# ABOUT: # This is the prototype RM-synthesis pipeline intended for use on Level-5 # ASKAP data. See POSSUM Report 62 for a full description. #-----------------------------------------------------------------------------# # USAGE INSTRUCTIONS: # Execute the following Python scripts in order to create a test dataset and # run the Level-5 RM-pipeline on the data. ./0_mk_test_ascii_data.py -n PAF_MKII_Tsys.dat -f 1.0e9,1.3e9 catalogue.csv testASCIIData/ ./1_verify_ascii_data.py testASCIIData/ ./2_create_session.py -o testSessionASCII/ testASCIIData/ testASCIIData/testCat.txt testASCIIData/testCatDesc.sql #> Edit the file 'testSessionASCII/inputs.config' to modify default pipeline inputs. ./3_extract_spectra.py testSessionASCII/ ./4_do_RM-synthesis.py testSessionASCII/ ./5_do_RM-clean.py testSessionASCII/ ./6_measure_complexity.py testSessionASCII/ ./rmPipeViewer.py # OR: ./0_mk_test_image_data.py -n PAF_MKII_Tsys.dat -f 1.0e9,1.3e9 catalogue.csv testImageData/ ./1_verify_image_data.py testImageData/ ./2_create_session.py -o testSessionImage/ testImageData/ testImageData/testCat.txt testImageData/testCatDesc.sql #> Edit the file 'testSessionImage/inputs.config' to modify default pipeline inputs. ./3_extract_spectra.py testSessionImage/ ./4_do_RM-synthesis.py testSessionImage/ ./5_do_RM-clean.py testSessionImage/ ./6_measure_complexity.py testSessionImage/ ./rmPipeViewer.py # Note: a '-h' argument after most scripts will print help & usage information. x #-----------------------------------------------------------------------------# # TODO PPC: # Extractor * Set flag when source is near the edge of image or box contains NaNs. # Pipeline RM and measurements * Set flag when RM is detected near edge of spectrum. * Create a best-fit RM-thin model and subtract to get residual. TO BE PLOTTED * Implement complexity measurements based on residuals. IN PROGRESS - IN TESTING # GUI & interface * Re-write pipeline inputs tab to show driving file on left and derived parmaters on right. * Show the result values in the plotting window. * (Add a name filter to the table) * Annotate main result values on plots. * Subclass the plot control bar and add a button to hide the legends * Pipeline script to batch create publication plots and export results tables. # LONG TERM TODO: * re-write feedback for RM-clean and implement useful logging. #-----------------------------------------------------------------------------# TODO PVACAT: * Integrate new scripts to run qu-fitting and model comparison