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This commit is contained in:
Roman Krivonos
2025-10-28 00:11:18 +03:00
parent 22c164cd41
commit 777c92ef2e
6 changed files with 526 additions and 70 deletions
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16
arches/arches/config.py
View File

@@ -23,3 +23,19 @@ Radius=15"
"""
skip=['0862471401','0862471501','0862470501']
# energy bands taken from Tatischeff 2012
emin=[
'2000', # continuum, 2-4 keV
'4170', # continuum, 4.17-5.86 keV (T12)
'6300', # 6.4 keV line, 6.3-6.48 keV (T12)
'6564', # 6.7 keV line, 6.564-6.753 keV (T12)
'8000', # high-energy continuum, 8-12 keV
]
emax=[
'4000',
'5860',
'6480',
'6753',
'12000',
]

270
arches/arches/utils.py
View File

@@ -15,6 +15,7 @@ from pathlib import Path
import pandas
import pickle
import pyds9
import subprocess
from os.path import dirname
import inspect
@@ -27,6 +28,7 @@ from astropy.coordinates import SkyCoord # High-level coordinates
from astropy.coordinates import ICRS, Galactic, FK4, FK5 # Low-level frames
from astropy.coordinates import Angle, Latitude, Longitude # Angles
from astropy.time import Time, TimeDelta, TimezoneInfo, TimeFromEpoch
from astropy.convolution import interpolate_replace_nans
import statistics
import shutil
@@ -63,6 +65,12 @@ def remove_file(filename):
def move_files(pattern, destination):
for file in glob.glob(pattern):
shutil.move(file, os.path.join(destination,file))
def test_file(fn):
if not (os.path.isfile(fn)==True):
print(f'requested filename {fn} is not found')
cwd = os.getcwd()
print(f"Current directory: {cwd}")
sys.exit()
def get_first_file(pattern):
files = glob.glob(pattern)
@@ -541,3 +549,265 @@ def get_ds9_regions(image, src_fn, bkg_fn):
r2_bkg = regionbkg.split(",")[3].replace('\n','')
print(" r2_bkg = ", r2_bkg, "(physical, annulus)")
return x_source,y_source,r_source,x_bkg,y_bkg,r_bkg,r2_bkg
def run_evqpb(key, work_dir=None, evtfile=None, attfile=None, pimin=[200,], pimax=[12000,], label=['',], exposurefactor=10.0):
test_file(evtfile)
test_file(attfile)
# Run the SAS task evqpb over each one of _original_ event files.
evqpb_outset=work_dir+f'/EPIC_{key}_QPB.fits' # Name of the output file
inargs = [f'table={evtfile}', f'attfile={attfile}',
f'outset={evqpb_outset}',
f'exposurefactor={exposurefactor}',]
w("evqpb", inargs).run()
gti=f'EPIC_{key}_gti.fit'
test_file(gti)
expression=f'gti({gti},TIME)'
# filter the EPIC event files to create cleaned and filtered for
# flaring particle background event files for your observation
sci_clean=work_dir+f'/EPIC_{key}_filtered.fits' # Name of the output file
inargs = [f'table={evtfile}', 'withfilteredset=yes',
f'filteredset={sci_clean}',
'destruct=yes','keepfilteroutput=true',
f'expression={expression}']
w("evselect", inargs).run()
# Use the same expression to filter the FWC event files:
qpb_clean=work_dir+f'/EPIC_{key}_QPB_clean.fits' # Name of the output file
inargs = [f'table={evqpb_outset}', 'withfilteredset=yes',
f'filteredset={qpb_clean}',
'destruct=yes','keepfilteroutput=true',
f'expression={expression}']
w("evselect", inargs).run()
for idx, lab in enumerate(label):
if(key=='PN'):
expression=f'(#XMMEA_EP)&&(PATTERN<=4)&&(PI>={pimin[idx]})&&(PI<={pimax[idx]})'
else:
expression=f'(#XMMEA_EM)&&(PATTERN<=12)&&(PI>={pimin[idx]})&&(PI<={pimax[idx]})'
print(lab,expression)
sci_image=work_dir+f'/EPIC_{key}_sci_image{lab}.fits' # Name of the output file
# Extract an image for the science exposure
inargs = [f'table={sci_clean}', f'expression={expression}',
'imagebinning=binSize', f'imageset={sci_image}',
'withimageset=yes','xcolumn=X', 'ycolumn=Y',
'ximagebinsize=80', 'yimagebinsize=80',
]
w("evselect", inargs).run()
qpb_image=work_dir+f'/EPIC_{key}_qpb_image{lab}.fits' # Name of the output file
# Extract an image for the FWC exposure
inargs = [f'table={qpb_clean}', f'expression={expression}',
'imagebinning=binSize', f'imageset={qpb_image}',
'withimageset=yes','xcolumn=X', 'ycolumn=Y',
'ximagebinsize=80', 'yimagebinsize=80','zcolumn=EWEIGHT',
]
w("evselect", inargs).run()
#hdul = fits.open(qpb_image)
#primary_hdu = hdul[0]
#qpb_data = hdul[0].data
#qpb_header = hdul[0].header
#hdul.close()
#result = interpolate_replace_nans(image, kernel)
# -- Subtract background --
# skip, due to low statistics
"""
cor_image=work_dir+f'/EPIC_{key}_cor_image{lab}.fits' # Name of the output file
cmd = ['farith', f'{sci_image}', f'{qpb_image}', f'{cor_image}', 'SUB',
'copyprime=yes',
'clobber=yes']
result = subprocess.run(cmd, capture_output=True, text=True, check=True)
"""
def run_mosaic(outfile_cts=None,outfile_qpb=None,outfile_exp=None,
outfile_sub=None,outfile_flx=None,outfile_pix=None,
cts=None,qpb=None,exp=None,nn=3,devmax=5.0,cutbox=100):
ref_crd = SkyCoord(arches_ra, arches_dec, frame=FK5(), unit="deg")
nn2=nn*nn
print(outfile_cts)
print(cts[0])
print(exp[0])
# take first image as reference
ref_hdul = fits.open(cts[0])
ref_data = ref_hdul[0].data
ref_header = ref_hdul[0].header
ref_hdul.close()
ref_wcs = WCS(ref_header)
(nx,ny) = ref_data.shape
map_flx = np.zeros(ref_data.shape,dtype=np.float64)
map_cts = np.zeros(ref_data.shape,dtype=np.float64)
map_qpb = np.zeros(ref_data.shape,dtype=np.float64)
map_exp = np.zeros(ref_data.shape,dtype=np.float64)
map_pix = np.zeros(ref_data.shape,dtype=np.float64) # number of subpixels inside
# take reference exposure
exp_hdul = fits.open(exp[0])
exp_data = exp_hdul[0].data
exp_header = exp_hdul[0].header
exp_hdul.close()
exp_wcs = WCS(exp_header)
"""
for row_index in range(len(ref_data)):
for col_index in range(len(ref_data[row_index])):
refx, refy = ref_wcs.world_to_pixel(ref_crd)
if(np.absolute(refx-row_index)>cutbox):
continue
if(np.absolute(refy-col_index)>cutbox):
continue
sky = ref_wcs.pixel_to_world(row_index, col_index)
exp_xx, exp_yy = exp_wcs.world_to_pixel(sky)
exp_x = int(np.round(exp_xx))
exp_y = int(np.round(exp_yy))
if not (exp_data[exp_y, exp_x]>0):
continue
map_cts[col_index][row_index]=1.0
sep_arcmin = sky.separation(ref_crd).arcmin
if(sep_arcmin > devmax):
continue
map_cts[col_index][row_index]=2.0
ref_hdul[0].data=map_cts
ref_hdul.writeto(outfile_cts,overwrite=True)
sys.exit()
"""
for idx,in_cts in enumerate(cts):
#if not (idx==2):
# continue
hdul0 = fits.open(in_cts)
c_data = hdul0[0].data
c_header = hdul0[0].header
c_wcs = WCS(c_header)
hdul0.close()
print(f"{in_cts} filter {c_header['FILTER']}")
hdul0 = fits.open(qpb[idx])
q_data = hdul0[0].data
q_header = hdul0[0].header
q_wcs = WCS(q_header)
hdul0.close()
hdul0 = fits.open(exp[idx])
e_data = hdul0[0].data
e_header = hdul0[0].header
e_wcs = WCS(e_header)
hdul0.close()
print(exp[idx])
xx, yy = c_wcs.world_to_pixel(ref_crd)
ref_x = int(np.rint(xx))
ref_y = int(np.rint(yy))
xmin = ref_x - cutbox
xmax = ref_x + cutbox
ymin = ref_y - cutbox
ymax = ref_y + cutbox
if(xmin<0):
xmin=0
if(xmax>=nx):
xmax=nx
if(ymin<0):
ymin=0
if(ymax>=ny):
ymax=ny
#for row_index in range(len(c_data)):
# for col_index in range(len(c_data[row_index])):
for row_index in range(xmin,xmax):
for col_index in range(ymin,ymax):
c_sky = c_wcs.pixel_to_world(row_index, col_index)
exp_xx, exp_yy = e_wcs.world_to_pixel(c_sky)
exp_x = int(np.rint(np.float64(exp_xx)))
exp_y = int(np.rint(np.float64(exp_yy)))
if not (e_data[exp_y, exp_x]>0):
continue
sep_arcmin = c_sky.separation(ref_crd).arcmin
if(sep_arcmin > devmax):
continue
#xx, yy = ref_wcs.world_to_pixel(c_sky)
#refx = int(np.round(xx))
#refy = int(np.round(yy))
# do subpixeling
for ii in range(nn):
for jj in range(nn):
xx0=np.float64(row_index)-0.5+(np.float64(ii+1)-0.5)/np.float64(nn)
yy0=np.float64(col_index)-0.5+(np.float64(jj+1)-0.5)/np.float64(nn)
subpix_sky = c_wcs.pixel_to_world(xx0, yy0)
sub_xx, sub_yy = ref_wcs.world_to_pixel(subpix_sky)
refx = np.int32(np.rint(np.float64(sub_xx)))
refy = np.int32(np.rint(np.float64(sub_yy)))
exp_xx, exp_yy = e_wcs.world_to_pixel(subpix_sky)
exp_x = np.int32(np.rint(np.float64(exp_xx)))
exp_y = np.int32(np.rint(np.float64(exp_yy)))
if (refx>=0 and refx<nx and refy>=0 and refy<ny):
map_cts[refy][refx]+=float(c_data[col_index][row_index])/nn2
map_qpb[refy][refx]+=float(q_data[col_index][row_index])/nn2
map_pix[refy][refx]+=1.0/nn2
map_exp[refy][refx]+=np.float64(e_data[exp_y][exp_x])/nn2
# Convert summed sky back to normal units
for x in range(nx):
for y in range(ny):
if(map_exp[y][x]>0):
map_flx[y][x]=(map_cts[y][x]-map_qpb[y][x])/map_exp[y][x]
map_cts[y][x]=map_cts[world_to_pixely][x]/map_pix[y][x]
map_qpb[y][x]=map_qpb[y][x]/map_pix[y][x]
map_exp[y][x]=map_exp[y][x]/map_pix[y][x]
else:
map_flx[y][x]=0.0
if(outfile_pix):
ref_hdul[0].data=map_pix
ref_hdul.writeto(outfile_pix,overwrite=True)
ref_hdul[0].data=map_cts
ref_hdul.writeto(outfile_cts,overwrite=True)
ref_hdul[0].data=map_exp
ref_hdul.writeto(outfile_exp,overwrite=True)
ref_hdul[0].data=map_qpb
ref_hdul.writeto(outfile_qpb,overwrite=True)
ref_hdul[0].data=map_flx
ref_hdul.writeto(outfile_flx,overwrite=True)
#sys.exit()
"""
cmd = ['farith', f'{outfile_cts}', f'{outfile_qpb}', f'{outfile_sub}', 'SUB',
'copyprime=yes', 'clobber=yes']
result = subprocess.run(cmd, capture_output=True, text=True, check=True)
cmd = ['farith', f'{outfile_sub}', f'{outfile_exp}', f'{outfile_rat}', 'DIV',
'copyprime=yes', 'clobber=yes']
result = subprocess.run(cmd, capture_output=True, text=True, check=True)
"""

3
data/FWC/README.md Normal file
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@@ -0,0 +1,3 @@
Files taken from here:
https://www.cosmos.esa.int/web/xmm-newton/filter-closed

79
scripts/06_sas_QPB.py
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@@ -52,81 +52,22 @@ for obsid in files:
# https://www.cosmos.esa.int/web/xmm-newton/sas-thread-background
#
attfiles = glob.glob(events_dir+f'/{obsid}/*{obsid}_AttHk.ds')
if(attfiles):
print(f"*** {attfiles} ***")
else:
print("AttHk?")
sys.exit()
attfile = get_first_file(events_dir+f'/{obsid}/*{obsid}_AttHk.ds')
attfile = attfiles[0]
if not os.path.isfile(attfile):
print ("File "+attfile+" does not exist, please check. \n")
sys.exit()
spec=[]
bkg=[]
resp=[]
arf=[]
#for imos in [1,2]:
for key in ['MOS1','MOS2','PN']:
evtfile = get_first_file(events_dir+f'/{obsid}/*{obsid}_E{key}*_ImagingEvts.ds')
# Run the SAS task evqpb over each one of these event files.
evqpb_outset=work_dir+f'/EPIC_{key}_QPB.fits' # Name of the output file
inargs = [f'table={evtfile}', f'attfile={attfile}',
f'outset={evqpb_outset}',
f'exposurefactor=2.0',]
w("evqpb", inargs).run()
# first element contains all energies
label=['',]
pimin=[200,]
pimax=[12000,]
for idx,e1 in enumerate(emin):
label.append(f"_{idx}")
pimin.append(emin[idx])
pimax.append(emax[idx])
gti=f'EPIC_{key}_gti.fit'
expression=f'gti({gti},TIME)'
# filter the EPIC event files to create cleaned and filtered for
# flaring particle background event files for your observation
sci_clean=work_dir+f'/EPIC_{key}_filtered.fits' # Name of the output file
inargs = [f'table={evtfile}', 'withfilteredset=yes',
f'filteredset={sci_clean}',
'destruct=yes','keepfilteroutput=true',
f'expression={expression}']
w("evselect", inargs).run()
# Use the same expression to filter the FWC event files:
qpb_clean=work_dir+f'/EPIC_{key}_QPB_clean.fits' # Name of the output file
inargs = [f'table={evqpb_outset}', 'withfilteredset=yes',
f'filteredset={qpb_clean}',
'destruct=yes','keepfilteroutput=true',
f'expression={expression}']
w("evselect", inargs).run()
if(key=='PN'):
expression='(#XMMEA_EP)&&(PATTERN<=4)&&(PI>=200)&&(PI<=12000)'
else:
expression='(#XMMEA_EM)&&(PATTERN<=12)&&(PI>=200)&&(PI<=12000)'
sci_image=work_dir+f'/EPIC_{key}_sci_image.fits' # Name of the output file
# Extract an image for the science exposure
inargs = [f'table={sci_clean}', f'expression={expression}',
'imagebinning=binSize', f'imageset={sci_image}',
'withimageset=yes','xcolumn=X', 'ycolumn=Y',
'ximagebinsize=80', 'yimagebinsize=80',
]
w("evselect", inargs).run()
qpb_image=work_dir+f'/EPIC_{key}_qpb_image.fits' # Name of the output file
# Extract an image for the FWC exposure
inargs = [f'table={qpb_clean}', f'expression={expression}',
'imagebinning=binSize', f'imageset={qpb_image}',
'withimageset=yes','xcolumn=X', 'ycolumn=Y',
'ximagebinsize=80', 'yimagebinsize=80','zcolumn=EWEIGHT',
]
w("evselect", inargs).run()
# Subtract background
cor_image=work_dir+f'/EPIC_{key}_cor_image.fits' # Name of the output file
cmd = ['farith', f'{sci_image}', f'{qpb_image}', f'{cor_image}', 'SUB',
'copyprime=yes',
'clobber=yes']
result = subprocess.run(cmd, capture_output=True, text=True, check=True)
run_evqpb(key, work_dir=work_dir, evtfile=evtfile, attfile=attfile, label=label, pimin=pimin, pimax=pimax)
continue

77
scripts/07_sas_eimageget.py Executable file
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@@ -0,0 +1,77 @@
#!/usr/bin/env python
from pysas.wrapper import Wrapper as w
import os, sys
from os.path import dirname
import inspect
import glob
import os.path
from os import path
import subprocess
import numpy as np
import matplotlib.pyplot as plt
from astropy.io import fits
from astropy.table import Table
from matplotlib.colors import LogNorm
import re
import pyds9
import arches
from arches.utils import *
from arches.config import *
root_path=dirname(dirname(dirname(inspect.getfile(arches))))
print("Arches root path: {}".format(root_path))
fwc_dir=root_path+'/data/FWC'
archive_dir=root_path+'/data/archive'
events_dir=root_path+'/data/processed'
events_dir_oot=root_path+'/data/processed-oot'
products_dir=root_path+'/products/sas'
ds9reg_dir=root_path+'/data/ds9reg'
create_folder(products_dir)
inargs = ['--version']
t = w('sasver', inargs)
t.run()
files = glob.glob(archive_dir+'/*')
for obsid in files:
obsid = os.path.basename(obsid)
if(obsid in skip):
continue
work_dir = init_work_dir(obsid, products_dir=products_dir)
os.chdir(work_dir)
#
# https://www.cosmos.esa.int/web/xmm-newton/sas-thread-images
#
attfile = get_first_file(events_dir+f'/{obsid}/*{obsid}_AttHk.ds')
for key in ['MOS1','MOS2','PN']:
evtfile = get_first_file(events_dir+f'/{obsid}/*{obsid}_E{key}*_ImagingEvts.ds')
fwcfile = get_first_file(fwc_dir+f'/{key}_closed_FF_2025_v1.fits')
pimin=" ".join(emin)
pimax=" ".join(emax)
gti=f'EPIC_{key}_gti.fit'
sci_clean=work_dir+f'/EPIC_{key}_filtered.fits' # Name of the output file
inargs = [f'evtfile={evtfile}','withemtaglenoise=no',
f'fwcfile={fwcfile}','withfwcimages=yes',
f'gtifile={gti}',
f'attfile={attfile}',
f'pimin={pimin}',
f'pimax={pimax}',
]
if(key=='PN'):
evtfile_oot = get_first_file(events_dir_oot+f'/{obsid}/*{obsid}_E{key}*_ImagingEvts.ds')
inargs.append(f'ootfile={evtfile_oot}')
w("eimageget", inargs).run()
#sys.exit()

149
scripts/08_sas_mosaic.py Executable file
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@@ -0,0 +1,149 @@
#!/usr/bin/env python
from pysas.wrapper import Wrapper as w
import os, sys
from os.path import dirname
import inspect
import glob
import os.path
from os import path
import subprocess
import numpy as np
import matplotlib.pyplot as plt
from astropy.io import fits
from astropy.table import Table
from matplotlib.colors import LogNorm
import re
import pyds9
import arches
from arches.utils import *
from arches.config import *
root_path=dirname(dirname(dirname(inspect.getfile(arches))))
print("Arches root path: {}".format(root_path))
archive_dir=root_path+'/data/archive'
events_dir=root_path+'/data/processed'
products_dir=root_path+'/products/sas'
create_folder(products_dir)
mosaic_dir=root_path+'/products/mosaic'
create_folder(mosaic_dir)
ds9reg_dir=root_path+'/data/ds9reg'
inargs = ['--version']
t = w('sasver', inargs)
t.run()
files = glob.glob(archive_dir+'/*')
# run over energies
for idx,e in enumerate(emin):
label=f"_{idx}"
e1=emin[idx]
e2=emax[idx]
# all MOS1
m1_ima=[]
m1_qpb=[]
m1_exp=[]
# all MOS2
m2_ima=[]
m2_qpb=[]
m2_exp=[]
# all MOS
mos_ima=[]
mos_qpb=[]
mos_exp=[]
# all PNs
pn_ima=[]
pn_qpb=[]
pn_exp=[]
# all MOS1,2,PN
ima=[]
qpb=[]
exp=[]
for obsid in files:
obsid = os.path.basename(obsid)
if(obsid in skip):
continue
work_dir = f'{products_dir}/{obsid}'
for ikey,key in enumerate(['MOS1','MOS2','PN']):
shortkey = key.replace("OS","")
expkey=f'S00{ikey+1}'
# sci and qpb image are produced by 06_sas_QPB.py
sci_image=work_dir+f'/EPIC_{key}_sci_image{label}.fits'
test_file(sci_image)
qpb_image=work_dir+f'/EPIC_{key}_qpb_image{label}.fits'
test_file(qpb_image)
# exposure image is produced by eimageget (07_sas_eimageget.py)
# example: P0862470801PNS003_ima_4exp.fits
exp_image=work_dir+f'/P{obsid}{shortkey}{expkey}_ima{label}exp.fits'
test_file(exp_image)
ima.append(sci_image)
qpb.append(qpb_image)
exp.append(exp_image)
if(key=='PN'):
pn_ima.append(sci_image)
pn_qpb.append(qpb_image)
pn_exp.append(exp_image)
if(key=='MOS1'):
m1_ima.append(sci_image)
m1_qpb.append(qpb_image)
m1_exp.append(exp_image)
if(key=='MOS2'):
m2_ima.append(sci_image)
m2_qpb.append(qpb_image)
m2_exp.append(exp_image)
if(key=='MOS1' or key=='MOS2'):
mos_ima.append(sci_image)
mos_qpb.append(qpb_image)
mos_exp.append(exp_image)
run_mosaic(outfile_cts=mosaic_dir+f'/m1_cts{label}.fits',
outfile_exp=mosaic_dir+f'/m1_exp{label}.fits',
outfile_qpb=mosaic_dir+f'/m1_qpb{label}.fits',
outfile_sub=mosaic_dir+f'/m1_sub{label}.fits',
outfile_flx=mosaic_dir+f'/m1_flx{label}.fits',
outfile_pix=mosaic_dir+f'/m1_pix{label}.fits',
cts=m1_ima,qpb=m1_qpb,exp=m1_exp)
run_mosaic(outfile_cts=mosaic_dir+f'/m2_cts{label}.fits',
outfile_exp=mosaic_dir+f'/m2_exp{label}.fits',
outfile_qpb=mosaic_dir+f'/m2_qpb{label}.fits',
outfile_sub=mosaic_dir+f'/m2_sub{label}.fits',
outfile_flx=mosaic_dir+f'/m2_flx{label}.fits',
cts=m2_ima,qpb=m2_qpb,exp=m2_exp)
run_mosaic(outfile_cts=mosaic_dir+f'/mos_cts{label}.fits',
outfile_exp=mosaic_dir+f'/mos_exp{label}.fits',
outfile_qpb=mosaic_dir+f'/mos_qpb{label}.fits',
outfile_sub=mosaic_dir+f'/mos_sub{label}.fits',
outfile_flx=mosaic_dir+f'/mos_flx{label}.fits',
cts=mos_ima,qpb=mos_qpb,exp=mos_exp)
run_mosaic(outfile_cts=mosaic_dir+f'/pn_cts{label}.fits',
outfile_exp=mosaic_dir+f'/pn_exp{label}.fits',
outfile_qpb=mosaic_dir+f'/pn_qpb{label}.fits',
outfile_sub=mosaic_dir+f'/pn_sub{label}.fits',
outfile_flx=mosaic_dir+f'/pn_flx{label}.fits',
cts=pn_ima,qpb=pn_qpb,exp=pn_exp)
run_mosaic(outfile_cts=mosaic_dir+f'/cts{label}.fits',
outfile_exp=mosaic_dir+f'/exp{label}.fits',
outfile_qpb=mosaic_dir+f'/qpb{label}.fits',
outfile_sub=mosaic_dir+f'/sub{label}.fits',
outfile_flx=mosaic_dir+f'/flx{label}.fits',
cts=ima,qpb=qpb,exp=exp)