generated from erosita/uds
spectra
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240
scripts/04_spectrum_pn.py
Executable file
240
scripts/04_spectrum_pn.py
Executable file
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#!/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'
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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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work_dir = init_work_dir(obsid)
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os.chdir(work_dir)
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eventfile=f'{products_dir}/{obsid}/EPIC_pn_gtiFilteredEvts.ds'
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if(os.path.isfile(eventfile)==False):
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print("*** run 02_filter_flares_pn.py ***")
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sys.exit()
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# EPIC_pn_gtiFilteredEvts.ds
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search_str = f'{products_dir}/{obsid}/EPIC_PN_Image_{obsid}.fit'
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print(search_str)
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epfiles = glob.glob(search_str)
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if not (epfiles):
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print("*** run 02_filter_flares_pn.py ***")
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sys.exit()
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out_IMFile = epfiles[0]
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# Visualize the image with ds9
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d = pyds9.DS9()
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d.set("file "+out_IMFile)
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d.set('cmap bb')
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d.set('scale log')
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#d.set(f"region {ds9reg_dir}/arches.reg")
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src_fn=f'{ds9reg_dir}/{obsid}/src.reg'
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if(os.path.isfile(src_fn)==True):
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d.set(f"region {src_fn}")
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bkg_fn=f'{ds9reg_dir}/{obsid}/bkg.reg'
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if(os.path.isfile(bkg_fn)==True):
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d.set(f"region {bkg_fn}")
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reply = input(f"{obsid}: Proceed to make spectrum/lightcurve? [y/[n]] ")
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if reply!='y':
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continue
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print(d.get("regions"))
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# Extract the relevant information from the ds9 regions.
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region1=(re.split("circle|annulus",d.get("regions").partition("physical")[2]))[1].replace('(','').replace(')','').replace('#',',')
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region2=(re.split("circle|annulus",d.get("regions").partition("physical")[2]))[2].replace('(','').replace(')','').replace('#',',')
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print("Identified first region: ", region1)
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print("Identified second region: ", region2)
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#print("region1 "+region1.partition("color")[2].replace('=','').replace('\n',''))
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#print("region2 "+region2.partition("color")[2].replace('=','').replace('\n',''))
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# Identify source and background regions using the 'white' color.
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c1=region1.partition("color")[2].replace('=','').replace('\n','')
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print("Region1 color: "+c1)
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if(c1=='white'):
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regionsrc = region1
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regionbkg = region2
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else:
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regionsrc = region2
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regionbkg = region1
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# Save and print selected region coordinates.
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x_source = regionsrc.split(",")[0].replace('\n','')
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y_source = regionsrc.split(",")[1].replace('\n','')
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r_source = regionsrc.split(",")[2].replace('\n','')
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print("The coordinates of the selected source region are: \n")
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print(" x_source = ", x_source, "(physical)")
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print(" y_source = ", y_source, "(physical)")
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print(" r_source = ", r_source, "(physical) \n")
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x_bkg = regionbkg.split(",")[0].replace('\n','')
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y_bkg = regionbkg.split(",")[1].replace('\n','')
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r_bkg = regionbkg.split(",")[2].replace('\n','')
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print("The coordinates of the selected background region are: \n")
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print(" x_bkg = ", x_bkg, "(physical)")
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print(" y_bkg = ", y_bkg, "(physical)")
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print(" r_bkg = ", r_bkg, "(physical) \n")
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# If the background is an annulus, save and print R2.
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if "annulus" in str(d.get("regions")):
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r2_bkg = regionbkg.split(",")[3].replace('\n','')
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print(" r2_bkg = ", r2_bkg, "(physical)")
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#########################################
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# Extract the source region light curve #
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#########################################
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# Define some parameters for filtering the event file and define the light curve binning
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q_flag = "#XMMEA_EP" # Quality flag for EPIC pn
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n_pattern = 4 # Pattern selection
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pn_pi_min = 200. # Low energy range eV
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pn_pi_max = 10000. # High energy range eV
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lc_bin = 100 # Light curve bin in secs
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# Define the output ligthcurve file name
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in_LCSRCFile = work_dir+'/EPIC_PN_source_lightcurve.lc' # Name of the output source light curve
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# SAS Command
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cmd = "evselect" # SAS task to be executed
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# Arguments of SAS Command
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expression = f'{q_flag}&&(PATTERN<={n_pattern})&&((X,Y) IN circle({x_source},{y_source},{r_source}))&&(PI in [{pn_pi_min}:{pn_pi_max}])' # event filter expression
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inargs = [f'table={eventfile}','energycolumn=PI','withrateset=yes',f'rateset={in_LCSRCFile}',
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f'timebinsize={lc_bin}','maketimecolumn=yes','makeratecolumn=yes',f'expression={expression}']
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print(" Filter expression to use: "+expression+" \n")
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print(" SAS command to be executed: "+cmd+", with arguments; \n")
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# Execute the SAS task with the parameters to produce the source region light curve
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w(cmd, inargs).run()
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# Inspect light curve
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plt.figure(figsize=(20,8)) # Size of figure
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plotLC(plt,pn_threshold,in_LCSRCFile) # Plot source region light curve
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plt.legend()
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plt.show()
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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" # Quality flag for EPIC pn
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n_pattern = 4 # Pattern selection
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# Define the output ligthcurve file name
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in_SPSRCFile = work_dir+'/EPIC_PN_source_spectrum.fits' # Name of the output source spectrum
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# SAS Command
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cmd = "evselect" # SAS task to be executed
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# Arguments of SAS Command
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expression = f'{q_flag}&&(PATTERN<={n_pattern})&&((X,Y) IN circle({x_source},{y_source},{r_source}))' # event filter expression
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inargs = [f'table={eventfile}','withspectrumset=yes',f'spectrumset={in_SPSRCFile}',
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'energycolumn=PI','spectralbinsize=5','withspecranges=yes','specchannelmin=0',
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'specchannelmax=20479',f'expression={expression}']
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print(" Filter expression to use: "+expression+" \n")
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print(" SAS command to be executed: "+cmd+", with arguments; \n")
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w(cmd, inargs).run()
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# Extract the background region spectrum with the same criteria
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# Define the output ligthcurve file name
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in_SPBKGFile = work_dir+'/EPIC_PN_background_spectrum.fits' # Name of the output background spectrum
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# SAS Command
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cmd = "evselect" # SAS task to be executed
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# Arguments of SAS Command
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expression = f'{q_flag}&&(PATTERN<={n_pattern})&&((X,Y) IN circle({x_bkg},{y_bkg},{r_bkg}))' # event filter expression
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inargs = [f'table={eventfile}','withspectrumset=yes',f'spectrumset={in_SPBKGFile}',
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'energycolumn=PI','spectralbinsize=5','withspecranges=yes','specchannelmin=0',
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'specchannelmax=20479',f'expression={expression}']
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print(" Filter expression to use: "+expression+" \n")
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print(" SAS command to be executed: "+cmd+", with arguments; \n")
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w(cmd, inargs).run()
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w("backscale", [f'spectrumset={in_SPSRCFile}',f'badpixlocation={eventfile}']).run()
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w("backscale", [f'spectrumset={in_SPBKGFile}',f'badpixlocation={eventfile}']).run()
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in_RESPFile = work_dir+'/EPIC_PN.rmf' # Name of the output redistribution
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w("rmfgen", [f'spectrumset={in_SPSRCFile}',f'rmfset={in_RESPFile}']).run()
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in_ARFFile = work_dir+'/EPIC_PN.arf' # Name of the output ancillary
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cmd = "arfgen" # SAS task to be executed
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print(" Checking for Response File ..... \n")
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# Check if RESP file is available.
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if os.path.isfile(in_RESPFile):
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print ("File "+in_RESPFile+" exists. \n")
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else:
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print ("File "+in_RESPFile+" does not exist, please check. \n")
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sys.exit()
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# Arguments of SAS Command
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inargs = [f'spectrumset={in_SPSRCFile}',f'arfset={in_ARFFile}',
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'withrmfset=yes',f'rmfset={in_RESPFile}',f'badpixlocation={eventfile}','detmaptype=psf']
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w(cmd, inargs).run()
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# rebin the spectra and link associated files
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in_GRPFile = work_dir+'/EPIC_PN_spectrum_grp.fits' # Name of the output specgruop
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inargs = [f'spectrumset={in_SPSRCFile}','mincounts=30','oversample=3',
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f'rmfset={in_RESPFile}',f'arfset={in_ARFFile}',
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f'backgndset={in_SPBKGFile}',f'groupedset={in_GRPFile}']
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w("specgroup", inargs).run()
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