetIds, + outcomeIds, + outcomeWashoutDays = c(365), + minPriorObservation = 365, + dechallengeStopInterval = 30, + dechallengeEvaluationWindow = 30, + riskWindowStart = c(1, 1), + startAnchor = c("cohort start", "cohort start"), + riskWindowEnd = c(0, 365), + endAnchor = c("cohort end", "cohort end"), + minCharacterizationMean = 0.01, + covariateSettings = FeatureExtraction::createCovariateSettings(useDemographicsGender = + T, useDemographicsAge = T, useDemographicsAgeGroup = T, useDemographicsRace = T, + useDemographicsEthnicity = T, useDemographicsIndexYear = T, useDemographicsIndexMonth + = T, useDemographicsTimeInCohort = T, useDemographicsPriorObservationTime = T, + useDemographicsPostObservationTime = T, useConditionGroupEraLongTerm = T, + useDrugGroupEraOverlapping = T, useDrugGroupEraLongTerm = T, + useProcedureOccurrenceLongTerm = T, useMeasurementLongTerm = T, + + useObservationLongTerm = T, useDeviceExposureLongTerm = T, + useVisitConceptCountLongTerm = T, useConditionGroupEraShortTerm = T, + useDrugGroupEraShortTerm = T, useProcedureOccurrenceShortTerm = T, + useMeasurementShortTerm = T, useObservationShortTerm = T, useDeviceExposureShortTerm + = T, useVisitConceptCountShortTerm = T, endDays = 0, longTermStartDays = -365, + shortTermStartDays = -30), + caseCovariateSettings = + Characterization::createDuringCovariateSettings(useConditionGroupEraDuring = T, + useDrugGroupEraDuring = T, useProcedureOccurrenceDuring = T, useDeviceExposureDuring + = T, useMeasurementDuring = T, useObservationDuring = T, useVisitConceptCountDuring = + T), + casePreTargetDuration = 365, + casePostOutcomeDuration = 365 +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{targetIds}}{A vector of cohort IDs to use as the target(s) for the characterization} + +\item{\code{outcomeIds}}{A vector of cohort IDs to use as the outcome(s) for the characterization} + +\item{\code{outcomeWashoutDays}}{A vector of integers specifying the washout days for each outcome (same length as the outcomeIds)} + +\item{\code{minPriorObservation}}{The number of days of minimum observation a patient in the target populations must have} + +\item{\code{dechallengeStopInterval}}{description} + +\item{\code{dechallengeEvaluationWindow}}{description} + +\item{\code{riskWindowStart}}{The number of days after start anchor to start the time-at-risk (can be a vector for multiple TARS)} + +\item{\code{startAnchor}}{The TAR starts relative to this either cohort start or cohort end (can be a vector for multiple TARS)} + +\item{\code{riskWindowEnd}}{The number of days after end anchor to end the time-at-risk (can be a vector for multiple TARS)} + +\item{\code{endAnchor}}{The TAR ends relative to this either cohort start or cohort end (can be a vector for multiple TARS)} + +\item{\code{minCharacterizationMean}}{The minimum fraction patients in the target have a covariate for it to be included} + +\item{\code{covariateSettings}}{Covariates for the database, cohort and risk factor characterization} + +\item{\code{caseCovariateSettings}}{Covariates for the case-series characterization} + +\item{\code{casePreTargetDuration}}{The number of days before target start to use for case-series} + +\item{\code{casePostOutcomeDuration}}{The number of days after outcome start to use for case-series} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CharacterizationModule-clone}{}}} +\subsection{Method \code{clone()}}{ +The objects of this class are cloneable with this method. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CharacterizationModule$clone(deep = FALSE)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{deep}}{Whether to make a deep clone.} +} +\if{html}{\out{
    }} +} +} +} diff --git a/man/CohortDiagnosticsModule.Rd b/man/CohortDiagnosticsModule.Rd new file mode 100644 index 00000000..13ba507d --- /dev/null +++ b/man/CohortDiagnosticsModule.Rd @@ -0,0 +1,266 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Module-CohortDiagnostics.R +\name{CohortDiagnosticsModule} +\alias{CohortDiagnosticsModule} +\title{Evaluate phenotypes with the \href{https://ohdsi.github.io/CohortDiagnostics/}{HADES CohortDiagnostics Package}} +\description{ +Development and evaluation of phenotype algorithms +against the OMOP Common Data Model. +} +\section{Super class}{ +\code{\link[Strategus:StrategusModule]{Strategus::StrategusModule}} -> \code{CohortDiagnosticsModule} +} +\section{Public fields}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{tablePrefix}}{The table prefix to append to results tables} +} +\if{html}{\out{
    }} +} +\section{Methods}{ +\subsection{Public methods}{ +\itemize{ +\item \href{#method-CohortDiagnosticsModule-new}{\code{CohortDiagnosticsModule$new()}} +\item \href{#method-CohortDiagnosticsModule-execute}{\code{CohortDiagnosticsModule$execute()}} +\item \href{#method-CohortDiagnosticsModule-createResultsDataModel}{\code{CohortDiagnosticsModule$createResultsDataModel()}} +\item \href{#method-CohortDiagnosticsModule-getResultsDataModelSpecification}{\code{CohortDiagnosticsModule$getResultsDataModelSpecification()}} +\item \href{#method-CohortDiagnosticsModule-uploadResults}{\code{CohortDiagnosticsModule$uploadResults()}} +\item \href{#method-CohortDiagnosticsModule-createModuleSpecifications}{\code{CohortDiagnosticsModule$createModuleSpecifications()}} +\item \href{#method-CohortDiagnosticsModule-validateModuleSpecifications}{\code{CohortDiagnosticsModule$validateModuleSpecifications()}} +\item \href{#method-CohortDiagnosticsModule-clone}{\code{CohortDiagnosticsModule$clone()}} +} +} +\if{html}{\out{ +
    Inherited methods + +
    +}} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortDiagnosticsModule-new}{}}} +\subsection{Method \code{new()}}{ +Initialize the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortDiagnosticsModule$new()}\if{html}{\out{
    }} +} + +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortDiagnosticsModule-execute}{}}} +\subsection{Method \code{execute()}}{ +Executes the CohortDiagnostics package +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortDiagnosticsModule$execute( + connectionDetails, + analysisSpecifications, + executionSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{connectionDetails}}{An object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{executionSettings}}{An object of type \code{ExecutionSettings} as created +by \code{\link[=createCdmExecutionSettings]{createCdmExecutionSettings()}} or \code{\link[=createResultsExecutionSettings]{createResultsExecutionSettings()}}.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortDiagnosticsModule-createResultsDataModel}{}}} +\subsection{Method \code{createResultsDataModel()}}{ +Create the results data model for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortDiagnosticsModule$createResultsDataModel( + resultsConnectionDetails, + resultsDatabaseSchema, + tablePrefix = self$tablePrefix +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsDatabaseSchema}}{The schema in the results database that holds the results data model.} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortDiagnosticsModule-getResultsDataModelSpecification}{}}} +\subsection{Method \code{getResultsDataModelSpecification()}}{ +Get the results data model specification for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortDiagnosticsModule$getResultsDataModelSpecification(tablePrefix = "")}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortDiagnosticsModule-uploadResults}{}}} +\subsection{Method \code{uploadResults()}}{ +Upload the results for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortDiagnosticsModule$uploadResults( + resultsConnectionDetails, + analysisSpecifications, + resultsDataModelSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{resultsDataModelSettings}}{The results data model settings as created using [@seealso \code{\link[=createResultsDataModelSettings]{createResultsDataModelSettings()}}]} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortDiagnosticsModule-createModuleSpecifications}{}}} +\subsection{Method \code{createModuleSpecifications()}}{ +Creates the CohortDiagnostics Module Specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortDiagnosticsModule$createModuleSpecifications( + cohortIds = NULL, + runInclusionStatistics = TRUE, + runIncludedSourceConcepts = TRUE, + runOrphanConcepts = TRUE, + runTimeSeries = FALSE, + runVisitContext = TRUE, + runBreakdownIndexEvents = TRUE, + runIncidenceRate = TRUE, + runCohortRelationship = TRUE, + runTemporalCohortCharacterization = TRUE, + temporalCovariateSettings = private$.getDefaultCovariateSettings(), + minCharacterizationMean = 0.01, + irWashoutPeriod = 0 +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{cohortIds}}{A list of cohort IDs to use when running the CohortDiagnostics. +Default is NULL which will use all cohorts present in the cohort definition set +in the analysis specification} + +\item{\code{runInclusionStatistics}}{Generate and export statistic on the cohort inclusion rules?} + +\item{\code{runIncludedSourceConcepts}}{Generate and export the source concepts included in the cohorts?} + +\item{\code{runOrphanConcepts}}{Generate and export potential orphan concepts?} + +\item{\code{runTimeSeries}}{Generate and export the time series diagnostics?} + +\item{\code{runVisitContext}}{Generate and export index-date visit context?} + +\item{\code{runBreakdownIndexEvents}}{Generate and export the breakdown of index events?} + +\item{\code{runIncidenceRate}}{Generate and export the cohort incidence rates?} + +\item{\code{runCohortRelationship}}{Generate and export the cohort relationship? Cohort relationship checks the temporal +relationship between two or more cohorts.} + +\item{\code{runTemporalCohortCharacterization}}{Generate and export the temporal cohort characterization? +Only records with values greater than 0.001 are returned.} + +\item{\code{temporalCovariateSettings}}{Either an object of type \code{covariateSettings} as created using one of +the createTemporalCovariateSettings function in the FeatureExtraction package, or a list +of such objects.} + +\item{\code{minCharacterizationMean}}{The minimum mean value for characterization output. Values below this will be cut off from output. This +will help reduce the file size of the characterization output, but will remove information +on covariates that have very low values. The default is 0.001 (i.e. 0.1 percent)} + +\item{\code{irWashoutPeriod}}{Number of days washout to include in calculation of incidence rates - default is 0} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortDiagnosticsModule-validateModuleSpecifications}{}}} +\subsection{Method \code{validateModuleSpecifications()}}{ +Validate the module specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortDiagnosticsModule$validateModuleSpecifications(moduleSpecifications)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{moduleSpecifications}}{The CohortIncidence module specifications} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortDiagnosticsModule-clone}{}}} +\subsection{Method \code{clone()}}{ +The objects of this class are cloneable with this method. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortDiagnosticsModule$clone(deep = FALSE)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{deep}}{Whether to make a deep clone.} +} +\if{html}{\out{
    }} +} +} +} diff --git a/man/CohortGeneratorModule.Rd b/man/CohortGeneratorModule.Rd new file mode 100644 index 00000000..9d9c25f7 --- /dev/null +++ b/man/CohortGeneratorModule.Rd @@ -0,0 +1,318 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Module-CohortGenerator.R +\name{CohortGeneratorModule} +\alias{CohortGeneratorModule} +\title{Generate cohorts with the \href{https://ohdsi.github.io/CohortGenerator/}{HADES CohortGenerator Package}} +\description{ +Generates cohorts against the OMOP Common Data Model +} +\section{Super class}{ +\code{\link[Strategus:StrategusModule]{Strategus::StrategusModule}} -> \code{CohortGeneratorModule} +} +\section{Public fields}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{cohortDefinitionSharedResourcesClassName}}{A constant for the name +of the cohort definition shared resources section of the analysis +specification} + +\item{\code{negativeControlOutcomeSharedResourcesClassName}}{A constant for the +name of the negative control outcome shared resources section of the +analysis specification} +} +\if{html}{\out{
    }} +} +\section{Methods}{ +\subsection{Public methods}{ +\itemize{ +\item \href{#method-CohortGeneratorModule-new}{\code{CohortGeneratorModule$new()}} +\item \href{#method-CohortGeneratorModule-execute}{\code{CohortGeneratorModule$execute()}} +\item \href{#method-CohortGeneratorModule-createResultsDataModel}{\code{CohortGeneratorModule$createResultsDataModel()}} +\item \href{#method-CohortGeneratorModule-getResultsDataModelSpecification}{\code{CohortGeneratorModule$getResultsDataModelSpecification()}} +\item \href{#method-CohortGeneratorModule-uploadResults}{\code{CohortGeneratorModule$uploadResults()}} +\item \href{#method-CohortGeneratorModule-createModuleSpecifications}{\code{CohortGeneratorModule$createModuleSpecifications()}} +\item \href{#method-CohortGeneratorModule-createCohortSharedResourceSpecifications}{\code{CohortGeneratorModule$createCohortSharedResourceSpecifications()}} +\item \href{#method-CohortGeneratorModule-createNegativeControlOutcomeCohortSharedResourceSpecifications}{\code{CohortGeneratorModule$createNegativeControlOutcomeCohortSharedResourceSpecifications()}} +\item \href{#method-CohortGeneratorModule-validateModuleSpecifications}{\code{CohortGeneratorModule$validateModuleSpecifications()}} +\item \href{#method-CohortGeneratorModule-validateCohortSharedResourceSpecifications}{\code{CohortGeneratorModule$validateCohortSharedResourceSpecifications()}} +\item \href{#method-CohortGeneratorModule-validateNegativeControlOutcomeCohortSharedResourceSpecifications}{\code{CohortGeneratorModule$validateNegativeControlOutcomeCohortSharedResourceSpecifications()}} +\item \href{#method-CohortGeneratorModule-clone}{\code{CohortGeneratorModule$clone()}} +} +} +\if{html}{\out{ +
    Inherited methods + +
    +}} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortGeneratorModule-new}{}}} +\subsection{Method \code{new()}}{ +Initialize the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortGeneratorModule$new()}\if{html}{\out{
    }} +} + +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortGeneratorModule-execute}{}}} +\subsection{Method \code{execute()}}{ +Generates the cohorts +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortGeneratorModule$execute( + connectionDetails, + analysisSpecifications, + executionSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{connectionDetails}}{An object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{executionSettings}}{An object of type \code{ExecutionSettings} as created +by \code{\link[=createCdmExecutionSettings]{createCdmExecutionSettings()}} or \code{\link[=createResultsExecutionSettings]{createResultsExecutionSettings()}}.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortGeneratorModule-createResultsDataModel}{}}} +\subsection{Method \code{createResultsDataModel()}}{ +Create the results data model for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortGeneratorModule$createResultsDataModel( + resultsConnectionDetails, + resultsDatabaseSchema, + tablePrefix = "" +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsDatabaseSchema}}{The schema in the results database that holds the results data model.} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortGeneratorModule-getResultsDataModelSpecification}{}}} +\subsection{Method \code{getResultsDataModelSpecification()}}{ +Get the results data model specification for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortGeneratorModule$getResultsDataModelSpecification(tablePrefix = "")}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortGeneratorModule-uploadResults}{}}} +\subsection{Method \code{uploadResults()}}{ +Upload the results for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortGeneratorModule$uploadResults( + resultsConnectionDetails, + analysisSpecifications, + resultsDataModelSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{resultsDataModelSettings}}{The results data model settings as created using [@seealso \code{\link[=createResultsDataModelSettings]{createResultsDataModelSettings()}}]} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortGeneratorModule-createModuleSpecifications}{}}} +\subsection{Method \code{createModuleSpecifications()}}{ +Creates the CohortGenerator Module Specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortGeneratorModule$createModuleSpecifications(generateStats = TRUE)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{generateStats}}{When TRUE, the Circe cohort definition SQL will +include steps to compute inclusion rule statistics.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortGeneratorModule-createCohortSharedResourceSpecifications}{}}} +\subsection{Method \code{createCohortSharedResourceSpecifications()}}{ +Create shared specifications for the cohort definition set +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortGeneratorModule$createCohortSharedResourceSpecifications( + cohortDefinitionSet +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{cohortDefinitionSet}}{The cohort definition set to include in the +specification. See the CohortGenerator package for details on how to +build this object.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortGeneratorModule-createNegativeControlOutcomeCohortSharedResourceSpecifications}{}}} +\subsection{Method \code{createNegativeControlOutcomeCohortSharedResourceSpecifications()}}{ +Create shared specifications for the negative control outcomes cohort set +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortGeneratorModule$createNegativeControlOutcomeCohortSharedResourceSpecifications( + negativeControlOutcomeCohortSet, + occurrenceType, + detectOnDescendants +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{negativeControlOutcomeCohortSet}}{The negative control outcome cohort +definition set defines the concepts to use to construct negative control +outcome cohorts. See the CohortGenerator package for more details.} + +\item{\code{occurrenceType}}{Either "first" or "all} + +\item{\code{detectOnDescendants}}{When TRUE, the concept ID for the negative +control will use the \code{concept_ancestor} table and will detect +descendant concepts when constructing the cohort.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortGeneratorModule-validateModuleSpecifications}{}}} +\subsection{Method \code{validateModuleSpecifications()}}{ +Validate the module specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortGeneratorModule$validateModuleSpecifications(moduleSpecifications)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{moduleSpecifications}}{The CohortGenerator module specifications} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortGeneratorModule-validateCohortSharedResourceSpecifications}{}}} +\subsection{Method \code{validateCohortSharedResourceSpecifications()}}{ +Validate the cohort shared resource specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortGeneratorModule$validateCohortSharedResourceSpecifications( + cohortSharedResourceSpecifications +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{cohortSharedResourceSpecifications}}{The cohort shared resource specifications} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortGeneratorModule-validateNegativeControlOutcomeCohortSharedResourceSpecifications}{}}} +\subsection{Method \code{validateNegativeControlOutcomeCohortSharedResourceSpecifications()}}{ +Validate the cohort shared resource specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortGeneratorModule$validateNegativeControlOutcomeCohortSharedResourceSpecifications( + negativeControlOutcomeCohortSharedResourceSpecifications +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{negativeControlOutcomeCohortSharedResourceSpecifications}}{The cohort shared resource specifications} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortGeneratorModule-clone}{}}} +\subsection{Method \code{clone()}}{ +The objects of this class are cloneable with this method. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortGeneratorModule$clone(deep = FALSE)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{deep}}{Whether to make a deep clone.} +} +\if{html}{\out{
    }} +} +} +} diff --git a/man/CohortIncidenceModule.Rd b/man/CohortIncidenceModule.Rd new file mode 100644 index 00000000..e286310c --- /dev/null +++ b/man/CohortIncidenceModule.Rd @@ -0,0 +1,220 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Module-CohortIncidence.R +\name{CohortIncidenceModule} +\alias{CohortIncidenceModule} +\title{Compute incidence with the \href{https://ohdsi.github.io/CohortIncidence/}{HADES CohortIncidence Package}} +\description{ +Computes incidence rates for cohorts against the OMOP Common Data Model +} +\section{Super class}{ +\code{\link[Strategus:StrategusModule]{Strategus::StrategusModule}} -> \code{CohortIncidenceModule} +} +\section{Public fields}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{tablePrefix}}{The table prefix to append to results tables} +} +\if{html}{\out{
    }} +} +\section{Methods}{ +\subsection{Public methods}{ +\itemize{ +\item \href{#method-CohortIncidenceModule-new}{\code{CohortIncidenceModule$new()}} +\item \href{#method-CohortIncidenceModule-execute}{\code{CohortIncidenceModule$execute()}} +\item \href{#method-CohortIncidenceModule-createResultsDataModel}{\code{CohortIncidenceModule$createResultsDataModel()}} +\item \href{#method-CohortIncidenceModule-getResultsDataModelSpecification}{\code{CohortIncidenceModule$getResultsDataModelSpecification()}} +\item \href{#method-CohortIncidenceModule-uploadResults}{\code{CohortIncidenceModule$uploadResults()}} +\item \href{#method-CohortIncidenceModule-createModuleSpecifications}{\code{CohortIncidenceModule$createModuleSpecifications()}} +\item \href{#method-CohortIncidenceModule-validateModuleSpecifications}{\code{CohortIncidenceModule$validateModuleSpecifications()}} +\item \href{#method-CohortIncidenceModule-clone}{\code{CohortIncidenceModule$clone()}} +} +} +\if{html}{\out{ +
    Inherited methods + +
    +}} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortIncidenceModule-new}{}}} +\subsection{Method \code{new()}}{ +Initialize the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortIncidenceModule$new()}\if{html}{\out{
    }} +} + +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortIncidenceModule-execute}{}}} +\subsection{Method \code{execute()}}{ +Execute the CohortIncidence package +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortIncidenceModule$execute( + connectionDetails, + analysisSpecifications, + executionSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{connectionDetails}}{An object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{executionSettings}}{An object of type \code{ExecutionSettings} as created +by \code{\link[=createCdmExecutionSettings]{createCdmExecutionSettings()}} or \code{\link[=createResultsExecutionSettings]{createResultsExecutionSettings()}}.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortIncidenceModule-createResultsDataModel}{}}} +\subsection{Method \code{createResultsDataModel()}}{ +Create the results data model for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortIncidenceModule$createResultsDataModel( + resultsConnectionDetails, + resultsDatabaseSchema, + tablePrefix = "" +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsDatabaseSchema}}{The schema in the results database that holds the results data model.} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortIncidenceModule-getResultsDataModelSpecification}{}}} +\subsection{Method \code{getResultsDataModelSpecification()}}{ +Get the results data model specification for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortIncidenceModule$getResultsDataModelSpecification(tablePrefix = "")}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortIncidenceModule-uploadResults}{}}} +\subsection{Method \code{uploadResults()}}{ +Upload the results for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortIncidenceModule$uploadResults( + resultsConnectionDetails, + analysisSpecifications, + resultsDataModelSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{resultsDataModelSettings}}{The results data model settings as created using [@seealso \code{\link[=createResultsDataModelSettings]{createResultsDataModelSettings()}}]} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortIncidenceModule-createModuleSpecifications}{}}} +\subsection{Method \code{createModuleSpecifications()}}{ +Creates the CohortIncidence Module Specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortIncidenceModule$createModuleSpecifications(irDesign = NULL)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{irDesign}}{The incidence rate design created from the CohortIncidence +package} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortIncidenceModule-validateModuleSpecifications}{}}} +\subsection{Method \code{validateModuleSpecifications()}}{ +Validate the module specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortIncidenceModule$validateModuleSpecifications(moduleSpecifications)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{moduleSpecifications}}{The CohortIncidence module specifications} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortIncidenceModule-clone}{}}} +\subsection{Method \code{clone()}}{ +The objects of this class are cloneable with this method. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortIncidenceModule$clone(deep = FALSE)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{deep}}{Whether to make a deep clone.} +} +\if{html}{\out{
    }} +} +} +} diff --git a/man/CohortMethodModule.Rd b/man/CohortMethodModule.Rd new file mode 100644 index 00000000..6b3b7c7c --- /dev/null +++ b/man/CohortMethodModule.Rd @@ -0,0 +1,254 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Module-CohortMethod.R +\name{CohortMethodModule} +\alias{CohortMethodModule} +\title{New-user cohort studies with the \href{https://ohdsi.github.io/CohortMethod/}{HADES CohortMethod Package}} +\description{ +Module for performing new-user cohort studies against +the OMOP Common Data Model +} +\section{Super class}{ +\code{\link[Strategus:StrategusModule]{Strategus::StrategusModule}} -> \code{CohortMethodModule} +} +\section{Methods}{ +\subsection{Public methods}{ +\itemize{ +\item \href{#method-CohortMethodModule-new}{\code{CohortMethodModule$new()}} +\item \href{#method-CohortMethodModule-execute}{\code{CohortMethodModule$execute()}} +\item \href{#method-CohortMethodModule-createResultsDataModel}{\code{CohortMethodModule$createResultsDataModel()}} +\item \href{#method-CohortMethodModule-getResultsDataModelSpecification}{\code{CohortMethodModule$getResultsDataModelSpecification()}} +\item \href{#method-CohortMethodModule-uploadResults}{\code{CohortMethodModule$uploadResults()}} +\item \href{#method-CohortMethodModule-createModuleSpecifications}{\code{CohortMethodModule$createModuleSpecifications()}} +\item \href{#method-CohortMethodModule-validateModuleSpecifications}{\code{CohortMethodModule$validateModuleSpecifications()}} +\item \href{#method-CohortMethodModule-clone}{\code{CohortMethodModule$clone()}} +} +} +\if{html}{\out{ +
    Inherited methods + +
    +}} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortMethodModule-new}{}}} +\subsection{Method \code{new()}}{ +Initialize the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortMethodModule$new()}\if{html}{\out{
    }} +} + +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortMethodModule-execute}{}}} +\subsection{Method \code{execute()}}{ +Executes the CohortMethod package +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortMethodModule$execute( + connectionDetails, + analysisSpecifications, + executionSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{connectionDetails}}{An object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{The analysis specifications for the study} + +\item{\code{executionSettings}}{An object of type \code{ExecutionSettings} as created +by \code{\link[=createCdmExecutionSettings]{createCdmExecutionSettings()}} or \code{\link[=createResultsExecutionSettings]{createResultsExecutionSettings()}}.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortMethodModule-createResultsDataModel}{}}} +\subsection{Method \code{createResultsDataModel()}}{ +Create the results data model for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortMethodModule$createResultsDataModel( + resultsConnectionDetails, + resultsDatabaseSchema, + tablePrefix = "" +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsDatabaseSchema}}{The schema in the results database that holds the results data model.} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortMethodModule-getResultsDataModelSpecification}{}}} +\subsection{Method \code{getResultsDataModelSpecification()}}{ +Get the results data model specification for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortMethodModule$getResultsDataModelSpecification(tablePrefix = "")}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortMethodModule-uploadResults}{}}} +\subsection{Method \code{uploadResults()}}{ +Upload the results for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortMethodModule$uploadResults( + resultsConnectionDetails, + analysisSpecifications, + resultsDataModelSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{resultsDataModelSettings}}{The results data model settings as created using [@seealso \code{\link[=createResultsDataModelSettings]{createResultsDataModelSettings()}}]} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortMethodModule-createModuleSpecifications}{}}} +\subsection{Method \code{createModuleSpecifications()}}{ +Creates the CohortMethod Module Specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortMethodModule$createModuleSpecifications( + cmAnalysisList, + targetComparatorOutcomesList, + analysesToExclude = NULL, + refitPsForEveryOutcome = FALSE, + refitPsForEveryStudyPopulation = TRUE, + cmDiagnosticThresholds = CohortMethod::createCmDiagnosticThresholds() +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{cmAnalysisList}}{A list of objects of type \code{cmAnalysis} as created using +the `\link[CohortMethod:createCmAnalysis]{CohortMethod::createCmAnalysis} function.} + +\item{\code{targetComparatorOutcomesList}}{A list of objects of type \code{targetComparatorOutcomes} as +created using the \link[CohortMethod:createTargetComparatorOutcomes]{CohortMethod::createTargetComparatorOutcomes} +function.} + +\item{\code{analysesToExclude}}{Analyses to exclude. See the Analyses to Exclude section for details.} + +\item{\code{refitPsForEveryOutcome}}{Should the propensity model be fitted for every outcome (i.e. +after people who already had the outcome are removed)? If +false, a single propensity model will be fitted, and people +who had the outcome previously will be removed afterwards.} + +\item{\code{refitPsForEveryStudyPopulation}}{Should the propensity model be fitted for every study population +definition? If false, a single propensity model will be fitted, +and the study population criteria will be applied afterwards.} + +\item{\code{cmDiagnosticThresholds}}{An object of type \code{CmDiagnosticThresholds} as created using +\code{\link[CohortMethod:createCmDiagnosticThresholds]{CohortMethod::createCmDiagnosticThresholds()}}.} +} +\if{html}{\out{
    }} +} +\subsection{Details}{ +Run a list of analyses for the target-comparator-outcomes of interest. This function will run all +specified analyses against all hypotheses of interest, meaning that the total number of outcome +models is \code{length(cmAnalysisList) * length(targetComparatorOutcomesList)} (if all analyses specify an +outcome model should be fitted). When you provide several analyses it will determine whether any of +the analyses have anything in common, and will take advantage of this fact. For example, if we +specify several analyses that only differ in the way the outcome model is fitted, then this +function will extract the data and fit the propensity model only once, and re-use this in all the +analysis. + +After completion, a tibble containing references to all generated files can be obtained using the +\code{\link[CohortMethod:getFileReference]{CohortMethod::getFileReference()}} function. A summary of the analysis results can be obtained using the +\code{\link[CohortMethod:getResultsSummary]{CohortMethod::getResultsSummary()}} function. +\subsection{Analyses to Exclude}{ + +Normally, \code{runCmAnalyses} will run all combinations of target-comparator-outcome-analyses settings. +However, sometimes we may not need all those combinations. Using the \code{analysesToExclude} argument, +we can remove certain items from the full matrix. This argument should be a data frame with at least +one of the following columns: +} +} + +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortMethodModule-validateModuleSpecifications}{}}} +\subsection{Method \code{validateModuleSpecifications()}}{ +Validate the module specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortMethodModule$validateModuleSpecifications(moduleSpecifications)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{moduleSpecifications}}{The CohortMethod module specifications} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-CohortMethodModule-clone}{}}} +\subsection{Method \code{clone()}}{ +The objects of this class are cloneable with this method. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{CohortMethodModule$clone(deep = FALSE)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{deep}}{Whether to make a deep clone.} +} +\if{html}{\out{
    }} +} +} +} diff --git a/man/EvidenceSynthesisModule.Rd b/man/EvidenceSynthesisModule.Rd new file mode 100644 index 00000000..1c0549c1 --- /dev/null +++ b/man/EvidenceSynthesisModule.Rd @@ -0,0 +1,422 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Module-EvidenceSynthesis.R +\name{EvidenceSynthesisModule} +\alias{EvidenceSynthesisModule} +\title{Meta-analysis with the \href{https://ohdsi.github.io/EvidenceSynthesis/}{HADES EvidenceSynthesis Package}} +\description{ +Module for for combining causal effect estimates and study diagnostics +across multiple data sites in a distributed study. This includes functions +for performing meta-analysis and forest plots +} +\section{Super class}{ +\code{\link[Strategus:StrategusModule]{Strategus::StrategusModule}} -> \code{EvidenceSynthesisModule} +} +\section{Methods}{ +\subsection{Public methods}{ +\itemize{ +\item \href{#method-EvidenceSynthesisModule-new}{\code{EvidenceSynthesisModule$new()}} +\item \href{#method-EvidenceSynthesisModule-execute}{\code{EvidenceSynthesisModule$execute()}} +\item \href{#method-EvidenceSynthesisModule-createResultsDataModel}{\code{EvidenceSynthesisModule$createResultsDataModel()}} +\item \href{#method-EvidenceSynthesisModule-getResultsDataModelSpecification}{\code{EvidenceSynthesisModule$getResultsDataModelSpecification()}} +\item \href{#method-EvidenceSynthesisModule-uploadResults}{\code{EvidenceSynthesisModule$uploadResults()}} +\item \href{#method-EvidenceSynthesisModule-validateModuleSpecifications}{\code{EvidenceSynthesisModule$validateModuleSpecifications()}} +\item \href{#method-EvidenceSynthesisModule-createEvidenceSynthesisSource}{\code{EvidenceSynthesisModule$createEvidenceSynthesisSource()}} +\item \href{#method-EvidenceSynthesisModule-createRandomEffectsMetaAnalysis}{\code{EvidenceSynthesisModule$createRandomEffectsMetaAnalysis()}} +\item \href{#method-EvidenceSynthesisModule-createFixedEffectsMetaAnalysis}{\code{EvidenceSynthesisModule$createFixedEffectsMetaAnalysis()}} +\item \href{#method-EvidenceSynthesisModule-createBayesianMetaAnalysis}{\code{EvidenceSynthesisModule$createBayesianMetaAnalysis()}} +\item \href{#method-EvidenceSynthesisModule-createEsDiagnosticThresholds}{\code{EvidenceSynthesisModule$createEsDiagnosticThresholds()}} +\item \href{#method-EvidenceSynthesisModule-createModuleSpecifications}{\code{EvidenceSynthesisModule$createModuleSpecifications()}} +\item \href{#method-EvidenceSynthesisModule-clone}{\code{EvidenceSynthesisModule$clone()}} +} +} +\if{html}{\out{ +
    Inherited methods + +
    +}} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-EvidenceSynthesisModule-new}{}}} +\subsection{Method \code{new()}}{ +Initialize the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{EvidenceSynthesisModule$new()}\if{html}{\out{
    }} +} + +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-EvidenceSynthesisModule-execute}{}}} +\subsection{Method \code{execute()}}{ +Executes the EvidenceSynthesis package +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{EvidenceSynthesisModule$execute( + connectionDetails, + analysisSpecifications, + executionSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{connectionDetails}}{An object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{executionSettings}}{An object of type \code{ExecutionSettings} as created +by \code{\link[=createCdmExecutionSettings]{createCdmExecutionSettings()}} or \code{\link[=createResultsExecutionSettings]{createResultsExecutionSettings()}}.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-EvidenceSynthesisModule-createResultsDataModel}{}}} +\subsection{Method \code{createResultsDataModel()}}{ +Create the results data model for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{EvidenceSynthesisModule$createResultsDataModel( + resultsConnectionDetails, + resultsDatabaseSchema, + tablePrefix = "" +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsDatabaseSchema}}{The schema in the results database that holds the results data model.} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-EvidenceSynthesisModule-getResultsDataModelSpecification}{}}} +\subsection{Method \code{getResultsDataModelSpecification()}}{ +Get the results data model specification for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{EvidenceSynthesisModule$getResultsDataModelSpecification(tablePrefix = "")}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-EvidenceSynthesisModule-uploadResults}{}}} +\subsection{Method \code{uploadResults()}}{ +Upload the results for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{EvidenceSynthesisModule$uploadResults( + resultsConnectionDetails, + analysisSpecifications, + resultsDataModelSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{resultsDataModelSettings}}{The results data model settings as created using [@seealso \code{\link[=createResultsDataModelSettings]{createResultsDataModelSettings()}}]} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-EvidenceSynthesisModule-validateModuleSpecifications}{}}} +\subsection{Method \code{validateModuleSpecifications()}}{ +Validate the module specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{EvidenceSynthesisModule$validateModuleSpecifications(moduleSpecifications)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{moduleSpecifications}}{The EvidenceSynthesis module specifications +Create an evidence synthesis source} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-EvidenceSynthesisModule-createEvidenceSynthesisSource}{}}} +\subsection{Method \code{createEvidenceSynthesisSource()}}{ +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{EvidenceSynthesisModule$createEvidenceSynthesisSource( + sourceMethod = "CohortMethod", + databaseIds = NULL, + analysisIds = NULL, + likelihoodApproximation = "adaptive grid" +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{sourceMethod}}{The source method generating the estimates to synthesize. Can be "CohortMethod" or +"SelfControlledCaseSeries"} + +\item{\code{databaseIds}}{The database IDs to include. Use \code{databaseIds = NULL} to include all database IDs.} + +\item{\code{analysisIds}}{The source method analysis IDs to include. Use \code{analysisIds = NULL} to include all +analysis IDs.} + +\item{\code{likelihoodApproximation}}{The type of likelihood approximation. Can be "adaptive grid" or "normal".} +} +\if{html}{\out{
    }} +} +\subsection{Returns}{ +An object of type \code{EvidenceSynthesisSource}. +Create parameters for a random-effects meta-analysis +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-EvidenceSynthesisModule-createRandomEffectsMetaAnalysis}{}}} +\subsection{Method \code{createRandomEffectsMetaAnalysis()}}{ +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{EvidenceSynthesisModule$createRandomEffectsMetaAnalysis( + alpha = 0.05, + evidenceSynthesisAnalysisId = 1, + evidenceSynthesisDescription = "Random-effects", + evidenceSynthesisSource = NULL, + controlType = "outcome" +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{alpha}}{The alpha (expected type I error) used for the confidence intervals.} + +\item{\code{evidenceSynthesisAnalysisId}}{description} + +\item{\code{evidenceSynthesisDescription}}{description} + +\item{\code{evidenceSynthesisSource}}{description} + +\item{\code{controlType}}{description +Create a parameter object for the function computeFixedEffectMetaAnalysis} +} +\if{html}{\out{
    }} +} +\subsection{Details}{ +Use DerSimonian-Laird meta-analysis +} + +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-EvidenceSynthesisModule-createFixedEffectsMetaAnalysis}{}}} +\subsection{Method \code{createFixedEffectsMetaAnalysis()}}{ +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{EvidenceSynthesisModule$createFixedEffectsMetaAnalysis( + alpha = 0.05, + evidenceSynthesisAnalysisId = 1, + evidenceSynthesisDescription = "Fixed-effects", + evidenceSynthesisSource = NULL, + controlType = "outcome" +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{alpha}}{The alpha (expected type I error) used for the confidence intervals.} + +\item{\code{evidenceSynthesisAnalysisId}}{description} + +\item{\code{evidenceSynthesisDescription}}{description} + +\item{\code{evidenceSynthesisSource}}{description} + +\item{\code{controlType}}{description +Create a parameter object for the function computeBayesianMetaAnalysis} +} +\if{html}{\out{
    }} +} +\subsection{Details}{ +Create an object defining the parameter values. +} + +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-EvidenceSynthesisModule-createBayesianMetaAnalysis}{}}} +\subsection{Method \code{createBayesianMetaAnalysis()}}{ +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{EvidenceSynthesisModule$createBayesianMetaAnalysis( + chainLength = 1100000, + burnIn = 1e+05, + subSampleFrequency = 100, + priorSd = c(2, 0.5), + alpha = 0.05, + robust = FALSE, + df = 4, + seed = 1, + evidenceSynthesisAnalysisId = 1, + evidenceSynthesisDescription = "Bayesian random-effects", + evidenceSynthesisSource = NULL, + controlType = "outcome" +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{chainLength}}{Number of MCMC iterations.} + +\item{\code{burnIn}}{Number of MCMC iterations to consider as burn in.} + +\item{\code{subSampleFrequency}}{Subsample frequency for the MCMC.} + +\item{\code{priorSd}}{A two-dimensional vector with the standard deviation of the prior for mu and tau, respectively.} + +\item{\code{alpha}}{The alpha (expected type I error) used for the credible intervals.} + +\item{\code{robust}}{Whether or not to use a t-distribution model; default: FALSE.} + +\item{\code{df}}{Degrees of freedom for the t-model, only used if robust is TRUE.} + +\item{\code{seed}}{The seed for the random number generator.} + +\item{\code{evidenceSynthesisAnalysisId}}{description} + +\item{\code{evidenceSynthesisDescription}}{description} + +\item{\code{evidenceSynthesisSource}}{description} + +\item{\code{controlType}}{description +Create EvidenceSynthesis diagnostics thresholds} +} +\if{html}{\out{
    }} +} +\subsection{Details}{ +Create an object defining the parameter values. +} + +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-EvidenceSynthesisModule-createEsDiagnosticThresholds}{}}} +\subsection{Method \code{createEsDiagnosticThresholds()}}{ +Threshold used to determine if we pass or fail diagnostics. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{EvidenceSynthesisModule$createEsDiagnosticThresholds( + mdrrThreshold = 10, + easeThreshold = 0.25, + i2Threshold = 0.4, + tauThreshold = log(2) +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{mdrrThreshold}}{What is the maximum allowed minimum detectable relative risk +(MDRR)?} + +\item{\code{easeThreshold}}{What is the maximum allowed expected absolute systematic error +(EASE).} + +\item{\code{i2Threshold}}{What is the maximum allowed I^2 (measure of between-database +heterogeneity in random-effects models)?} + +\item{\code{tauThreshold}}{What is the maximum allowed tau (measure of between-database +heterogeneity in Bayesian random-effects models)?} +} +\if{html}{\out{
    }} +} +\subsection{Returns}{ +An object of type \code{EsDiagnosticThresholds}. +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-EvidenceSynthesisModule-createModuleSpecifications}{}}} +\subsection{Method \code{createModuleSpecifications()}}{ +Creates the module Specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{EvidenceSynthesisModule$createModuleSpecifications( + evidenceSynthesisAnalysisList, + esDiagnosticThresholds = self$createEsDiagnosticThresholds() +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{evidenceSynthesisAnalysisList}}{A list of objects of type \code{EvidenceSynthesisAnalysis} as generated +by either the \href{../../Strategus/html/EvidenceSynthesisModule.html#method-createFixedEffectsMetaAnalysis}{\code{EvidenceSynthesisModule$createFixedEffectsMetaAnalysis()}} +or \href{../../Strategus/html/EvidenceSynthesisModule.html#method-createBayesianMetaAnalysis}{\code{EvidenceSynthesisModule$createBayesianMetaAnalysis()}} function.} + +\item{\code{esDiagnosticThresholds}}{An object of type\code{EsDiagnosticThresholds} as generated by the +\href{../../Strategus/html/EvidenceSynthesisModule.html#method-createEsDiagnosticThresholds}{\code{EvidenceSynthesisModule$createEsDiagnosticThresholds()}} function.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-EvidenceSynthesisModule-clone}{}}} +\subsection{Method \code{clone()}}{ +The objects of this class are cloneable with this method. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{EvidenceSynthesisModule$clone(deep = FALSE)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{deep}}{Whether to make a deep clone.} +} +\if{html}{\out{
    }} +} +} +} diff --git a/man/PatientLevelPredictionModule.Rd b/man/PatientLevelPredictionModule.Rd new file mode 100644 index 00000000..5c53846b --- /dev/null +++ b/man/PatientLevelPredictionModule.Rd @@ -0,0 +1,220 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Module-PatientLevelPrediction.R +\name{PatientLevelPredictionModule} +\alias{PatientLevelPredictionModule} +\title{Patient-level prediction with the \href{https://ohdsi.github.io/PatientLevelPrediction/}{HADES PatientLevelPrediction Package}} +\description{ +Module for performing patient-level prediction in an observational +database in the OMOP Common Data Model. +} +\section{Super class}{ +\code{\link[Strategus:StrategusModule]{Strategus::StrategusModule}} -> \code{PatientLevelPredictionModule} +} +\section{Public fields}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{tablePrefix}}{The table prefix to append to the results tables} +} +\if{html}{\out{
    }} +} +\section{Methods}{ +\subsection{Public methods}{ +\itemize{ +\item \href{#method-PatientLevelPredictionModule-new}{\code{PatientLevelPredictionModule$new()}} +\item \href{#method-PatientLevelPredictionModule-execute}{\code{PatientLevelPredictionModule$execute()}} +\item \href{#method-PatientLevelPredictionModule-createResultsDataModel}{\code{PatientLevelPredictionModule$createResultsDataModel()}} +\item \href{#method-PatientLevelPredictionModule-getResultsDataModelSpecification}{\code{PatientLevelPredictionModule$getResultsDataModelSpecification()}} +\item \href{#method-PatientLevelPredictionModule-uploadResults}{\code{PatientLevelPredictionModule$uploadResults()}} +\item \href{#method-PatientLevelPredictionModule-createModuleSpecifications}{\code{PatientLevelPredictionModule$createModuleSpecifications()}} +\item \href{#method-PatientLevelPredictionModule-validateModuleSpecifications}{\code{PatientLevelPredictionModule$validateModuleSpecifications()}} +\item \href{#method-PatientLevelPredictionModule-clone}{\code{PatientLevelPredictionModule$clone()}} +} +} +\if{html}{\out{ +
    Inherited methods + +
    +}} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-PatientLevelPredictionModule-new}{}}} +\subsection{Method \code{new()}}{ +Initialize the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{PatientLevelPredictionModule$new()}\if{html}{\out{
    }} +} + +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-PatientLevelPredictionModule-execute}{}}} +\subsection{Method \code{execute()}}{ +Executes the PatientLevelPrediction package +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{PatientLevelPredictionModule$execute( + connectionDetails, + analysisSpecifications, + executionSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{connectionDetails}}{An object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{executionSettings}}{An object of type \code{ExecutionSettings} as created +by \code{\link[=createCdmExecutionSettings]{createCdmExecutionSettings()}} or \code{\link[=createResultsExecutionSettings]{createResultsExecutionSettings()}}.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-PatientLevelPredictionModule-createResultsDataModel}{}}} +\subsection{Method \code{createResultsDataModel()}}{ +Create the results data model for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{PatientLevelPredictionModule$createResultsDataModel( + resultsConnectionDetails, + resultsDatabaseSchema, + tablePrefix = self$tablePrefix +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsDatabaseSchema}}{The schema in the results database that holds the results data model.} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-PatientLevelPredictionModule-getResultsDataModelSpecification}{}}} +\subsection{Method \code{getResultsDataModelSpecification()}}{ +Get the results data model specification for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{PatientLevelPredictionModule$getResultsDataModelSpecification(tablePrefix = "")}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-PatientLevelPredictionModule-uploadResults}{}}} +\subsection{Method \code{uploadResults()}}{ +Upload the results for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{PatientLevelPredictionModule$uploadResults( + resultsConnectionDetails, + analysisSpecifications, + resultsDataModelSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{resultsDataModelSettings}}{The results data model settings as created using [@seealso \code{\link[=createResultsDataModelSettings]{createResultsDataModelSettings()}}]} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-PatientLevelPredictionModule-createModuleSpecifications}{}}} +\subsection{Method \code{createModuleSpecifications()}}{ +Creates the PatientLevelPrediction Module Specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{PatientLevelPredictionModule$createModuleSpecifications(modelDesignList)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{modelDesignList}}{A list of model designs created using \code{PatientLevelPrediction::createModelDesign()}} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-PatientLevelPredictionModule-validateModuleSpecifications}{}}} +\subsection{Method \code{validateModuleSpecifications()}}{ +Validate the module specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{PatientLevelPredictionModule$validateModuleSpecifications(moduleSpecifications)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{moduleSpecifications}}{The PatientLevelPrediction module specifications} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-PatientLevelPredictionModule-clone}{}}} +\subsection{Method \code{clone()}}{ +The objects of this class are cloneable with this method. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{PatientLevelPredictionModule$clone(deep = FALSE)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{deep}}{Whether to make a deep clone.} +} +\if{html}{\out{
    }} +} +} +} diff --git a/man/SelfControlledCaseSeriesModule.Rd b/man/SelfControlledCaseSeriesModule.Rd new file mode 100644 index 00000000..90edb2ba --- /dev/null +++ b/man/SelfControlledCaseSeriesModule.Rd @@ -0,0 +1,238 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Module-SelfControlledCaseSeries.R +\name{SelfControlledCaseSeriesModule} +\alias{SelfControlledCaseSeriesModule} +\title{Self-Controlled Case Series design with the \href{https://ohdsi.github.io/SelfControlledCaseSeries/}{HADES SelfControlledCaseSeries Package}} +\description{ +Module for performing Self-Controlled Case Series (SCCS) analyses +against the OMOP Common Data Model. +} +\section{Super class}{ +\code{\link[Strategus:StrategusModule]{Strategus::StrategusModule}} -> \code{SelfControlledCaseSeriesModule} +} +\section{Public fields}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{tablePrefix}}{The table prefix for results tables} +} +\if{html}{\out{
    }} +} +\section{Methods}{ +\subsection{Public methods}{ +\itemize{ +\item \href{#method-SelfControlledCaseSeriesModule-new}{\code{SelfControlledCaseSeriesModule$new()}} +\item \href{#method-SelfControlledCaseSeriesModule-execute}{\code{SelfControlledCaseSeriesModule$execute()}} +\item \href{#method-SelfControlledCaseSeriesModule-createResultsDataModel}{\code{SelfControlledCaseSeriesModule$createResultsDataModel()}} +\item \href{#method-SelfControlledCaseSeriesModule-getResultsDataModelSpecification}{\code{SelfControlledCaseSeriesModule$getResultsDataModelSpecification()}} +\item \href{#method-SelfControlledCaseSeriesModule-uploadResults}{\code{SelfControlledCaseSeriesModule$uploadResults()}} +\item \href{#method-SelfControlledCaseSeriesModule-createModuleSpecifications}{\code{SelfControlledCaseSeriesModule$createModuleSpecifications()}} +\item \href{#method-SelfControlledCaseSeriesModule-validateModuleSpecifications}{\code{SelfControlledCaseSeriesModule$validateModuleSpecifications()}} +\item \href{#method-SelfControlledCaseSeriesModule-clone}{\code{SelfControlledCaseSeriesModule$clone()}} +} +} +\if{html}{\out{ +
    Inherited methods + +
    +}} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-SelfControlledCaseSeriesModule-new}{}}} +\subsection{Method \code{new()}}{ +Initialize the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{SelfControlledCaseSeriesModule$new()}\if{html}{\out{
    }} +} + +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-SelfControlledCaseSeriesModule-execute}{}}} +\subsection{Method \code{execute()}}{ +Executes the SelfControlledCaseSeries package +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{SelfControlledCaseSeriesModule$execute( + connectionDetails, + analysisSpecifications, + executionSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{connectionDetails}}{An object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{executionSettings}}{An object of type \code{ExecutionSettings} as created +by \code{\link[=createCdmExecutionSettings]{createCdmExecutionSettings()}} or \code{\link[=createResultsExecutionSettings]{createResultsExecutionSettings()}}.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-SelfControlledCaseSeriesModule-createResultsDataModel}{}}} +\subsection{Method \code{createResultsDataModel()}}{ +Create the results data model for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{SelfControlledCaseSeriesModule$createResultsDataModel( + resultsConnectionDetails, + resultsDatabaseSchema, + tablePrefix = "" +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsDatabaseSchema}}{The schema in the results database that holds the results data model.} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-SelfControlledCaseSeriesModule-getResultsDataModelSpecification}{}}} +\subsection{Method \code{getResultsDataModelSpecification()}}{ +Get the results data model specification for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{SelfControlledCaseSeriesModule$getResultsDataModelSpecification( + tablePrefix = "" +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-SelfControlledCaseSeriesModule-uploadResults}{}}} +\subsection{Method \code{uploadResults()}}{ +Upload the results for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{SelfControlledCaseSeriesModule$uploadResults( + resultsConnectionDetails, + analysisSpecifications, + resultsDataModelSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{resultsDataModelSettings}}{The results data model settings as created using [@seealso \code{\link[=createResultsDataModelSettings]{createResultsDataModelSettings()}}]} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-SelfControlledCaseSeriesModule-createModuleSpecifications}{}}} +\subsection{Method \code{createModuleSpecifications()}}{ +Creates the SelfControlledCaseSeries Module Specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{SelfControlledCaseSeriesModule$createModuleSpecifications( + sccsAnalysisList, + exposuresOutcomeList, + analysesToExclude = NULL, + combineDataFetchAcrossOutcomes = FALSE, + sccsDiagnosticThresholds = SelfControlledCaseSeries::createSccsDiagnosticThresholds() +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{sccsAnalysisList}}{description} + +\item{\code{exposuresOutcomeList}}{description} + +\item{\code{analysesToExclude}}{description} + +\item{\code{combineDataFetchAcrossOutcomes}}{description} + +\item{\code{sccsDiagnosticThresholds}}{description} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-SelfControlledCaseSeriesModule-validateModuleSpecifications}{}}} +\subsection{Method \code{validateModuleSpecifications()}}{ +Validate the module specifications +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{SelfControlledCaseSeriesModule$validateModuleSpecifications( + moduleSpecifications +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{moduleSpecifications}}{The SelfControlledCaseSeries module specifications} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-SelfControlledCaseSeriesModule-clone}{}}} +\subsection{Method \code{clone()}}{ +The objects of this class are cloneable with this method. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{SelfControlledCaseSeriesModule$clone(deep = FALSE)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{deep}}{Whether to make a deep clone.} +} +\if{html}{\out{
    }} +} +} +} diff --git a/man/Strategus-package.Rd b/man/Strategus-package.Rd index ec0b208a..a184bdf1 100644 --- a/man/Strategus-package.Rd +++ b/man/Strategus-package.Rd @@ -4,9 +4,9 @@ \name{Strategus-package} \alias{Strategus} \alias{Strategus-package} -\title{Strategus: Coordinating and Executing Analytics Using HADES Modules} +\title{Strategus: Coordinate and Execute OHDSI HADES Modules} \description{ -An R package for coordinating and executing analytics using HADES modules. +Coordinate and execute large scale analytics using OHDSI Health Analytics Data-to-Evidence Suite (HADES) (\url{https://ohdsi.github.io/Hades/}) modules. } \seealso{ Useful links: diff --git a/man/StrategusModule.Rd b/man/StrategusModule.Rd new file mode 100644 index 00000000..8e150ef4 --- /dev/null +++ b/man/StrategusModule.Rd @@ -0,0 +1,284 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/StrategusModule.R +\name{StrategusModule} +\alias{StrategusModule} +\title{StrategusModule defines the base class for each HADES module} +\description{ +StrategusModule serves as an internal base class that defines the core +functions and structure to be inherited and implemented by any specific +HADES module. It provides a standardized framework for creating modular +components within the Strategus pipeline. +} +\section{Public fields}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{moduleName}}{The name of the module taken from the class name. +This is set in the constructor of the class.} + +\item{\code{moduleClassName}}{The class name that identifies +the module specifications in the overall analysis specification. +This is set in the constructor of the class.} + +\item{\code{internalModuleSpecificationClassName}}{A constant value. +The base class name that identifies a module specification +in the analysis specification.} + +\item{\code{internalSharedResourcesClassName}}{A constant value. The class name +that identifies the shared resources section in the overall analysis +specification.} +} +\if{html}{\out{
    }} +} +\section{Methods}{ +\subsection{Public methods}{ +\itemize{ +\item \href{#method-StrategusModule-new}{\code{StrategusModule$new()}} +\item \href{#method-StrategusModule-execute}{\code{StrategusModule$execute()}} +\item \href{#method-StrategusModule-createResultsDataModel}{\code{StrategusModule$createResultsDataModel()}} +\item \href{#method-StrategusModule-getResultsDataModelSpecification}{\code{StrategusModule$getResultsDataModelSpecification()}} +\item \href{#method-StrategusModule-uploadResults}{\code{StrategusModule$uploadResults()}} +\item \href{#method-StrategusModule-createModuleSpecifications}{\code{StrategusModule$createModuleSpecifications()}} +\item \href{#method-StrategusModule-createSharedResourcesSpecifications}{\code{StrategusModule$createSharedResourcesSpecifications()}} +\item \href{#method-StrategusModule-validateModuleSpecifications}{\code{StrategusModule$validateModuleSpecifications()}} +\item \href{#method-StrategusModule-validateSharedResourcesSpecifications}{\code{StrategusModule$validateSharedResourcesSpecifications()}} +\item \href{#method-StrategusModule-clone}{\code{StrategusModule$clone()}} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-StrategusModule-new}{}}} +\subsection{Method \code{new()}}{ +Initialize the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{StrategusModule$new()}\if{html}{\out{
    }} +} + +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-StrategusModule-execute}{}}} +\subsection{Method \code{execute()}}{ +Executes the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{StrategusModule$execute( + connectionDetails, + analysisSpecifications, + executionSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{connectionDetails}}{An object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{executionSettings}}{An object of type \code{ExecutionSettings} as created +by \code{\link[=createCdmExecutionSettings]{createCdmExecutionSettings()}} or \code{\link[=createResultsExecutionSettings]{createResultsExecutionSettings()}}.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-StrategusModule-createResultsDataModel}{}}} +\subsection{Method \code{createResultsDataModel()}}{ +Create the results data model for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{StrategusModule$createResultsDataModel( + resultsConnectionDetails, + resultsDatabaseSchema, + tablePrefix = "" +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsDatabaseSchema}}{The schema in the results database that holds the results data model.} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-StrategusModule-getResultsDataModelSpecification}{}}} +\subsection{Method \code{getResultsDataModelSpecification()}}{ +Get the results data model specification for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{StrategusModule$getResultsDataModelSpecification(tablePrefix = "")}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} + +\item{\code{tablePrefix}}{A prefix to apply to the database table names (optional).} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-StrategusModule-uploadResults}{}}} +\subsection{Method \code{uploadResults()}}{ +Upload the results for the module +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{StrategusModule$uploadResults( + resultsConnectionDetails, + analysisSpecifications, + resultsDataModelSettings +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{resultsConnectionDetails}}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{analysisSpecifications}}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{\code{resultsDataModelSettings}}{The results data model settings as created using [@seealso \code{\link[=createResultsDataModelSettings]{createResultsDataModelSettings()}}]} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-StrategusModule-createModuleSpecifications}{}}} +\subsection{Method \code{createModuleSpecifications()}}{ +Base function for creating the module settings object. +Each module will have its own implementation and this base class method +will be used to ensure the class of the specifications is set properly. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{StrategusModule$createModuleSpecifications(moduleSpecifications)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{moduleSpecifications}}{An object of type \code{ModuleSpecifications}} + +\item{\code{moduleSpecifications}}{An object of type \code{ModuleSpecifications}} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-StrategusModule-createSharedResourcesSpecifications}{}}} +\subsection{Method \code{createSharedResourcesSpecifications()}}{ +Base function for creating the shared resources settings object. +Each module will have its own implementation if it needs to create +a shared resource. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{StrategusModule$createSharedResourcesSpecifications( + className, + sharedResourcesSpecifications +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{className}}{The class name of the shared resources specifications} + +\item{\code{sharedResourcesSpecifications}}{The shared resources specifications} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-StrategusModule-validateModuleSpecifications}{}}} +\subsection{Method \code{validateModuleSpecifications()}}{ +Base function for validating the module settings object. +Each module will have its own implementation and this base class method +will be used to ensure the module specifications are valid ahead of +execution +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{StrategusModule$validateModuleSpecifications(moduleSpecifications)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{moduleSpecifications}}{An object of type \code{ModuleSpecifications}} + +\item{\code{moduleSpecifications}}{An object of type \code{ModuleSpecifications}} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-StrategusModule-validateSharedResourcesSpecifications}{}}} +\subsection{Method \code{validateSharedResourcesSpecifications()}}{ +Base function for validating the shared resources +specification settings object. Each module will have its own +implementation and this base class method will be used to ensure +the module specifications are valid ahead of execution +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{StrategusModule$validateSharedResourcesSpecifications( + className, + sharedResourcesSpecifications +)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{className}}{The class name of the shared resources specifications} + +\item{\code{sharedResourcesSpecifications}}{The shared resources specifications} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-StrategusModule-clone}{}}} +\subsection{Method \code{clone()}}{ +The objects of this class are cloneable with this method. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{StrategusModule$clone(deep = FALSE)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{deep}}{Whether to make a deep clone.} +} +\if{html}{\out{
    }} +} +} +} diff --git a/man/addCharacterizationModuleSpecifications.Rd b/man/addCharacterizationModuleSpecifications.Rd new file mode 100644 index 00000000..10ea5fd4 --- /dev/null +++ b/man/addCharacterizationModuleSpecifications.Rd @@ -0,0 +1,23 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Settings.R +\name{addCharacterizationModuleSpecifications} +\alias{addCharacterizationModuleSpecifications} +\title{Add Characterization module specifications to analysis specifications} +\usage{ +addCharacterizationModuleSpecifications( + analysisSpecifications, + moduleSpecifications +) +} +\arguments{ +\item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{moduleSpecifications}{Created by the \href{../../docs/reference/CharacterizationModule.html#method-CharacterizationModule-createModuleSpecifications}{\code{CharacterizationModule$createModuleSpecifications()}} function.} +} +\value{ +Returns the \code{analysisSpecifications} object with the module specifications added. +} +\description{ +Add Characterization module specifications to analysis specifications +} diff --git a/man/addCohortDiagnosticsModuleSpecifications.Rd b/man/addCohortDiagnosticsModuleSpecifications.Rd new file mode 100644 index 00000000..2caa2ae7 --- /dev/null +++ b/man/addCohortDiagnosticsModuleSpecifications.Rd @@ -0,0 +1,23 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Settings.R +\name{addCohortDiagnosticsModuleSpecifications} +\alias{addCohortDiagnosticsModuleSpecifications} +\title{Add Cohort Diagnostics module specifications to analysis specifications} +\usage{ +addCohortDiagnosticsModuleSpecifications( + analysisSpecifications, + moduleSpecifications +) +} +\arguments{ +\item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{moduleSpecifications}{Created by the \href{../../docs/reference/CohortDiagnosticsModule.html#method-CohortDiagnosticsModule-createModuleSpecifications}{\code{CohortDiagnosticsModule$createModuleSpecifications()}} function.} +} +\value{ +Returns the \code{analysisSpecifications} object with the module specifications added. +} +\description{ +Add Cohort Diagnostics module specifications to analysis specifications +} diff --git a/man/addCohortGeneratorModuleSpecifications.Rd b/man/addCohortGeneratorModuleSpecifications.Rd new file mode 100644 index 00000000..1c623aac --- /dev/null +++ b/man/addCohortGeneratorModuleSpecifications.Rd @@ -0,0 +1,23 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Settings.R +\name{addCohortGeneratorModuleSpecifications} +\alias{addCohortGeneratorModuleSpecifications} +\title{Add Cohort Generator module specifications to analysis specifications} +\usage{ +addCohortGeneratorModuleSpecifications( + analysisSpecifications, + moduleSpecifications +) +} +\arguments{ +\item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{moduleSpecifications}{Created by the \href{../../docs/reference/CohortGeneratorModule.html#method-CohortGeneratorModule-createModuleSpecifications}{\code{CohortGeneratorModule$createModuleSpecifications()}} function.} +} +\value{ +Returns the \code{analysisSpecifications} object with the module specifications added. +} +\description{ +Add Cohort Generator module specifications to analysis specifications +} diff --git a/man/addCohortIncidenceModuleSpecifications.Rd b/man/addCohortIncidenceModuleSpecifications.Rd new file mode 100644 index 00000000..dac1fbfa --- /dev/null +++ b/man/addCohortIncidenceModuleSpecifications.Rd @@ -0,0 +1,23 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Settings.R +\name{addCohortIncidenceModuleSpecifications} +\alias{addCohortIncidenceModuleSpecifications} +\title{Add Cohort Incidence module specifications to analysis specifications} +\usage{ +addCohortIncidenceModuleSpecifications( + analysisSpecifications, + moduleSpecifications +) +} +\arguments{ +\item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{moduleSpecifications}{Created by the \href{../../docs/reference/CohortIncidenceModule.html#method-CohortIncidenceModule-createModuleSpecifications}{\code{CohortIncidenceModule$createModuleSpecifications()}} function.} +} +\value{ +Returns the \code{analysisSpecifications} object with the module specifications added. +} +\description{ +Add Cohort Incidence module specifications to analysis specifications +} diff --git a/man/addCohortMethodeModuleSpecifications.Rd b/man/addCohortMethodeModuleSpecifications.Rd new file mode 100644 index 00000000..ace52173 --- /dev/null +++ b/man/addCohortMethodeModuleSpecifications.Rd @@ -0,0 +1,23 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Settings.R +\name{addCohortMethodeModuleSpecifications} +\alias{addCohortMethodeModuleSpecifications} +\title{Add Cohort Method module specifications to analysis specifications} +\usage{ +addCohortMethodeModuleSpecifications( + analysisSpecifications, + moduleSpecifications +) +} +\arguments{ +\item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{moduleSpecifications}{Created by the \href{../../docs/reference/CohortMethodModule.html#method-CohortMethodModule-createModuleSpecifications}{\code{CohortMethodModule$createModuleSpecifications()}} function.} +} +\value{ +Returns the \code{analysisSpecifications} object with the module specifications added. +} +\description{ +Add Cohort Method module specifications to analysis specifications +} diff --git a/man/addEvidenceSynthesisModuleSpecifications.Rd b/man/addEvidenceSynthesisModuleSpecifications.Rd new file mode 100644 index 00000000..94ebbb61 --- /dev/null +++ b/man/addEvidenceSynthesisModuleSpecifications.Rd @@ -0,0 +1,23 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Settings.R +\name{addEvidenceSynthesisModuleSpecifications} +\alias{addEvidenceSynthesisModuleSpecifications} +\title{Add Evidence Synthesis module specifications to analysis specifications} +\usage{ +addEvidenceSynthesisModuleSpecifications( + analysisSpecifications, + moduleSpecifications +) +} +\arguments{ +\item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{moduleSpecifications}{Created by the \href{../../docs/reference/EvidenceSynthesisModule.html#method-EvidenceSynthesisModule-createModuleSpecifications}{\code{EvidenceSynthesisModule$createModuleSpecifications()}} function.} +} +\value{ +Returns the \code{analysisSpecifications} object with the module specifications added. +} +\description{ +Add Evidence Synthesis module specifications to analysis specifications +} diff --git a/man/addModuleSpecifications.Rd b/man/addModuleSpecifications.Rd index 490686cb..6549bfbe 100644 --- a/man/addModuleSpecifications.Rd +++ b/man/addModuleSpecifications.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/Settings.R \name{addModuleSpecifications} \alias{addModuleSpecifications} -\title{Add module specifications to analysis specifications} +\title{Add generic module specifications to analysis specifications} \usage{ addModuleSpecifications(analysisSpecifications, moduleSpecifications) } @@ -10,11 +10,11 @@ addModuleSpecifications(analysisSpecifications, moduleSpecifications) \item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} -\item{moduleSpecifications}{An object of type \code{ModuleSpecifications}.} +\item{moduleSpecifications}{An object of type \code{ModuleSpecifications}} } \value{ Returns the \code{analysisSpecifications} object with the module specifications added. } \description{ -Add module specifications to analysis specifications +Add generic module specifications to analysis specifications } diff --git a/man/addPatientLevelPredictionModuleSpecifications.Rd b/man/addPatientLevelPredictionModuleSpecifications.Rd new file mode 100644 index 00000000..eb9d9f62 --- /dev/null +++ b/man/addPatientLevelPredictionModuleSpecifications.Rd @@ -0,0 +1,23 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Settings.R +\name{addPatientLevelPredictionModuleSpecifications} +\alias{addPatientLevelPredictionModuleSpecifications} +\title{Add Patient Level Prediction module specifications to analysis specifications} +\usage{ +addPatientLevelPredictionModuleSpecifications( + analysisSpecifications, + moduleSpecifications +) +} +\arguments{ +\item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{moduleSpecifications}{Created by the \href{../../docs/reference/PatientLevelPredictionModule.html#method-PatientLevelPredictionModule-createModuleSpecifications}{\code{PatientLevelPredictionModule$createModuleSpecifications()}} function.} +} +\value{ +Returns the \code{analysisSpecifications} object with the module specifications added. +} +\description{ +Add Patient Level Prediction module specifications to analysis specifications +} diff --git a/man/addSelfControlledCaseSeriesModuleSpecifications.Rd b/man/addSelfControlledCaseSeriesModuleSpecifications.Rd new file mode 100644 index 00000000..bcc3a0b4 --- /dev/null +++ b/man/addSelfControlledCaseSeriesModuleSpecifications.Rd @@ -0,0 +1,23 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Settings.R +\name{addSelfControlledCaseSeriesModuleSpecifications} +\alias{addSelfControlledCaseSeriesModuleSpecifications} +\title{Add Self Controlled Case Series Module module specifications to analysis specifications} +\usage{ +addSelfControlledCaseSeriesModuleSpecifications( + analysisSpecifications, + moduleSpecifications +) +} +\arguments{ +\item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{moduleSpecifications}{Created by the \href{../../docs/reference/SelfControlledCaseSeriesModule.html#method-SelfControlledCaseSeriesModule-createModuleSpecifications}{\code{SelfControlledCaseSeriesModule$createModuleSpecifications()}} function.} +} +\value{ +Returns the \code{analysisSpecifications} object with the module specifications added. +} +\description{ +Add Self Controlled Case Series Module module specifications to analysis specifications +} diff --git a/man/addSharedResources.Rd b/man/addSharedResources.Rd index f4e6522b..23926dfa 100644 --- a/man/addSharedResources.Rd +++ b/man/addSharedResources.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/Settings.R \name{addSharedResources} \alias{addSharedResources} -\title{Add shared resources to analysis specifications} +\title{Add shared resources (i.e. cohorts) to analysis specifications} \usage{ addSharedResources(analysisSpecifications, sharedResources) } @@ -16,5 +16,5 @@ by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecifici Returns the \code{analysisSpecifications} object with the module specifications added. } \description{ -Add shared resources to analysis specifications +Add shared resources (i.e. cohorts) to analysis specifications } diff --git a/man/compareLockFiles.Rd b/man/compareLockFiles.Rd deleted file mode 100644 index 9dca734f..00000000 --- a/man/compareLockFiles.Rd +++ /dev/null @@ -1,21 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/RenvHelpers.R -\name{compareLockFiles} -\alias{compareLockFiles} -\title{Compare two renv.lock files} -\usage{ -compareLockFiles(filename1, filename2) -} -\arguments{ -\item{filename1}{The first renv.lock file name} - -\item{filename2}{The second renv.lock file name} -} -\value{ -A data.frame with the comparison of the rev.lock files -} -\description{ -Used to compare renv.lock files and return the results in a data.frame. -The return value will include a "full join" representation of the packages -across the two lock files. -} diff --git a/man/createCdmExecutionSettings.Rd b/man/createCdmExecutionSettings.Rd index 96768f97..e90caa61 100644 --- a/man/createCdmExecutionSettings.Rd +++ b/man/createCdmExecutionSettings.Rd @@ -5,7 +5,6 @@ \title{Create CDM execution settings} \usage{ createCdmExecutionSettings( - connectionDetailsReference, workDatabaseSchema, cdmDatabaseSchema, cohortTableNames = CohortGenerator::getCohortTableNames(cohortTable = "cohort"), @@ -14,16 +13,12 @@ createCdmExecutionSettings( resultsFolder, logFileName = file.path(resultsFolder, "strategus-log.txt"), minCellCount = 5, - integerAsNumeric = getOption("databaseConnectorIntegerAsNumeric", default = TRUE), - integer64AsNumeric = getOption("databaseConnectorInteger64AsNumeric", default = TRUE), - resultsConnectionDetailsReference = NULL, - resultsDatabaseSchema = NULL + incremental = TRUE, + maxCores = parallel::detectCores(), + modulesToExecute = c() ) } \arguments{ -\item{connectionDetailsReference}{A string that can be used to retrieve database connection details from a secure local -store.} - \item{workDatabaseSchema}{A database schema where intermediate data can be stored. The user (as identified in the connection details) will need to have write access to this database schema.} @@ -38,21 +33,22 @@ connection details) will need to have read access to this database schema.} \item{workFolder}{A folder in the local file system where intermediate results can be written.} -\item{resultsFolder}{A folder in the local file system where the module output will be written.} +\item{resultsFolder}{The root folder holding the study results.} \item{logFileName}{Logging information from Strategus and all modules will be located in this file. Individual modules will continue to have their own module-specific logs. By default this will be written to the root of the \code{resultsFolder}} \item{minCellCount}{The minimum number of subjects contributing to a count before it can be included in results.} -\item{integerAsNumeric}{Logical: should 32-bit integers be converted to numeric (double) values? If FALSE 32-bit integers will be represented using R's native \code{Integer} class. Default is TRUE} - -\item{integer64AsNumeric}{Logical: should 64-bit integers be converted to numeric (double) values? If FALSE 64-bit integers will be represented using \code{bit64::integer64}. Default is TRUE} +\item{incremental}{This value will be passed to each module that supports execution in an incremental manner. Modules +and their underlying packages may use the \code{workFolder} contents to determine their state of execution +and attempt to pick up where they left off when this value is set to TRUE.} -\item{resultsConnectionDetailsReference}{A string that can be used to retrieve the results database connection -details from a secure local store.} +\item{maxCores}{The maximum number of processing cores to use for execution. The default is to +use all available cores on the machine.} -\item{resultsDatabaseSchema}{A schema where the results tables are stored} +\item{modulesToExecute}{(Optional) A vector with the list of modules to execute. When an empty vector/NULL is supplied (default), +all modules in the analysis specification are executed.} } \value{ An object of type \code{ExecutionSettings}. diff --git a/man/createResultDataModel.Rd b/man/createResultDataModel.Rd new file mode 100644 index 00000000..d5dcc8f4 --- /dev/null +++ b/man/createResultDataModel.Rd @@ -0,0 +1,27 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/ResultDataModel.R +\name{createResultDataModel} +\alias{createResultDataModel} +\title{Create Result Data Model} +\usage{ +createResultDataModel( + analysisSpecifications, + resultsDataModelSettings, + resultsConnectionDetails +) +} +\arguments{ +\item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{resultsDataModelSettings}{The results data model settings as created using [@seealso \code{\link[=createResultsDataModelSettings]{createResultsDataModelSettings()}}]} + +\item{resultsConnectionDetails}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} +} +\description{ +Use this at the study design stage to create data models for modules +This functions loads modules and executes any custom code to create +the results data model in the specified schema in the results database. +} diff --git a/man/createResultDataModels.Rd b/man/createResultDataModels.Rd deleted file mode 100644 index 69975988..00000000 --- a/man/createResultDataModels.Rd +++ /dev/null @@ -1,50 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/ResultModelCreation.R -\name{createResultDataModels} -\alias{createResultDataModels} -\title{Create Result Data Models} -\usage{ -createResultDataModels( - analysisSpecifications, - executionSettings, - executionScriptFolder = NULL, - keyringName = NULL, - restart = FALSE, - enforceModuleDependencies = TRUE -) -} -\arguments{ -\item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created -by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} - -\item{executionSettings}{An object of type \code{ExecutionSettings} as created -by \code{\link[=createCdmExecutionSettings]{createCdmExecutionSettings()}} or \code{\link[=createResultsExecutionSettings]{createResultsExecutionSettings()}}.} - -\item{executionScriptFolder}{Optional: the path to use for storing the execution script. -when NULL, this function will use a temporary -file location to create the script to execute.} - -\item{keyringName}{The name of the keyring to operate on. This function assumes you have -created the keyring before calling this function. It defaults to -NULL to select the default keyring. If the keyring is password -protected, the password must be stored in the environment variable -STRATEGUS_KEYRING_PASSWORD so it is retrieved using the command -Sys.getenv("STRATEGUS_KEYRING_PASSWORD")} - -\item{restart}{Restart run? Requires \code{executionScriptFolder} to be specified, and be -the same as the \code{executionScriptFolder} used in the run to restart.} - -\item{enforceModuleDependencies}{When set to TRUE, Strategus will enforce -module dependencies that are declared by each module. For example, the -CohortDiagnostics module declares a dependency on the CohortGenerator module -and Strategus will require that an analysis specification declare that both -modules must exist in order to execute the analysis. When set to FALSE, -Strategus will not enforce these module dependencies which assumes you have -properly run all module dependencies yourself. Setting this to FALSE is not -recommended since it is potentially unsafe.} -} -\description{ -Use this at the study design stage to create data models for modules -This functions loads modules and executes any custom code to create schemas in a results database -If recreate is set to TRUE all existing data will be removed, otherwise -} diff --git a/man/createResultsDataModelSettings.Rd b/man/createResultsDataModelSettings.Rd new file mode 100644 index 00000000..28afc453 --- /dev/null +++ b/man/createResultsDataModelSettings.Rd @@ -0,0 +1,26 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/Settings.R +\name{createResultsDataModelSettings} +\alias{createResultsDataModelSettings} +\title{Create Results Data Model Settings} +\usage{ +createResultsDataModelSettings( + resultsDatabaseSchema, + resultsFolder, + logFileName = file.path(resultsFolder, "strategus-results-data-model-log.txt") +) +} +\arguments{ +\item{resultsDatabaseSchema}{The schema in the results database that holds the results data model.} + +\item{resultsFolder}{The root folder holding the study results.} + +\item{logFileName}{Log location for data model operations} +} +\value{ +An object of type \code{ResultsDataModelSettings} +} +\description{ +The results data model settings are used to create the results data +model and to upload results. +} diff --git a/man/createResultsExecutionSettings.Rd b/man/createResultsExecutionSettings.Rd index 2c088e1a..52ce80c2 100644 --- a/man/createResultsExecutionSettings.Rd +++ b/man/createResultsExecutionSettings.Rd @@ -5,34 +5,32 @@ \title{Create Results execution settings} \usage{ createResultsExecutionSettings( - resultsConnectionDetailsReference, resultsDatabaseSchema, workFolder, resultsFolder, logFileName = file.path(resultsFolder, "strategus-log.txt"), minCellCount = 5, - integerAsNumeric = getOption("databaseConnectorIntegerAsNumeric", default = TRUE), - integer64AsNumeric = getOption("databaseConnectorInteger64AsNumeric", default = TRUE) + maxCores = parallel::detectCores(), + modulesToExecute = c() ) } \arguments{ -\item{resultsConnectionDetailsReference}{A string that can be used to retrieve the results database connection -details from a secure local store.} - -\item{resultsDatabaseSchema}{A schema where the results tables are stored} +\item{resultsDatabaseSchema}{The schema in the results database that holds the results data model.} \item{workFolder}{A folder in the local file system where intermediate results can be written.} -\item{resultsFolder}{A folder in the local file system where the module output will be written.} +\item{resultsFolder}{The root folder holding the study results.} \item{logFileName}{Logging information from Strategus and all modules will be located in this file. Individual modules will continue to have their own module-specific logs. By default this will be written to the root of the \code{resultsFolder}} \item{minCellCount}{The minimum number of subjects contributing to a count before it can be included in results.} -\item{integerAsNumeric}{Logical: should 32-bit integers be converted to numeric (double) values? If FALSE 32-bit integers will be represented using R's native \code{Integer} class. Default is TRUE} +\item{maxCores}{The maximum number of processing cores to use for execution. The default is to +use all available cores on the machine.} -\item{integer64AsNumeric}{Logical: should 64-bit integers be converted to numeric (double) values? If FALSE 64-bit integers will be represented using \code{bit64::integer64}. Default is TRUE} +\item{modulesToExecute}{(Optional) A vector with the list of modules to execute. When an empty vector/NULL is supplied (default), +all modules in the analysis specification are executed.} } \value{ An object of type \code{ExecutionSettings}. diff --git a/man/dot-nullList.Rd b/man/dot-nullList.Rd deleted file mode 100644 index 5b697abe..00000000 --- a/man/dot-nullList.Rd +++ /dev/null @@ -1,12 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/Settings.R -\name{.nullList} -\alias{.nullList} -\title{Used when serializing connection details to retain NULL values} -\usage{ -.nullList() -} -\description{ -Used when serializing connection details to retain NULL values -} -\keyword{internal} diff --git a/man/ensureAllModulesInstantiated.Rd b/man/ensureAllModulesInstantiated.Rd deleted file mode 100644 index 0fc9ed20..00000000 --- a/man/ensureAllModulesInstantiated.Rd +++ /dev/null @@ -1,47 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/ModuleInstantiation.R -\name{ensureAllModulesInstantiated} -\alias{ensureAllModulesInstantiated} -\title{Ensure all modules are instantiated} -\usage{ -ensureAllModulesInstantiated( - analysisSpecifications, - forceVerification = FALSE, - enforceModuleDependencies = TRUE -) -} -\arguments{ -\item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created -by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} - -\item{forceVerification}{When set to TRUE, the verification process is forced -to re-evaluate if a module is properly installed. The default is FALSE -since if a module is successfully validated, the module will contain -the hash value of the module's renv.lock file in the file system so it can -by-pass running this check every time.} - -\item{enforceModuleDependencies}{When set to TRUE, Strategus will enforce -module dependencies that are declared by each module. For example, the -CohortDiagnostics module declares a dependency on the CohortGenerator module -and Strategus will require that an analysis specification declare that both -modules must exist in order to execute the analysis. When set to FALSE, -Strategus will not enforce these module dependencies which assumes you have -properly run all module dependencies yourself. Setting this to FALSE is not -recommended since it is potentially unsafe.} -} -\value{ -A list containing the install status of all modules -(TRUE if all are installed properly) and a tibble listing -the instantiated modules. -} -\description{ -Ensure that all modules referenced in the analysis specifications are instantiated -locally in the folder specified in the \code{INSTANTIATED_MODULES_FOLDER} environmental -variable. - -Missing modules will be fetched from remote repositories. - -This function will also check whether there are different versions of the same -module specified, which is not allowed, and whether all modules required by the -specified modules are also instantiated. -} diff --git a/man/execute.Rd b/man/execute.Rd index 40f20941..d2e61279 100644 --- a/man/execute.Rd +++ b/man/execute.Rd @@ -4,14 +4,7 @@ \alias{execute} \title{Execute analysis specifications.} \usage{ -execute( - analysisSpecifications, - executionSettings, - executionScriptFolder = NULL, - keyringName = NULL, - restart = FALSE, - enforceModuleDependencies = TRUE -) +execute(analysisSpecifications, executionSettings, connectionDetails) } \arguments{ \item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created @@ -20,32 +13,17 @@ by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecifici \item{executionSettings}{An object of type \code{ExecutionSettings} as created by \code{\link[=createCdmExecutionSettings]{createCdmExecutionSettings()}} or \code{\link[=createResultsExecutionSettings]{createResultsExecutionSettings()}}.} -\item{executionScriptFolder}{Optional: the path to use for storing the execution script. -when NULL, this function will use a temporary -file location to create the script to execute.} - -\item{keyringName}{The name of the keyring to operate on. This function assumes you have -created the keyring before calling this function. It defaults to -NULL to select the default keyring. If the keyring is password -protected, the password must be stored in the environment variable -STRATEGUS_KEYRING_PASSWORD so it is retrieved using the command -Sys.getenv("STRATEGUS_KEYRING_PASSWORD")} - -\item{restart}{Restart run? Requires \code{executionScriptFolder} to be specified, and be -the same as the \code{executionScriptFolder} used in the run to restart.} - -\item{enforceModuleDependencies}{When set to TRUE, Strategus will enforce -module dependencies that are declared by each module. For example, the -CohortDiagnostics module declares a dependency on the CohortGenerator module -and Strategus will require that an analysis specification declare that both -modules must exist in order to execute the analysis. When set to FALSE, -Strategus will not enforce these module dependencies which assumes you have -properly run all module dependencies yourself. Setting this to FALSE is not -recommended since it is potentially unsafe.} +\item{connectionDetails}{An object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} } \value{ -Does not return anything. Is called for the side-effect of executing the specified -analyses. +Returns a list of lists that contains +\itemize{ +\item moduleName: The name of the module executed +\item result: The result of the execution. See purrr::safely for details on +this result. +\item executionTime: The time for the module to execute +} } \description{ Execute analysis specifications. diff --git a/man/getCdmDatabaseMetaData.Rd b/man/getCdmDatabaseMetaData.Rd new file mode 100644 index 00000000..ba080c42 --- /dev/null +++ b/man/getCdmDatabaseMetaData.Rd @@ -0,0 +1,20 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DatabaseMetaData.R +\name{getCdmDatabaseMetaData} +\alias{getCdmDatabaseMetaData} +\title{Gets the metadata for your OMOP CDM Database} +\usage{ +getCdmDatabaseMetaData(cdmExecutionSettings, connectionDetails) +} +\arguments{ +\item{cdmExecutionSettings}{An object of type \code{CdmExecutionSettings} as +created \code{\link[=createCdmExecutionSettings]{createCdmExecutionSettings()}}.} + +\item{connectionDetails}{An object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} +} +\description{ +This function is used to gather metadata about your OMOP CDM and inspect +for informational purposes. This information will be saved with your +results when executing an analysis specification. +} diff --git a/man/getModuleList.Rd b/man/getModuleList.Rd deleted file mode 100644 index 005f84b3..00000000 --- a/man/getModuleList.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/Settings.R -\name{getModuleList} -\alias{getModuleList} -\title{Provides a list of HADES modules to run through Strategus} -\usage{ -getModuleList() -} -\value{ -A data.frame() of modules that work with Strategus. This will contain: -module = The name of the module -version = The version of the module -remote_repo = The remote location of the module (i.e. github.com) -remote_username = The organization of the module (i.e. OHDSI) -module_type = 'cdm' or 'results'. 'cdm' refers to modules that are designed to work against -patient level data in the OMOP CDM format. 'results' refers to modules that are designed -to work against a results database containing output from a 'cdm' module. -} -\description{ -This function provides a list of modules and their locations -that may be used with Strategus. -} diff --git a/man/installLatestModule.Rd b/man/installLatestModule.Rd deleted file mode 100644 index ffe9432e..00000000 --- a/man/installLatestModule.Rd +++ /dev/null @@ -1,21 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/ModuleInstantiation.R -\name{installLatestModule} -\alias{installLatestModule} -\title{Install the latest release of a module} -\usage{ -installLatestModule(moduleName) -} -\arguments{ -\item{moduleName}{The name of the module to install (i.e. "CohortGeneratorModule"). -This parameter must match a value found in the \code{module} column of \code{getModuleList()}} -} -\value{ -None - this function is called for its side effects -} -\description{ -This function will call out to the OHDSI GitHub repo to find the latest -version of the module and attempt to install it. Only modules that are listed -in the \code{getModuleList()} function are allowed since it will have a known -GitHub location. -} diff --git a/man/lockFileToDataFrame.Rd b/man/lockFileToDataFrame.Rd deleted file mode 100644 index e5569b87..00000000 --- a/man/lockFileToDataFrame.Rd +++ /dev/null @@ -1,12 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/RenvHelpers.R -\name{lockFileToDataFrame} -\alias{lockFileToDataFrame} -\title{Convert a lock file to a data.frame} -\usage{ -lockFileToDataFrame(lf) -} -\description{ -Convert a lock file to a data.frame -} -\keyword{internal} diff --git a/man/mandatoryPackages.Rd b/man/mandatoryPackages.Rd deleted file mode 100644 index 3c0c9f7e..00000000 --- a/man/mandatoryPackages.Rd +++ /dev/null @@ -1,12 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/RenvHelpers.R -\name{mandatoryPackages} -\alias{mandatoryPackages} -\title{List of mandatory packages for a Strategus module} -\usage{ -mandatoryPackages() -} -\description{ -List of mandatory packages for a Strategus module -} -\keyword{internal} diff --git a/man/retrieveConnectionDetails.Rd b/man/retrieveConnectionDetails.Rd deleted file mode 100644 index 0c8b899d..00000000 --- a/man/retrieveConnectionDetails.Rd +++ /dev/null @@ -1,28 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/Settings.R -\name{retrieveConnectionDetails} -\alias{retrieveConnectionDetails} -\title{Retrieve connection details from the secure location} -\usage{ -retrieveConnectionDetails(connectionDetailsReference, keyringName = NULL) -} -\arguments{ -\item{connectionDetailsReference}{A string that can be used to retrieve the settings from -the secure store.} - -\item{keyringName}{The name of the keyring to operate on. This function assumes you have -created the keyring before calling this function. It defaults to -NULL to select the default keyring. If the keyring is password -protected, the password must be stored in the environment variable -STRATEGUS_KEYRING_PASSWORD so it is retrieved using the command -Sys.getenv("STRATEGUS_KEYRING_PASSWORD")} -} -\value{ -Returns an object of type \code{connectionDetails}. -} -\description{ -Retrieve connection details from the secure location -} -\seealso{ -\code{\link[=storeConnectionDetails]{storeConnectionDetails()}} -} diff --git a/man/runSchemaCreation.Rd b/man/runSchemaCreation.Rd deleted file mode 100644 index 821bab19..00000000 --- a/man/runSchemaCreation.Rd +++ /dev/null @@ -1,35 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/ResultModelCreation.R -\name{runSchemaCreation} -\alias{runSchemaCreation} -\title{Create module(s) result data model} -\usage{ -runSchemaCreation( - analysisSpecifications, - keyringSettings, - moduleIndex, - executionSettings, - ... -) -} -\arguments{ -\item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created -by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} - -\item{keyringSettings}{The keyringSettings from the executionSettings context} - -\item{moduleIndex}{The index of the module in the analysis specification} - -\item{executionSettings}{An object of type \code{ExecutionSettings} as created -by \code{\link[=createCdmExecutionSettings]{createCdmExecutionSettings()}} or \code{\link[=createResultsExecutionSettings]{createResultsExecutionSettings()}}.} - -\item{...}{For future expansion} -} -\description{ -This function will create the results data model for the modules in the -\code{analysisSpecifications}. A module can implement its own results data model -creation function by implementing the function \code{createDataModelSchema} in -its Main.R. The default behavior is to use the \code{ResultsModelManager} to create -the results data model based on the \code{resultsDataModelSpecification.csv} in the -module's results folder. -} diff --git a/man/storeConnectionDetails.Rd b/man/storeConnectionDetails.Rd deleted file mode 100644 index b75ce038..00000000 --- a/man/storeConnectionDetails.Rd +++ /dev/null @@ -1,36 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/Settings.R -\name{storeConnectionDetails} -\alias{storeConnectionDetails} -\title{Store connection details in a secure location} -\usage{ -storeConnectionDetails( - connectionDetails, - connectionDetailsReference, - keyringName = NULL -) -} -\arguments{ -\item{connectionDetails}{An object of type \code{connectionDetails} as created by the -\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} - -\item{connectionDetailsReference}{A string that can be used to retrieve the settings from -the secure store.} - -\item{keyringName}{The name of the keyring to operate on. This function assumes you have -created the keyring before calling this function. It defaults to -NULL to select the default keyring. If the keyring is password -protected, the password must be stored in the environment variable -STRATEGUS_KEYRING_PASSWORD so it is retrieved using the command -Sys.getenv("STRATEGUS_KEYRING_PASSWORD")} -} -\value{ -Does not return anything. Is called for the side effect of having the connection details -stored. -} -\description{ -Store connection details in a secure location -} -\seealso{ -\code{\link[=retrieveConnectionDetails]{retrieveConnectionDetails()}} -} diff --git a/man/suggestedPacakges.Rd b/man/suggestedPacakges.Rd deleted file mode 100644 index e1ed2d31..00000000 --- a/man/suggestedPacakges.Rd +++ /dev/null @@ -1,12 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/RenvHelpers.R -\name{suggestedPacakges} -\alias{suggestedPacakges} -\title{List of suggested packages for a Strategus module} -\usage{ -suggestedPacakges() -} -\description{ -List of suggested packages for a Strategus module -} -\keyword{internal} diff --git a/man/syncLockFile.Rd b/man/syncLockFile.Rd deleted file mode 100644 index 66dd8bff..00000000 --- a/man/syncLockFile.Rd +++ /dev/null @@ -1,31 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/RenvHelpers.R -\name{syncLockFile} -\alias{syncLockFile} -\title{Synchronize renv.lock files and overwrite the target file -(read the description)} -\usage{ -syncLockFile(sourceOfTruthLockFileName, targetLockFileName) -} -\arguments{ -\item{sourceOfTruthLockFileName}{The renv.lock file to use as the source of -truth} - -\item{targetLockFileName}{The target renv.lock file that will be synced with -the source of truth} -} -\value{ -A data.frame containing the different packages and their version that -were involved in the synchronization process -} -\description{ -Used to synchronize the values from the "source of truth" renv.lock file to -the target renv.lock file. Packages are compared (by name) and if the version -of the package in the "source of truth" is greater the one found in the -target, the target renv.lock file will be updated. This function will -automatically update the target file. - -Version comparison is handled by the \code{semver} package and since most packages -use semantic versioning. When a package does not use semantic versioning, -a warning is provided so the user can review. -} diff --git a/man/unlockKeyring.Rd b/man/unlockKeyring.Rd deleted file mode 100644 index 9f1d7dc2..00000000 --- a/man/unlockKeyring.Rd +++ /dev/null @@ -1,25 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/Settings.R -\name{unlockKeyring} -\alias{unlockKeyring} -\title{Helper function to unlock a keyring} -\usage{ -unlockKeyring(keyringName) -} -\arguments{ -\item{keyringName}{The name of the keyring to operate on. This function assumes you have -created the keyring before calling this function. It defaults to -NULL to select the default keyring. If the keyring is password -protected, the password must be stored in the environment variable -STRATEGUS_KEYRING_PASSWORD so it is retrieved using the command -Sys.getenv("STRATEGUS_KEYRING_PASSWORD")} -} -\value{ -Returns TRUE if the keyring was unlocked using the password otherwise -it returns FALSE -} -\description{ -This helper function is used to unlock a keyring by using the password -stored in Sys.getenv("STRATEGUS_KEYRING_PASSWORD"). It will alert -the user if the environment variable with the password is not set. -} diff --git a/man/uploadResults.Rd b/man/uploadResults.Rd new file mode 100644 index 00000000..e56f3889 --- /dev/null +++ b/man/uploadResults.Rd @@ -0,0 +1,25 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/ResultDataModel.R +\name{uploadResults} +\alias{uploadResults} +\title{Upload results} +\usage{ +uploadResults( + analysisSpecifications, + resultsDataModelSettings, + resultsConnectionDetails +) +} +\arguments{ +\item{analysisSpecifications}{An object of type \code{AnalysisSpecifications} as created +by \code{\link[=createEmptyAnalysisSpecificiations]{createEmptyAnalysisSpecificiations()}}.} + +\item{resultsDataModelSettings}{The results data model settings as created using [@seealso \code{\link[=createResultsDataModelSettings]{createResultsDataModelSettings()}}]} + +\item{resultsConnectionDetails}{The connection details to the results database which +is an object of class \code{connectionDetails} as created by the +\code{\link[DatabaseConnector:createConnectionDetails]{DatabaseConnector::createConnectionDetails()}} function.} +} +\description{ +Upload the results for a given analysis +} diff --git a/man/validateLockFile.Rd b/man/validateLockFile.Rd deleted file mode 100644 index 42d79be0..00000000 --- a/man/validateLockFile.Rd +++ /dev/null @@ -1,17 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/RenvHelpers.R -\name{validateLockFile} -\alias{validateLockFile} -\title{Validate an renv.lock file to ensure it is ready for use by Strategus} -\usage{ -validateLockFile(filename) -} -\arguments{ -\item{filename}{The renv.lock file to validate} -} -\description{ -Will check an renv.lock file for a module to verify that it only references -tagged packages and includes the packages required by Strategus. It will -also check for suggested packages that are useful for testing, such as -RSQLite. -} diff --git a/man/verifyModuleInstallation.Rd b/man/verifyModuleInstallation.Rd deleted file mode 100644 index d0b96c1b..00000000 --- a/man/verifyModuleInstallation.Rd +++ /dev/null @@ -1,45 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/ModuleInstantiation.R -\name{verifyModuleInstallation} -\alias{verifyModuleInstallation} -\title{Verify a module is properly installed} -\usage{ -verifyModuleInstallation( - module, - version, - silent = FALSE, - forceVerification = FALSE -) -} -\arguments{ -\item{module}{The name of the module to verify (i.e. "CohortGeneratorModule")} - -\item{version}{The version of the module to verify (i.e. "0.2.1")} - -\item{silent}{When TRUE output of this verification process is suppressed} - -\item{forceVerification}{When set to TRUE, the verification process is forced -to re-evaluate if a module is properly installed. The default is FALSE -since if a module is successfully validated, the module will contain -the hash value of the module's renv.lock file in the file system so it can -by-pass running this check every time.} -} -\value{ -A list with the output of the consistency check -} -\description{ -In some instances a module may fail to instantiate and install due to problems -when calling renv::restore for the module's renv.lock file. This function -will allow you to surface inconsistencies between the module renv.lock file -and the module's renv project library. This function will check to that a -module has been properly installed using internal functions of the \code{renv} -package. If a module is verified to work via this function, the hash of -the module's renv.lock file will be written to a text file in the module -directory to indicate that it is ready for use. This will allow subsequent -calls to work faster since the initial verification process can take some -time.It is possible to re-run the verification of a module -by using the \code{forceVerification} parameter. - -To fix issues with a module, you will need to open the module's .Rproj in -RStudio instance and debug the issues when calling renv::restore(). -} diff --git a/man/withModuleRenv.Rd b/man/withModuleRenv.Rd deleted file mode 100644 index dd61f4e0..00000000 --- a/man/withModuleRenv.Rd +++ /dev/null @@ -1,41 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/ModuleEnv.R -\name{withModuleRenv} -\alias{withModuleRenv} -\title{Load module execution space inside and renv -inspired by targets::tar_script but allowing custom variable execution} -\usage{ -withModuleRenv( - code, - moduleFolder, - injectVars = list(), - tempScriptFile = tempfile(fileext = ".R"), - job = FALSE, - processName = paste(moduleFolder, "_renv_run") -) -} -\arguments{ -\item{code}{code block to execute} - -\item{moduleFolder}{Instantiated Strategus module folder} - -\item{injectVars}{list of var names list(name=value) to replace (e.g. replace list(foo = "some string") will -find the pattern foo and replace it with the string some string - be careful!} - -\item{tempScriptFile}{tempFile to write script to} - -\item{job}{run as rstudio job} - -\item{processName}{String name for process} -} -\value{ -NULL invisibly -} -\description{ -Designed to allow more human readable code that is executed inside a module as well as simple variable substituion -for injecting constants (e.g. simple parameters or file paths used inside and outside of modules) -} -\details{ -This pattern also allows dependency injection which could be used if you don't want to use and renv and (instead) -would like to use docker images or just execution in the base environment for testing/debugging -} diff --git a/man/zipResults.Rd b/man/zipResults.Rd index 4e673245..bacb866f 100644 --- a/man/zipResults.Rd +++ b/man/zipResults.Rd @@ -7,8 +7,7 @@ zipResults(resultsFolder, zipFile) } \arguments{ -\item{resultsFolder}{The folder holding the study results. This is found in -\code{executionSettings$resultsFolder}.} +\item{resultsFolder}{The root folder holding the study results.} \item{zipFile}{The path to the zip file to be created.} } diff --git a/pkgdown/extra.css b/pkgdown/extra.css new file mode 100644 index 00000000..603a9c35 --- /dev/null +++ b/pkgdown/extra.css @@ -0,0 +1,18 @@ +[aria-label="hadesLogo"] { + background-image: url('https://ohdsi.github.io/Hades/images/hadesMini.png'); + background-size: contain; + background-repeat: no-repeat; + background-position: center; + width: 80px; + height: 36px; + font-size: 0; +} +li:has(a[aria-label="hadesLogo"]:hover) { + background-image: url('https://ohdsi.github.io/Hades/images/hadesMini.png'); + background-size: contain; + background-repeat: no-repeat; + background-position: center; + width: 80px; + height: 36px; + font-size: 0; +} diff --git a/tests/testthat/setup.R b/tests/testthat/setup.R index 9d0a2c45..df82317d 100644 --- a/tests/testthat/setup.R +++ b/tests/testthat/setup.R @@ -1,18 +1,9 @@ library(testthat) library(Strategus) library(Eunomia) +library(CohortGenerator) library(dplyr) -# allows unit tests to run on mac without issue -baseBackend <- Sys.getenv("R_KEYRING_BACKEND") -Sys.setenv("R_KEYRING_BACKEND" = "file") -withr::defer( - { - Sys.setenv("R_KEYRING_BACKEND" = baseBackend) - }, - testthat::teardown_env() -) - if (dir.exists(Sys.getenv("DATABASECONNECTOR_JAR_FOLDER"))) { jdbcDriverFolder <- Sys.getenv("DATABASECONNECTOR_JAR_FOLDER") } else { @@ -28,25 +19,12 @@ if (dir.exists(Sys.getenv("DATABASECONNECTOR_JAR_FOLDER"))) { testthat::teardown_env() ) } - # Create a unique ID for the table identifiers tableSuffix <- paste0(substr(.Platform$OS.type, 1, 3), format(Sys.time(), "%y%m%d%H%M%S"), sample(1:100, 1)) tableSuffix <- abs(digest::digest2int(tableSuffix)) -usingTempDir <- Sys.getenv("STRATEGUS_UNIT_TEST_FOLDER") == "" -tempDir <- ifelse(usingTempDir, tempfile(), Sys.getenv("STRATEGUS_UNIT_TEST_FOLDER")) +tempDir <- tempfile() tempDir <- gsub("\\\\", "/", tempDir) # Correct windows path -renvCachePath <- file.path(tempDir, "strategus/renv") -moduleFolder <- file.path(tempDir, "strategus/modules") -Sys.setenv("INSTANTIATED_MODULES_FOLDER" = moduleFolder) -withr::defer( - { - if (usingTempDir) { - unlink(c(tempDir, renvCachePath, moduleFolder), recursive = TRUE, force = TRUE) - } - }, - testthat::teardown_env() -) # Assemble a list of connectionDetails for the tests ----------- connectionDetailsList <- list() @@ -175,39 +153,3 @@ if (!(Sys.getenv("CDM5_SQL_SERVER_USER") == "" & tempEmulationSchema = NULL ) } - -# Keyring helpers -------------- -# Set the keyring name & password for testing -keyringName <- "strategus" -keyringPassword <- "ohdsi" - -deleteKeyringForUnitTest <- function(selectedKeyring = keyringName, selectedKeyringPassword = keyringPassword) { - # Create a keyring called "strategus" that is password protected - allKeyrings <- keyring::keyring_list() - if (selectedKeyring %in% allKeyrings$keyring) { - if (keyring::keyring_is_locked(keyring = selectedKeyring)) { - keyring::keyring_unlock(keyring = selectedKeyring, password = selectedKeyringPassword) - } - # Delete all keys from the keyring so we can delete it - keys <- keyring::key_list(keyring = selectedKeyring) - if (nrow(keys) > 0) { - for (i in 1:nrow(keys)) { - keyring::key_delete(keys$service[1], keyring = selectedKeyring) - } - } - keyring::keyring_delete(keyring = selectedKeyring) - } -} - -createKeyringForUnitTest <- function(selectedKeyring = keyringName, selectedKeyringPassword = keyringPassword) { - # Delete any existing keyrings - deleteKeyringForUnitTest(selectedKeyring = selectedKeyring) - # Create & Lock the keyring - keyring::keyring_create(keyring = selectedKeyring, password = selectedKeyringPassword) - keyring::keyring_lock(keyring = selectedKeyring) -} - -skip_if_not_secret_service <- function() { - if (keyring::default_backend()$name != "secret service") skip("Not secret service") - invisible(TRUE) -} diff --git a/tests/testthat/test-DatabaseMetaData.R b/tests/testthat/test-DatabaseMetaData.R index c6eda6ca..8ac9c62a 100644 --- a/tests/testthat/test-DatabaseMetaData.R +++ b/tests/testthat/test-DatabaseMetaData.R @@ -1,5 +1,4 @@ test_that("Test DatabaseMetaData error conditions", { - skip_if_not_secret_service() # Run this test in isolation as it will make changes to the CDM schema. eunomiaConnectionDetails <- Eunomia::getEunomiaConnectionDetails() connection <- DatabaseConnector::connect(eunomiaConnectionDetails) @@ -32,24 +31,12 @@ test_that("Test DatabaseMetaData error conditions", { ) } DatabaseConnector::disconnect(connection) - unlink(eunomiaConnectionDetails$server, recursive = TRUE, force = TRUE) }, testthat::teardown_env() ) - # Setup keyring for the test - Sys.setenv("STRATEGUS_KEYRING_PASSWORD" = keyringPassword) - createKeyringForUnitTest(selectedKeyring = keyringName, selectedKeyringPassword = keyringPassword) - on.exit(deleteKeyringForUnitTest()) - # Confirm an error is thrown when 1 or more of these tables are missing - Strategus::storeConnectionDetails( - connectionDetails = eunomiaConnectionDetails, - connectionDetailsReference = dbms, - keyringName = keyringName - ) executionSettings <- Strategus::createCdmExecutionSettings( - connectionDetailsReference = dbms, workDatabaseSchema = workDatabaseSchema, cdmDatabaseSchema = cdmDatabaseSchema, cohortTableNames = CohortGenerator::getCohortTableNames(), @@ -58,9 +45,9 @@ test_that("Test DatabaseMetaData error conditions", { minCellCount = 5 ) expect_error( - Strategus:::createDatabaseMetaData( - executionSettings = executionSettings, - keyringName = keyringName + Strategus::getCdmDatabaseMetaData( + cdmExecutionSettings = executionSettings, + connectionDetails = eunomiaConnectionDetails ), regexp = "FATAL ERROR: Your OMOP CDM is missing the following required tables: cdm_source, vocabulary, observation_period" ) @@ -79,9 +66,9 @@ test_that("Test DatabaseMetaData error conditions", { } expect_error( - Strategus:::createDatabaseMetaData( - executionSettings = executionSettings, - keyringName = keyringName + Strategus::getCdmDatabaseMetaData( + cdmExecutionSettings = executionSettings, + connectionDetails = eunomiaConnectionDetails ), regexp = "FATAL ERROR: The CDM_SOURCE table in your OMOP CDM is empty." ) @@ -98,9 +85,9 @@ test_that("Test DatabaseMetaData error conditions", { ) expect_error( - Strategus:::createDatabaseMetaData( - executionSettings = executionSettings, - keyringName = keyringName + Strategus::getCdmDatabaseMetaData( + cdmExecutionSettings = executionSettings, + connectionDetails = eunomiaConnectionDetails ), regexp = "FATAL ERROR: The VOCABULARY table in your OMOP CDM is missing the version" ) @@ -115,9 +102,9 @@ test_that("Test DatabaseMetaData error conditions", { backup_table = "vocabulary_bak" ) expect_error( - Strategus:::createDatabaseMetaData( - executionSettings = executionSettings, - keyringName = keyringName + Strategus::getCdmDatabaseMetaData( + cdmExecutionSettings = executionSettings, + connectionDetails = eunomiaConnectionDetails ), regexp = "FATAL ERROR: The OBSERVATION_PERIOD table in your OMOP CDM lacks a maximum observation_period_end_date" ) diff --git a/tests/testthat/test-EvidenceSynthesisModule.R b/tests/testthat/test-EvidenceSynthesisModule.R new file mode 100644 index 00000000..297dcd84 --- /dev/null +++ b/tests/testthat/test-EvidenceSynthesisModule.R @@ -0,0 +1,418 @@ +library(testthat) +library(Strategus) + +esTestDataConnectionDetails <- DatabaseConnector::createConnectionDetails( + dbms = "sqlite", + server = system.file("testdata/esmodule/results.sqlite", package = "Strategus") +) + +workFolder <- tempfile("work") +dir.create(workFolder) +testResultsFolder <- tempfile("results") +dir.create(testResultsFolder) +# jobContext <- readRDS("tests/testJobContext.rds") +# jobContext$moduleExecutionSettings$workSubFolder <- workFolder +# jobContext$moduleExecutionSettings$resultsSubFolder <- testResultsFolder +# jobContext$moduleExecutionSettings$resultsConnectionDetails <- esTestDataConnectionDetails + +createEsModuleSpecs <- function() { + esModuleSettingsCreator <- EvidenceSynthesisModule$new() + # Create EvidenceSynthesisModule settings --------------------------------------- + + evidenceSynthesisSourceCmGrid <- esModuleSettingsCreator$createEvidenceSynthesisSource( + sourceMethod = "CohortMethod", + likelihoodApproximation = "adaptive grid" + ) + + evidenceSynthesisSourceCmNormal <- esModuleSettingsCreator$createEvidenceSynthesisSource( + sourceMethod = "CohortMethod", + databaseIds = c(1, 2, 4), + analysisIds = c(1, 3), + likelihoodApproximation = "normal" + ) + + evidenceSynthesisSourceSccsGrid <- esModuleSettingsCreator$createEvidenceSynthesisSource( + sourceMethod = "SelfControlledCaseSeries", + likelihoodApproximation = "adaptive grid" + ) + + evidenceSynthesisSourceSccsNormal <- esModuleSettingsCreator$createEvidenceSynthesisSource( + sourceMethod = "SelfControlledCaseSeries", + databaseIds = c(1, 2, 4), + analysisIds = c(1, 3), + likelihoodApproximation = "normal" + ) + + fixedEffectsMetaAnalysisCm <- esModuleSettingsCreator$createFixedEffectsMetaAnalysis( + evidenceSynthesisAnalysisId = 1, + evidenceSynthesisSource = evidenceSynthesisSourceCmNormal + ) + + randomEffectsMetaAnalysisCm <- esModuleSettingsCreator$createRandomEffectsMetaAnalysis( + evidenceSynthesisAnalysisId = 2, + evidenceSynthesisSource = evidenceSynthesisSourceCmNormal + ) + + bayesianMetaAnalysisCm <- esModuleSettingsCreator$createBayesianMetaAnalysis( + evidenceSynthesisAnalysisId = 3, + evidenceSynthesisSource = evidenceSynthesisSourceCmGrid + ) + + fixedEffectsMetaAnalysisSccs <- esModuleSettingsCreator$createFixedEffectsMetaAnalysis( + evidenceSynthesisAnalysisId = 4, + evidenceSynthesisSource = evidenceSynthesisSourceSccsNormal + ) + + randomEffectsMetaAnalysisSccs <- esModuleSettingsCreator$createRandomEffectsMetaAnalysis( + evidenceSynthesisAnalysisId = 5, + evidenceSynthesisSource = evidenceSynthesisSourceSccsNormal + ) + + bayesianMetaAnalysisSccs <- esModuleSettingsCreator$createBayesianMetaAnalysis( + evidenceSynthesisAnalysisId = 6, + evidenceSynthesisSource = evidenceSynthesisSourceSccsGrid + ) + + evidenceSynthesisModuleSpecs <- esModuleSettingsCreator$createModuleSpecifications( + evidenceSynthesisAnalysisList = list( + fixedEffectsMetaAnalysisCm, + randomEffectsMetaAnalysisCm, + bayesianMetaAnalysisCm, + fixedEffectsMetaAnalysisSccs, + randomEffectsMetaAnalysisSccs, + bayesianMetaAnalysisSccs + ) + ) + + analysisSpecifications <- createEmptyAnalysisSpecificiations() %>% + addModuleSpecifications(evidenceSynthesisModuleSpecs) + + return(analysisSpecifications) +} + +test_that("Run module", { + esAnalysisSpecifications <- createEsModuleSpecs() + resultsExecutionSettings <- Strategus::createResultsExecutionSettings( + resultsDatabaseSchema = "main", + resultsFolder = testResultsFolder, + workFolder = workFolder + ) + Strategus::execute( + analysisSpecifications = esAnalysisSpecifications, + executionSettings = resultsExecutionSettings, + connectionDetails = esTestDataConnectionDetails + ) + resultsFiles <- list.files(file.path(testResultsFolder, "EvidenceSynthesisModule")) + expect_true("es_analysis.csv" %in% resultsFiles) + expect_true("es_cm_result.csv" %in% resultsFiles) + expect_true("es_cm_diagnostics_summary.csv" %in% resultsFiles) + expect_true("es_sccs_result.csv" %in% resultsFiles) + expect_true("es_sccs_diagnostics_summary.csv" %in% resultsFiles) +}) + +test_that("Skipped analyses as specified", { + # We specified we didn't want cohort method analysis ID 2 in evidence synthesis ID 2: + results <- CohortGenerator::readCsv(file.path(testResultsFolder, "EvidenceSynthesisModule", "es_cm_result.csv")) + expect_false(any(results$evidenceSynthesisAnalysisId == 2 & results$analysisId == 2)) + + results <- CohortGenerator::readCsv(file.path(testResultsFolder, "EvidenceSynthesisModule", "es_sccs_result.csv")) + expect_false(any(results$evidenceSynthesisAnalysisId == 2 & results$analysisId == 2)) +}) + +getApproximation <- function(setting) { + tibble( + evidenceSynthesisAnalysisId = setting$evidenceSynthesisAnalysisId, + likelihoodApproximation = setting$evidenceSynthesisSource$likelihoodApproximation + ) %>% + return() +} + +getDatabaseIds <- function(setting, databaseIds) { + if (!is.null(setting$evidenceSynthesisSource$databaseIds)) { + databaseIds <- setting$evidenceSynthesisSource$databaseIds + } + tibble( + evidenceSynthesisAnalysisId = setting$evidenceSynthesisAnalysisId, + databaseId = databaseIds + ) %>% + return() +} + +test_that("Include only allowed CM estimates in meta-analysis", { + # Should only include estimates in meta-analysis that are + # 1. Either unblinded or not outcome of interest + # 2. Has a valid estimate (normal approx) or LL profile (adaptive grid) + # 3. Is not excluded in createEvidenceSynthesisSource() + connection <- DatabaseConnector::connect(esTestDataConnectionDetails) + on.exit(DatabaseConnector::disconnect(connection)) + + esAnalysisSpecifications <- createEsModuleSpecs() + esSettings <- esAnalysisSpecifications$moduleSpecifications[[1]]$settings + + # Determine if unblinded: + sql <- " + SELECT cm_target_comparator_outcome.target_id, + cm_target_comparator_outcome.comparator_id, + cm_target_comparator_outcome.outcome_id, + analysis_id, + database_id, + unblind AS include_1 + FROM main.cm_target_comparator_outcome + LEFT JOIN main.cm_diagnostics_summary + ON cm_diagnostics_summary.target_id = cm_target_comparator_outcome.target_id + AND cm_diagnostics_summary.comparator_id = cm_target_comparator_outcome.comparator_id + AND cm_diagnostics_summary.outcome_id = cm_target_comparator_outcome.outcome_id; + " + criterion1 <- DatabaseConnector::querySql(connection, sql, snakeCaseToCamelCase = TRUE) + # Must have some blinded results for this test to work: + expect_gt(sum(criterion1$include1 == 0), 0) + + # Determine if valid estimate or LL profile: + approximations <- bind_rows(lapply(esSettings$evidenceSynthesisAnalysisList, getApproximation)) + sql <- " + SELECT cm_result.target_id, + cm_result.comparator_id, + cm_result.outcome_id, + cm_result.analysis_id, + cm_result.database_id, + CASE + WHEN log_rr IS NOT NULL AND se_log_rr IS NOT NULL THEN 1 + ELSE 0 + END AS has_valid_estimate, + CASE + WHEN profiles.target_id IS NOT NULL THEN 1 + ELSE 0 + END AS has_ll_profile + FROM main.cm_result + LEFT JOIN ( + SELECT DISTINCT target_id, + comparator_id, + outcome_id, + analysis_id, + database_id + FROM main.cm_likelihood_profile + ) profiles + ON cm_result.target_id = profiles.target_id + AND cm_result.comparator_id = profiles.comparator_id + AND cm_result.outcome_id = profiles.outcome_id + AND cm_result.analysis_id = profiles.analysis_id + AND cm_result.database_id = profiles.database_id + " + criterion2 <- DatabaseConnector::querySql(connection, sql, snakeCaseToCamelCase = TRUE) %>% + cross_join(approximations) %>% + mutate(include2 = if_else(likelihoodApproximation == "normal", + hasValidEstimate, + hasLlProfile + )) + + # Determine if database was excluded in createEvidenceSynthesisSource(): + databaseIds <- unique(criterion2$databaseId) + criterion3 <- bind_rows(lapply(esSettings$evidenceSynthesisAnalysisList, getDatabaseIds, databaseIds = databaseIds)) %>% + mutate(include3 = 1) + + # Combine all criteria, and check if agree with results: + allowed <- criterion1 %>% + inner_join(criterion2, + by = join_by(targetId, comparatorId, outcomeId, analysisId, databaseId), + relationship = "one-to-many" + ) %>% + inner_join(criterion3, by = join_by(databaseId, evidenceSynthesisAnalysisId)) %>% + mutate(include = include1 & include2 & include3) %>% + group_by(targetId, comparatorId, outcomeId, analysisId, evidenceSynthesisAnalysisId) %>% + summarize(nAllowed = sum(include), .groups = "drop") + + results <- CohortGenerator::readCsv(file.path(testResultsFolder, "EvidenceSynthesisModule", "es_cm_result.csv")) + results <- results %>% + left_join(allowed, by = join_by(targetId, comparatorId, outcomeId, analysisId, evidenceSynthesisAnalysisId)) + expect_true(all(results$nDatabases == results$nAllowed)) +}) + +test_that("Include only allowed SCCS estimates in meta-analysis", { + # Should only include estimates in meta-analysis that are + # 1. Unblinded. + # 2. Has a valid estimate (normal approx) or LL profile (adaptive grid) + # 3. Is not excluded in createEvidenceSynthesisSource() + connection <- DatabaseConnector::connect(esTestDataConnectionDetails) + on.exit(DatabaseConnector::disconnect(connection)) + + esAnalysisSpecifications <- createEsModuleSpecs() + esSettings <- esAnalysisSpecifications$moduleSpecifications[[1]]$settings + + # Determine if unblinded or true effect size is known: + sql <- " + SELECT sccs_diagnostics_summary.exposures_outcome_set_id, + sccs_diagnostics_summary.covariate_id, + sccs_diagnostics_summary.analysis_id, + sccs_diagnostics_summary.database_id, + unblind AS include_1 + FROM main.sccs_exposure + INNER JOIN main.sccs_diagnostics_summary + ON sccs_exposure.exposures_outcome_set_id = sccs_diagnostics_summary.exposures_outcome_set_id + INNER JOIN main.sccs_covariate + ON sccs_exposure.era_id = sccs_covariate.era_id + AND sccs_covariate.covariate_id = sccs_diagnostics_summary.covariate_id + AND sccs_covariate.exposures_outcome_set_id = sccs_diagnostics_summary.exposures_outcome_set_id + AND sccs_covariate.analysis_id = sccs_diagnostics_summary.analysis_id + AND sccs_covariate.database_id = sccs_diagnostics_summary.database_id; + " + criterion1 <- DatabaseConnector::querySql(connection, sql, snakeCaseToCamelCase = TRUE) + # Must have some blinded results for this test to work: + expect_gt(sum(criterion1$include1 == 0), 0) + + # Determine if valid estimate or LL profile: + approximations <- bind_rows(lapply(esSettings$evidenceSynthesisAnalysisList, getApproximation)) + sql <- " + SELECT sccs_result.exposures_outcome_set_id, + sccs_result.covariate_id, + sccs_result.analysis_id, + sccs_result.database_id, + CASE + WHEN log_rr IS NOT NULL AND se_log_rr IS NOT NULL THEN 1 + ELSE 0 + END AS has_valid_estimate, + CASE + WHEN profiles.exposures_outcome_set_id IS NOT NULL THEN 1 + ELSE 0 + END AS has_ll_profile + FROM main.sccs_result + LEFT JOIN ( + SELECT DISTINCT exposures_outcome_set_id, + covariate_id, + analysis_id, + database_id + FROM main.sccs_likelihood_profile + ) profiles + ON sccs_result.exposures_outcome_set_id = profiles.exposures_outcome_set_id + AND sccs_result.covariate_id = profiles.covariate_id + AND sccs_result.analysis_id = profiles.analysis_id + AND sccs_result.database_id = profiles.database_id + " + criterion2 <- DatabaseConnector::querySql(connection, sql, snakeCaseToCamelCase = TRUE) %>% + cross_join(approximations) %>% + mutate(include2 = if_else(likelihoodApproximation == "normal", + hasValidEstimate, + hasLlProfile + )) + + # Determine if database was excluded in createEvidenceSynthesisSource(): + databaseIds <- unique(criterion2$databaseId) + criterion3 <- bind_rows(lapply(esSettings$evidenceSynthesisAnalysisList, getDatabaseIds, databaseIds = databaseIds)) %>% + mutate(include3 = 1) + + # Combine all criteria, and check if agree with results: + allowed <- criterion1 %>% + inner_join(criterion2, + by = join_by(exposuresOutcomeSetId, covariateId, analysisId, databaseId), + relationship = "one-to-many" + ) %>% + inner_join(criterion3, by = join_by(databaseId, evidenceSynthesisAnalysisId)) %>% + mutate(include = include1 & include2 & include3) %>% + group_by(exposuresOutcomeSetId, covariateId, analysisId, evidenceSynthesisAnalysisId) %>% + summarize(nAllowed = sum(include), .groups = "drop") + + results <- CohortGenerator::readCsv(file.path(testResultsFolder, "EvidenceSynthesisModule", "es_sccs_result.csv")) + results <- results %>% + left_join(allowed, by = join_by(exposuresOutcomeSetId, covariateId, analysisId, evidenceSynthesisAnalysisId)) + expect_true(all(results$nDatabases == results$nAllowed)) +}) + +test_that("Output conforms to results model", { + model <- CohortGenerator::readCsv(file.path(testResultsFolder, "EvidenceSynthesisModule", "resultsDataModelSpecification.csv")) + tables <- unique(model$tableName) + for (table in tables) { + data <- readr::read_csv(file.path(testResultsFolder, "EvidenceSynthesisModule", sprintf("%s.csv", table)), show_col_types = FALSE) + observed <- colnames(data) + observed <- sort(observed) + expected <- model$columnName[model$tableName == table] + expected <- sort(expected) + expect_equal(observed, expected) + } +}) + +test_that("Check MDRR values", { + # CohortMethod + results <- CohortGenerator::readCsv(file.path(testResultsFolder, "EvidenceSynthesisModule", "es_cm_result.csv")) + diagnostics <- CohortGenerator::readCsv(file.path(testResultsFolder, "EvidenceSynthesisModule", "es_cm_diagnostics_summary.csv")) + combined <- results %>% + inner_join(diagnostics, by = join_by(targetId, comparatorId, outcomeId, analysisId, evidenceSynthesisAnalysisId)) + noDbs <- combined %>% + filter(nDatabases == 0) + expect_true(all(is.infinite(noDbs$mdrr))) + expect_true(all(noDbs$mdrrDiagnostic == "FAIL")) + expect_true(all(noDbs$unblind == 0)) + + oneDb <- combined %>% + filter(nDatabases == 1) + # All per-DB MDRRs were set to 2 in simulation code: + expect_true(all(oneDb$mdrr == 2)) + expect_true(all(oneDb$mdrrDiagnostic == "PASS")) + + multiDbs <- combined %>% + filter(nDatabases > 1, !is.na(seLogRr)) + + expect_true(all(!is.na(multiDbs$mdrr))) + + # SCCS + results <- CohortGenerator::readCsv(file.path(testResultsFolder, "EvidenceSynthesisModule", "es_sccs_result.csv")) + diagnostics <- CohortGenerator::readCsv(file.path(testResultsFolder, "EvidenceSynthesisModule", "es_sccs_diagnostics_summary.csv")) + combined <- results %>% + inner_join(diagnostics, by = join_by(analysisId, exposuresOutcomeSetId, covariateId, evidenceSynthesisAnalysisId)) + noDbs <- combined %>% + filter(nDatabases == 0) + expect_true(all(is.infinite(noDbs$mdrr))) + expect_true(all(noDbs$mdrrDiagnostic == "FAIL")) + expect_true(all(noDbs$unblind == 0)) + + oneDb <- combined %>% + filter(nDatabases == 1) + # All per-DB MDRRs were set to 2 in simulation code: + expect_true(all(oneDb$mdrr == 2)) + expect_true(all(oneDb$mdrrDiagnostic == "PASS")) + + multiDbs <- combined %>% + filter(nDatabases > 1, !is.na(seLogRr)) + + expect_true(all(!is.na(multiDbs$mdrr))) +}) + +test_that("Don't error when no negative controls present", { + # Create dataset without negative controls + tempFile <- tempfile(fileext = ".sqlite") + file.copy(system.file("testdata/esmodule/results.sqlite", package = "Strategus"), tempFile) + on.exit(unlink(tempFile)) + tempConnectionDetails <- DatabaseConnector::createConnectionDetails( + dbms = "sqlite", + server = tempFile + ) + connection <- DatabaseConnector::connect(tempConnectionDetails) + DatabaseConnector::renderTranslateExecuteSql(connection, "UPDATE cm_target_comparator_outcome SET true_effect_size = NULL;") + DatabaseConnector::disconnect(connection) + + # tempJobContext <- jobContext + # tempJobContext$settings$evidenceSynthesisAnalysisList <- list(tempJobContext$settings$evidenceSynthesisAnalysisList[[1]]) + # tempJobContext$moduleExecutionSettings$resultsConnectionDetails <- tempConnectionDetails + # execute(tempJobContext) + + esAnalysisSpecifications <- createEsModuleSpecs() + esAnalysisSpecifications$moduleSpecifications[[1]]$settings$evidenceSynthesisAnalysisList <- list(esAnalysisSpecifications$moduleSpecifications[[1]]$settings$evidenceSynthesisAnalysisList[[1]]) + resultsExecutionSettings <- Strategus::createResultsExecutionSettings( + resultsDatabaseSchema = "main", + resultsFolder = testResultsFolder, + workFolder = workFolder + ) + Strategus::execute( + analysisSpecifications = esAnalysisSpecifications, + executionSettings = resultsExecutionSettings, + connectionDetails = tempConnectionDetails + ) + + estimates <- readr::read_csv(file.path(testResultsFolder, "EvidenceSynthesisModule", "es_cm_result.csv"), show_col_types = FALSE) + expect_gt(nrow(estimates), 0) + expect_true(all(is.na(estimates$calibrated_rr))) +}) + + +# readr::write_csv(OhdsiRTools::createResultsSchemaStub(testResultsFolder), "resultsDataModelSpecification.csv") + +unlink(workFolder) +unlink(testResultsFolder) diff --git a/tests/testthat/test-Execution.R b/tests/testthat/test-Execution.R new file mode 100644 index 00000000..3a4ad6a2 --- /dev/null +++ b/tests/testthat/test-Execution.R @@ -0,0 +1,285 @@ +test_that("Execute study, upload results, excute results modules and upload results", { + analysisSpecifications <- ParallelLogger::loadSettingsFromJson( + fileName = system.file("testdata/cdmModulesAnalysisSpecifications.json", + package = "Strategus" + ) + ) + studyRootFolder <- file.path(tempDir, "EunomiaTestStudy") + workFolder <- file.path(studyRootFolder, "work_folder") + resultsFolder <- file.path(studyRootFolder, "results_folder") + if (!dir.exists(studyRootFolder)) { + dir.create(studyRootFolder, recursive = TRUE) + } + + withr::defer( + { + unlink(studyRootFolder, recursive = TRUE, force = TRUE) + }, + testthat::teardown_env() + ) + + # Execute the study --------------------------- + executionSettings <- createCdmExecutionSettings( + workDatabaseSchema = workDatabaseSchema, + cdmDatabaseSchema = cdmDatabaseSchema, + cohortTableNames = CohortGenerator::getCohortTableNames(cohortTable = "unit_test"), + workFolder = workFolder, + resultsFolder = resultsFolder + ) + + ParallelLogger::saveSettingsToJson( + object = executionSettings, + file.path(studyRootFolder, "eunomiaExecutionSettings.json") + ) + + executionSettings <- ParallelLogger::loadSettingsFromJson( + fileName = file.path(studyRootFolder, "eunomiaExecutionSettings.json") + ) + + expect_warning( + Strategus::execute( + connectionDetails = connectionDetails, + analysisSpecifications = analysisSpecifications, + executionSettings = executionSettings + ) + ) + + # Create a results DB and upload results + dbFilePath <- file.path(studyRootFolder, "testdm.sqlite") + mydb <- dbConnect(RSQLite::SQLite(), dbFilePath) + dbDisconnect(mydb) + + withr::defer( + { + unlink(dbFilePath, recursive = TRUE, force = TRUE) + }, + testthat::teardown_env() + ) + + resultsConnectionDetails <- DatabaseConnector::createConnectionDetails( + dbms = "sqlite", + server = dbFilePath + ) + + resultsDataModelSettings <- Strategus::createResultsDataModelSettings( + resultsDatabaseSchema = "main", + resultsFolder = executionSettings$resultsFolder + ) + + # Create cdm modules results data model ------------------------- + cdmModulesAnalysisSpecifications <- ParallelLogger::loadSettingsFromJson( + fileName = system.file("testdata/cdmModulesAnalysisSpecifications.json", + package = "Strategus" + ) + ) + + Strategus::createResultDataModel( + analysisSpecifications = cdmModulesAnalysisSpecifications, + resultsDataModelSettings = resultsDataModelSettings, + resultsConnectionDetails = resultsConnectionDetails + ) + + # Upload cdm related results -------------------- + Strategus::uploadResults( + analysisSpecifications = analysisSpecifications, + resultsDataModelSettings = resultsDataModelSettings, + resultsConnectionDetails = resultsConnectionDetails + ) + + # Execute results modules ------------------------- + resultsModulesAnalysisSpecifications <- ParallelLogger::loadSettingsFromJson( + fileName = system.file("testdata/resultsModulesAnalysisSpecifications.json", + package = "Strategus" + ) + ) + + resultsExecutionSettings <- Strategus::createResultsExecutionSettings( + resultsDatabaseSchema = resultsDataModelSettings$resultsDatabaseSchema, + workFolder = file.path(studyRootFolder, "results_modules", "work_folder"), + resultsFolder = file.path(studyRootFolder, "results_modules", "results_folder") + ) + + Strategus::execute( + connectionDetails = resultsConnectionDetails, + analysisSpecifications = resultsModulesAnalysisSpecifications, + executionSettings = resultsExecutionSettings + ) + + # Create the results data model ------ + resultsDataModelSettings <- Strategus::createResultsDataModelSettings( + resultsDatabaseSchema = "main", + resultsFolder = resultsExecutionSettings$resultsFolder + ) + + # NOTE: This will throw a warning since the database metadata + # does not exist + expect_warning( + Strategus::createResultDataModel( + analysisSpecifications = resultsModulesAnalysisSpecifications, + resultsDataModelSettings = resultsDataModelSettings, + resultsConnectionDetails = resultsConnectionDetails + ) + ) + + # Upload the results ------------- + resultsDataModelSettings <- Strategus::createResultsDataModelSettings( + resultsDatabaseSchema = resultsDataModelSettings$resultsDatabaseSchema, + resultsFolder = resultsExecutionSettings$resultsFolder + ) + + # NOTE: This will throw a warning since the database metadata + # does not exist + expect_warning( + Strategus::uploadResults( + analysisSpecifications = resultsModulesAnalysisSpecifications, + resultsDataModelSettings = resultsDataModelSettings, + resultsConnectionDetails = resultsConnectionDetails + ) + ) + + # Get a list of tables + connection <- DatabaseConnector::connect(resultsConnectionDetails) + on.exit(DatabaseConnector::disconnect(connection)) + tableList <- DatabaseConnector::getTableNames( + connection = connection, + databaseSchema = resultsDataModelSettings$resultsDatabaseSchema + ) + + expect_true(length(tableList) > 0) +}) + +test_that("Execute on Oracle stops if table names exceed length limit", { + sqlRenderTempEmulationSchema <- getOption("sqlRenderTempEmulationSchema", default = "") + options(sqlRenderTempEmulationSchema = "some_schema") + on.exit(options(sqlRenderTempEmulationSchema = sqlRenderTempEmulationSchema)) + + connectionDetails <- DatabaseConnector::createConnectionDetails( + dbms = "oracle" + ) + executionSettings <- Strategus::createCdmExecutionSettings( + workDatabaseSchema = "does_not_matter", + cdmDatabaseSchema = "does_not_matter", + cohortTableNames = CohortGenerator::getCohortTableNames("some_really_long_table_name_for_testing_that_oracle_throws_a_warning"), + workFolder = file.path(tempDir, "work_folder"), + resultsFolder = file.path(tempDir, "results_folder"), + minCellCount = 5 + ) + + analysisSpecifications <- ParallelLogger::loadSettingsFromJson( + fileName = system.file("testdata/cdmModulesAnalysisSpecifications.json", + package = "Strategus" + ) + ) + + expect_error( + Strategus::execute( + connectionDetails = connectionDetails, + analysisSpecifications = analysisSpecifications, + executionSettings = executionSettings + ) + ) +}) + +test_that("Negative control outcomes are optional", { + analysisSpecifications <- ParallelLogger::loadSettingsFromJson( + fileName = system.file("testdata/cdmModulesAnalysisSpecifications.json", + package = "Strategus" + ) + ) + + # Remove the nco section + analysisSpecifications$sharedResources <- list(analysisSpecifications$sharedResources[[1]]) + + # Remove all but CG + analysisSpecifications$moduleSpecifications <- list(analysisSpecifications$moduleSpecifications[[3]]) + + executionSettings <- createCdmExecutionSettings( + workDatabaseSchema = workDatabaseSchema, + cdmDatabaseSchema = cdmDatabaseSchema, + cohortTableNames = CohortGenerator::getCohortTableNames(cohortTable = "unit_test"), + workFolder = file.path(tempDir, "work_folder"), + resultsFolder = file.path(tempDir, "results_folder") + ) + + expect_output( + Strategus::execute( + connectionDetails = connectionDetails, + analysisSpecifications = analysisSpecifications, + executionSettings = executionSettings + ), + "Generating cohort set", + ignore.case = TRUE + ) +}) + +test_that("Specify subset of modules to run with modules not in specification fails", { + analysisSpecifications <- ParallelLogger::loadSettingsFromJson( + fileName = system.file("testdata/cdmModulesAnalysisSpecifications.json", + package = "Strategus" + ) + ) + executionSettings <- createCdmExecutionSettings( + workDatabaseSchema = workDatabaseSchema, + cdmDatabaseSchema = cdmDatabaseSchema, + cohortTableNames = CohortGenerator::getCohortTableNames(cohortTable = "unit_test"), + workFolder = file.path(tempDir, "work_folder"), + resultsFolder = file.path(tempDir, "results_folder"), + modulesToExecute = c("foobar") + ) + + expect_error( + Strategus::execute( + connectionDetails = connectionDetails, + analysisSpecifications = analysisSpecifications, + executionSettings = executionSettings + ) + ) + + executionSettings <- createResultsExecutionSettings( + resultsDatabaseSchema = "main", + workFolder = file.path(tempDir, "work_folder"), + resultsFolder = file.path(tempDir, "results_folder"), + modulesToExecute = c("foobar") + ) + + expect_error( + Strategus::execute( + connectionDetails = connectionDetails, + analysisSpecifications = analysisSpecifications, + executionSettings = executionSettings + ) + ) +}) + +test_that("Specify subset of modules to run", { + analysisSpecifications <- ParallelLogger::loadSettingsFromJson( + fileName = system.file("testdata/cdmModulesAnalysisSpecifications.json", + package = "Strategus" + ) + ) + + modulesToExecute <- c("CohortGeneratorModule", "CohortIncidenceModule") + executionSettings <- createCdmExecutionSettings( + workDatabaseSchema = workDatabaseSchema, + cdmDatabaseSchema = cdmDatabaseSchema, + cohortTableNames = CohortGenerator::getCohortTableNames(cohortTable = "unit_test"), + workFolder = file.path(tempDir, "work_folder"), + resultsFolder = file.path(tempDir, "results_folder"), + modulesToExecute = modulesToExecute + ) + + output <- Strategus::execute( + connectionDetails = connectionDetails, + analysisSpecifications = analysisSpecifications, + executionSettings = executionSettings + ) + + modulesExecuted <- sapply( + X = output, + FUN = function(x) { + x$moduleName + } + ) + + expect_true(all(modulesExecuted %in% modulesToExecute)) +}) diff --git a/tests/testthat/test-ModuleInstantiation.R b/tests/testthat/test-ModuleInstantiation.R deleted file mode 100644 index bee17942..00000000 --- a/tests/testthat/test-ModuleInstantiation.R +++ /dev/null @@ -1,58 +0,0 @@ -test_that("Prevent multiple modules with different versions in analysis specification", { - analysisSpecifications <- ParallelLogger::loadSettingsFromJson( - fileName = system.file("testdata/unitTestAnalysisSpecification.json", - package = "Strategus" - ) - ) - - # Duplicate the module - analysisSpecifications$moduleSpecifications[[2]] <- analysisSpecifications$moduleSpecifications[[1]] - analysisSpecifications$moduleSpecifications[[2]]$version <- "x" - - expect_error( - ensureAllModulesInstantiated( - analysisSpecifications = analysisSpecifications - ) - ) -}) - -# TODO: We'd like to test this functionality but both methods require that -# the module is instantiated which is very time consuming. Instead these -# tests should mock the MetaData.json that exists in the instantiated -# modules so that these methods work faster. -# test_that("Enforce module dependencies", { -# analysisSpecifications <- ParallelLogger::loadSettingsFromJson( -# fileName = system.file("testdata/analysisSpecification.json", -# package = "Strategus" -# ) -# ) -# -# # Remove the cohort generator module which is a dependency for all -# # the other modules -# analysisSpecifications$moduleSpecifications <- analysisSpecifications$moduleSpecifications[-1] -# modules <- getModuleTable(analysisSpecifications, distinct = TRUE) -# -# expect_error( -# checkModuleDependencies( -# modules = modules, -# enforceModuleDependencies = TRUE -# ) -# ) -# }) -# -# test_that("Do not enforce module dependencies", { -# analysisSpecifications <- ParallelLogger::loadSettingsFromJson( -# fileName = system.file("testdata/unitTestAnalysisSpecification.json", -# package = "Strategus" -# ) -# ) -# -# modules <- getModuleTable(analysisSpecifications, distinct = TRUE) -# -# expect_silent( -# checkModuleDependencies( -# modules = modules, -# enforceModuleDependencies = FALSE -# ) -# ) -# }) diff --git a/tests/testthat/test-Modules.R b/tests/testthat/test-Modules.R new file mode 100644 index 00000000..937bf39b --- /dev/null +++ b/tests/testthat/test-Modules.R @@ -0,0 +1,41 @@ +library(testthat) +library(Strategus) + +testResultsDataModelFormat <- function(moduleName) { + module <- get(moduleName)$new() + rdms <- module$getResultsDataModelSpecification() + expect_true(all(CohortGenerator::isSnakeCase(rdms$tableName))) + expect_true(all(CohortGenerator::isSnakeCase(rdms$columnName))) +} + +test_that("CharacterizationModule results data model is in correct format", { + testResultsDataModelFormat("CharacterizationModule") +}) + +test_that("CohortDiagnosticsModule results data model is in correct format", { + testResultsDataModelFormat("CohortDiagnosticsModule") +}) + +test_that("CohortGeneratorModule results data model is in correct format", { + testResultsDataModelFormat("CohortGeneratorModule") +}) + +test_that("CohortIncidenceModule results data model is in correct format", { + testResultsDataModelFormat("CohortIncidenceModule") +}) + +test_that("CohortMethodModule results data model is in correct format", { + testResultsDataModelFormat("CohortMethodModule") +}) + +test_that("EvidenceSynthesisModule results data model is in correct format", { + testResultsDataModelFormat("EvidenceSynthesisModule") +}) + +test_that("PatientLevelPredictionModule results data model is in correct format", { + testResultsDataModelFormat("PatientLevelPredictionModule") +}) + +test_that("SelfControlledCaseSeriesModule results data model is in correct format", { + testResultsDataModelFormat("SelfControlledCaseSeriesModule") +}) diff --git a/tests/testthat/test-RenvHelpers.R b/tests/testthat/test-RenvHelpers.R deleted file mode 100644 index 01b89043..00000000 --- a/tests/testthat/test-RenvHelpers.R +++ /dev/null @@ -1,103 +0,0 @@ -test_that("Check renv.lock compare", { - compare <- Strategus::compareLockFiles( - filename1 = system.file("testdata/renv.lock", package = "Strategus"), - filename2 = system.file("testdata/renv.lock", package = "Strategus") - ) - expect_true(nrow(compare) > 0) - expect_true(nrow(compare[compare$lockfile1Version != compare$lockfile1Version, ]) == 0) -}) - -test_that("Check renv.lock sync detects no changes", { - expect_null( - Strategus::syncLockFile( - sourceOfTruthLockFileName = system.file("testdata/renv.lock", package = "Strategus"), - targetLockFileName = system.file("testdata/renv.lock", package = "Strategus") - ) - ) -}) - -test_that("Check renv.lock sync works", { - tempDir <- tempdir() - tempLockFile <- file.path(tempDir, "renv.lock") - on.exit(unlink(tempLockFile)) - file.copy( - from = system.file("testdata/renv.lock", package = "Strategus"), - to = file.path(tempDir, "renv.lock") - ) - # Get the expected value - lf <- renv::lockfile_read( - file = system.file("testdata/renv.lock", package = "Strategus") - ) - expectedVersion <- lf$Packages$zip$Version - oldVersion <- "0.0.1" - renv::record( - records = paste0("zip@", oldVersion), - lockfile = tempLockFile - ) - - # Confirm the update ahead of the test worked - tempLf <- renv::lockfile_read( - file = tempLockFile - ) - expect_equal(tempLf$Packages$zip$Version, oldVersion) - - # Perform the sync - Strategus::syncLockFile( - sourceOfTruthLockFileName = system.file("testdata/renv.lock", package = "Strategus"), - targetLockFileName = tempLockFile - ) - - # Confirm that the newer version from the source of truth was applied - tempLf <- renv::lockfile_read( - file = tempLockFile - ) - expect_equal(tempLf$Packages$zip$Version, expectedVersion) -}) - -test_that("Test renv.lock validation", { - tmp <- tempfile() - on.exit(unlink(tmp)) - file.copy( - from = system.file("testdata/renv.lock", package = "Strategus"), - to = tmp - ) - - # All tests must pass on our internal lock file - expect_message( - object = Strategus::validateLockFile( - filename = tmp - ), - regexp = "PASSED" - ) - - # Remove the mandatory dependency - tmpLockFile <- renv::lockfile_read(file = tmp) - tmpLockFile$Packages$renv <- NULL - invisible(renv::lockfile_write(lockfile = tmpLockFile, file = tmp)) - expect_message( - object = Strategus::validateLockFile( - filename = tmp - ), - regexp = "FAILED" - ) - - # Remove suggested packages - tmpLockFile$Packages$RSQLite <- NULL - invisible(renv::lockfile_write(lockfile = tmpLockFile, file = tmp)) - expect_message( - object = Strategus::validateLockFile( - filename = tmp - ), - regexp = "FAILED" - ) - - # Mess up the CohortGenerator package to use a "HEAD" ref - tmpLockFile$Packages$CohortGenerator$RemoteRef <- "HEAD" - invisible(renv::lockfile_write(lockfile = tmpLockFile, file = tmp)) - invisible(expect_message( - object = Strategus::validateLockFile( - filename = tmp - ), - regexp = "FAILED" - )) -}) diff --git a/tests/testthat/test-Settings.R b/tests/testthat/test-Settings.R index d5f8362d..08970cb3 100644 --- a/tests/testthat/test-Settings.R +++ b/tests/testthat/test-Settings.R @@ -1,104 +1,410 @@ test_that("Test analysis specification creation", { - cohortSharedResource <- list(id = 1) - class(cohortSharedResource) <- c("CohortDefinitionSharedResources", "SharedResources") + # Setup some test data ------------ + cohortDefinitionSet <- getCohortDefinitionSet( + settingsFileName = system.file("testdata/Cohorts.csv", package = "Strategus"), + jsonFolder = system.file("testdata/cohorts", package = "Strategus"), + sqlFolder = system.file("testdata/sql", package = "Strategus") + ) + subsetOperations <- list( + createDemographicSubset( + name = "Demographic Criteria", + ageMin = 18, + ageMax = 64 + ) + ) + subsetDef <- createCohortSubsetDefinition( + name = "test definition", + definitionId = 1, + subsetOperators = subsetOperations + ) + cohortDefinitionSet <- cohortDefinitionSet |> + addCohortSubsetDefinition(subsetDef) - negativeControlOutcomeCohortSharedResource <- list(id = 1) - class(negativeControlOutcomeCohortSharedResource) <- c("NegativeControlOutcomeSharedResources", "SharedResources") + ncoCohortSet <- readCsv(file = system.file("testdata/negative_controls_concept_set.csv", + package = "Strategus" + )) - moduleSpecifications <- list( - module = "CohortGeneratorModule", - version = "0.0.16", - remoteRepo = "github.com", - remoteUsername = "ohdsi", - settings = list() + # Exposures-outcomes + negativeControlOutcomeIds <- ncoCohortSet$cohortId + outcomeOfInterestIds <- c(3) + exposureOfInterestIds <- c(1, 2) + + # Test Module Settings ---------------------- + # Characterization ------------------------------- + cModuleSettingsCreator <- CharacterizationModule$new() + cModuleSpecifications <- cModuleSettingsCreator$createModuleSpecifications( + targetIds = c(1, 2), + outcomeIds = 3 ) - class(moduleSpecifications) <- c("CohortGeneratorModuleSpecifications", "ModuleSpecifications") - analysisSpecification <- createEmptyAnalysisSpecificiations() %>% - addSharedResources(cohortSharedResource) %>% - addSharedResources(negativeControlOutcomeCohortSharedResource) %>% - addModuleSpecifications(moduleSpecifications) + # Cohort Diagnostics ----------------- + cdModuleSettingsCreator <- CohortDiagnosticsModule$new() + cdModuleSpecifications <- cdModuleSettingsCreator$createModuleSpecifications( + runInclusionStatistics = TRUE, + runIncludedSourceConcepts = TRUE, + runOrphanConcepts = TRUE, + runTimeSeries = FALSE, + runVisitContext = TRUE, + runBreakdownIndexEvents = TRUE, + runIncidenceRate = TRUE, + runCohortRelationship = TRUE, + runTemporalCohortCharacterization = TRUE + ) - expect_equal(length(analysisSpecification$sharedResources), 2) - expect_equal(length(analysisSpecification$moduleSpecifications), 1) -}) + # Cohort Generator ----------------- + cgModuleSettingsCreator <- CohortGeneratorModule$new() -test_that("Create results execution settings", { - executionSettings <- createResultsExecutionSettings( - resultsConnectionDetailsReference = "test", - resultsDatabaseSchema = "test", - workFolder = tempfile(), - resultsFolder = tempfile(), - minCellCount = 5 + # Create the settings & validate them + cohortSharedResourcesSpecifications <- cgModuleSettingsCreator$createCohortSharedResourceSpecifications(cohortDefinitionSet) + cgModuleSettingsCreator$validateCohortSharedResourceSpecifications(cohortSharedResourcesSpecifications) + + ncoCohortSharedResourceSpecifications <- cgModuleSettingsCreator$createNegativeControlOutcomeCohortSharedResourceSpecifications(ncoCohortSet, "first", TRUE) + cgModuleSettingsCreator$validateNegativeControlOutcomeCohortSharedResourceSpecifications(ncoCohortSharedResourceSpecifications) + + cgModuleSpecifications <- cgModuleSettingsCreator$createModuleSpecifications() + + # Characterization ------------------------------- + cModuleSettingsCreator <- CharacterizationModule$new() + cModuleSpecifications <- cModuleSettingsCreator$createModuleSpecifications( + targetIds = c(1, 2), + outcomeIds = 3 ) - expect_equal(class(executionSettings), c("ResultsExecutionSettings", "ExecutionSettings")) -}) + # Cohort Incidence ----------------- + ciModuleSettingsCreator <- CohortIncidenceModule$new() + targets <- list( + CohortIncidence::createCohortRef(id = 1, name = "Celecoxib"), + CohortIncidence::createCohortRef(id = 2, name = "Diclofenac"), + CohortIncidence::createCohortRef(id = 4, name = "Celecoxib Age >= 30"), + CohortIncidence::createCohortRef(id = 5, name = "Diclofenac Age >= 30") + ) + outcomes <- list(CohortIncidence::createOutcomeDef(id = 1, name = "GI bleed", cohortId = 3, cleanWindow = 9999)) -test_that("Get module list", { - moduleList <- getModuleList() - expect_true(nrow(moduleList) > 0) -}) + tars <- list( + CohortIncidence::createTimeAtRiskDef(id = 1, startWith = "start", endWith = "end"), + CohortIncidence::createTimeAtRiskDef(id = 2, startWith = "start", endWith = "start", endOffset = 365) + ) + analysis1 <- CohortIncidence::createIncidenceAnalysis( + targets = c(1, 2, 4, 5), + outcomes = c(1), + tars = c(1, 2) + ) + + irDesign <- CohortIncidence::createIncidenceDesign( + targetDefs = targets, + outcomeDefs = outcomes, + tars = tars, + analysisList = list(analysis1), + strataSettings = CohortIncidence::createStrataSettings( + byYear = TRUE, + byGender = TRUE + ) + ) + + ciModuleSpecifications <- ciModuleSettingsCreator$createModuleSpecifications( + irDesign = irDesign$toList() + ) + + # Cohort Method ---------------------- + cmModuleSettingsCreator <- CohortMethodModule$new() + negativeControlOutcomes <- lapply( + X = ncoCohortSet$cohortId, + FUN = CohortMethod::createOutcome, + outcomeOfInterest = FALSE, + trueEffectSize = 1, + priorOutcomeLookback = 30 + ) + + outcomesOfInterest <- lapply( + X = 3, + FUN = CohortMethod::createOutcome, + outcomeOfInterest = TRUE + ) + + outcomes <- append( + negativeControlOutcomes, + outcomesOfInterest + ) + + tcos1 <- CohortMethod::createTargetComparatorOutcomes( + targetId = 1, + comparatorId = 2, + outcomes = outcomes, + excludedCovariateConceptIds = c(1118084, 1124300) + ) + tcos2 <- CohortMethod::createTargetComparatorOutcomes( + targetId = 4, + comparatorId = 5, + outcomes = outcomes, + excludedCovariateConceptIds = c(1118084, 1124300) + ) + + targetComparatorOutcomesList <- list(tcos1, tcos2) + + covarSettings <- FeatureExtraction::createDefaultCovariateSettings(addDescendantsToExclude = TRUE) + + getDbCmDataArgs <- CohortMethod::createGetDbCohortMethodDataArgs( + washoutPeriod = 183, + firstExposureOnly = TRUE, + removeDuplicateSubjects = "remove all", + maxCohortSize = 100000, + covariateSettings = covarSettings + ) + + createStudyPopArgs <- CohortMethod::createCreateStudyPopulationArgs( + minDaysAtRisk = 1, + riskWindowStart = 0, + startAnchor = "cohort start", + riskWindowEnd = 30, + endAnchor = "cohort end" + ) + + matchOnPsArgs <- CohortMethod::createMatchOnPsArgs() + fitOutcomeModelArgs <- CohortMethod::createFitOutcomeModelArgs(modelType = "cox") + createPsArgs <- CohortMethod::createCreatePsArgs( + stopOnError = FALSE, + control = Cyclops::createControl(cvRepetitions = 1) + ) + computeSharedCovBalArgs <- CohortMethod::createComputeCovariateBalanceArgs() + computeCovBalArgs <- CohortMethod::createComputeCovariateBalanceArgs( + covariateFilter = FeatureExtraction::getDefaultTable1Specifications() + ) + + cmAnalysis1 <- CohortMethod::createCmAnalysis( + analysisId = 1, + description = "No matching, simple outcome model", + getDbCohortMethodDataArgs = getDbCmDataArgs, + createStudyPopArgs = createStudyPopArgs, + fitOutcomeModelArgs = fitOutcomeModelArgs + ) + + cmAnalysis2 <- CohortMethod::createCmAnalysis( + analysisId = 2, + description = "Matching on ps and covariates, simple outcomeModel", + getDbCohortMethodDataArgs = getDbCmDataArgs, + createStudyPopArgs = createStudyPopArgs, + createPsArgs = createPsArgs, + matchOnPsArgs = matchOnPsArgs, + computeSharedCovariateBalanceArgs = computeSharedCovBalArgs, + computeCovariateBalanceArgs = computeCovBalArgs, + fitOutcomeModelArgs = fitOutcomeModelArgs + ) + + cmAnalysisList <- list(cmAnalysis1, cmAnalysis2) + + analysesToExclude <- NULL -test_that("Verify that unlocking keyring without password fails", { - allKeyrings <- keyring::keyring_list() - if (!keyringName %in% allKeyrings$keyring) { - keyring::keyring_create(keyring = keyringName, password = keyringPassword) + cmModuleSpecifications <- cmModuleSettingsCreator$createModuleSpecifications( + cmAnalysisList = cmAnalysisList, + targetComparatorOutcomesList = targetComparatorOutcomesList, + analysesToExclude = analysesToExclude + ) + + # EvidenceSythesis ------------------ + esModuleSettingsCreator <- EvidenceSynthesisModule$new() + evidenceSynthesisSourceCm <- esModuleSettingsCreator$createEvidenceSynthesisSource( + sourceMethod = "CohortMethod", + likelihoodApproximation = "adaptive grid" + ) + metaAnalysisCm <- esModuleSettingsCreator$createBayesianMetaAnalysis( + evidenceSynthesisAnalysisId = 1, + alpha = 0.05, + evidenceSynthesisDescription = "Bayesian random-effects alpha 0.05 - adaptive grid", + evidenceSynthesisSource = evidenceSynthesisSourceCm + ) + evidenceSynthesisSourceSccs <- esModuleSettingsCreator$createEvidenceSynthesisSource( + sourceMethod = "SelfControlledCaseSeries", + likelihoodApproximation = "adaptive grid" + ) + metaAnalysisSccs <- esModuleSettingsCreator$createBayesianMetaAnalysis( + evidenceSynthesisAnalysisId = 2, + alpha = 0.05, + evidenceSynthesisDescription = "Bayesian random-effects alpha 0.05 - adaptive grid", + evidenceSynthesisSource = evidenceSynthesisSourceSccs + ) + evidenceSynthesisAnalysisList <- list(metaAnalysisCm, metaAnalysisSccs) + evidenceSynthesisAnalysisSpecifications <- esModuleSettingsCreator$createModuleSpecifications( + evidenceSynthesisAnalysisList + ) + # PatientLevelPrediction ------------------------------- + plpModuleSettingsCreator <- PatientLevelPredictionModule$new() + makeModelDesignSettings <- function(targetId, outcomeId, popSettings, covarSettings) { + invisible(PatientLevelPrediction::createModelDesign( + targetId = targetId, + outcomeId = outcomeId, + restrictPlpDataSettings = PatientLevelPrediction::createRestrictPlpDataSettings(), + populationSettings = popSettings, + covariateSettings = covarSettings, + preprocessSettings = PatientLevelPrediction::createPreprocessSettings(), + modelSettings = PatientLevelPrediction::setLassoLogisticRegression(), + splitSettings = PatientLevelPrediction::createDefaultSplitSetting(), + runCovariateSummary = T + )) } - # Lock the keyring - keyring::keyring_lock(keyring = keyringName) - # Remove STRATEGUS_KEYRING_PASSWORD in case it is already set - Sys.unsetenv("STRATEGUS_KEYRING_PASSWORD") + plpPopulationSettings <- PatientLevelPrediction::createStudyPopulationSettings( + startAnchor = "cohort start", + riskWindowStart = 1, + endAnchor = "cohort start", + riskWindowEnd = 365, + minTimeAtRisk = 1 + ) + plpCovarSettings <- FeatureExtraction::createDefaultCovariateSettings() - # Try to unlock and expect error - expect_error(unlockKeyring(keyring = keyringName)) -}) + modelDesignList <- list() + for (i in 1:length(exposureOfInterestIds)) { + for (j in 1:length(outcomeOfInterestIds)) { + modelDesignList <- append( + modelDesignList, + list( + makeModelDesignSettings( + targetId = exposureOfInterestIds[i], + outcomeId = outcomeOfInterestIds[j], + popSettings = plpPopulationSettings, + covarSettings = plpCovarSettings + ) + ) + ) + } + } -test_that("Store and retrieve connection details", { - # Setup keyring for the test - Sys.setenv("STRATEGUS_KEYRING_PASSWORD" = keyringPassword) - createKeyringForUnitTest(selectedKeyring = keyringName, selectedKeyringPassword = keyringPassword) - on.exit(deleteKeyringForUnitTest()) + plpModuleSpecifications <- plpModuleSettingsCreator$createModuleSpecifications( + modelDesignList = modelDesignList + ) - for (i in 1:length(connectionDetailsList)) { - connectionDetails <- connectionDetailsList[[i]]$connectionDetails - dbms <- connectionDetailsList[[i]]$connectionDetails$dbms + # SelfControlledCaseSeries ------------------------------- + sccsModuleSettingsCreator <- SelfControlledCaseSeriesModule$new() - message("************* Store connection details for ", dbms, " *************") + exposuresOutcomeList <- list() + for (exposureOfInterestId in exposureOfInterestIds) { + for (outcomeOfInterestId in outcomeOfInterestIds) { + exposuresOutcomeList[[length(exposuresOutcomeList) + 1]] <- SelfControlledCaseSeries::createExposuresOutcome( + outcomeId = outcomeOfInterestId, + exposures = list(SelfControlledCaseSeries::createExposure(exposureId = exposureOfInterestId)) + ) + } + for (negativeControlOutcomeId in negativeControlOutcomeIds) { + exposuresOutcomeList[[length(exposuresOutcomeList) + 1]] <- SelfControlledCaseSeries::createExposuresOutcome( + outcomeId = negativeControlOutcomeId, + exposures = list(SelfControlledCaseSeries::createExposure(exposureId = exposureOfInterestId, trueEffectSize = 1)) + ) + } + } - # Verify that the connection details are valid - # by connecting to the DB - conn <- DatabaseConnector::connect( - connectionDetails - ) - DatabaseConnector::disconnect(conn) + getDbSccsDataArgs <- SelfControlledCaseSeries::createGetDbSccsDataArgs( + studyStartDate = "", + studyEndDate = "", + maxCasesPerOutcome = 1e6, + useNestingCohort = TRUE, + nestingCohortId = 1, + deleteCovariatesSmallCount = 0 + ) - # Store the connection details in keyring - storeConnectionDetails( - connectionDetails = connectionDetails, - connectionDetailsReference = dbms, - keyringName = keyringName - ) + createStudyPopulation6AndOlderArgs <- SelfControlledCaseSeries::createCreateStudyPopulationArgs( + minAge = 18, + naivePeriod = 365 + ) - connectionDetailsFromKeyring <- retrieveConnectionDetails( - connectionDetailsReference = dbms, - keyringName = keyringName - ) + covarPreExp <- SelfControlledCaseSeries::createEraCovariateSettings( + label = "Pre-exposure", + includeEraIds = "exposureId", + start = -30, + end = -1, + endAnchor = "era start" + ) + + covarExposureOfInt <- SelfControlledCaseSeries::createEraCovariateSettings( + label = "Main", + includeEraIds = "exposureId", + start = 0, + startAnchor = "era start", + end = 0, + endAnchor = "era end", + profileLikelihood = TRUE, + exposureOfInterest = TRUE + ) + + calendarTimeSettings <- SelfControlledCaseSeries::createCalendarTimeCovariateSettings( + calendarTimeKnots = 5, + allowRegularization = TRUE, + computeConfidenceIntervals = FALSE + ) + + seasonalitySettings <- SelfControlledCaseSeries::createSeasonalityCovariateSettings( + seasonKnots = 5, + allowRegularization = TRUE, + computeConfidenceIntervals = FALSE + ) + + createSccsIntervalDataArgs <- SelfControlledCaseSeries::createCreateSccsIntervalDataArgs( + eraCovariateSettings = list(covarPreExp, covarExposureOfInt), + seasonalityCovariateSettings = seasonalitySettings, + calendarTimeCovariateSettings = calendarTimeSettings, + minCasesForTimeCovariates = 100000 + ) - # Verify that the connection details retrieved - # allow for a connection to the DB - connFromKeyring <- DatabaseConnector::connect( - connectionDetailsFromKeyring + fitSccsModelArgs <- SelfControlledCaseSeries::createFitSccsModelArgs( + control = Cyclops::createControl( + cvType = "auto", + selectorType = "byPid", + startingVariance = 0.1, + seed = 1, + resetCoefficients = TRUE, + noiseLevel = "quiet" ) - expect_silent(DatabaseConnector::disconnect(connFromKeyring)) - } + ) + + sccsAnalysis1 <- SelfControlledCaseSeries::createSccsAnalysis( + analysisId = 1, + description = "SCCS age 18-", + getDbSccsDataArgs = getDbSccsDataArgs, + createStudyPopulationArgs = createStudyPopulation6AndOlderArgs, + createIntervalDataArgs = createSccsIntervalDataArgs, + fitSccsModelArgs = fitSccsModelArgs + ) + + sccsAnalysisList <- list(sccsAnalysis1) + + sccsModuleSpecifications <- sccsModuleSettingsCreator$createModuleSpecifications( + sccsAnalysisList = sccsAnalysisList, + exposuresOutcomeList = exposuresOutcomeList, + combineDataFetchAcrossOutcomes = FALSE + ) + + + # Create analysis specifications --------------- + analysisSpecifications <- createEmptyAnalysisSpecificiations() |> + addSharedResources(cohortSharedResourcesSpecifications) |> + addSharedResources(ncoCohortSharedResourceSpecifications) |> + addCharacterizationModuleSpecifications(cModuleSpecifications) |> + addCohortDiagnosticsModuleSpecifications(cdModuleSpecifications) |> + addCohortGeneratorModuleSpecifications(cgModuleSpecifications) |> + addCohortIncidenceModuleSpecifications(ciModuleSpecifications) |> + addCohortMethodeModuleSpecifications(cmModuleSpecifications) |> + addEvidenceSynthesisModuleSpecifications(evidenceSynthesisAnalysisSpecifications) |> + addSelfControlledCaseSeriesModuleSpecifications(sccsModuleSpecifications) |> + addPatientLevelPredictionModuleSpecifications(plpModuleSpecifications) + + expect_equal(length(analysisSpecifications$sharedResources), 2) + expect_equal(length(analysisSpecifications$moduleSpecifications), 8) }) -test_that("Retrieve connection details that do not exists throws informative error", { - # Setup keyring for the test - Sys.setenv("STRATEGUS_KEYRING_PASSWORD" = keyringPassword) - createKeyringForUnitTest(selectedKeyring = keyringName, selectedKeyringPassword = keyringPassword) - on.exit(deleteKeyringForUnitTest()) - expect_error(retrieveConnectionDetails(connectionDetailsReference = "does-not-exist", keyringName = keyringName)) +test_that("Create results execution settings", { + executionSettings <- createResultsExecutionSettings( + resultsDatabaseSchema = "test", + workFolder = tempfile(), + resultsFolder = tempfile(), + minCellCount = 5 + ) + + expect_equal(class(executionSettings), c("ResultsExecutionSettings", "ExecutionSettings")) +}) + +test_that("Create results data model settings", { + settings <- createResultsDataModelSettings( + resultsDatabaseSchema = "test", + resultsFolder = tempfile() + ) + + expect_equal(class(settings), c("ResultsDataModelSettings")) }) diff --git a/tests/testthat/test-Strategus.R b/tests/testthat/test-Strategus.R deleted file mode 100644 index fbd25d33..00000000 --- a/tests/testthat/test-Strategus.R +++ /dev/null @@ -1,147 +0,0 @@ -test_that("Run unit test study", { - # NOTE: Need to set this in each test otherwise it goes out of scope - renv:::renv_scope_envvars(RENV_PATHS_CACHE = renvCachePath) - - # Setup keyring for the test - Sys.setenv("STRATEGUS_KEYRING_PASSWORD" = keyringPassword) - createKeyringForUnitTest(selectedKeyring = keyringName, selectedKeyringPassword = keyringPassword) - on.exit(deleteKeyringForUnitTest()) - - analysisSpecifications <- ParallelLogger::loadSettingsFromJson( - fileName = system.file("testdata/unitTestAnalysisSpecification.json", - package = "Strategus" - ) - ) - - withr::defer( - { - if (usingTempDir) { - unlink(file.path(tempDir, "EunomiaTestStudy"), recursive = TRUE, force = TRUE) - } - }, - testthat::teardown_env() - ) - - for (i in 1:length(connectionDetailsList)) { - connectionDetails <- connectionDetailsList[[i]]$connectionDetails - dbms <- connectionDetailsList[[i]]$connectionDetails$dbms - workDatabaseSchema <- connectionDetailsList[[i]]$workDatabaseSchema - cdmDatabaseSchema <- connectionDetailsList[[i]]$cdmDatabaseSchema - tempEmulationSchema <- connectionDetailsList[[i]]$tempEmulationSchema - cohortTableNames <- connectionDetailsList[[i]]$cohortTableNames - studyRootFolder <- file.path(tempDir, "EunomiaTestStudy", dbms) - workFolder <- file.path(studyRootFolder, "work_folder") - resultsFolder <- file.path(studyRootFolder, "results_folder") - scriptFolder <- file.path(studyRootFolder, "script_folder") - - message("************* Running Strategus on ", dbms, " *************") - - # Using a named and secured keyring - Strategus::storeConnectionDetails( - connectionDetails = connectionDetails, - connectionDetailsReference = dbms, - keyringName = keyringName - ) - - resultsConnectionDetailsReference <- NULL - resultsDatabaseSchema <- NULL - - # Only run this code if we're testing on SQLite - if (dbms == "sqlite") { - resultsConnectionDetailsReference <- "result-store" - resultsDatabaseSchema <- "main" - Strategus::storeConnectionDetails( - connectionDetails, - resultsConnectionDetailsReference, - keyringName = keyringName - ) - resultsExecutionSettings <- Strategus::createResultsExecutionSettings( - resultsConnectionDetailsReference = resultsConnectionDetailsReference, - resultsDatabaseSchema = resultsDatabaseSchema, - workFolder = workFolder, - resultsFolder = resultsFolder - ) - Strategus::createResultDataModels( - analysisSpecifications = analysisSpecifications, - executionSettings = resultsExecutionSettings, - keyringName = keyringName - ) - } - - executionSettings <- createCdmExecutionSettings( - connectionDetailsReference = dbms, - workDatabaseSchema = workDatabaseSchema, - cdmDatabaseSchema = cdmDatabaseSchema, - tempEmulationSchema = tempEmulationSchema, - cohortTableNames = cohortTableNames, - workFolder = workFolder, - resultsFolder = resultsFolder, - minCellCount = 5, - resultsDatabaseSchema = resultsDatabaseSchema, - resultsConnectionDetailsReference = resultsConnectionDetailsReference - ) - - if (!dir.exists(studyRootFolder)) { - dir.create(studyRootFolder, recursive = TRUE) - } - ParallelLogger::saveSettingsToJson( - object = executionSettings, - file.path(studyRootFolder, "eunomiaExecutionSettings.json") - ) - - executionSettings <- ParallelLogger::loadSettingsFromJson( - fileName = file.path(studyRootFolder, "eunomiaExecutionSettings.json") - ) - - Strategus::execute( - analysisSpecifications = analysisSpecifications, - executionSettings = executionSettings, - executionScriptFolder = scriptFolder, - keyringName = keyringName - ) - - expect_true(file.exists(file.path(resultsFolder, "TestModule1_1", "done"))) - } -}) - -test_that("Execute on Oracle stops if table names exceed length limit", { - sqlRenderTempEmulationSchema <- getOption("sqlRenderTempEmulationSchema", default = "") - options(sqlRenderTempEmulationSchema = "some_schema") - on.exit(options(sqlRenderTempEmulationSchema = sqlRenderTempEmulationSchema)) - - Sys.setenv("STRATEGUS_KEYRING_PASSWORD" = keyringPassword) - createKeyringForUnitTest(selectedKeyring = keyringName, selectedKeyringPassword = keyringPassword) - on.exit(deleteKeyringForUnitTest()) - - connectionDetails <- DatabaseConnector::createConnectionDetails( - dbms = "oracle" - ) - Strategus::storeConnectionDetails( - connectionDetails = connectionDetails, - connectionDetailsReference = "oracle-test", - keyringName = keyringName - ) - executionSettings <- Strategus::createCdmExecutionSettings( - connectionDetailsReference = "oracle-test", - workDatabaseSchema = "does_not_matter", - cdmDatabaseSchema = "does_not_matter", - cohortTableNames = CohortGenerator::getCohortTableNames("some_really_long_table_name_for_testing_that_oracle_throws_a_warning"), - workFolder = file.path(tempDir, "work_folder"), - resultsFolder = file.path(tempDir, "results_folder"), - minCellCount = 5 - ) - - analysisSpecifications <- ParallelLogger::loadSettingsFromJson( - fileName = system.file("testdata/unitTestAnalysisSpecification.json", - package = "Strategus" - ) - ) - - expect_error( - Strategus::execute( - analysisSpecifications = analysisSpecifications, - executionSettings = executionSettings, - keyringName = keyringName - ) - ) -}) diff --git a/vignettes/CreatingAnalysisSpecification.Rmd b/vignettes/CreatingAnalysisSpecification.Rmd index 5ad08532..cc195865 100644 --- a/vignettes/CreatingAnalysisSpecification.Rmd +++ b/vignettes/CreatingAnalysisSpecification.Rmd @@ -38,17 +38,12 @@ This walk through will show how to use `Strategus` to define an analysis specifi ## Setting up your R environment -To start, we must install the [HADES](https://ohdsi.github.io/Hades/) libraries in order to create the settings for the analysis specification. The following script will install the necessary HADES packages for this vignette. - -```{r, eval=FALSE} -# Install correct versions of HADES packages -remotes::install_github("ohdsi/CohortGenerator", ref = "v0.9.0") -remotes::install_github("ohdsi/CohortDiagnostics", ref = "v3.2.5") -remotes::install_github("ohdsi/Characterization", ref = "v0.2.0") -remotes::install_github("ohdsi/CohortIncidence", ref = "v3.3.0") -remotes::install_github("ohdsi/CohortMethod", ref = "v5.3.0") -remotes::install_github("ohdsi/SelfControlledCaseSeries", ref = "v5.2.0") -remotes::install_github("ohdsi/PatientLevelPrediction", ref = "v6.3.6") +Use `renv` and the [renv.lock](https://github.com/ohdsi-studies/StrategusStudyRepoTemplate/blob/main/renv.lock) from the Strategus study template to set up your R environment. This is done by copying the `renv.lock` file into the root of a new project and the restore of the environment is done by calling [renv::restore()](https://rstudio.github.io/renv/reference/restore.html). This will ensure that you have all of the R dependencies including the OHDSI HADES libraries and Strategus. The following code will download the renv.lock file to your machine, install `renv` and restore the R environment: + +```{r results='hide', eval=FALSE} +download.file("https://github.com/ohdsi-studies/StrategusStudyRepoTemplate/blob/main/renv.lock") +install.packages("renv") +renv::restore() ``` ## Cohorts for the study @@ -56,63 +51,46 @@ remotes::install_github("ohdsi/PatientLevelPrediction", ref = "v6.3.6") To start, we'll need to define cohorts and negative control outcomes to use in our example analysis specification. We've included the cohorts and negative control outcomes in the `Strategus` package for this example and the code below will load them for use when assembling the analysis specification. ```{r, results='hide', eval=FALSE} -library(CohortGenerator) -cohortDefinitionSet <- getCohortDefinitionSet( +cohortDefinitionSet <- CohortGenerator::getCohortDefinitionSet( settingsFileName = "testdata/Cohorts.csv", jsonFolder = "testdata/cohorts", sqlFolder = "testdata/sql", packageName = "Strategus" ) -ncoCohortSet <- readCsv(file = system.file("testdata/negative_controls_concept_set.csv", +ncoCohortSet <- CohortGenerator::readCsv(file = system.file("testdata/negative_controls_concept_set.csv", package = "Strategus" )) ``` -### Cohort Definitions & Negative Control Outcomes - -This is the list of cohort definitions we will use when assembling the analysis specification for Strategus. - -```{r eval=FALSE} -kable(cohortDefinitionSet[, c("cohortId", "cohortName")]) -``` - -And the negative control outcomes when performing empirical calibration. - -```{r eval=FALSE} -kable(ncoCohortSet) -``` - - # Assembling HADES modules The building blocks of the `Strategus` analysis specification are HADES modules. For purposes of this walk through, a module is a specific analytic task you would like to perform. As shown in the subsequent sections, the high-level pattern for using a module consists of: -1. Download the module's settings function. -2. Create the module specifications using the settings function(s) from the module -3. Compose the analysis pipeline from one or more module settings +1. Instantiate the module object. For example, CohortGenerator's module is created using: `cg <- CohortGeneratorModule$new()` +2. Create the module specifications using the settings function(s) from the module. See [the module list](docs/reference/index.html#hades-modules) for more details. +3. Compose the analysis pipeline from one or more module settings. ## CohortGenerator Module Settings -The following code downloads the settings functions from the `CohortGeneratorModule` which then activates some additional functions we can use for creating the analysis specification. In the analysis specification, we will add the cohort definitions and negative control outcomes to the `sharedResources` section since these elements may be used by any of the HADES modules. To do this, we will use the `createCohortSharedResourceSpecifications` and `createNegativeControlOutcomeCohortSharedResourceSpecifications` functions respectively. In addition, we will use the `cohortGeneratorModuleSpecifications` function to specify the cohort generation settings. +The following code instantiates a new CohortGenerator module `cgModule`. `cgModule` then exposes functions we can use for creating the module specifications to add to the analysis specification. In the analysis specification, we will add the cohort definitions and negative control outcomes to the `sharedResources` section since these elements may be used by any of the HADES modules. To do this, we will use the `createCohortSharedResourceSpecifications` and `createNegativeControlOutcomeCohortSharedResourceSpecifications` functions of the CohortGenerator module. In addition, we will use the `createModuleSpecifications` function to specify the cohort generation settings. ```{r eval=FALSE} -source("https://raw.githubusercontent.com/OHDSI/CohortGeneratorModule/v0.4.1/SettingsFunctions.R") +cgModule <- CohortGeneratorModule$new() # Create the cohort definition shared resource element for the analysis specification -cohortDefinitionSharedResource <- createCohortSharedResourceSpecifications( +cohortDefinitionSharedResource <- cgModule$createCohortSharedResourceSpecifications( cohortDefinitionSet = cohortDefinitionSet ) # Create the negative control outcome shared resource element for the analysis specification -ncoSharedResource <- createNegativeControlOutcomeCohortSharedResourceSpecifications( +ncoSharedResource <- cgModule$createNegativeControlOutcomeCohortSharedResourceSpecifications( negativeControlOutcomeCohortSet = ncoCohortSet, occurrenceType = "all", detectOnDescendants = TRUE ) # Create the module specification -cohortGeneratorModuleSpecifications <- createCohortGeneratorModuleSpecifications( - incremental = TRUE, +cohortGeneratorModuleSpecifications <- cgModule$createModuleSpecifications( generateStats = TRUE ) ``` @@ -122,8 +100,8 @@ cohortGeneratorModuleSpecifications <- createCohortGeneratorModuleSpecifications The following code creates the `cohortDiagnosticsModuleSpecifications` to run cohort diagnostics on the cohorts in the study. ```{r eval=FALSE} -source("https://raw.githubusercontent.com/OHDSI/CohortDiagnosticsModule/v0.2.0/SettingsFunctions.R") -cohortDiagnosticsModuleSpecifications <- createCohortDiagnosticsModuleSpecifications( +cdModule <- CohortDiagnosticsModule$new() +cohortDiagnosticsModuleSpecifications <- cdModule$createModuleSpecifications( runInclusionStatistics = TRUE, runIncludedSourceConcepts = TRUE, runOrphanConcepts = TRUE, @@ -132,8 +110,7 @@ cohortDiagnosticsModuleSpecifications <- createCohortDiagnosticsModuleSpecificat runBreakdownIndexEvents = TRUE, runIncidenceRate = TRUE, runCohortRelationship = TRUE, - runTemporalCohortCharacterization = TRUE, - incremental = FALSE + runTemporalCohortCharacterization = TRUE ) ``` @@ -142,38 +119,37 @@ cohortDiagnosticsModuleSpecifications <- createCohortDiagnosticsModuleSpecificat The following code creates the `cohortIncidenceModuleSpecifications` to perform an incidence rate analysis for the target cohorts and outcome in this study. ```{r eval=FALSE} -source("https://raw.githubusercontent.com/OHDSI/CohortIncidenceModule/v0.4.1/SettingsFunctions.R") -library(CohortIncidence) +ciModule <- CohortIncidenceModule$new() targets <- list( - createCohortRef(id = 1, name = "Celecoxib"), - createCohortRef(id = 2, name = "Diclofenac"), - createCohortRef(id = 4, name = "Celecoxib Age >= 30"), - createCohortRef(id = 5, name = "Diclofenac Age >= 30") + CohortIncidence::createCohortRef(id = 1, name = "Celecoxib"), + CohortIncidence::createCohortRef(id = 2, name = "Diclofenac"), + CohortIncidence::createCohortRef(id = 4, name = "Celecoxib Age >= 30"), + CohortIncidence::createCohortRef(id = 5, name = "Diclofenac Age >= 30") ) -outcomes <- list(createOutcomeDef(id = 1, name = "GI bleed", cohortId = 3, cleanWindow = 9999)) +outcomes <- list(CohortIncidence::createOutcomeDef(id = 1, name = "GI bleed", cohortId = 3, cleanWindow = 9999)) tars <- list( - createTimeAtRiskDef(id = 1, startWith = "start", endWith = "end"), - createTimeAtRiskDef(id = 2, startWith = "start", endWith = "start", endOffset = 365) + CohortIncidence::createTimeAtRiskDef(id = 1, startWith = "start", endWith = "end"), + CohortIncidence::createTimeAtRiskDef(id = 2, startWith = "start", endWith = "start", endOffset = 365) ) -analysis1 <- createIncidenceAnalysis( +analysis1 <- CohortIncidence::createIncidenceAnalysis( targets = c(1, 2, 4, 5), outcomes = c(1), tars = c(1, 2) ) -irDesign <- createIncidenceDesign( +irDesign <- CohortIncidence::createIncidenceDesign( targetDefs = targets, outcomeDefs = outcomes, tars = tars, analysisList = list(analysis1), - strataSettings = createStrataSettings( + strataSettings = CohortIncidence::createStrataSettings( byYear = TRUE, byGender = TRUE ) ) -cohortIncidenceModuleSpecifications <- createCohortIncidenceModuleSpecifications( +cohortIncidenceModuleSpecifications <- ciModule$createModuleSpecifications( irDesign = irDesign$toList() ) ``` @@ -184,19 +160,10 @@ The following code creates the `characterizationModuleSpecifications` to perform ```{r eval=FALSE} -source("https://raw.githubusercontent.com/OHDSI/CharacterizationModule/v0.6.0/SettingsFunctions.R") -characterizationModuleSpecifications <- createCharacterizationModuleSpecifications( +cModule <- CharacterizationModule$new() +characterizationModuleSpecifications <- cModule$createModuleSpecifications( targetIds = c(1, 2), - outcomeIds = 3, - covariateSettings = FeatureExtraction::createDefaultCovariateSettings(), - dechallengeStopInterval = 30, - dechallengeEvaluationWindow = 30, - timeAtRisk = data.frame( - riskWindowStart = c(1, 1), - startAnchor = c("cohort start", "cohort start"), - riskWindowEnd = c(0, 365), - endAnchor = c("cohort end", "cohort end") - ) + outcomeIds = 3 ) ``` @@ -206,11 +173,10 @@ characterizationModuleSpecifications <- createCharacterizationModuleSpecificatio The following code creates the `cohortMethodModuleSpecifications` to perform a comparative cohort analysis for this study. ```{r eval=FALSE} -library(CohortMethod) -source("https://raw.githubusercontent.com/OHDSI/CohortMethodModule/v0.3.1/SettingsFunctions.R") +cmModule <- CohortMethodModule$new() negativeControlOutcomes <- lapply( X = ncoCohortSet$cohortId, - FUN = createOutcome, + FUN = CohortMethod::createOutcome, outcomeOfInterest = FALSE, trueEffectSize = 1, priorOutcomeLookback = 30 @@ -218,7 +184,7 @@ negativeControlOutcomes <- lapply( outcomesOfInterest <- lapply( X = 3, - FUN = createOutcome, + FUN = CohortMethod::createOutcome, outcomeOfInterest = TRUE ) @@ -296,7 +262,7 @@ cmAnalysisList <- list(cmAnalysis1, cmAnalysis2) analysesToExclude <- NULL -cohortMethodModuleSpecifications <- createCohortMethodModuleSpecifications( +cohortMethodModuleSpecifications <- cmModule$createModuleSpecifications( cmAnalysisList = cmAnalysisList, targetComparatorOutcomesList = targetComparatorOutcomesList, analysesToExclude = analysesToExclude @@ -306,11 +272,10 @@ cohortMethodModuleSpecifications <- createCohortMethodModuleSpecifications( ## SelfControlledCaseSeries Module Settings -The following code creates the `cohortMethodModuleSpecifications` to perform a comparative cohort analysis for this study. +The following code creates the `sccsModuleSpecifications` to perform a self-controlled case series analysis for this study. ```{r eval=FALSE} -library(SelfControlledCaseSeries) -source("https://raw.githubusercontent.com/OHDSI/SelfControlledCaseSeriesModule/v0.5.0/SettingsFunctions.R") +sccsModule <- SelfControlledCaseSeriesModule$new() # Exposures-outcomes ----------------------------------------------------------- negativeControlOutcomeIds <- ncoCohortSet$cohortId @@ -320,15 +285,15 @@ exposureOfInterestIds <- c(1, 2) exposuresOutcomeList <- list() for (exposureOfInterestId in exposureOfInterestIds) { for (outcomeOfInterestId in outcomeOfInterestIds) { - exposuresOutcomeList[[length(exposuresOutcomeList) + 1]] <- createExposuresOutcome( + exposuresOutcomeList[[length(exposuresOutcomeList) + 1]] <- SelfControlledCaseSeries::createExposuresOutcome( outcomeId = outcomeOfInterestId, - exposures = list(createExposure(exposureId = exposureOfInterestId)) + exposures = list(SelfControlledCaseSeries::createExposure(exposureId = exposureOfInterestId)) ) } for (negativeControlOutcomeId in negativeControlOutcomeIds) { - exposuresOutcomeList[[length(exposuresOutcomeList) + 1]] <- createExposuresOutcome( + exposuresOutcomeList[[length(exposuresOutcomeList) + 1]] <- SelfControlledCaseSeries::createExposuresOutcome( outcomeId = negativeControlOutcomeId, - exposures = list(createExposure(exposureId = exposureOfInterestId, trueEffectSize = 1)) + exposures = list(SelfControlledCaseSeries::createExposure(exposureId = exposureOfInterestId, trueEffectSize = 1)) ) } } @@ -409,7 +374,7 @@ sccsAnalysis1 <- SelfControlledCaseSeries::createSccsAnalysis( sccsAnalysisList <- list(sccsAnalysis1) # SCCS module specs ------------------------------------------------------------ -sccsModuleSpecifications <- creatSelfControlledCaseSeriesModuleSpecifications( +sccsModuleSpecifications <- sccsModule$createModuleSpecifications( sccsAnalysisList = sccsAnalysisList, exposuresOutcomeList = exposuresOutcomeList, combineDataFetchAcrossOutcomes = FALSE @@ -418,10 +383,10 @@ sccsModuleSpecifications <- creatSelfControlledCaseSeriesModuleSpecifications( ## PatientLevelPrediction Module Settings -The following code creates the `plpModuleSpecifications` to perform a self-controlled case series analysis for this study. +The following code creates the `plpModuleSpecifications` to perform a patient-level prediction analysis for this study. ```{r eval=FALSE} -source("https://raw.githubusercontent.com/OHDSI/PatientLevelPredictionModule/v0.3.0/SettingsFunctions.R") +plpModule <- PatientLevelPredictionModule$new() makeModelDesignSettings <- function(targetId, outcomeId, popSettings, covarSettings) { invisible(PatientLevelPrediction::createModelDesign( @@ -463,7 +428,9 @@ for (i in 1:length(exposureOfInterestIds)) { } } -plpModuleSpecifications <- createPatientLevelPredictionModuleSpecifications(modelDesignList = modelDesignList) +plpModuleSpecifications <- plpModule$createModuleSpecifications( + modelDesignList = modelDesignList +) ``` # Strategus Analysis Specifications diff --git a/vignettes/CreatingModules.Rmd b/vignettes/CreatingModules.Rmd deleted file mode 100644 index ce93dabc..00000000 --- a/vignettes/CreatingModules.Rmd +++ /dev/null @@ -1,139 +0,0 @@ ---- -title: "Creating Strategus Modules" -author: "Anthony G. Sena" -date: "`r Sys.Date()`" -output: - pdf_document: - number_sections: yes - toc: yes - html_document: - number_sections: yes - toc: yes -vignette: > - %\VignetteEngine{knitr::rmarkdown} - %\VignetteIndexEntry{Creating Strategus Module} - %\VignetteEncoding{UTF-8} ---- - -```{r setup, include=FALSE} -knitr::opts_chunk$set(echo = TRUE) -skeletonFolder <- ifelse(basename(getwd()) == "vignettes", - "module_skeleton", - file.path("vignettes", "module_skeleton") -) -``` - -# Background - -This document aims to document the steps necessary to create analytic module that is compatible with [Strategus](https://github.com/OHDSI/Strategus). Please treat this document as a **work in progress** as Strategus is still under development. - - -# Getting Started - -A Strategus analytic module is an R Project that uses [renv](https://rstudio.github.io/renv/index.html). **NOTE**: Please make sure you are using renv > 1.0.0 when creating a new analytic module to make sure it is compatible with Strategus. - -A Strategus module will contain the following files: - -```{r comment='', echo=FALSE} -fs::dir_tree(skeletonFolder, recurse = TRUE) -``` -Here we will detail how each file is used by Strategus and what is required in the contents of the file. - -## Creating YourProjectModule.Rproj and activating `renv` - -This is the R Project (.Rproj) file for your module and should end in "Module". You may create this as a standard R Project via RStudio. Once the project is created, please use `renv::init()` to set up the `renv` folder as shown above. This will create the necessary `.RProfile` in the root of your project and the `renv` subfolder with the necessary R code for `renv`'s operations. - -## README.md - -This is a standard README markdown file that describes the module. - -## NEWS.md - -This is a standard NEWS markdown file that is a change log for your module. See [this post](https://blog.r-hub.io/2020/05/08/pkg-news/) for more information. - -## MetaData.json - -MetaData.json holds information that describes the module and its dependencies: - -```{r comment='', echo=FALSE} -cat(readLines(file.path(skeletonFolder, "MetaData.json")), sep = "\n") -``` -To detail the contents of the JSON file: - -- **Name**: The name of the module -- **Version**: The version of the module. This should have a corresponding git tag in the repository when the module is released otherwise Strategus will not be able to download it. -- **Dependencies**: A list of modules that are required to have successfully executed **BEFORE** this module is executed. If there are no dependencies, leave this as an empty array `[]`. -- **TablePrefix**: The prefix to use when creating the results tables in the `resultsDataModelSpecification.csv`. Please see [Main.R] for more information on how this value is used. - -## Main.R - -This file holds the main executable for your module. This file must contain a function called `execute(jobContext)`. - -```{r comment='', echo=FALSE} -cat(readLines(file.path(skeletonFolder, "Main.R")), sep = "\n") -``` - -As shown in the code above, your `execute(jobContext)` should handle: validating the `jobContext` object to ensure it has all of the information necessary for your code to function, a section to execute the analytics and finally code to assemble the output. Here we will describe the requirements for the way in which your module must output its results: - -- A single .ZIP file is created that holds all of the result files as described below. -- Output files are required to be in .CSV format. Use CohortGenerator v0.5.0 or higher which contains a helper function for `writeCsv()` which will ensure your output is formatted properly. For more information, please see: https://ohdsi.github.io/CohortGenerator/reference/writeCsv.html. **IMPORTANT:** File names _must_ correspond to the table names that are specified in the `resultsModuleSpecification.csv`. -- You must include a file named `resultsModuleSpecification.csv` in your output directory. The format of this file is as follows: - -```{r comment='', echo=FALSE} -cat(readLines(file.path(skeletonFolder, "resources", "resultsDataModelSpecification.csv")), sep = "\n") -``` -The `resultsModuleSpecification.csv` has the following columns: - -- **table_name**: The table name to use to hold the data. -- **column_name**: The column name in the table. -- **data_type**: The data type for the column. See https://www.postgresql.org/docs/current/datatype.html for examples. -- **is_required**: Will this column allow for NULL values? Yes/No -- **primary_key**: Is this column part of the table's primary key? Yes/No - -## SettingsFunctions.R - -This file contains one or more functions required to create the module settings for use in Strategus. We plan to later remove this requirement when we can describe the module specification using the [OpenAPI 3.0 Specification](https://swagger.io/specification/). For now, your module should contain a function similar to the following: - -```{r comment='', echo=FALSE} -cat(readLines(file.path(skeletonFolder, "SettingsFunctions.R")), sep = "\n") -``` - -As shown above, this example comes from the `CohortGeneratorModule` and the function name reflects the fact that the function will create the settings used to dictate the behavior of the module. The parameters of the function will differ based on the requirements of your module - if there are choices to be made when running your module, you should include these as parameters to your module specification function. - -Internal to the function above, the formal parameters to the function are used to construct a `list()` named `analysis` which holds the analysis settings. Next the `MetaData.json` file is used to obtain the module name/version for inclusion in the `specifications` list. The `specifications` list contains the `remoteRepo` and `remoteUsername` properties to indicate where your module is stored on GitHub. Finally, we set the `class()` of the `specifications` object to `c("CohortGeneratorModuleSpecifications", "ModuleSpecifications")`. For your module, you will want to substitute `"CohortGeneratorModuleSpecifications"` for the name of your module and retain the `"ModuleSpecifications"` in the vector. - -The following JSON fragment shows how the output of `createCohortGeneratorModuleSpecifications()` is used in the `moduleSpecifications` section of the overall analysis settings JSON for Strategus: - -```{r comment='', echo=FALSE} -cat(readLines(file.path(skeletonFolder, "resources", "exampleAnalysisSpecifications.json")), sep = "\n") -``` - -## renv.lock - -Each module will make use of [renv](https://rstudio.github.io/renv/articles/renv.html) to capture its R package dependencies. Furthermore, Strategus will make use of the `renv` settings in your module to create a run-time environment when executing your module to ensure all of the necessary dependencies are available to your module. - -It is recommended to use the HADES-wide renv.lock file which is available at https://github.com/OHDSI/Hades/blob/main/hadesWideReleases. Find the most recent release based on the folder name and copy the `renv.lock` file into the root of your module project. - -If you need to install additional dependencies for your project, use `renv::record()` to record it in the lock file. - -# Extra files - -It is advisable to add an `extras` folder to your project to include other useful files for managing and testing your module. We'll detail those files here: - -## ModuleMaintenance.R - -This file is used to store utility functions for your module, such as the code mentioned earlier for generating the [renv.lock] file. Here is an example of the contents of ModuleMaintenance.R: - -```{r comment='', echo=FALSE} -cat(readLines(file.path(skeletonFolder, "extras", "ModuleMaintenance.R")), sep = "\n") -``` -## Test Files - -The following file is used to create a test jobContext for use in the `execute(jobContext)` as described in [Main.R]: - -https://github.com/OHDSI/CohortGeneratorModule/blob/main/extras/test/CreateJobContext.R - -And the following file is used to create a test harness for running your module: - -https://github.com/OHDSI/CohortGeneratorModule/blob/main/extras/test/TestModuleStandalone.R - diff --git a/vignettes/ExecuteStrategus.Rmd b/vignettes/ExecuteStrategus.Rmd index c1f5c996..5328e21f 100644 --- a/vignettes/ExecuteStrategus.Rmd +++ b/vignettes/ExecuteStrategus.Rmd @@ -20,52 +20,30 @@ always_allow_html: true knitr::opts_chunk$set(echo = TRUE) ``` -A Strategus study is defined by *analysis specifications*. These specifications describe which modules to run, with which settings. The 'Creating Analysis Specification' vignette describes how to create analysis specifications. In this vignette, we demonstrate how to run a study once it is specified. +A Strategus study is defined by *analysis specifications*. These specifications describe which modules to run, with which settings. The [Creating Analysis Specification](CreatingAnalysisSpecification.Rmd) vignette describes how to create analysis specifications. In this vignette, we demonstrate how to run a study defined by an analysis specification. # Creating execution settings -In addition to analysis specifications, Strategus also requires *execution settings*. The execution settings specify how the study should be executed in a specific environment, for example how to connect to a database, and what local folders to use. Many Strategus studies run against data in the OMOP Common Data Model (CDM), and in this vignette we focus on this type of studies. (Other studies, such as meta-analyses, may run against results data instead). In this example, we will make use of the [Eunomia](https://github.com/ohdsi/eunomia) data set which is an OMOP CDM with simulated data used for example purposes. When running a study against your own CDM data, you will need to specify the database connection details for your environment. Execution settings for studies against the CDM can be created using `createCdmExecutionSettings()`. +Strategus execution requires you to specify *execution settings*. The execution settings specify how the study should be executed in a specific environment, for example how to connect to a database, and what local folders to use. Many Strategus studies run against data in the OMOP Common Data Model (CDM), and in this vignette we focus on this type of studies. (Other studies, such as meta-analyses, may run against results data instead). In this example, we will make use of the [Eunomia](https://github.com/ohdsi/eunomia) data set which is an OMOP CDM with simulated data used for example purposes. When running a study against your own CDM data, you will need to specify the database connection details for your environment. Execution settings for studies against the CDM can be created using `createCdmExecutionSettings()`. -Note that Strategus uses [keyring](https://r-lib.github.io/keyring/index.html) to store the connection information securely, so that sensitive information is not stored directly in the `executionSettings` variable. +## Creating the connection details -## Storing the connection details - -In this example, we first create a `connectionDetails` reference for Eunomia. In your environment, the `connectionDetails` would be specific to your OMOP CDM connection. +In this example, we first create a `connectionDetails` for Eunomia. In your environment, the `connectionDetails` would be specific to your OMOP CDM. Please see the [DatabaseConnector](https://ohdsi.github.io/DatabaseConnector/articles/Connecting.html) package documentation for more details. ```{r eval=FALSE} library(Strategus) -folder <- "c:/strategus" -``` -```{r echo=FALSE, warning=FALSE, message=FALSE} -library(Strategus) -outputFolder <- tempfile("vignetteFolder") -dir.create(outputFolder) -``` - -```{r} -# Note: specifying the `databaseFile` so the Eunomia database is permanent, not temporary: -connectionDetails <- Eunomia::getEunomiaConnectionDetails( - databaseFile = file.path(outputFolder, "cdm.sqlite") -) -``` - -Next we will use `Strategus` to store the connection details and provide a `connectionDetailsReference` that Strategus will use to look up the connection details. - -```{r eval=FALSE} -storeConnectionDetails( - connectionDetails = connectionDetails, - connectionDetailsReference = "eunomia" -) +library(Eunomia) +connectionDetails <- getEunomiaConnectionDetails() ``` -Note that we only need to store connection details once. We can re-use these details in all future studies. ## Creating an execution settings object -Next, we will use `Strategus` to create the CDM execution settings. The `connectionDetailsReference` refers to the connection details we stored earlier: +Next, we will use `Strategus` to create the CDM execution settings: -```{r} +```{r eval=FALSE} +outputFolder <- tempfile("vignetteFolder") +dir.create(outputFolder) executionSettings <- createCdmExecutionSettings( - connectionDetailsReference = "eunomia", workDatabaseSchema = "main", cdmDatabaseSchema = "main", cohortTableNames = CohortGenerator::getCohortTableNames(), @@ -77,7 +55,7 @@ executionSettings <- createCdmExecutionSettings( Finally, we can write out the execution settings to the file system to capture this information. -```{r} +```{r eval=FALSE} ParallelLogger::saveSettingsToJson( object = executionSettings, file.path(outputFolder, "eunomiaExecutionSettings.json") @@ -86,23 +64,11 @@ ParallelLogger::saveSettingsToJson( # Executing the study -## Specifying the instantiated modules folder - -Strategus studies use modules to perform the analytics, and each module has a version. Different studies can use the same modules, but a single study can only use one version of a particular module. These modules need to be instantiated before they can be executed, a sometimes time-consuming task. We must specify a global location where these modules will be instantiated so that, once a module is instantiated, it can be used in all future studies: +For this study, we will use an analysis specifications created for testing `Strategus`, and the execution settings we created earlier: ```{r eval=FALSE} -Sys.setenv("INSTANTIATED_MODULES_FOLDER" = "c:/strategus/modules") -``` - -We recommend adding this environmental variable to your `.renviron` file, so it is always set. - -## Running the study - -For this study, we will use analysis specifications created elsewhere, and the execution settings we created earlier: - -```{r} analysisSpecifications <- ParallelLogger::loadSettingsFromJson( - fileName = system.file("testdata/analysisSpecification.json", + fileName = system.file("testdata/cdmModulesAnalysisSpecifications.json", package = "Strategus" ) ) @@ -116,13 +82,16 @@ And finally we execute the study: ```{r eval=FALSE} execute( + connectionDetails = connectionDetails, analysisSpecifications = analysisSpecifications, - executionSettings = executionSettings, - executionScriptFolder = file.path(outputFolder, "script_folder") + executionSettings = executionSettings ) ``` -This will first instantiate all the modules if they haven't already been instantiated, and will then execute each module in sequence according to the analysis specifications. The results will appear in subfolders of the 'results_folder', as specified in the execution settings. -```{r echo=FALSE} +This will first instantiate all the modules if they haven't already been instantiated, and will then execute each module in sequence according to the analysis specifications. The results will appear in sub folders of the 'results_folder', as specified in the execution settings. + +Once the analysis is complete, you can review the study results. For more information see the [Working with Results](WorkingWithResults.html) article. + +```{r eval=F, echo=FALSE} unlink(outputFolder, recursive = TRUE) ``` diff --git a/vignettes/IntroductionToStrategus.Rmd b/vignettes/IntroductionToStrategus.Rmd index c8da5728..f70ffade 100644 --- a/vignettes/IntroductionToStrategus.Rmd +++ b/vignettes/IntroductionToStrategus.Rmd @@ -16,21 +16,20 @@ knitr::opts_chunk$set(echo = TRUE, warning = FALSE) # Introduction to Strategus -The `Strategus` package is a new approach for coordinating and executing analytics using HADES modules. The goal is to have OHDSI network sites install `Strategus` and exchange an analysis specification in JSON format to execute a network study. The analysis specification will capture all of the design choices that pertain to the methods used in a given study. The analysis specification format aims to allow for combining different HADES modules together as a pipeline to execute a study. In addition, the analysis specification makes use of specific HADES module versions to clearly state which modules are required to run the study with the aim to make the execution and results reproducible. +The `Strategus` package is a new approach for coordinating and executing analytics using HADES modules. The goal is to have OHDSI network sites install `Strategus` and exchange an analysis specification in JSON format to execute a network study. The analysis specification will capture all of the design choices that pertain to the methods used in a given study. The analysis specification format aims to allow for combining different HADES modules together as a pipeline to execute a study. + +For more details on how Strategus is used as part of a network study, please see the [Strategus Study Repo Template](https://github.com/ohdsi-studies/StrategusStudyRepoTemplate). ## Using Strategus The high-level steps in using `Strategus` consists of the following: -1. Create the analysis specification for the study. This will include things like picking the cohorts for the study, the analyses to perform (i.e. Cohort Diagnostics, Comparative Cohort Study, etc) and the choices for each analysis. See [here](CreatingAnalysisSpecification.html) for more details. -2. Create the execution settings that specify how to connect to the OMOP CDM in your environment. See [here](CreateExecutionSettings.html) for more details. -3. Execute the study using `Strategus` which will require both the analysis specification and the execution settings in order to run the study and extract the results. See [here](ExecuteStrategus.html) for more details. -4. Upload the results and use Shiny to view the results _Coming Soon_. +1. Create the analysis specification for the study. This will include things like picking the cohorts for the study and to specify the analysis settings for each the HADES modules (i.e. Cohort Diagnostics, Comparative Cohort Study, etc). See the [Creating Analysis Specification](CreatingAnalysisSpecification.html) article for more details. +2. Create the execution settings that specify how to connect to the OMOP CDM in your environment and execute your study. See the [Execute Strategus](ExecuteStrategus.html) for more details. +3. Upload the results and use Shiny to view the results. See the [Working with Results](WorkingWithResults.html) for more details. ## What is a HADES module? -A HADES module aims to standardize the input and output produced by a HADES package. It also self-describes the R dependencies it needs to run properly via `Strategus`. - -From a technical perspective, a HADES module is a lightweight R script uses the `Strategus` JSON analysis specification to call one or more HADES packages to produce a standardized set of results. The HADES module contains an [renv lock file](https://github.com/rstudio/renv) which enumerates the module's R package dependencies. Taken together, the module provides a reproducible way to execute a step in an analysis by ensuring the proper dependencies are available along with the code that was used to execute the analysis. +A HADES module aims to standardize the input and output produced by a [HADES package](https://ohdsi.github.io/Hades/packageStatuses.html). Each HADES module contains a function to create the settings to carry out the analytic tasks. These module settings are then added to the analysis specification to build a pipeline of analytic tasks that span one or more modules. Each HADES module is responsible for writing results as comma-separated value (.csv) files. CSV output was purposely chosen to provide transparency for the results generated so that users of `Strategus` can review their results before providing them to a network study coordinator. In addition to the CSV results, each module will produce a `resultsDataModelSpecification.csv` which describes the data-definition language (DDL) to store the CSV results in a PostgreSQL database. The definition of the `resultsDataModelSpecification.csv` is described in more details in the [ResultModelManager documentation](https://ohdsi.github.io/ResultModelManager/articles/ExampleProject.html). Finally, each HADES module provides functions for creating the PostgreSQL results tables based on the `resultsDataModelSpecification.csv` and for uploading the CSV results to the results database. -For more information on how to create modules, see [here](CreatingModules.html) +From a technical perspective, a HADES module is an R6 class that accepts the `Strategus` JSON analysis specification to call one or more HADES packages to produce a standardized set of results. When used with [renv](https://rstudio.github.io/renv/), Strategus provides a reproducible way to execute each step in an analysis specification by ensuring the proper dependencies are available along with the code that was used to execute the analysis. diff --git a/vignettes/WorkingWithResults.Rmd b/vignettes/WorkingWithResults.Rmd new file mode 100644 index 00000000..6840811c --- /dev/null +++ b/vignettes/WorkingWithResults.Rmd @@ -0,0 +1,118 @@ +--- +title: "Working With Results" +author: "Anthony G. Sena" +date: "`r Sys.Date()`" +output: + pdf_document: + number_sections: yes + toc: yes + html_document: + number_sections: yes + toc: yes +vignette: > + %\VignetteEngine{knitr::rmarkdown} + %\VignetteIndexEntry{Working With Results} + %\VignetteEncoding{UTF-8} +always_allow_html: true +--- + +```{r setup, include=FALSE, echo=FALSE, warning=FALSE} +library(Strategus) +options(width = 200) +``` + +# Working With Results + +Once you have executed an analysis specification through `Strategus` you will want to review results and share them with a network study coordinator. This vignette will cover the ways in which you can work with results produced by Strategus. + +## Manual review + +Each HADES module in an analysis specification will write results in comma-separated value (csv) format to the file system in the `resultsFolder` specified in the execution settings. These files may be reviewed with your favorite text editor to ensure that any policies related to censoring for your data source are met before sharing with a network coordinator. + +## Reviewing results using R Shiny results viewer + +To review results produced by Strategus via the R Shiny, your results must be loaded into a PostgreSQL database. Strategus and the HADES modules provide a way to create the results database tables and upload the results. This guide assumes that you have access to a PostgreSQL instance with a database and schema called `study_results` and permission to create tables & upload results. + +### Creating the results data model + +In the code below, we start by creating the connection details to the PostgreSQL instance that we will use to create the results data model. Next, we'll create the `resultsDataModelSettings` to specify the schema to hold the results data model and the location where the Strategus results are stored on the file system. Finally, we'll create the results data model by passing in the `analysisSpecification` for the study which will detail which module's results tables to include in the results data model. + +```{r eval=F} +resultsConnectionDetails <- DatabaseConnector::createConnectionDetails( + dbms = "postgresql", + user = "user", + password = "password", + server = "127.0.0.1/strategus_results" +) + +resultsDataModelSettings <- Strategus::createResultsDataModelSettings( + resultsDatabaseSchema = "study_results", + resultsFolder = "path/to/results", +) + +Strategus::createResultDataModel( + analysisSpecifications = analysisSpecifications, + resultsDataModelSettings = resultsDataModelSettings, + resultsConnectionDetails = resultsConnectionDetails +) +``` + +**NOTE:**: The script above assumes you have set up the `study_results` schema before running this script. It also assumes that the `study_results` schema is empty. If you need to re-create the results data model for some reason, you will need to manually drop all of the tables and then you can re-use this script to create the tables. + +For more information on the tables and relationships in the results data model please see the [results data model documentation](https://ohdsi.github.io/Strategus/results-schema/index.html). + +### Uploading results + +We will use the same inputs from the `createResultDataModel` to call the `uploadResults` function to upload the results to the results database. + +```{r eval=F} +Strategus::uploadResults( + analysisSpecifications = analysisSpecifications, + resultsDataModelSettings = resultsDataModelSettings, + resultsConnectionDetails = resultsConnectionDetails +) +``` + + +### Reviewing results using R Shiny + +We will use the [ShinyAppBuilder](https://ohdsi.github.io/ShinyAppBuilder/) and [OhdsiShinyModules](https://ohdsi.github.io/OhdsiShinyModules/) to connect to the results database to review results. The code below is used to create a configuration that tells the Shiny results viewer which modules were used in the study and then it will launch the results viewer application and connect to the PostgreSQL database specified in the `resultsConnectionDetails` and display the results stored in the `study_results` schema. + +```{r eval=F} +library(ShinyAppBuilder) +library(OhdsiShinyModules) + +# ADD OR REMOVE MODULES TAILORED TO YOUR STUDY +shinyConfig <- initializeModuleConfig() |> + addModuleConfig( + createDefaultAboutConfig() + ) |> + addModuleConfig( + createDefaultDatasourcesConfig() + ) |> + addModuleConfig( + createDefaultCohortGeneratorConfig() + ) |> + addModuleConfig( + createDefaultCohortDiagnosticsConfig() + ) |> + addModuleConfig( + createDefaultCharacterizationConfig() + ) |> + addModuleConfig( + createDefaultPredictionConfig() + ) |> + addModuleConfig( + createDefaultEstimationConfig() + ) + +# now create the shiny app based on the config file and view the results +# based on the connection +ShinyAppBuilder::createShinyApp( + config = shinyConfig, + connectionDetails = resultsConnectionDetails, + resultDatabaseSettings = createDefaultResultDatabaseSettings(schema = "study_results"), + title = "Celecoxib vs. Diclofinac for the risk of GI Bleed", + studyDescription = "This study is showcasing the capabilities of running Strategus on Eunomia." +) +``` diff --git a/vignettes/module_skeleton/.Rprofile b/vignettes/module_skeleton/.Rprofile deleted file mode 100644 index 81b960f5..00000000 --- a/vignettes/module_skeleton/.Rprofile +++ /dev/null @@ -1 +0,0 @@ -source("renv/activate.R") diff --git a/vignettes/module_skeleton/Main.R b/vignettes/module_skeleton/Main.R deleted file mode 100644 index c2a13ee5..00000000 --- a/vignettes/module_skeleton/Main.R +++ /dev/null @@ -1,16 +0,0 @@ -execute <- function(jobContext) { - # VALIDATE THE jobContext - rlang::inform("Validating inputs") - - # YOUR VALIDATION CODE GOES HERE.... - - # EXECUTE THE ANALYTICS - rlang::inform("Executing") - - # YOUR EXECUTION CODE GOES HERE.... - - # ASSEMBLE AND .ZIP THE RESULTS - rlang::inform("Export data") - - # YOUR CODE GOES HERE.... -} diff --git a/vignettes/module_skeleton/MetaData.json b/vignettes/module_skeleton/MetaData.json deleted file mode 100644 index 0460d12d..00000000 --- a/vignettes/module_skeleton/MetaData.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "Name": "CohortGeneratorModule", - "Version": "0.0.1", - "Dependencies": ["SomePrerequisiteModule"], - "TablePrefix": "cg_" -} diff --git a/vignettes/module_skeleton/NEWS.md b/vignettes/module_skeleton/NEWS.md deleted file mode 100644 index 8fd5bcf9..00000000 --- a/vignettes/module_skeleton/NEWS.md +++ /dev/null @@ -1,4 +0,0 @@ -CohortGeneratorModule 0.0.1 -======================= - -Initial version \ No newline at end of file diff --git a/vignettes/module_skeleton/README.md b/vignettes/module_skeleton/README.md deleted file mode 100644 index 33382e3f..00000000 --- a/vignettes/module_skeleton/README.md +++ /dev/null @@ -1,50 +0,0 @@ -# CohortGeneratorModule - -# Introduction - -This R project contains functionality for generating cohorts using a JSON specification that is -under development. This module design then uses CohortGenerator and other OHDSI packages to generate -the cohorts based on the specification. - -# Example - -Please see the code located in `extras/CodeToRunModule.R` for an example of using the module. - -# Technology - -CohortGeneratorModule is an R project. - -# System requirements - -Requires R (version 4.1.3 or higher). - -# Getting Started - -1. Make sure your R environment is properly configured. This means that Java must be installed. See [these instructions](https://ohdsi.github.io/Hades/rSetup.html) for how to configure your R environment. - -2. TODO - need to describe in context of Strategus - - -# User Documentation - -Coming Soon - -# Support - -Please use the GitHub bug tracker - -# Contributing - -Read [here](https://ohdsi.github.io/Hades/contribute.html) how you can contribute to this package. - -# License - -CohortGeneratorModule is licensed under Apache License 2.0 - -# Development - -This package is being developed in RStudio. - -### Development status - -Beta diff --git a/vignettes/module_skeleton/SettingsFunctions.R b/vignettes/module_skeleton/SettingsFunctions.R deleted file mode 100644 index 252b62c5..00000000 --- a/vignettes/module_skeleton/SettingsFunctions.R +++ /dev/null @@ -1,18 +0,0 @@ -createCohortGeneratorModuleSpecifications <- function(incremental = TRUE, - generateStats = TRUE) { - analysis <- list() - for (name in names(formals(createCohortGeneratorModuleSpecifications))) { - analysis[[name]] <- get(name) - } - - checkmate::assert_file_exists("MetaData.json") - moduleInfo <- ParallelLogger::loadSettingsFromJson("MetaData.json") - - specifications <- list(module = moduleInfo$Name, - version = moduleInfo$Version, - remoteRepo = "github.com", - remoteUsername = "ohdsi", - settings = analysis) - class(specifications) <- c("CohortGeneratorModuleSpecifications", "ModuleSpecifications") - return(specifications) -} diff --git a/vignettes/module_skeleton/YourProjectModule.Rproj b/vignettes/module_skeleton/YourProjectModule.Rproj deleted file mode 100644 index eaa6b818..00000000 --- a/vignettes/module_skeleton/YourProjectModule.Rproj +++ /dev/null @@ -1,18 +0,0 @@ -Version: 1.0 - -RestoreWorkspace: Default -SaveWorkspace: Default -AlwaysSaveHistory: Default - -EnableCodeIndexing: Yes -UseSpacesForTab: Yes -NumSpacesForTab: 2 -Encoding: UTF-8 - -RnwWeave: Sweave -LaTeX: pdfLaTeX - -BuildType: Package -PackageUseDevtools: Yes -PackageInstallArgs: --no-multiarch --with-keep.source -PackageRoxygenize: rd,collate,namespace diff --git a/vignettes/module_skeleton/extras/CreateJobContextForTesting.R b/vignettes/module_skeleton/extras/CreateJobContextForTesting.R deleted file mode 100644 index 1ad1dac5..00000000 --- a/vignettes/module_skeleton/extras/CreateJobContextForTesting.R +++ /dev/null @@ -1,143 +0,0 @@ -# Create a job context for testing purposes -library(Strategus) -library(dplyr) -source("SettingsFunctions.R") - -# Generic Helpers ---------------------------- -getModuleInfo <- function() { - checkmate::assert_file_exists("MetaData.json") - return(ParallelLogger::loadSettingsFromJson("MetaData.json")) -} - -# Sample Data Helpers ---------------------------- -getSampleCohortDefintionSet <- function() { - sampleCohorts <- CohortGenerator::createEmptyCohortDefinitionSet() - cohortJsonFiles <- list.files(path = system.file("testdata/name/cohorts", package = "CohortGenerator"), full.names = TRUE) - for (i in 1:length(cohortJsonFiles)) { - cohortJsonFileName <- cohortJsonFiles[i] - cohortName <- tools::file_path_sans_ext(basename(cohortJsonFileName)) - cohortJson <- readChar(cohortJsonFileName, file.info(cohortJsonFileName)$size) - sampleCohorts <- rbind(sampleCohorts, data.frame( - cohortId = as.double(i), - cohortName = cohortName, - json = cohortJson, - sql = "", - stringsAsFactors = FALSE - )) - } - - # Add subsets to the cohort definition set - maleOnlySubsetOperators <- list( - CohortGenerator::createDemographicSubset( - name = "Gender == Male", - gender = 8507 - ) - ) - maleOnlySubsetDef <- CohortGenerator::createCohortSubsetDefinition( - name = "Males", - definitionId = 1, - subsetOperators = maleOnlySubsetOperators - ) - # Define a subset for males age 40+ - maleAgeBoundedSubsetOperators <- list( - CohortGenerator::createDemographicSubset( - name = "Gender == Male, Age 40+", - gender = 8507, - ageMin = 40 - ) - ) - maleAgeBoundedSubsetDef <- CohortGenerator::createCohortSubsetDefinition( - name = "Male, Age 40+", - definitionId = 2, - subsetOperators = maleAgeBoundedSubsetOperators - ) - - subsetDef1 <- CohortGenerator::createCohortSubsetDefinition( - name = "Celecoxib new users, male >= 18, any exposure to celecoxib", - definitionId = 3, - subsetOperators = list( - CohortGenerator::createCohortSubset( - name = "Restrict to those with prior celecoxib", - cohortIds = 1, - negate = FALSE, - cohortCombinationOperator = "all", - startWindow = CohortGenerator::createSubsetCohortWindow(-99999, 99999, "cohortStart"), - endWindow = CohortGenerator::createSubsetCohortWindow(-99999, 99999, "cohortStart") - ), - CohortGenerator::createLimitSubset( - name = "Earlist event", - priorTime = 365, - followUpTime = 1, - limitTo = "firstEver" - ), - CohortGenerator::createDemographicSubset( - name = "Male and age 18+", - ageMin = 18, - gender = 8507 - ) - ) - ) - - - sampleCohorts <- sampleCohorts %>% - CohortGenerator::addCohortSubsetDefinition(maleOnlySubsetDef) %>% - CohortGenerator::addCohortSubsetDefinition(maleAgeBoundedSubsetDef) %>% - CohortGenerator::addCohortSubsetDefinition(subsetDef1) - return(sampleCohorts) -} - -createCohortSharedResource <- function(cohortDefinitionSet = getSampleCohortDefintionSet()) { - sharedResource <- createCohortSharedResourceSpecifications(cohortDefinitionSet = cohortDefinitionSet) - return(sharedResource) -} - -createNegativeControlSharedResource <- function() { - negativeControlOutcomes <- readCsv(file = system.file("testdata/negativecontrols/negativecontrolOutcomes.csv", - package = "CohortGenerator", - mustWork = TRUE - )) - negativeControlOutcomes$cohortId <- negativeControlOutcomes$outcomeConceptId - createNegativeControlOutcomeCohortSharedResourceSpecifications( - negativeControlOutcomeCohortSet = negativeControlOutcomes, - occurrenceType = "all", - detectOnDescendants = FALSE - ) -} - -# Create CohortGeneratorModule settings --------------------------------------- -cohortGeneratorModuleSpecifications <- createCohortGeneratorModuleSpecifications( - incremental = FALSE, - generateStats = TRUE -) - -# Module Settings Spec ---------------------------- -analysisSpecifications <- createEmptyAnalysisSpecificiations() %>% - addSharedResources(createCohortSharedResource()) %>% - addSharedResources(createNegativeControlSharedResource()) %>% - addModuleSpecifications(cohortGeneratorModuleSpecifications) - -# executionSettings <- Strategus::createExecutionSettings( -executionSettings <- Strategus::createCdmExecutionSettings( - connectionDetailsReference = "dummy", - workDatabaseSchema = "main", - cdmDatabaseSchema = "main", - cohortTableNames = CohortGenerator::getCohortTableNames(cohortTable = "cohort"), - workFolder = "dummy", - resultsFolder = "dummy", - minCellCount = 5 -) - -# Job Context ---------------------------- -module <- "CohortGeneratorModule" -moduleIndex <- 1 -moduleExecutionSettings <- executionSettings -moduleExecutionSettings$workSubFolder <- "dummy" -moduleExecutionSettings$resultsSubFolder <- "dummy" -moduleExecutionSettings$databaseId <- 123 -jobContext <- list( - sharedResources = analysisSpecifications$sharedResources, - settings = analysisSpecifications$moduleSpecifications[[moduleIndex]]$settings, - moduleExecutionSettings = moduleExecutionSettings -) -saveRDS(jobContext, "tests/testJobContext.rds") -# ParallelLogger::saveSettingsToJson(analysisSpecifications, fileName = "extras/analysisSettings.json") diff --git a/vignettes/module_skeleton/extras/ModuleMaintenance.R b/vignettes/module_skeleton/extras/ModuleMaintenance.R deleted file mode 100644 index e5ee2791..00000000 --- a/vignettes/module_skeleton/extras/ModuleMaintenance.R +++ /dev/null @@ -1,14 +0,0 @@ -# Format and check code: -styler::style_dir() -OhdsiRTools::updateCopyrightYearFolder() -OhdsiRTools::findNonAsciiStringsInFolder() -devtools::spell_check() - -# Generate renv lock file and activate renv: -OhdsiRTools::createRenvLockFile( - rootPackage = "CohortGenerator", - includeRootPackage = TRUE, - mode = "description", - additionalRequiredPackages = c("checkmate", "CirceR") -) -renv::init() diff --git a/vignettes/module_skeleton/renv.lock b/vignettes/module_skeleton/renv.lock deleted file mode 100644 index 41386505..00000000 --- a/vignettes/module_skeleton/renv.lock +++ /dev/null @@ -1,321 +0,0 @@ -{ - "R" : { - "Version" : "4.1.3", - "Repositories" : [ - { - "Name" : "CRAN", - "URL" : "https://cloud.r-project.org" - } - ] - }, - "Packages" : { - "glue" : { - "Package" : "glue", - "Version" : "1.6.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "cli" : { - "Package" : "cli", - "Version" : "3.3.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "rlang" : { - "Package" : "rlang", - "Version" : "1.0.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "crayon" : { - "Package" : "crayon", - "Version" : "1.5.1", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "ellipsis" : { - "Package" : "ellipsis", - "Version" : "0.3.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "fansi" : { - "Package" : "fansi", - "Version" : "1.0.3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "lifecycle" : { - "Package" : "lifecycle", - "Version" : "1.0.1", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "magrittr" : { - "Package" : "magrittr", - "Version" : "2.0.3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "pkgconfig" : { - "Package" : "pkgconfig", - "Version" : "2.0.3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "utf8" : { - "Package" : "utf8", - "Version" : "1.2.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "vctrs" : { - "Package" : "vctrs", - "Version" : "0.4.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "bit" : { - "Package" : "bit", - "Version" : "4.0.4", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "cpp11" : { - "Package" : "cpp11", - "Version" : "0.4.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "hms" : { - "Package" : "hms", - "Version" : "1.1.1", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "pillar" : { - "Package" : "pillar", - "Version" : "1.7.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "prettyunits" : { - "Package" : "prettyunits", - "Version" : "1.1.1", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "purrr" : { - "Package" : "purrr", - "Version" : "0.3.4", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "R6" : { - "Package" : "R6", - "Version" : "2.5.1", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "bit64" : { - "Package" : "bit64", - "Version" : "4.0.5", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "progress" : { - "Package" : "progress", - "Version" : "1.2.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "Rcpp" : { - "Package" : "Rcpp", - "Version" : "1.0.8.3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "tibble" : { - "Package" : "tibble", - "Version" : "3.1.6", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "tidyselect" : { - "Package" : "tidyselect", - "Version" : "1.1.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "tzdb" : { - "Package" : "tzdb", - "Version" : "0.3.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "withr" : { - "Package" : "withr", - "Version" : "2.5.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "clipr" : { - "Package" : "clipr", - "Version" : "0.8.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "rJava" : { - "Package" : "rJava", - "Version" : "1.0-6", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "stringi" : { - "Package" : "stringi", - "Version" : "1.7.6", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "triebeard" : { - "Package" : "triebeard", - "Version" : "0.3.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "vroom" : { - "Package" : "vroom", - "Version" : "1.5.7", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "backports" : { - "Package" : "backports", - "Version" : "1.4.1", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "DBI" : { - "Package" : "DBI", - "Version" : "1.1.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "generics" : { - "Package" : "generics", - "Version" : "0.1.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "jsonlite" : { - "Package" : "jsonlite", - "Version" : "1.8.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "readr" : { - "Package" : "readr", - "Version" : "2.1.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "snow" : { - "Package" : "snow", - "Version" : "0.4-4", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "SqlRender" : { - "Package" : "SqlRender", - "Version" : "1.9.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "stringr" : { - "Package" : "stringr", - "Version" : "1.4.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "urltools" : { - "Package" : "urltools", - "Version" : "1.7.3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "xml2" : { - "Package" : "xml2", - "Version" : "1.3.3", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "checkmate" : { - "Package" : "checkmate", - "Version" : "2.1.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "DatabaseConnector" : { - "Package" : "DatabaseConnector", - "Version" : "5.0.2", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "digest" : { - "Package" : "digest", - "Version" : "0.6.29", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "dplyr" : { - "Package" : "dplyr", - "Version" : "1.0.8", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "lubridate" : { - "Package" : "lubridate", - "Version" : "1.8.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "ParallelLogger" : { - "Package" : "ParallelLogger", - "Version" : "3.0.0", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "RJSONIO" : { - "Package" : "RJSONIO", - "Version" : "1.3-1.6", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "renv" : { - "Package" : "renv", - "Version" : "0.15.4", - "Source" : "Repository", - "Repository" : "CRAN" - }, - "CirceR" : { - "Package" : "CirceR", - "Version" : "1.1.1", - "Source" : "GitHub", - "RemoteType" : "github", - "RemoteHost" : "api.github.com", - "RemoteRepo" : "CirceR", - "RemoteUsername" : "ohdsi", - "RemoteRef" : "v1.1.1" - }, - "CohortGenerator" : { - "Package" : "CohortGenerator", - "Version" : "0.5.0", - "Source" : "GitHub", - "RemoteType" : "github", - "RemoteHost" : "api.github.com", - "RemoteRepo" : "CohortGenerator", - "RemoteUsername" : "ohdsi", - "RemoteRef" : "develop" - } - } -} diff --git a/vignettes/module_skeleton/renv/.gitignore b/vignettes/module_skeleton/renv/.gitignore deleted file mode 100644 index 22a0d01d..00000000 --- a/vignettes/module_skeleton/renv/.gitignore +++ /dev/null @@ -1,7 +0,0 @@ -sandbox/ -library/ -local/ -cellar/ -lock/ -python/ -staging/ diff --git a/vignettes/module_skeleton/renv/activate.R b/vignettes/module_skeleton/renv/activate.R deleted file mode 100644 index 2969c732..00000000 --- a/vignettes/module_skeleton/renv/activate.R +++ /dev/null @@ -1,1201 +0,0 @@ - -local({ - - # the requested version of renv - version <- "1.0.2" - attr(version, "sha") <- NULL - - # the project directory - project <- getwd() - - # use start-up diagnostics if enabled - diagnostics <- Sys.getenv("RENV_STARTUP_DIAGNOSTICS", unset = "FALSE") - if (diagnostics) { - start <- Sys.time() - profile <- tempfile("renv-startup-", fileext = ".Rprof") - utils::Rprof(profile) - on.exit({ - utils::Rprof(NULL) - elapsed <- signif(difftime(Sys.time(), start, units = "auto"), digits = 2L) - writeLines(sprintf("- renv took %s to run the autoloader.", format(elapsed))) - writeLines(sprintf("- Profile: %s", profile)) - print(utils::summaryRprof(profile)) - }, add = TRUE) - } - - # figure out whether the autoloader is enabled - enabled <- local({ - - # first, check config option - override <- getOption("renv.config.autoloader.enabled") - if (!is.null(override)) - return(override) - - # next, check environment variables - # TODO: prefer using the configuration one in the future - envvars <- c( - "RENV_CONFIG_AUTOLOADER_ENABLED", - "RENV_AUTOLOADER_ENABLED", - "RENV_ACTIVATE_PROJECT" - ) - - for (envvar in envvars) { - envval <- Sys.getenv(envvar, unset = NA) - if (!is.na(envval)) - return(tolower(envval) %in% c("true", "t", "1")) - } - - # enable by default - TRUE - - }) - - if (!enabled) - return(FALSE) - - # avoid recursion - if (identical(getOption("renv.autoloader.running"), TRUE)) { - warning("ignoring recursive attempt to run renv autoloader") - return(invisible(TRUE)) - } - - # signal that we're loading renv during R startup - options(renv.autoloader.running = TRUE) - on.exit(options(renv.autoloader.running = NULL), add = TRUE) - - # signal that we've consented to use renv - options(renv.consent = TRUE) - - # load the 'utils' package eagerly -- this ensures that renv shims, which - # mask 'utils' packages, will come first on the search path - library(utils, lib.loc = .Library) - - # unload renv if it's already been loaded - if ("renv" %in% loadedNamespaces()) - unloadNamespace("renv") - - # load bootstrap tools - `%||%` <- function(x, y) { - if (is.null(x)) y else x - } - - catf <- function(fmt, ..., appendLF = TRUE) { - - quiet <- getOption("renv.bootstrap.quiet", default = FALSE) - if (quiet) - return(invisible()) - - msg <- sprintf(fmt, ...) - cat(msg, file = stdout(), sep = if (appendLF) "\n" else "") - - invisible(msg) - - } - - header <- function(label, - ..., - prefix = "#", - suffix = "-", - n = min(getOption("width"), 78)) - { - label <- sprintf(label, ...) - n <- max(n - nchar(label) - nchar(prefix) - 2L, 8L) - if (n <= 0) - return(paste(prefix, label)) - - tail <- paste(rep.int(suffix, n), collapse = "") - paste0(prefix, " ", label, " ", tail) - - } - - startswith <- function(string, prefix) { - substring(string, 1, nchar(prefix)) == prefix - } - - bootstrap <- function(version, library) { - - friendly <- renv_bootstrap_version_friendly(version) - section <- header(sprintf("Bootstrapping renv %s", friendly)) - catf(section) - - # attempt to download renv - catf("- Downloading renv ... ", appendLF = FALSE) - withCallingHandlers( - tarball <- renv_bootstrap_download(version), - error = function(err) { - catf("FAILED") - stop("failed to download:\n", conditionMessage(err)) - } - ) - catf("OK") - on.exit(unlink(tarball), add = TRUE) - - # now attempt to install - catf("- Installing renv ... ", appendLF = FALSE) - withCallingHandlers( - status <- renv_bootstrap_install(version, tarball, library), - error = function(err) { - catf("FAILED") - stop("failed to install:\n", conditionMessage(err)) - } - ) - catf("OK") - - # add empty line to break up bootstrapping from normal output - catf("") - - return(invisible()) - } - - renv_bootstrap_tests_running <- function() { - getOption("renv.tests.running", default = FALSE) - } - - renv_bootstrap_repos <- function() { - - # get CRAN repository - cran <- getOption("renv.repos.cran", "https://cloud.r-project.org") - - # check for repos override - repos <- Sys.getenv("RENV_CONFIG_REPOS_OVERRIDE", unset = NA) - if (!is.na(repos)) { - - # check for RSPM; if set, use a fallback repository for renv - rspm <- Sys.getenv("RSPM", unset = NA) - if (identical(rspm, repos)) - repos <- c(RSPM = rspm, CRAN = cran) - - return(repos) - - } - - # check for lockfile repositories - repos <- tryCatch(renv_bootstrap_repos_lockfile(), error = identity) - if (!inherits(repos, "error") && length(repos)) - return(repos) - - # retrieve current repos - repos <- getOption("repos") - - # ensure @CRAN@ entries are resolved - repos[repos == "@CRAN@"] <- cran - - # add in renv.bootstrap.repos if set - default <- c(FALLBACK = "https://cloud.r-project.org") - extra <- getOption("renv.bootstrap.repos", default = default) - repos <- c(repos, extra) - - # remove duplicates that might've snuck in - dupes <- duplicated(repos) | duplicated(names(repos)) - repos[!dupes] - - } - - renv_bootstrap_repos_lockfile <- function() { - - lockpath <- Sys.getenv("RENV_PATHS_LOCKFILE", unset = "renv.lock") - if (!file.exists(lockpath)) - return(NULL) - - lockfile <- tryCatch(renv_json_read(lockpath), error = identity) - if (inherits(lockfile, "error")) { - warning(lockfile) - return(NULL) - } - - repos <- lockfile$R$Repositories - if (length(repos) == 0) - return(NULL) - - keys <- vapply(repos, `[[`, "Name", FUN.VALUE = character(1)) - vals <- vapply(repos, `[[`, "URL", FUN.VALUE = character(1)) - names(vals) <- keys - - return(vals) - - } - - renv_bootstrap_download <- function(version) { - - sha <- attr(version, "sha", exact = TRUE) - - methods <- if (!is.null(sha)) { - - # attempting to bootstrap a development version of renv - c( - function() renv_bootstrap_download_tarball(sha), - function() renv_bootstrap_download_github(sha) - ) - - } else { - - # attempting to bootstrap a release version of renv - c( - function() renv_bootstrap_download_tarball(version), - function() renv_bootstrap_download_cran_latest(version), - function() renv_bootstrap_download_cran_archive(version) - ) - - } - - for (method in methods) { - path <- tryCatch(method(), error = identity) - if (is.character(path) && file.exists(path)) - return(path) - } - - stop("All download methods failed") - - } - - renv_bootstrap_download_impl <- function(url, destfile) { - - mode <- "wb" - - # https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17715 - fixup <- - Sys.info()[["sysname"]] == "Windows" && - substring(url, 1L, 5L) == "file:" - - if (fixup) - mode <- "w+b" - - args <- list( - url = url, - destfile = destfile, - mode = mode, - quiet = TRUE - ) - - if ("headers" %in% names(formals(utils::download.file))) - args$headers <- renv_bootstrap_download_custom_headers(url) - - do.call(utils::download.file, args) - - } - - renv_bootstrap_download_custom_headers <- function(url) { - - headers <- getOption("renv.download.headers") - if (is.null(headers)) - return(character()) - - if (!is.function(headers)) - stopf("'renv.download.headers' is not a function") - - headers <- headers(url) - if (length(headers) == 0L) - return(character()) - - if (is.list(headers)) - headers <- unlist(headers, recursive = FALSE, use.names = TRUE) - - ok <- - is.character(headers) && - is.character(names(headers)) && - all(nzchar(names(headers))) - - if (!ok) - stop("invocation of 'renv.download.headers' did not return a named character vector") - - headers - - } - - renv_bootstrap_download_cran_latest <- function(version) { - - spec <- renv_bootstrap_download_cran_latest_find(version) - type <- spec$type - repos <- spec$repos - - baseurl <- utils::contrib.url(repos = repos, type = type) - ext <- if (identical(type, "source")) - ".tar.gz" - else if (Sys.info()[["sysname"]] == "Windows") - ".zip" - else - ".tgz" - name <- sprintf("renv_%s%s", version, ext) - url <- paste(baseurl, name, sep = "/") - - destfile <- file.path(tempdir(), name) - status <- tryCatch( - renv_bootstrap_download_impl(url, destfile), - condition = identity - ) - - if (inherits(status, "condition")) - return(FALSE) - - # report success and return - destfile - - } - - renv_bootstrap_download_cran_latest_find <- function(version) { - - # check whether binaries are supported on this system - binary <- - getOption("renv.bootstrap.binary", default = TRUE) && - !identical(.Platform$pkgType, "source") && - !identical(getOption("pkgType"), "source") && - Sys.info()[["sysname"]] %in% c("Darwin", "Windows") - - types <- c(if (binary) "binary", "source") - - # iterate over types + repositories - for (type in types) { - for (repos in renv_bootstrap_repos()) { - - # retrieve package database - db <- tryCatch( - as.data.frame( - utils::available.packages(type = type, repos = repos), - stringsAsFactors = FALSE - ), - error = identity - ) - - if (inherits(db, "error")) - next - - # check for compatible entry - entry <- db[db$Package %in% "renv" & db$Version %in% version, ] - if (nrow(entry) == 0) - next - - # found it; return spec to caller - spec <- list(entry = entry, type = type, repos = repos) - return(spec) - - } - } - - # if we got here, we failed to find renv - fmt <- "renv %s is not available from your declared package repositories" - stop(sprintf(fmt, version)) - - } - - renv_bootstrap_download_cran_archive <- function(version) { - - name <- sprintf("renv_%s.tar.gz", version) - repos <- renv_bootstrap_repos() - urls <- file.path(repos, "src/contrib/Archive/renv", name) - destfile <- file.path(tempdir(), name) - - for (url in urls) { - - status <- tryCatch( - renv_bootstrap_download_impl(url, destfile), - condition = identity - ) - - if (identical(status, 0L)) - return(destfile) - - } - - return(FALSE) - - } - - renv_bootstrap_download_tarball <- function(version) { - - # if the user has provided the path to a tarball via - # an environment variable, then use it - tarball <- Sys.getenv("RENV_BOOTSTRAP_TARBALL", unset = NA) - if (is.na(tarball)) - return() - - # allow directories - if (dir.exists(tarball)) { - name <- sprintf("renv_%s.tar.gz", version) - tarball <- file.path(tarball, name) - } - - # bail if it doesn't exist - if (!file.exists(tarball)) { - - # let the user know we weren't able to honour their request - fmt <- "- RENV_BOOTSTRAP_TARBALL is set (%s) but does not exist." - msg <- sprintf(fmt, tarball) - warning(msg) - - # bail - return() - - } - - catf("- Using local tarball '%s'.", tarball) - tarball - - } - - renv_bootstrap_download_github <- function(version) { - - enabled <- Sys.getenv("RENV_BOOTSTRAP_FROM_GITHUB", unset = "TRUE") - if (!identical(enabled, "TRUE")) - return(FALSE) - - # prepare download options - pat <- Sys.getenv("GITHUB_PAT") - if (nzchar(Sys.which("curl")) && nzchar(pat)) { - fmt <- "--location --fail --header \"Authorization: token %s\"" - extra <- sprintf(fmt, pat) - saved <- options("download.file.method", "download.file.extra") - options(download.file.method = "curl", download.file.extra = extra) - on.exit(do.call(base::options, saved), add = TRUE) - } else if (nzchar(Sys.which("wget")) && nzchar(pat)) { - fmt <- "--header=\"Authorization: token %s\"" - extra <- sprintf(fmt, pat) - saved <- options("download.file.method", "download.file.extra") - options(download.file.method = "wget", download.file.extra = extra) - on.exit(do.call(base::options, saved), add = TRUE) - } - - url <- file.path("https://api.github.com/repos/rstudio/renv/tarball", version) - name <- sprintf("renv_%s.tar.gz", version) - destfile <- file.path(tempdir(), name) - - status <- tryCatch( - renv_bootstrap_download_impl(url, destfile), - condition = identity - ) - - if (!identical(status, 0L)) - return(FALSE) - - renv_bootstrap_download_augment(destfile) - - return(destfile) - - } - - # Add Sha to DESCRIPTION. This is stop gap until #890, after which we - # can use renv::install() to fully capture metadata. - renv_bootstrap_download_augment <- function(destfile) { - sha <- renv_bootstrap_git_extract_sha1_tar(destfile) - if (is.null(sha)) { - return() - } - - # Untar - tempdir <- tempfile("renv-github-") - on.exit(unlink(tempdir, recursive = TRUE), add = TRUE) - untar(destfile, exdir = tempdir) - pkgdir <- dir(tempdir, full.names = TRUE)[[1]] - - # Modify description - desc_path <- file.path(pkgdir, "DESCRIPTION") - desc_lines <- readLines(desc_path) - remotes_fields <- c( - "RemoteType: github", - "RemoteHost: api.github.com", - "RemoteRepo: renv", - "RemoteUsername: rstudio", - "RemotePkgRef: rstudio/renv", - paste("RemoteRef: ", sha), - paste("RemoteSha: ", sha) - ) - writeLines(c(desc_lines[desc_lines != ""], remotes_fields), con = desc_path) - - # Re-tar - local({ - old <- setwd(tempdir) - on.exit(setwd(old), add = TRUE) - - tar(destfile, compression = "gzip") - }) - invisible() - } - - # Extract the commit hash from a git archive. Git archives include the SHA1 - # hash as the comment field of the tarball pax extended header - # (see https://www.kernel.org/pub/software/scm/git/docs/git-archive.html) - # For GitHub archives this should be the first header after the default one - # (512 byte) header. - renv_bootstrap_git_extract_sha1_tar <- function(bundle) { - - # open the bundle for reading - # We use gzcon for everything because (from ?gzcon) - # > Reading from a connection which does not supply a 'gzip' magic - # > header is equivalent to reading from the original connection - conn <- gzcon(file(bundle, open = "rb", raw = TRUE)) - on.exit(close(conn)) - - # The default pax header is 512 bytes long and the first pax extended header - # with the comment should be 51 bytes long - # `52 comment=` (11 chars) + 40 byte SHA1 hash - len <- 0x200 + 0x33 - res <- rawToChar(readBin(conn, "raw", n = len)[0x201:len]) - - if (grepl("^52 comment=", res)) { - sub("52 comment=", "", res) - } else { - NULL - } - } - - renv_bootstrap_install <- function(version, tarball, library) { - - # attempt to install it into project library - dir.create(library, showWarnings = FALSE, recursive = TRUE) - output <- renv_bootstrap_install_impl(library, tarball) - - # check for successful install - status <- attr(output, "status") - if (is.null(status) || identical(status, 0L)) - return(status) - - # an error occurred; report it - header <- "installation of renv failed" - lines <- paste(rep.int("=", nchar(header)), collapse = "") - text <- paste(c(header, lines, output), collapse = "\n") - stop(text) - - } - - renv_bootstrap_install_impl <- function(library, tarball) { - - # invoke using system2 so we can capture and report output - bin <- R.home("bin") - exe <- if (Sys.info()[["sysname"]] == "Windows") "R.exe" else "R" - R <- file.path(bin, exe) - - args <- c( - "--vanilla", "CMD", "INSTALL", "--no-multiarch", - "-l", shQuote(path.expand(library)), - shQuote(path.expand(tarball)) - ) - - system2(R, args, stdout = TRUE, stderr = TRUE) - - } - - renv_bootstrap_platform_prefix <- function() { - - # construct version prefix - version <- paste(R.version$major, R.version$minor, sep = ".") - prefix <- paste("R", numeric_version(version)[1, 1:2], sep = "-") - - # include SVN revision for development versions of R - # (to avoid sharing platform-specific artefacts with released versions of R) - devel <- - identical(R.version[["status"]], "Under development (unstable)") || - identical(R.version[["nickname"]], "Unsuffered Consequences") - - if (devel) - prefix <- paste(prefix, R.version[["svn rev"]], sep = "-r") - - # build list of path components - components <- c(prefix, R.version$platform) - - # include prefix if provided by user - prefix <- renv_bootstrap_platform_prefix_impl() - if (!is.na(prefix) && nzchar(prefix)) - components <- c(prefix, components) - - # build prefix - paste(components, collapse = "/") - - } - - renv_bootstrap_platform_prefix_impl <- function() { - - # if an explicit prefix has been supplied, use it - prefix <- Sys.getenv("RENV_PATHS_PREFIX", unset = NA) - if (!is.na(prefix)) - return(prefix) - - # if the user has requested an automatic prefix, generate it - auto <- Sys.getenv("RENV_PATHS_PREFIX_AUTO", unset = NA) - if (auto %in% c("TRUE", "True", "true", "1")) - return(renv_bootstrap_platform_prefix_auto()) - - # empty string on failure - "" - - } - - renv_bootstrap_platform_prefix_auto <- function() { - - prefix <- tryCatch(renv_bootstrap_platform_os(), error = identity) - if (inherits(prefix, "error") || prefix %in% "unknown") { - - msg <- paste( - "failed to infer current operating system", - "please file a bug report at https://github.com/rstudio/renv/issues", - sep = "; " - ) - - warning(msg) - - } - - prefix - - } - - renv_bootstrap_platform_os <- function() { - - sysinfo <- Sys.info() - sysname <- sysinfo[["sysname"]] - - # handle Windows + macOS up front - if (sysname == "Windows") - return("windows") - else if (sysname == "Darwin") - return("macos") - - # check for os-release files - for (file in c("/etc/os-release", "/usr/lib/os-release")) - if (file.exists(file)) - return(renv_bootstrap_platform_os_via_os_release(file, sysinfo)) - - # check for redhat-release files - if (file.exists("/etc/redhat-release")) - return(renv_bootstrap_platform_os_via_redhat_release()) - - "unknown" - - } - - renv_bootstrap_platform_os_via_os_release <- function(file, sysinfo) { - - # read /etc/os-release - release <- utils::read.table( - file = file, - sep = "=", - quote = c("\"", "'"), - col.names = c("Key", "Value"), - comment.char = "#", - stringsAsFactors = FALSE - ) - - vars <- as.list(release$Value) - names(vars) <- release$Key - - # get os name - os <- tolower(sysinfo[["sysname"]]) - - # read id - id <- "unknown" - for (field in c("ID", "ID_LIKE")) { - if (field %in% names(vars) && nzchar(vars[[field]])) { - id <- vars[[field]] - break - } - } - - # read version - version <- "unknown" - for (field in c("UBUNTU_CODENAME", "VERSION_CODENAME", "VERSION_ID", "BUILD_ID")) { - if (field %in% names(vars) && nzchar(vars[[field]])) { - version <- vars[[field]] - break - } - } - - # join together - paste(c(os, id, version), collapse = "-") - - } - - renv_bootstrap_platform_os_via_redhat_release <- function() { - - # read /etc/redhat-release - contents <- readLines("/etc/redhat-release", warn = FALSE) - - # infer id - id <- if (grepl("centos", contents, ignore.case = TRUE)) - "centos" - else if (grepl("redhat", contents, ignore.case = TRUE)) - "redhat" - else - "unknown" - - # try to find a version component (very hacky) - version <- "unknown" - - parts <- strsplit(contents, "[[:space:]]")[[1L]] - for (part in parts) { - - nv <- tryCatch(numeric_version(part), error = identity) - if (inherits(nv, "error")) - next - - version <- nv[1, 1] - break - - } - - paste(c("linux", id, version), collapse = "-") - - } - - renv_bootstrap_library_root_name <- function(project) { - - # use project name as-is if requested - asis <- Sys.getenv("RENV_PATHS_LIBRARY_ROOT_ASIS", unset = "FALSE") - if (asis) - return(basename(project)) - - # otherwise, disambiguate based on project's path - id <- substring(renv_bootstrap_hash_text(project), 1L, 8L) - paste(basename(project), id, sep = "-") - - } - - renv_bootstrap_library_root <- function(project) { - - prefix <- renv_bootstrap_profile_prefix() - - path <- Sys.getenv("RENV_PATHS_LIBRARY", unset = NA) - if (!is.na(path)) - return(paste(c(path, prefix), collapse = "/")) - - path <- renv_bootstrap_library_root_impl(project) - if (!is.null(path)) { - name <- renv_bootstrap_library_root_name(project) - return(paste(c(path, prefix, name), collapse = "/")) - } - - renv_bootstrap_paths_renv("library", project = project) - - } - - renv_bootstrap_library_root_impl <- function(project) { - - root <- Sys.getenv("RENV_PATHS_LIBRARY_ROOT", unset = NA) - if (!is.na(root)) - return(root) - - type <- renv_bootstrap_project_type(project) - if (identical(type, "package")) { - userdir <- renv_bootstrap_user_dir() - return(file.path(userdir, "library")) - } - - } - - renv_bootstrap_validate_version <- function(version, description = NULL) { - - # resolve description file - # - # avoid passing lib.loc to `packageDescription()` below, since R will - # use the loaded version of the package by default anyhow. note that - # this function should only be called after 'renv' is loaded - # https://github.com/rstudio/renv/issues/1625 - description <- description %||% packageDescription("renv") - - # check whether requested version 'version' matches loaded version of renv - sha <- attr(version, "sha", exact = TRUE) - valid <- if (!is.null(sha)) - renv_bootstrap_validate_version_dev(sha, description) - else - renv_bootstrap_validate_version_release(version, description) - - if (valid) - return(TRUE) - - # the loaded version of renv doesn't match the requested version; - # give the user instructions on how to proceed - remote <- if (!is.null(description[["RemoteSha"]])) { - paste("rstudio/renv", description[["RemoteSha"]], sep = "@") - } else { - paste("renv", description[["Version"]], sep = "@") - } - - # display both loaded version + sha if available - friendly <- renv_bootstrap_version_friendly( - version = description[["Version"]], - sha = description[["RemoteSha"]] - ) - - fmt <- paste( - "renv %1$s was loaded from project library, but this project is configured to use renv %2$s.", - "- Use `renv::record(\"%3$s\")` to record renv %1$s in the lockfile.", - "- Use `renv::restore(packages = \"renv\")` to install renv %2$s into the project library.", - sep = "\n" - ) - catf(fmt, friendly, renv_bootstrap_version_friendly(version), remote) - - FALSE - - } - - renv_bootstrap_validate_version_dev <- function(version, description) { - expected <- description[["RemoteSha"]] - is.character(expected) && startswith(expected, version) - } - - renv_bootstrap_validate_version_release <- function(version, description) { - expected <- description[["Version"]] - is.character(expected) && identical(expected, version) - } - - renv_bootstrap_hash_text <- function(text) { - - hashfile <- tempfile("renv-hash-") - on.exit(unlink(hashfile), add = TRUE) - - writeLines(text, con = hashfile) - tools::md5sum(hashfile) - - } - - renv_bootstrap_load <- function(project, libpath, version) { - - # try to load renv from the project library - if (!requireNamespace("renv", lib.loc = libpath, quietly = TRUE)) - return(FALSE) - - # warn if the version of renv loaded does not match - renv_bootstrap_validate_version(version) - - # execute renv load hooks, if any - hooks <- getHook("renv::autoload") - for (hook in hooks) - if (is.function(hook)) - tryCatch(hook(), error = warnify) - - # load the project - renv::load(project) - - TRUE - - } - - renv_bootstrap_profile_load <- function(project) { - - # if RENV_PROFILE is already set, just use that - profile <- Sys.getenv("RENV_PROFILE", unset = NA) - if (!is.na(profile) && nzchar(profile)) - return(profile) - - # check for a profile file (nothing to do if it doesn't exist) - path <- renv_bootstrap_paths_renv("profile", profile = FALSE, project = project) - if (!file.exists(path)) - return(NULL) - - # read the profile, and set it if it exists - contents <- readLines(path, warn = FALSE) - if (length(contents) == 0L) - return(NULL) - - # set RENV_PROFILE - profile <- contents[[1L]] - if (!profile %in% c("", "default")) - Sys.setenv(RENV_PROFILE = profile) - - profile - - } - - renv_bootstrap_profile_prefix <- function() { - profile <- renv_bootstrap_profile_get() - if (!is.null(profile)) - return(file.path("profiles", profile, "renv")) - } - - renv_bootstrap_profile_get <- function() { - profile <- Sys.getenv("RENV_PROFILE", unset = "") - renv_bootstrap_profile_normalize(profile) - } - - renv_bootstrap_profile_set <- function(profile) { - profile <- renv_bootstrap_profile_normalize(profile) - if (is.null(profile)) - Sys.unsetenv("RENV_PROFILE") - else - Sys.setenv(RENV_PROFILE = profile) - } - - renv_bootstrap_profile_normalize <- function(profile) { - - if (is.null(profile) || profile %in% c("", "default")) - return(NULL) - - profile - - } - - renv_bootstrap_path_absolute <- function(path) { - - substr(path, 1L, 1L) %in% c("~", "/", "\\") || ( - substr(path, 1L, 1L) %in% c(letters, LETTERS) && - substr(path, 2L, 3L) %in% c(":/", ":\\") - ) - - } - - renv_bootstrap_paths_renv <- function(..., profile = TRUE, project = NULL) { - renv <- Sys.getenv("RENV_PATHS_RENV", unset = "renv") - root <- if (renv_bootstrap_path_absolute(renv)) NULL else project - prefix <- if (profile) renv_bootstrap_profile_prefix() - components <- c(root, renv, prefix, ...) - paste(components, collapse = "/") - } - - renv_bootstrap_project_type <- function(path) { - - descpath <- file.path(path, "DESCRIPTION") - if (!file.exists(descpath)) - return("unknown") - - desc <- tryCatch( - read.dcf(descpath, all = TRUE), - error = identity - ) - - if (inherits(desc, "error")) - return("unknown") - - type <- desc$Type - if (!is.null(type)) - return(tolower(type)) - - package <- desc$Package - if (!is.null(package)) - return("package") - - "unknown" - - } - - renv_bootstrap_user_dir <- function() { - dir <- renv_bootstrap_user_dir_impl() - path.expand(chartr("\\", "/", dir)) - } - - renv_bootstrap_user_dir_impl <- function() { - - # use local override if set - override <- getOption("renv.userdir.override") - if (!is.null(override)) - return(override) - - # use R_user_dir if available - tools <- asNamespace("tools") - if (is.function(tools$R_user_dir)) - return(tools$R_user_dir("renv", "cache")) - - # try using our own backfill for older versions of R - envvars <- c("R_USER_CACHE_DIR", "XDG_CACHE_HOME") - for (envvar in envvars) { - root <- Sys.getenv(envvar, unset = NA) - if (!is.na(root)) - return(file.path(root, "R/renv")) - } - - # use platform-specific default fallbacks - if (Sys.info()[["sysname"]] == "Windows") - file.path(Sys.getenv("LOCALAPPDATA"), "R/cache/R/renv") - else if (Sys.info()[["sysname"]] == "Darwin") - "~/Library/Caches/org.R-project.R/R/renv" - else - "~/.cache/R/renv" - - } - - renv_bootstrap_version_friendly <- function(version, shafmt = NULL, sha = NULL) { - sha <- sha %||% attr(version, "sha", exact = TRUE) - parts <- c(version, sprintf(shafmt %||% " [sha: %s]", substring(sha, 1L, 7L))) - paste(parts, collapse = "") - } - - renv_bootstrap_exec <- function(project, libpath, version) { - if (!renv_bootstrap_load(project, libpath, version)) - renv_bootstrap_run(version, libpath) - } - - renv_bootstrap_run <- function(version, libpath) { - - # perform bootstrap - bootstrap(version, libpath) - - # exit early if we're just testing bootstrap - if (!is.na(Sys.getenv("RENV_BOOTSTRAP_INSTALL_ONLY", unset = NA))) - return(TRUE) - - # try again to load - if (requireNamespace("renv", lib.loc = libpath, quietly = TRUE)) { - return(renv::load(project = getwd())) - } - - # failed to download or load renv; warn the user - msg <- c( - "Failed to find an renv installation: the project will not be loaded.", - "Use `renv::activate()` to re-initialize the project." - ) - - warning(paste(msg, collapse = "\n"), call. = FALSE) - - } - - - renv_bootstrap_in_rstudio <- function() { - commandArgs()[[1]] == "RStudio" - } - - # Used to work around buglet in RStudio if hook uses readline - renv_bootstrap_flush_console <- function() { - tryCatch({ - tools <- as.environment("tools:rstudio") - tools$.rs.api.sendToConsole("", echo = FALSE, focus = FALSE) - }, error = function(cnd) {}) - } - - renv_json_read <- function(file = NULL, text = NULL) { - - jlerr <- NULL - - # if jsonlite is loaded, use that instead - if ("jsonlite" %in% loadedNamespaces()) { - - json <- catch(renv_json_read_jsonlite(file, text)) - if (!inherits(json, "error")) - return(json) - - jlerr <- json - - } - - # otherwise, fall back to the default JSON reader - json <- catch(renv_json_read_default(file, text)) - if (!inherits(json, "error")) - return(json) - - # report an error - if (!is.null(jlerr)) - stop(jlerr) - else - stop(json) - - } - - renv_json_read_jsonlite <- function(file = NULL, text = NULL) { - text <- paste(text %||% read(file), collapse = "\n") - jsonlite::fromJSON(txt = text, simplifyVector = FALSE) - } - - renv_json_read_default <- function(file = NULL, text = NULL) { - - # find strings in the JSON - text <- paste(text %||% read(file), collapse = "\n") - pattern <- '["](?:(?:\\\\.)|(?:[^"\\\\]))*?["]' - locs <- gregexpr(pattern, text, perl = TRUE)[[1]] - - # if any are found, replace them with placeholders - replaced <- text - strings <- character() - replacements <- character() - - if (!identical(c(locs), -1L)) { - - # get the string values - starts <- locs - ends <- locs + attr(locs, "match.length") - 1L - strings <- substring(text, starts, ends) - - # only keep those requiring escaping - strings <- grep("[[\\]{}:]", strings, perl = TRUE, value = TRUE) - - # compute replacements - replacements <- sprintf('"\032%i\032"', seq_along(strings)) - - # replace the strings - mapply(function(string, replacement) { - replaced <<- sub(string, replacement, replaced, fixed = TRUE) - }, strings, replacements) - - } - - # transform the JSON into something the R parser understands - transformed <- replaced - transformed <- gsub("{}", "`names<-`(list(), character())", transformed, fixed = TRUE) - transformed <- gsub("[[{]", "list(", transformed, perl = TRUE) - transformed <- gsub("[]}]", ")", transformed, perl = TRUE) - transformed <- gsub(":", "=", transformed, fixed = TRUE) - text <- paste(transformed, collapse = "\n") - - # parse it - json <- parse(text = text, keep.source = FALSE, srcfile = NULL)[[1L]] - - # construct map between source strings, replaced strings - map <- as.character(parse(text = strings)) - names(map) <- as.character(parse(text = replacements)) - - # convert to list - map <- as.list(map) - - # remap strings in object - remapped <- renv_json_remap(json, map) - - # evaluate - eval(remapped, envir = baseenv()) - - } - - renv_json_remap <- function(json, map) { - - # fix names - if (!is.null(names(json))) { - lhs <- match(names(json), names(map), nomatch = 0L) - rhs <- match(names(map), names(json), nomatch = 0L) - names(json)[rhs] <- map[lhs] - } - - # fix values - if (is.character(json)) - return(map[[json]] %||% json) - - # handle true, false, null - if (is.name(json)) { - text <- as.character(json) - if (text == "true") - return(TRUE) - else if (text == "false") - return(FALSE) - else if (text == "null") - return(NULL) - } - - # recurse - if (is.recursive(json)) { - for (i in seq_along(json)) { - json[i] <- list(renv_json_remap(json[[i]], map)) - } - } - - json - - } - - # load the renv profile, if any - renv_bootstrap_profile_load(project) - - # construct path to library root - root <- renv_bootstrap_library_root(project) - - # construct library prefix for platform - prefix <- renv_bootstrap_platform_prefix() - - # construct full libpath - libpath <- file.path(root, prefix) - - if (renv_bootstrap_in_rstudio()) { - # RStudio only updates console once .Rprofile is finished, so - # instead run code on sessionInit - setHook("rstudio.sessionInit", function(...) { - renv_bootstrap_exec(project, libpath, version) - renv_bootstrap_flush_console() - }) - } else { - renv_bootstrap_exec(project, libpath, version) - } - - invisible() - -}) diff --git a/vignettes/module_skeleton/renv/settings.dcf b/vignettes/module_skeleton/renv/settings.dcf deleted file mode 100644 index 169d82f1..00000000 --- a/vignettes/module_skeleton/renv/settings.dcf +++ /dev/null @@ -1,10 +0,0 @@ -bioconductor.version: -external.libraries: -ignored.packages: -package.dependency.fields: Imports, Depends, LinkingTo -r.version: -snapshot.type: implicit -use.cache: TRUE -vcs.ignore.cellar: TRUE -vcs.ignore.library: TRUE -vcs.ignore.local: TRUE diff --git a/vignettes/module_skeleton/renv/settings.json b/vignettes/module_skeleton/renv/settings.json deleted file mode 100644 index ffdbb320..00000000 --- a/vignettes/module_skeleton/renv/settings.json +++ /dev/null @@ -1,19 +0,0 @@ -{ - "bioconductor.version": null, - "external.libraries": [], - "ignored.packages": [], - "package.dependency.fields": [ - "Imports", - "Depends", - "LinkingTo" - ], - "ppm.enabled": null, - "ppm.ignored.urls": [], - "r.version": null, - "snapshot.type": "implicit", - "use.cache": true, - "vcs.ignore.cellar": true, - "vcs.ignore.library": true, - "vcs.ignore.local": true, - "vcs.manage.ignores": true -} diff --git a/vignettes/module_skeleton/resources/exampleAnalysisSpecifications.json b/vignettes/module_skeleton/resources/exampleAnalysisSpecifications.json deleted file mode 100644 index a3111323..00000000 --- a/vignettes/module_skeleton/resources/exampleAnalysisSpecifications.json +++ /dev/null @@ -1,28 +0,0 @@ -{ - "sharedResources": [ - { - "cohortDefinitions": [ - { - "cohortId": "1", - "cohortName": "celecoxib", - "cohortDefinition": "...truncated..." - } - ], - "attr_class": ["CohortDefinitionSharedResources", "SharedResources"] - } - ], - "moduleSpecifications": [ - { - "module": "CohortGeneratorModule", - "version": "0.0.1", - "remoteRepo": "github.com", - "remoteUsername": "ohdsi", - "settings": { - "incremental": true, - "generateStats": true - }, - "attr_class": ["CohortGeneratorModuleSpecifications", "ModuleSpecifications"] - } - ], - "attr_class": "AnalysisSpecifications" -} diff --git a/vignettes/module_skeleton/resources/resultsDataModelSpecification.csv b/vignettes/module_skeleton/resources/resultsDataModelSpecification.csv deleted file mode 100644 index 7a739753..00000000 --- a/vignettes/module_skeleton/resources/resultsDataModelSpecification.csv +++ /dev/null @@ -1,8 +0,0 @@ -table_name,column_name,data_type,is_required,primary_key,empty_is_na -my_table,cohort_id,bigint,Yes,Yes,No -my_table,cohort_name,varchar,Yes,No,No -my_table,generation_status,varchar,No,No,No -my_table,start_time,Timestamp,No,No,No -my_table,end_time,Timestamp,No,No,No -my_table,database_id,varchar,Yes,Yes,No - diff --git a/vignettes/module_skeleton/tests/test-eunomia.R b/vignettes/module_skeleton/tests/test-eunomia.R deleted file mode 100644 index 743a3634..00000000 --- a/vignettes/module_skeleton/tests/test-eunomia.R +++ /dev/null @@ -1,41 +0,0 @@ -library(testthat) -library(Eunomia) -connectionDetails <- getEunomiaConnectionDetails() - -workFolder <- tempfile("work") -dir.create(workFolder) -resultsfolder <- tempfile("results") -dir.create(resultsfolder) -jobContext <- readRDS("tests/testJobContext.rds") -jobContext$moduleExecutionSettings$workSubFolder <- workFolder -jobContext$moduleExecutionSettings$resultsSubFolder <- resultsfolder -jobContext$moduleExecutionSettings$connectionDetails <- connectionDetails -jobContext$moduleExecutionSettings$resultsConnectionDetails <- connectionDetails -jobContext$moduleExecutionSettings$resultsDatabaseSchema <- jobContext$moduleExecutionSettings$workDatabaseSchema - -test_that("Test createDataModelSchema", { - source("Main.R") - createDataModelSchema(jobContext) - - # Verify that the table(s) are created - connection <- DatabaseConnector::connect( - connectionDetails = jobContext$moduleExecutionSettings$resultsConnectionDetails - ) - on.exit(DatabaseConnector::disconnect(connection)) - tableList <- DatabaseConnector::getTableNames( - connection = connection - ) - resultsTablesCreated <- tableList[grep(getModuleInfo()$TablePrefix, tableList)] - expect_true(length(resultsTablesCreated) > 0) -}) - -test_that("Run module", { - source("Main.R") - execute(jobContext) - resultsFiles <- list.files(resultsfolder) - expect_true("cg_cohort_definition.csv" %in% resultsFiles) -}) - -unlink(workFolder) -unlink(resultsfolder) -unlink(connectionDetails$server()) diff --git a/vignettes/module_skeleton/tests/testJobContext.rds b/vignettes/module_skeleton/tests/testJobContext.rds deleted file mode 100644 index 1d40f1fe..00000000 Binary files a/vignettes/module_skeleton/tests/testJobContext.rds and /dev/null differ diff --git a/vignettes/module_skeleton/tests/testScript.R b/vignettes/module_skeleton/tests/testScript.R deleted file mode 100644 index 02d8c189..00000000 --- a/vignettes/module_skeleton/tests/testScript.R +++ /dev/null @@ -1,10 +0,0 @@ -library(testthat) - -testFiles <- list.files(file.path("tests"), "test-.*\\.R", full.names = TRUE) -for (testFile in testFiles) { - message(sprintf("*** Running tests in '%s' ***", testFile)) - source(testFile) -} - - -# Note: testthat default structure does not work for non-packages: https://github.com/r-lib/testthat/issues/1490