generated from erosita/uds
192 lines
8.0 KiB
Python
Executable File
192 lines
8.0 KiB
Python
Executable File
#!/usr/bin/env python
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from pysas.wrapper import Wrapper as w
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import os, sys
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from os.path import dirname
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import inspect
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import glob
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import os.path
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from os import path
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import subprocess
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import numpy as np
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import matplotlib.pyplot as plt
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from astropy.io import fits
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from astropy.table import Table
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from matplotlib.colors import LogNorm
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import re
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import pyds9
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import arches
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from arches.utils import *
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from arches.config import *
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root_path=dirname(dirname(dirname(inspect.getfile(arches))))
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print("Arches root path: {}".format(root_path))
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archive_dir=root_path+'/data/archive'
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events_dir=root_path+'/data/processed'
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products_dir=root_path+'/products/sas'
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ds9reg_dir=root_path+'/data/ds9reg'
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create_folder(products_dir)
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inargs = ['--version']
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t = w('sasver', inargs)
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t.run()
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files = glob.glob(archive_dir+'/*')
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for obsid in files:
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obsid = os.path.basename(obsid)
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if(obsid in skip):
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continue
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work_dir = init_work_dir(obsid, products_dir=products_dir)
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os.chdir(work_dir)
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#
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# Create QPB
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# https://www.cosmos.esa.int/web/xmm-newton/sas-thread-background
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#
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attfiles = glob.glob(events_dir+f'/{obsid}/*{obsid}_AttHk.ds')
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if(attfiles):
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print(f"*** {attfiles} ***")
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else:
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print("AttHk?")
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sys.exit()
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attfile = attfiles[0]
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if not os.path.isfile(attfile):
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print ("File "+attfile+" does not exist, please check. \n")
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sys.exit()
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spec=[]
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bkg=[]
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resp=[]
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arf=[]
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#for imos in [1,2]:
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for key in ['MOS1','MOS2','PN']:
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evtfile = get_first_file(events_dir+f'/{obsid}/*{obsid}_E{key}*_ImagingEvts.ds')
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# Run the SAS task evqpb over each one of these event files.
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evqpb_outset=work_dir+f'/EPIC_{key}_QPB.fits' # Name of the output file
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inargs = [f'table={evtfile}', f'attfile={attfile}',
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f'outset={evqpb_outset}',
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f'exposurefactor=2.0',]
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w("evqpb", inargs).run()
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gti=f'EPIC_{key}_gti.fit'
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expression=f'gti({gti},TIME)'
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# filter the EPIC event files to create cleaned and filtered for
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# flaring particle background event files for your observation
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sci_clean=work_dir+f'/EPIC_{key}_filtered.fits' # Name of the output file
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inargs = [f'table={evtfile}', 'withfilteredset=yes',
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f'filteredset={sci_clean}',
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'destruct=yes','keepfilteroutput=true',
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f'expression={expression}']
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w("evselect", inargs).run()
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# Use the same expression to filter the FWC event files:
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qpb_clean=work_dir+f'/EPIC_{key}_QPB_clean.fits' # Name of the output file
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inargs = [f'table={evqpb_outset}', 'withfilteredset=yes',
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f'filteredset={qpb_clean}',
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'destruct=yes','keepfilteroutput=true',
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f'expression={expression}']
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w("evselect", inargs).run()
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if(key=='PN'):
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expression='(#XMMEA_EP)&&(PATTERN<=4)&&(PI>=200)&&(PI<=12000)'
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else:
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expression='(#XMMEA_EM)&&(PATTERN<=12)&&(PI>=200)&&(PI<=12000)'
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sci_image=work_dir+f'/EPIC_{key}_sci_image.fits' # Name of the output file
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# Extract an image for the science exposure
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inargs = [f'table={sci_clean}', f'expression={expression}',
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'imagebinning=binSize', f'imageset={sci_image}',
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'withimageset=yes','xcolumn=X', 'ycolumn=Y',
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'ximagebinsize=80', 'yimagebinsize=80',
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]
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w("evselect", inargs).run()
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qpb_image=work_dir+f'/EPIC_{key}_qpb_image.fits' # Name of the output file
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# Extract an image for the FWC exposure
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inargs = [f'table={qpb_clean}', f'expression={expression}',
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'imagebinning=binSize', f'imageset={qpb_image}',
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'withimageset=yes','xcolumn=X', 'ycolumn=Y',
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'ximagebinsize=80', 'yimagebinsize=80','zcolumn=EWEIGHT',
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]
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w("evselect", inargs).run()
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# Subtract background
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cor_image=work_dir+f'/EPIC_{key}_cor_image.fits' # Name of the output file
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cmd = ['farith', f'{sci_image}', f'{qpb_image}', f'{cor_image}', 'SUB',
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'copyprime=yes',
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'clobber=yes']
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result = subprocess.run(cmd, capture_output=True, text=True, check=True)
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continue
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#
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# How to use the FWC event files for spectra generation
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#
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src_fn=f'{ds9reg_dir}/{obsid}/src.reg'
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bkg_fn=f'{ds9reg_dir}/{obsid}/bkg.reg'
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x_source,y_source,r_source,x_bkg,y_bkg,r_bkg,r2_bkg = get_ds9_regions(sci_image, src_fn, bkg_fn)
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######################################
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# Extract the source region spectrum #
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######################################
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# Define some parameters for filtering the event file
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q_flag = "#XMMEA_EP" if (key=='PN') else "#XMMEA_EM" # Quality flag for EPIC pn
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n_pattern = 4 if (key=='PN') else 12 # Pattern selection
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# for the source region of the science exposure
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sci_spec_file = work_dir+f'/EPIC_{key}_source_spectrum.fits' # Name of the output source spectrum
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expression = f'{q_flag}&&(PATTERN<={n_pattern})&&((X,Y) IN circle({x_source},{y_source},{r_source}))'
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inargs = [f'table={sci_clean}','withspectrumset=yes',f'spectrumset={sci_spec_file}',
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'energycolumn=PI','spectralbinsize=5','withspecranges=yes','specchannelmin=0',
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'specchannelmax=11999',f'expression={expression}']
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w("evselect", inargs).run()
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# for the background region of the science exposure
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sci_bkg_file = work_dir+f'/EPIC_{key}_background_spectrum.fits'
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if(r2_bkg==None):
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expression = f'{q_flag}&&(PATTERN<={n_pattern})&&((X,Y) IN circle({x_bkg},{y_bkg},{r_bkg}))'
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else:
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expression = f'{q_flag}&&(PATTERN<={n_pattern})&&((X,Y) IN annulus({x_bkg},{y_bkg},{r_bkg},{r2_bkg}))'
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inargs = [f'table={sci_clean}','withspectrumset=yes',f'spectrumset={sci_bkg_file}',
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'energycolumn=PI','spectralbinsize=5','withspecranges=yes','specchannelmin=0',
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'specchannelmax=11999',f'expression={expression}']
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w("evselect", inargs).run()
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# for the source region of the science exposure
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qpb_spec_file = work_dir+f'/EPIC_{key}_qpb_source_spectrum.fits' # Name of the output source spectrum
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expression = f'{q_flag}&&(PATTERN<={n_pattern})&&((X,Y) IN circle({x_source},{y_source},{r_source}))'
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inargs = [f'table={qpb_clean}','withspectrumset=yes',f'spectrumset={qpb_spec_file}',
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'energycolumn=PI','spectralbinsize=5','withspecranges=yes','specchannelmin=0',
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'specchannelmax=11999',f'expression={expression}', 'zcolumn=EWEIGHT',]
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w("evselect", inargs).run()
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# for the source region of the science exposure
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qpb_bkg_file = work_dir+f'/EPIC_{key}_qpb_background_spectrum.fits' # Name of the output source spectrum
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if(r2_bkg==None):
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expression = f'{q_flag}&&(PATTERN<={n_pattern})&&((X,Y) IN circle({x_bkg},{y_bkg},{r_bkg}))'
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else:
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expression = f'{q_flag}&&(PATTERN<={n_pattern})&&((X,Y) IN annulus({x_bkg},{y_bkg},{r_bkg},{r2_bkg}))'
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inargs = [f'table={qpb_clean}','withspectrumset=yes',f'spectrumset={qpb_bkg_file}',
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'energycolumn=PI','spectralbinsize=5','withspecranges=yes','specchannelmin=0',
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'specchannelmax=11999',f'expression={expression}', 'zcolumn=EWEIGHT',]
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w("evselect", inargs).run()
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"""
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By using the zcolumn parameter in the generation of the spectra for the FWC exposure,
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we ensure that the produced FWC spectra are correctly scaled for the ratio of exposure times
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between science and FWC exposures. By doing so, the FWC spectra are ready to be
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subtracted from the science spectra.
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"""
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#sys.exit()
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