parseltongue:process_phase_reference_data
function: process_phase_reference_data
################################################################################ # Process Phase Referencing Data def process_phase_reference_data(aips_uvdata, PhaseReferencingInfoDict): """Runs through the list of phase referencing observations to make images """ # make sure the argument is a list if(type(PhaseReferencingInfoDict) != type([0])): PhaseReferencingInfoDict = [PhaseReferencingInfoDict] # declare some local variables in case they need to be cleaned up in a # try block junk = AIPSImage('JUNKJUNKJUNKJUNK', 'JUNKCL', 1,1) split_uvdata = [junk] image_noself = junk imgdata = junk cal_data = junk del junk # Ok, what are the numbers of the gain tables which are important CL_base = Gainuse_Before_Fring CL_first_fring = aips_uvdata.table_highver('AIPS CL') +1 CL_second_fring = CL_first_fring +1 # remove any old CL tables if there was a problem if(check_table_version_valid(aips_uvdata, 'AIPS CL', CL_first_fring)): aips_uvdata.zap_table('AIPS CL', CL_first_fring) if(check_table_version_valid(aips_uvdata, 'AIPS CL', CL_second_fring)): aips_uvdata.zap_table('AIPS CL', CL_second_fring) # Clear any old SN tables if(aips_uvdata.table_highver('AIPS SN') > 0): aips_uvdata.zap_table('AIPS SN', -1) # Set up some FRING information fring_snver = 1 fring_aparm = [None, 0,0,0,0,0,0,0,0,0] fring_dparm = [None, 0,0,0,0,0,0,0,0,0] fring_aparm[1] = 3 # need at least 3 antennas for a solution fring_aparm[6] = 0 # turn most printing off fring_aparm[7] = 0 # default SNR level fring_aparm[9] = 1 # use search_list fring_dparm[1] = 2 # use small number as we only have a point-source model fring_dparm[4] = t_int fring_dparm[8] = 0 # do not zero rates or delays # define the split class splitclass = 'SPLIT' # Now loop over all pairings. for prid in PhaseReferencingInfoDict: # now, for each calibrator-target pair, run through and make # the sequence of images and statistical data try: #################################################################### # Step 1: Run Fring on the calibrator in point-source mode search_list = range(0,len(prid['Calibrator_Search_List'])) for antenna in xrange(len(search_list)): search_list[antenna] = \ antenna_dict[prid['Calibrator_Search_List'][antenna]] this_refant = search_list[0] search_list[0] = None run_fring(aips_uvdata, this_refant, search_list, prid['Calibrator_Solint_Fring'], 0, # solsub prid['Calibrator_Name'], CL_base, prid['Calibrator_Timerange'], final_flagver, Bandpass_Global, None, # image None, # ncomp None, # flux None, # smodel fring_aparm, fring_dparm, fring_snver) print 'fring done' run_clcal(aips_uvdata, CL_base, CL_first_fring, this_refant, [prid['Calibrator_Name'],prid['Target_Name']], prid['Calibrator_Name'], None, # do all timerange for these objects 'CALI', 'AMBG', snver_first=fring_snver, snver_last = fring_snver) # show the phases if(pause_after_plots): snplot('CL',CL_first_fring,'PHAS',opcode='ALSI', snuvdata=aips_uvdata,sources_use=[prid['Calibrator_Name'], prid['Target_Name']], nplots=len(aips_uvdata.antennas)) possm_2([prid['Calibrator_Name'],prid['Target_Name']], 'LL', CL_first_fring, -1, this_refant, final_flagver, bpver=Bandpass_Global) #################################################################### # Step 2: process target source to make images # split this sucker out split_uvdata = \ split_data(aips_uvdata, splitclass, 1, prid['Target_Name'], CL_first_fring, Bandpass_Global, final_flagver) # Run with robust = 8 for natural weighting robust = 8 # Now process the data to make an image and self-cal and make an # image. I need a string to uniquely describe the process result_name = prid['Target_Name'] + '.' + prid['Calibrator_Name'] + \ '.' + processing_option.__str__() + ".%.0f"%robust (statistics_noself, statistics, image_noself, imgdata, cal_data) = \ process_single_source_file_to_images( split_uvdata[0], prid['Target_Name'], result_name, robust, prid['Target_Timerange'], this_refant, prid['Target_Solint'], # seconds prid['Target_Solint_Amp'], # seconds imsize, # pixels cellsize, # arcsec prid['Target_Source_Size'], 1, # starting sequence number prid['Target_SelfCal_Iterations'], use_initial_point_source_calibration=1, save_image_plots=1, save_output_data=0 ) prid['Target_Statistics_PNSCR8'] = statistics_noself prid['Target_Statistics_PWSCR8'] = statistics # Run with robust = 0 for smaller beam size robust = 0 # Now process the data to make an image and self-cal and make an # image. I need a string to uniquely describe the process result_name = prid['Target_Name'] + '.' + prid['Calibrator_Name'] + \ '.' + processing_option.__str__() + ".%.0f"%robust (statistics_noself, statistics, image_noself, imgdata, cal_data) = \ process_single_source_file_to_images( split_uvdata[0], prid['Target_Name'], result_name, robust, prid['Target_Timerange'], this_refant, prid['Target_Solint'], # seconds prid['Target_Solint_Amp'], # seconds imsize, # pixels cellsize, # arcsec prid['Target_Source_Size'], 3, # starting sequence number prid['Target_SelfCal_Iterations'], use_initial_point_source_calibration=1, save_image_plots=1, save_output_data=0 ) prid['Target_Statistics_PNSCR0'] = statistics_noself prid['Target_Statistics_PWSCR0'] = statistics # Now zap the split data split_uvdata[0].zap() #################################################################### # Step 3: split out the calibrator to make an image to FRING with. # Then reFRING split_uvdata = \ split_data(aips_uvdata, splitclass, 1, prid['Calibrator_Name'], CL_first_fring, Bandpass_Global, final_flagver) # Run with robust = 8 for natural weighting robust = 8 # Now process the data to make an image and self-cal and make an # image. I need a string to uniquely describe the process result_name = 'tmp' (statistics_noself, statistics, image_noself, imgdata, cal_data) = \ process_single_source_file_to_images( split_uvdata[0], prid['Calibrator_Name'], result_name, robust, prid['Calibrator_Timerange'], this_refant, prid['Calibrator_Calib_Solint'], # seconds prid['Calibrator_Calib_Solint_Amp'], # seconds imsize, # pixels cellsize, # arcsec prid['Calibrator_Source_Size'], 1, # starting sequence number prid['Calibrator_SelfCal_Iterations'], use_initial_point_source_calibration=1, save_image_plots=0, save_output_data=1 # save just the self-caled image ) # zap the split data before I forget split_uvdata[0].zap() # Now fring using the new image aips_uvdata.zap_table('AIPS SN', -1) run_fring(aips_uvdata, this_refant, search_list, prid['Calibrator_Solint_Fring'], 0, # solsub prid['Calibrator_Name'], CL_base, prid['Calibrator_Timerange'], final_flagver, Bandpass_Global, imgdata, # image prid['Calibrator_Ncomp'], prid['Calibrator_Flux_Fraction']*statistics['Pixel_Max'], None, # smodel fring_aparm, fring_dparm, fring_snver) run_clcal(aips_uvdata, CL_base, CL_second_fring, this_refant, [prid['Calibrator_Name'],prid['Target_Name']], prid['Calibrator_Name'], None, # do all timerange for these objects 'CALI', 'AMBG', snver_first=fring_snver, snver_last = fring_snver) #################################################################### # Step 4: process target source to make images # split this sucker out split_uvdata = \ split_data(aips_uvdata, splitclass, 1, prid['Target_Name'], CL_second_fring, Bandpass_Global, final_flagver) # Run with robust = 8 for natural weighting robust = 8 # Now process the data to make an image and self-cal and make an # image. I need a string to uniquely describe the process result_name = prid['Target_Name'] + '.' + prid['Calibrator_Name'] + \ '.' + processing_option.__str__() + ".%.0f"%robust (statistics_noself, statistics, image_noself, imgdata, cal_data) = \ process_single_source_file_to_images( split_uvdata[0], prid['Target_Name'], result_name, robust, prid['Target_Timerange'], this_refant, prid['Target_Solint'], # seconds prid['Target_Solint_Amp'], # seconds imsize, # pixels cellsize, # arcsec prid['Target_Source_Size'], 5, # starting sequence number prid['Target_SelfCal_Iterations'], use_initial_point_source_calibration=1, save_image_plots=1, save_output_data=0 ) prid['Target_Statistics_INSCR8'] = statistics_noself prid['Target_Statistics_IWSCR8'] = statistics # Run with robust = 0 for smaller beam size robust = 0 # Now process the data to make an image and self-cal and make an # image. I need a string to uniquely describe the process result_name = prid['Target_Name'] + '.' + prid['Calibrator_Name'] + \ '.' + processing_option.__str__() + ".%.0f"%robust (statistics_noself, statistics, image_noself, imgdata, cal_data) = \ process_single_source_file_to_images( split_uvdata[0], prid['Target_Name'], result_name, robust, prid['Target_Timerange'], this_refant, prid['Target_Solint'], # seconds prid['Target_Solint_Amp'], # seconds imsize, # pixels cellsize, # arcsec prid['Target_Source_Size'], 7, # starting sequence number prid['Target_SelfCal_Iterations'], use_initial_point_source_calibration=1, save_image_plots=1, save_output_data=0 ) prid['Target_Statistics_INSCR0'] = statistics_noself prid['Target_Statistics_IWSCR0'] = statistics # Now zap the split data split_uvdata[0].zap() # Remove the new CL tables aips_uvdata.zap_table('AIPS CL', CL_first_fring) aips_uvdata.zap_table('AIPS CL', CL_second_fring) finally: if(split_uvdata[0].exists()): split_uvdata[0].zap() if(image_noself.exists()): image_noself.zap() if(imgdata.exists()): imgdata.zap() if(cal_data.exists()): cal_data.zap()
parseltongue/process_phase_reference_data.txt · Last modified: 2007/07/09 15:16 by 127.0.0.1