Updated readme

README.md

@@ -1,81 +1,27 @@
 # Search package for finding and retrieving TESS/Kepler/K2 mission data
-This package is a stand-alone implementation of the lightkurve search functionalty modernized for the 2024 data environment.  
+This package is a stand-alone implementation of the lightkurve search functionalty  
 
 ## Changes Include:
-  - This redevelopment uses pandas dataframs as the back-end for storing search results and mission tables.
-  - Its cloud-first, defaulting to retrieve mast products from aws buckets where available, and returning S3 bucket URI's as part of the table results.
-  - We've replaced the TESScut search functionality querying MAST FFI products and constructing a sector list) with a tesswcs implementation to identify observed sectors
-  - We've unified TESSCut and TargetPixelFile search functionality into search_cubedata,  search_lightcurve has been renamed search_timeseries for thematic resonance.
-  - we've deprecated download_all, just use download. it wraps download_one.  
-  - TBD - replace astrocut TESScut api query with a URL based API Query?
-  - (Not Yet Implemented) The intent is to include additional memmory caching options (not implemented yet) , and potentially cacheless options.
+  - The class structure has been modified. The base class is MASTSearch. Users are intended to use mission-specific classes (KeplerSearch/K2Search/TESSSearch) to obtain mission-specific results.
+  - Result tables are saved as pandas dataframs
+  - The TESScut search functionality now uses tesswcs to identify observed sectors
+  - Data products are now generalized (timeseries contains lightcurve products, cubedata contains target pixel files and TESSCut, and dvreports contains pdfs contining data validation reports) 
+  - 'download' now defaults to the AWS cloud storage. 
+  - 'download' downloads files to disk. It no longer returns a lightkurve object. 
+
 
 
 ## Usage
   from newlk_search import search
-  result = search.search_cubedata("KIC 11904151", mission="Kepler", cadence="long")
-
+  # Get long-cadence target pixel files for Kepler 
+  result = search.KeplerSearch("KIC 11904151", cadence="long").cubedata
+  # Search for TESS TPFs by coordinate
   result = search.search_timeseries("297.5835, 40.98339", quarter=6, author="Kepler")
 
   result.download()
 
-  ## Documentation 
-  this should probably exist
 
   ## Contact
-  Please Don't
-
-Mermaid Test
-```mermaid
-graph TD
-subgraph sg1[class Search_Mission]
-Search_Mission --> Search_Timeseries
-Search_Mission --> Search_Cubedata
-
-Search_Timeseries --> Search_Timeseries_MissionProducts
-Search_Timeseries --> Search_Timeseries_HLSP
-
-Search_Cubedata --> Search_CubeData_MissionProducts
-Search_Cubedata --> Search_CubeData_HLSP
-end
-
-subgraph  sg2[class Search_Kepler]
-Search_Kepler --> SK_T[Search_Timeseries]
-SK_T --> SK_T_M[Search_Timeseries_MissionProducts]
-SK_T --> SK_T_H[Search_Timeseries_HLSP]
-
-Search_Kepler --> SK_C[Search_Cubedata]
-SK_C --> SK_TP[Search_TargetPixelFile]
-SK_C --> SK_TC[Search_TESSCut]
-end
-
-subgraph  sg3[class Search_K2]
-Search_K2 --> SK2_T[Search_Timeseries]
-SK2_T --> SK2_T_M[Search_Timeseries_MissionProducts]
-SK2_T --> SK2_T_H[Search_Timeseries_HLSP]
-
-Search_K2 --> SK2_C[Search_Cubedata]
-SK2_C --> SK2_TP[Search_TargetPixelFile]
-SK2_C --> SK2_TC[Search_TESSCut]
-end
-
-subgraph  sg4[class Search_TESS]
-Search_TESS --> ST_T[Search_Timeseries]
-ST_T --> ST_T_M[Search_Timeseries_MissionProducts]
-ST_T --> ST_T_H[Search_Timeseries_HLSP]
-
-Search_TESS --> ST_C[Search_Cubedata]
-ST_C --> ST_TP[Search_TargetPixelFile]
-ST_C --> ST_TC[Search_TESSCut]
-
-ST_TP --> ST_TP_M[Search_TPF_MissionProducts]
-ST_TP --> ST_TP_H[Search_TPF_HLSP]
+  If you encounter a problem, please open an issue.
 
-ST_TC --> ST_TC_M[Search_TESSCut_MissionProducts]
-ST_TC --> ST_TC_H[Search_TESSCut_HLSP]
-end
 
-sg1 --> sg2
-sg1 --> sg3
-sg1 --> sg4
-```