Merge pull request #136 from mantidproject/update-inputs-file

Clean up of user inputs file and restructure of files

legacy/original_analysis/process_inputs.py

@@ -0,0 +1,135 @@
+from mvesuvio.util import handle_config
+
+def completeBootIC(bootIC, bckwdIC, fwdIC, yFitIC):
+    if not (bootIC.runBootstrap):
+        return
+
+    try:  # Assume it is not running a test if atribute is not found
+        bootIC.runningTest
+    except AttributeError:
+        bootIC.runningTest = False
+
+    setBootstrapDirs(bckwdIC, fwdIC, bootIC, yFitIC)
+    return
+
+
+def setBootstrapDirs(bckwdIC, fwdIC, bootIC, yFitIC):
+    """Form bootstrap output data paths"""
+    experimentPath = _get_expr_path()
+    scriptName = handle_config.get_script_name()
+
+    # Select script name and experiments path
+    sampleName = bckwdIC.scriptName  # Name of sample currently running
+
+    # Used to store running times required to estimate Bootstrap total run time.
+    bootIC.runTimesPath = experimentPath / "running_times.txt"
+
+    # Make bootstrap and jackknife data directories
+    if bootIC.bootstrapType == "JACKKNIFE":
+        bootPath = experimentPath / "jackknife_data"
+    else:
+        bootPath = experimentPath / "bootstrap_data"
+    bootPath.mkdir(exist_ok=True)
+
+    # Folders for skipped and unskipped MS
+    if bootIC.skipMSIterations:
+        dataPath = bootPath / "skip_MS_corrections"
+    else:
+        dataPath = bootPath / "with_MS_corrections"
+    dataPath.mkdir(exist_ok=True)
+
+    # Create text file for logs
+    logFilePath = dataPath / "data_files_log.txt"
+    if not (logFilePath.is_file()):
+        with open(logFilePath, "w") as txtFile:
+            txtFile.write(header_string())
+
+    for IC in [bckwdIC, fwdIC]:  # Make save paths for .npz files
+        bootName, bootNameYFit = genBootFilesName(IC, bootIC)
+
+        IC.bootSavePath = (
+            dataPath / bootName
+        )  # works because modeRunning has same strings as procedure
+        IC.bootYFitSavePath = dataPath / bootNameYFit
+
+        IC.logFilePath = logFilePath
+        IC.bootSavePathLog = logString(bootName, IC, yFitIC, bootIC, isYFit=False)
+        IC.bootYFitSavePathLog = logString(
+            bootNameYFit, IC, yFitIC, bootIC, isYFit=True
+        )
+    return
+
+
+def genBootFilesName(IC, bootIC):
+    """Generates save file name for either BACKWARD or FORWARD class"""
+
+    nSamples = bootIC.nSamples
+    if bootIC.bootstrapType == "JACKKNIFE":
+        nSamples = 3 if bootIC.runningTest else noOfHistsFromTOFBinning(IC)
+
+    # Build Filename based on ic
+    corr = ""
+    if IC.MSCorrectionFlag & (IC.noOfMSIterations > 0):
+        corr += "_MS"
+    if IC.GammaCorrectionFlag & (IC.noOfMSIterations > 0):
+        corr += "_GC"
+
+    fileName = f"spec_{IC.firstSpec}-{IC.lastSpec}_iter_{IC.noOfMSIterations}{corr}"
+    bootName = fileName + f"_nsampl_{nSamples}" + ".npz"
+    bootNameYFit = fileName + "_ySpaceFit" + f"_nsampl_{nSamples}" + ".npz"
+    return bootName, bootNameYFit
+
+
+def header_string():
+    return """
+    This file contains some information about each data file in the folder.
+    ncp data file: boot type | procedure | tof binning | masked tof range.
+    yspace fit data file: boot type | procedure | symmetrisation | rebin pars | fit model | mask type
+    """
+
+
+def logString(bootDataName, IC, yFitIC, bootIC, isYFit):
+    if isYFit:
+        log = (
+            bootDataName
+            + " : "
+            + bootIC.bootstrapType
+            + " | "
+            + str(bootIC.fitInYSpace)
+            + " | "
+            + str(yFitIC.symmetrisationFlag)
+            + " | "
+            + yFitIC.rebinParametersForYSpaceFit
+            + " | "
+            + yFitIC.fitModel
+            + " | "
+            + str(yFitIC.maskTypeProcedure)
+        )
+    else:
+        log = (
+            bootDataName
+            + " : "
+            + bootIC.bootstrapType
+            + " | "
+            + str(bootIC.procedure)
+            + " | "
+            + IC.tofBinning
+            + " | "
+            + str(IC.maskTOFRange)
+        )
+    return log
+
+
+def noOfHistsFromTOFBinning(IC):
+    # Convert first to float and then to int because of decimal points
+    start, spacing, end = [int(float(s)) for s in IC.tofBinning.split(",")]
+    return int((end - start) / spacing) - 1  # To account for last column being ignored
+
+
+def buildFinalWSName(procedure: str, IC):
+    scriptName = handle_config.get_script_name()
+    # Format of corrected ws from last iteration
+    name = scriptName + "_" + procedure + "_" + str(IC.noOfMSIterations)
+    return name
+
+

src/mvesuvio/analysis_fitting.py

@@ -9,6 +9,8 @@
 import jacobi
 import time
 
+from mvesuvio.util import handle_config
+
 repoPath = Path(__file__).absolute().parent  # Path to the repository
 
 
@@ -64,7 +66,7 @@ def extractNCPFromWorkspaces(wsFinal, ic):
 
     # Ensure shape of ncp matches data
     shape = ncpForEachMass.shape
-    assert shape[0] == ic.noOfMasses
+    assert shape[0] == len(ic.masses)
     assert shape[1] == wsFinal.getNumberHistograms()
     # Final dimension can be missing last col or not
     assert (shape[2] == wsFinal.blocksize()) | (shape[2] == wsFinal.blocksize() - 1)
@@ -93,7 +95,8 @@ def calculateMantidResolutionFirstMass(IC, yFitIC, ws):
         else:
             AppendSpectra(resName, "tmp", OutputWorkspace=resName)
 
-    MaskDetectors(resName, WorkspaceIndexList=IC.maskedDetectorIdx)
+    masked_idx = [ws.spectrumInfo().isMasked(i) for i in range(ws.getNumberHistograms())]
+    MaskDetectors(resName, WorkspaceIndexList=np.flatnonzero(masked_idx))
     wsResSum = SumSpectra(InputWorkspace=resName, OutputWorkspace=resName + "_Sum")
 
     normalise_workspace(wsResSum)
@@ -125,7 +128,8 @@ def subtractAllMassesExceptFirst(ic, ws, ncpForEachMass):
 
     wsSubMass = CloneWorkspace(InputWorkspace=ws, OutputWorkspace=ws.name() + "_Mass0")
     passDataIntoWS(dataX, dataY, dataE, wsSubMass)
-    MaskDetectors(Workspace=wsSubMass, WorkspaceIndexList=ic.maskedDetectorIdx)
+    wsMask, maskList = ExtractMask(ws)
+    MaskDetectors(Workspace=wsSubMass, MaskedWorkspace=wsMask)
     SumSpectra(
         InputWorkspace=wsSubMass.name(), OutputWorkspace=wsSubMass.name() + "_Sum"
     )
@@ -1507,7 +1511,8 @@ def extractData(ws, wsRes, ic):
 
 
 def loadInstrParsFileIntoArray(ic):
-    data = np.loadtxt(ic.InstrParsPath, dtype=str)[1:].astype(float)
+    ipFilesPath = Path(handle_config.read_config_var("caching.ipfolder"))
+    data = np.loadtxt(str(ipFilesPath / ic.ipfile), dtype=str)[1:].astype(float)
     spectra = data[:, 0]
     select_rows = np.where((spectra >= ic.firstSpec) & (spectra <= ic.lastSpec))
     instrPars = data[select_rows]

src/mvesuvio/analysis_reduction.py

@@ -502,7 +502,8 @@ def _create_means_table(self):
             self._mean_intensity_ratios,
             self._std_intensity_ratios,
         ):
-            table.addRow([label, mass, mean_width, std_width, mean_intensity, std_intensity])
+            # Explicit conversion to float required to match profiles table
+            table.addRow([label, float(mass), float(mean_width), float(std_width), float(mean_intensity), float(std_intensity)])
             self.log().notice(f"{label:6s}  {mean_width:10.5f} \u00B1 {std_width:7.5f}" + \
                 f"{mean_intensity:10.5f} \u00B1 {std_intensity:7.5f}\n")