] pool = Pool(7) result = pool.map(run, plt) pool.close() pool.join() uvfmeas = m(f"uvfmeas vis={','.join([f'{mu.secondary}.{freq}' for freq in FREQS])} "\ f"stokes=i log=secondary_uvfmeas_both_log.txt "\ f"device=secondary_uvfmeas_both.png/PNG").run() logger.log(logging.INFO, uvfmeas) # import sys # sys.exit() # Acquire information of the fit to the model of secondary fit_pack = mu.model_secondary(if1='secondary_uvfmeas_7700_log.txt', if2='secondary_uvfmeas_9500_log.txt') # Now move things into a directory structure mu.mv_uv('notsys') # Reload the data with Tsys and use model as reference flux model for index, freq in enumerate(FREQS): ifsel = index + 1 primary = f"{mu.primary}.{freq}" secondary = f"{mu.secondary}.{freq}" mosaic = f"{mu.science}.{freq}" # Obtain mflux string from the fitpack information mfflux = mu.mfcal_flux(fit_pack, ifcal=ifsel) # Load in the data
uvsplit = mu.mirstr(f"uvsplit vis={uv} options=mosaic").run() print(uvsplit) # Automated flagging pgflag = mu.mirstr(f"pgflag vis={secondary} command='<b' stokes=i,q,u,v flagpar=8,5,5,3,6,3 options=nodisp").run() print(pgflag) pgflag = mu.mirstr(f"pgflag vis={secondary} command='<b' stokes=i,v,q,u flagpar=8,2,2,3,6,3 options=nodisp").run() print(pgflag) pgflag = mu.mirstr(f"pgflag vis={secondary} command='<b' stokes=i,v,u,q flagpar=8,2,2,3,6,3 options=nodisp").run() print(pgflag) sec_model = mu.model_secondary() mfflux = mu.mfcal_flux(sec_model, ifcal=1) print(mfflux) # Primary calibration mfcal = mu.mirstr(f'mfcal vis={secondary} flux={mfflux} interval=0.1').run() gpcal = mu.mirstr(f"gpcal vis={secondary} interval=0.1 nfbin={NFBIN} flux={mfflux.split(',')[0]} spec={mfflux.split(',')[1]},{mfflux.split(',')[2]} options=xyvary,qusolve").run() print(mfcal) print(gpcal) # Automated flagging pgflag = mu.mirstr(f"pgflag vis={secondary} command='<b' stokes=i,q,u,v flagpar=8,5,5,3,6,3 options=nodisp").run() print(pgflag)