def find_time_interval(fits):
"""
find time interval of the fits file
input: fits --- fits file name
output: [tmin, tmax] --- start and stop time in seconds from 1998.1.1
"""
cmd = 'dmstat "' + fits + '[cols time]" centroid=no >' + zspace
scf.run_ascds(cmd)
out = scf.read_file(zspace, remove=1)
chk = 0
for val in out:
mc1 = re.search('min', val)
mc2 = re.search('max', val)
if mc1 is not None:
atemp = re.split('\s+', val)
tmin = int(float(atemp[1]))
chk += 1
elif mc2 is not None:
atemp = re.split('\s+', val)
tmax = int(float(atemp[1]))
chk += 1
if chk > 1:
break
return [tmin, tmax]
def find_time_interval(fits):
"""
find time interval of the fits file
input: fits --- fits file name
output: [tmin, tmax] --- start and stop time in seconds from 1998.1.1
"""
cmd = 'dmstat "' + fits + '[cols time]" centroid=no >' + zspace
try:
scf.run_ascds(cmd)
except:
return [0, 0]
out = scf.read_file(zspace, remove=1)
chk = 0
for val in out:
mc1 = re.search('min', val)
mc2 = re.search('max', val)
if mc1 is not None:
atemp = re.split('\s+', val)
tmin = int(float(atemp[1]))
chk += 1
elif mc2 is not None:
atemp = re.split('\s+', val)
tmax = int(float(atemp[1]))
chk += 1
if chk > 1:
break
return [tmin, tmax]
def sib_corr_comb(start, stop, lev):
"""
combined fits files into one per ccd
input: start --- start time of the interval <yyyy>:<ddd>:<hh>:<mm>:<ss>
stop --- stop time of the interval <yyyy>:<ddd>:<hh>:<mm>:<ss>
lev --- data level "Lev1" or "Lve2"
output: combined data: lres_ccd<ccd>_merged.fits in Data directory
"""
#
#--- convert the time to seconds from 1998.1.1
#
tstart = tcnv.axTimeMTA(start)
tstop = tcnv.axTimeMTA(stop)
#
#--- make a list of data fits files
#
lres = s_dir + lev + '/Outdir/lres/'
cmd = 'ls ' + lres + '*fits > ' + zspace
os.system(cmd)
data = scf.read_file(zspace, remove=1)
#
#--- initialize ccd_list<ccd>
#
for ccd in range(0, 10):
exec 'ccd_list%s = []' % (str(ccd))
for ent in data:
#
#--- check whether the data are inside of the specified time period
#
[tmin, tmax] = find_time_interval(ent)
if tmin >= tstart and tmax <= tstop:
btemp = re.split('_acis', ent)
head = btemp[0]
#
#--- add the fits file to ccd_list
#
for ccd in range(0, 10):
chk = 'acis' + str(ccd)
mc = re.search(chk, ent)
if mc is not None:
line = str(ent)
exec "ccd_list%s.append('%s')" % (str(ccd), line)
break
#
#--- combined all fits files of a specific ccd into one fits file
#
for ccd in range(0, 10):
exec "alist = ccd_list%s" % (str(ccd))
if len(alist) > 0:
#
#--- the first of the list is simply copied to temp.fits
#
cmd = 'cp ' + alist[0] + ' temp.fits'
os.system(cmd)
for k in range(1, len(alist)):
cmd = 'dmmerge "' + alist[k] + ',temp.fits" outfile=zmerged.fits outBlock=""'
cmd = cmd + 'columnList="" clobber="yes"'
scf.run_ascds(cmd)
cmd = 'mv ./zmerged.fits ./temp.fits'
os.system(cmd)
cmd = 'mv ./temp.fits ' + s_dir + lev + '/Data/lres_ccd' + str(ccd) + '_merged.fits'
os.system(cmd)
def find_excess_file(lev = 'Lev2'):
"""
find data with extremely high radiation and remove it.
this is done mainly in Lev2 and copied the procesure in Lev2
input: lev --- level. default Lev2 (other option is Lev1)
output: excess radiation data fits files in ./lres/Save/.
"""
if lev == 'Lev2':
lres = s_dir + lev + '/Outdir/lres/'
cmd = 'ls ' + lres + 'mtaf*fits > ' + zspace
os.system(cmd)
data = scf.read_file(zspace, remove=1)
cmd = 'mkdir ' + lres + 'Save'
os.system(cmd)
for ent in data:
cmd = 'dmlist ' + ent + ' opt=data > ' + zspace
scf.run_ascds(cmd)
out = scf.read_file(zspace, remove=1)
ssoft = 0.0
soft = 0.0
med = 0.0
hard = 0.0
harder = 0.0
hardest = 0.0
tot = 0
for val in out:
atemp = re.split('\s+', val)
if mcf.chkNumeric(atemp[0]):
ssoft += float(atemp[6])
soft += float(atemp[7])
med += float(atemp[8])
hard += float(atemp[9])
harder += float(atemp[10])
hardest += float(atemp[11])
tot += 1
else:
continue
if tot > 1:
ssoft /= tot
soft /= tot
med /= tot
hard /= tot
harder /= tot
hardest /= tot
mc = re.search('acis6', ent)
chk = 0
if mc is not None:
if (med > 200):
chk = 1
else:
if (soft > 500) or (med > 150):
chk = 1
if chk > 0:
cmd = 'mv ' + ent + ' ' + lres + 'Save/.'
os.system(cmd)
else:
#
#--- for Lev1, we move the files which removed in Lev2. we assume that we already
#--- run Lev2 on this function
#
epath = s_dir + '/Lev2/Outdir/lres/Save/'
if os.listdir(epath) != []:
cmd = 'ls ' + s_dir + '/Lev2/Outdir/lres/Save/*fits > ' + zspace
os.system(cmd)
data = scf.read_file(zspace, remove=1)
l1_lres = s_dir + '/Lev1/Outdir/lres/'
l1_dir = l1_lres + '/Save/'
cmd = 'mkdir ' + l1_dir
os.system(cmd)
for ent in data:
atemp = re.split('mtaf', ent)
btemp = re.split('N', atemp[1])
mc = re.search('_', btemp[0])
if mc is not None:
ctemp = re.split('_', btemp[0])
obsid = ctemp[0]
else:
obsid = btemp[0]
atemp = re.split('acis', ent)
btemp = re.split('lres', atemp[1])
ccd = btemp[0]
cid = 'acis' + str(ccd) + 'lres_sibkg.fits'
cmd = 'mv ' + l1_lres + 'mtaf' + obsid + '*' + cid + ' ' + l1_dir + '/.'
os.system(cmd)
def correct_factor(lev):
"""
adjust lres reuslts files for the area removed as the sources remvoed
input: lev --- level 1 or 2
output: adjusted fits files in lres
"""
#
#--- read all correciton factor information
#
file = s_dir + lev + '/Reg_files/ratio_table'
data = scf.read_file(file)
ratio = {}
for ent in data:
#atemp = re.split('\s+', ent)
atemp = re.split(':', ent)
rate = float(atemp[1].strip())
btemp = re.split('N', atemp[0])
mc = re.search('_', btemp[0])
if mc is not None:
ctemp = re.split('_', btemp[0])
msid = ctemp[0]
else:
msid = btemp[0]
ctemp = re.split('ccd', atemp[0])
dtemp = re.split('_', ctemp[1])
ccd = dtemp[0]
ind = str(msid) + '.' + str(ccd)
ratio[ind] = rate
#
#--- find all fits file names processed
#
cmd = 'ls ' + s_dir + lev + '/Outdir/lres/mtaf*.fits > ' + zspace
os.system(cmd)
data = scf.read_file(zspace, remove=1)
for fits in data:
atemp = re.split('N', fits)
btemp = re.split('mtaf', atemp[0])
msid = btemp[1]
mc = re.search('_', msid)
if mc is not None:
ctemp = re.split('_', msid)
msid = ctemp[0]
atemp = re.split('acis', fits)
btemp = re.split('lres', atemp[1])
ccd = btemp[0]
ind = str(msid) + '.' + str(ccd)
try:
div = ratio[ind]
except:
continue
if div >= 1:
continue
#
#--- correct the observation rate by devided by the ratio (all sources removed area)/(original are)
#
elif div > 0:
line = 'SSoft=SSoft/' + str(div) + ',Soft=Soft/' + str(div) + ',Med=Med/' + str(div) + ','
line = line + 'Hard=Hard/' + str(div) + ',Harder=Harder/' + str(div) + ',Hardest=Hardest/' + str(div)
cmd = 'dmtcalc infile =' + ent + ' outfile=out.fits expression="' + line + '" clobber=yes'
scf.run_ascds(cmd)
cmd = 'mv out.fits ' + ent
os.system(cmd)
else:
print "Warning!!! div < 0 for " + str(ent)
continue
def sib_corr_comb(start, stop, lev):
"""
combined fits files into one per ccd
input: start --- start time of the interval <yyyy>:<ddd>:<hh>:<mm>:<ss>
stop --- stop time of the interval <yyyy>:<ddd>:<hh>:<mm>:<ss>
lev --- data level "Lev1" or "Lve2"
output: combined data: lres_ccd<ccd>_merged.fits in Data directory
"""
#
#--- convert the time to seconds from 1998.1.1
#
tstart = Chandra.Time.DateTime(start).secs
tstop = Chandra.Time.DateTime(stop).secs
#
#--- make a list of data fits files
#
lres = cor_dir + lev + '/Outdir/lres/'
cmd = 'ls ' + lres + '*fits > ' + zspace
os.system(cmd)
data = mcf.read_data_file(zspace, remove=1)
#
#--- initialize ccd_list
#
ccd_list = [[] for x in range(0, 10)]
for ent in data:
#
#--- check whether the data are inside of the specified time period
#
[tmin, tmax] = find_time_interval(ent)
if tmin >= tstart and tmax <= tstop:
btemp = re.split('_acis', ent)
head = btemp[0]
#
#--- add the fits file to ccd_list
#
for ccd in range(0, 10):
chk = 'acis' + str(ccd)
mc = re.search(chk, ent)
if mc is not None:
ccd_list[ccd].append(str(ent))
break
#
#--- combined all fits files of a specific ccd into one fits file
#
for ccd in range(0, 10):
if len(ccd_list[ccd]) > 0:
#
#--- the first of the list is simply copied to temp.fits
#
cmd = 'cp ' + ccd_list[ccd][0] + ' temp.fits'
os.system(cmd)
for k in range(1, len(ccd_list[ccd])):
cmd = 'dmmerge "' + ccd_list[ccd][k]
cmd = cmd + ',temp.fits" outfile=zmerged.fits outBlock=""'
cmd = cmd + 'columnList="" clobber="yes"'
try:
scf.run_ascds(cmd)
except:
continue
cmd = 'mv ./zmerged.fits ./temp.fits'
os.system(cmd)
cmd = 'mv ./temp.fits ' + cor_dir + lev + '/Data/lres_ccd'
cmd = cmd + str(ccd) + '_merged.fits'
os.system(cmd)
def find_excess_file(lev='Lev2'):
"""
find data with extremely high radiation and remove it.
this is done mainly in Lev2 and copied the procesure in Lev2
input: lev --- level. default Lev2 (other option is Lev1)
output: excess radiation data fits files in ./lres/Save/.
"""
if lev == 'Lev2':
lres = cor_dir + lev + '/Outdir/lres/'
cmd = 'ls ' + lres + 'mtaf*fits > ' + zspace
os.system(cmd)
data = mcf.read_data_file(zspace, remove=1)
cmd = 'mkdir ' + lres + 'Save'
os.system(cmd)
for ent in data:
cmd = 'dmlist ' + ent + ' opt=data > ' + zspace
try:
scf.run_ascds(cmd)
except:
continue
out = mcf.read_data_file(zspace, remove=1)
ssoft = 0.0
soft = 0.0
med = 0.0
hard = 0.0
harder = 0.0
hardest = 0.0
tot = 0.0
for val in out:
atemp = re.split('\s+', val)
try:
chk = float(atemp[0])
ssoft += float(atemp[6])
soft += float(atemp[7])
med += float(atemp[8])
hard += float(atemp[9])
harder += float(atemp[10])
hardest += float(atemp[11])
tot += 1.0
except:
continue
if tot > 1:
ssoft /= tot
soft /= tot
med /= tot
hard /= tot
harder /= tot
hardest /= tot
mc = re.search('acis6', ent)
chk = 0
if mc is not None:
if (med > 200):
chk = 1
else:
if (soft > 500) or (med > 150):
chk = 1
if chk > 0:
cmd = 'mv ' + ent + ' ' + lres + 'Save/.'
os.system(cmd)
else:
#
#--- for Lev1, we move the files which removed in Lev2. we assume that we already
#--- run Lev2 on this function
#
epath = cor_dir + '/Lev2/Outdir/lres/Save/'
if os.listdir(epath) != []:
cmd = 'ls ' + cor_dir + '/Lev2/Outdir/lres/Save/*fits > ' + zspace
os.system(cmd)
data = mcf.read_data_file(zspace, remove=1)
l1_lres = cor_dir + '/Lev1/Outdir/lres/'
l1_dir = l1_lres + '/Save/'
cmd = 'mkdir ' + l1_dir
os.system(cmd)
for ent in data:
atemp = re.split('mtaf', ent)
btemp = re.split('N', atemp[1])
mc = re.search('_', btemp[0])
if mc is not None:
ctemp = re.split('_', btemp[0])
obsid = ctemp[0]
else:
obsid = btemp[0]
atemp = re.split('acis', ent)
btemp = re.split('lres', atemp[1])
ccd = btemp[0]
cid = 'acis' + str(ccd) + 'lres_sibkg.fits'
cmd = 'mv ' + l1_lres + 'mtaf' + obsid + '*' + cid + ' ' + l1_dir + '/.'
os.system(cmd)
def correct_factor(lev):
"""
adjust lres reuslts files for the area removed as the sources remvoed
input: lev --- level 1 or 2
output: adjusted fits files in lres
"""
#
#--- read all correciton factor information
#
ifile = cor_dir + lev + '/Reg_files/ratio_table'
data = mcf.read_data_file(ifile)
ratio = {}
for ent in data:
atemp = re.split(':', ent)
rate = float(atemp[1].strip())
btemp = re.split('N', atemp[0])
mc = re.search('_', btemp[0])
if mc is not None:
ctemp = re.split('_', btemp[0])
msid = ctemp[0]
else:
msid = btemp[0]
ctemp = re.split('ccd', atemp[0])
dtemp = re.split('_', ctemp[1])
ccd = dtemp[0]
ind = str(msid) + '.' + str(ccd)
ratio[ind] = rate
#
#--- find all fits file names processed
#
cmd = 'ls ' + cor_dir + lev + '/Outdir/lres/mtaf*.fits > ' + zspace
os.system(cmd)
data = mcf.read_data_file(zspace, remove=1)
for fits in data:
atemp = re.split('N', fits)
btemp = re.split('mtaf', atemp[0])
msid = btemp[1]
mc = re.search('_', msid)
if mc is not None:
ctemp = re.split('_', msid)
msid = ctemp[0]
atemp = re.split('acis', fits)
btemp = re.split('lres', atemp[1])
ccd = btemp[0]
ind = str(msid) + '.' + str(ccd)
try:
div = ratio[ind]
except:
continue
if div >= 1:
continue
#
#--- correct the observation rate by devided by the ratio
#--- (all sources removed area)/(original are)
#
elif div > 0:
line = 'SSoft=SSoft/' + str(div) + ',Soft=Soft/'
line = line + str(div) + ',Med=Med/' + str(div) + ','
line = line + 'Hard=Hard/' + str(div) + ',Harder=Harder/'
line = line + str(div) + ',Hardest=Hardest/' + str(div)
cmd = 'dmtcalc infile =' + ent + ' outfile=out.fits expression="'
cmd = cmd + line + '" clobber=yes'
scf.run_ascds(cmd)
cmd = 'mv out.fits ' + ent
os.system(cmd)
else:
print("Warning!!! div < 0 for " + str(ent))
continue
def exclude_sources(fits):
"""
remove the area around the main source and all point sources from data
input: fits --- input fits file name
output: out_name --- source removed fits file (<header>_ccd<ccd>_cleaned.fits)
"""
#
#--- read fits header
#
fout = pyfits.open(fits)
#
#--- find which ccds used
#
ccd_list = []
for k in range(0, 10):
bname = 'BIASFIL' + str(k)
try:
val = fout[1].header[bname]
ccd_list.append(k)
except:
continue
ccd_list.sort()
#
#--- create key word dictionary
#
v_dict = {}
for name in [
'SIM_X', 'SIM_Y', 'SIM_Z', 'RA_NOM', 'DEC_NOM', 'ROLL_NOM',
'RA_TARG', 'DEC_TARG'
]:
lname = name.lower()
try:
out = fout[1].header[name]
v_dict[lname] = str(out)
except:
v_dict[lname] = 'NA'
#
#--- guess a source center position on the sky coordinates from the information extracted from the header
#
cmd = ' dmcoords none none opt=cel '
cmd = cmd + ' ra=' + v_dict['ra_targ'] + ' dec=' + v_dict['dec_targ']
cmd = cmd + ' sim="' + v_dict['sim_x'] + ' ' + v_dict[
'sim_y'] + ' ' + v_dict['sim_z'] + '" '
cmd = cmd + ' detector=acis celfmt=deg ' + ' ra_nom=' + v_dict['ra_nom']
cmd = cmd + ' dec_nom=' + v_dict['dec_nom'] + ' roll_nom=' + v_dict[
'roll_nom'] + ' '
cmd = cmd + ' ra_asp=")ra_nom" dec_asp=")dec_nom" verbose=1 >' + zspace
scf.run_ascds(cmd)
data = mcf.read_data_file(zspace, remove=1)
for ent in data:
mc = re.search('SKY', ent)
if mc is not None:
atemp = re.split('\s+', ent)
skyx = atemp[1]
skyy = atemp[2]
break
#
#-- keep the record of the source position for the later use (e.g. used for evt1 processing);
#
o_fits = fits.replace('.gz', '')
coord_file = o_fits.replace('.fits', '_source_coord')
ofile = './Reg_files/' + coord_file
line = str(skyx) + ':' + str(skyy) + '\n'
with open(ofile, 'w') as fo:
fo.write(line)
#
#-- remove the 200 pix radius area around the source
#
cmd = ' dmcopy "' + fits + '[exclude sky=circle(' + skyx + ',' + skyy + ',200)]" '
cmd = cmd + ' outfile=source_removed.fits clobber="yes"'
scf.run_ascds(cmd)
#
#--- get a file size: will be used to measure the size of removed area later.
#--- assumption here is the x-ray hit ccd evenly, but of course it is not,
#--- but this is the best guess we canget
#
size = {}
for ccd in ccd_list:
cmd = ' dmcopy "' + fits + '[ccd_id=' + str(ccd)
cmd = cmd + ']" outfile=test.fits clobber=yes'
scf.run_ascds(cmd)
cmd = 'ls -l test.fits > ' + zspace
os.system(cmd)
data = mcf.read_data_file(zspace, remove=1)
for line in data:
atemp = re.split('\s+', line)
try:
size[ccd] = int(float(atemp[4]))
except:
size[ccd] = int(float(atemp[3]))
mcf.rm_files('test.fits')
#
#--- now separate observations to indivisual ccds
#
file_list = []
for ccd in ccd_list:
tail = '_ccd' + str(ccd) + '.fits'
out = o_fits.replace('.fits', tail)
file_list.append(out)
cmd = ' dmcopy "source_removed.fits[ccd_id=' + str(ccd)
cmd = cmd + ']" outfile= ' + out + ' clobber=yes'
scf.run_ascds(cmd)
mcf.rm_files('source_removed.fits')
#
#--- process each ccd
#
for pfits in file_list:
reg_file = pfits.replace('.fits', '_block_src.reg')
#
#--- find point sources
#
cmd = ' celldetect infile=' + pfits
cmd = cmd + ' fixedcell=9 outfile=acisi_block_src.fits regfile=acisi_block_src.reg clobber=yes'
scf.run_ascds(cmd)
data = mcf.read_data_file('acisi_block_src.reg')
exclude = []
for ent in data:
atemp = re.split('\,', ent)
#
#--- increase the area covered around the sources 3 times to make sure leaks
#--- from a bright source is minimized
#
val2 = float(atemp[2]) * 3
val3 = float(atemp[3]) * 3
line = atemp[0] + ',' + atemp[1] + ',' + str(val2) + ',' + str(
val3) + ',' + atemp[4]
exclude.append(line)
out_name = pfits.replace('.gz', '')
out_name = out_name.replace('.fits', '_cleaned.fits')
#
#--- if we actually found point sources, remove them from the ccds
#
e_cnt = len(exclude)
if e_cnt > 0:
cnt = 0
chk = 0
round = 0
line = ''
while cnt < e_cnt:
#
#--- remove 6 sources at a time so that it won't tax memory too much
#
for i in range(cnt, cnt + 6):
if i >= e_cnt:
chk += 1
break
if line == '':
line = exclude[i]
else:
line = line + '+' + exclude[i]
cnt += 6
if round == 0:
cmd = ' dmcopy "' + pfits + '[exclude sky=' + line
cmd = cmd + ']" outfile=out.fits clobber="yes"'
scf.run_ascds(cmd)
round += 1
else:
cmd = 'mv out.fits temp.fits'
os.system(cmd)
cmd = ' dmcopy "temp.fits[exclude sky=' + line
cmd = cmd + ']" outfile=out.fits clobber="yes"'
scf.run_ascds(cmd)
round += 1
if chk > 0:
break
else:
line = ''
mcf.rm_files('temp.fits')
cmd = 'mv out.fits ' + out_name
os.system(cmd)
else:
cmd = 'cp ' + pfits + ' ' + out_name
os.system(cmd)
#
#--- find the size of cleaned up file size
#
cmd = 'ls -l ' + out_name + '>' + zspace
os.system(cmd)
data = mcf.read_data_file(zspace, remove=1)
for line in data:
atemp = re.split('\s+', line)
try:
asize = float(atemp[4])
except:
asize = float(atempp[3])
for pccd in range(0, 10):
check = 'ccd' + str(pccd)
mc = re.search(check, out_name)
if mc is not None:
break
#
#--- compute the ratio of the cleaned to the original file;
#--- 1 - ratio is the potion that we removed from the original data
#
#ratio = asize / float(size[str(pccd)])
ratio = asize / float(size[pccd])
#
#--- record the ratio for later use
#
with open('./Reg_files/ratio_table', 'a') as fo:
line = reg_file + ': ' + str(ratio) + '\n'
fo.write(line)
cmd = 'mv acisi_block_src.reg ./Reg_files/' + reg_file
os.system(cmd)
mcf.rm_files('acisi_block_src.fits')
def exclude_sources(fits):
"""
remove the area around the main source and all point sources from data
input: fits --- input fits file name
output: out_name --- source removed fits file (<header>_ccd<ccd>_cleaned.fits)
"""
#
#--- read which ccds are used and several other info from fits header
#
cmd = ' dmlist ' + fits + ' opt=head > ' + zspace
scf.run_ascds(cmd)
data = scf.read_file(zspace, remove=1)
ccd_list = []
for ent in data:
mc = re.search('bias file used', ent)
if mc is not None:
atemp = re.split('CCD', ent)
val = atemp[1].strip()
ccd_list.append(val)
continue
for name in ['SIM_X', 'SIM_Y', 'SIM_Z', 'RA_NOM', 'DEC_NOM', 'ROLL_NOM', 'RA_TARG', 'DEC_TARG']:
mc = re.search(name, ent)
if mc is not None:
lname = name.lower()
atemp = re.split('\s+', ent)
val = atemp[2].strip()
exec "%s = %s" % (lname, val)
break
#
#--- sort ccd list
#
ccd_list.sort()
#
#--- guess a source center position on the sky coordinates from the information extracted from the header
#
cmd = ' dmcoords none none opt=cel '
cmd = cmd + ' ra=' + str(ra_targ) + ' dec=' + str(dec_targ )
cmd = cmd + ' sim="' + str(sim_x) + ' ' + str(sim_y) + ' ' + str(sim_z) + '" '
cmd = cmd + ' detector=acis celfmt=deg '
cmd = cmd + ' ra_nom=' + str(ra_nom) + ' dec_nom=' + str(dec_nom) + ' roll_nom=' + str(roll_nom) + ' '
cmd = cmd + ' ra_asp=")ra_nom" dec_asp=")dec_nom" verbose=1 >' + zspace
scf.run_ascds(cmd)
data = scf.read_file(zspace, remove=1)
for ent in data:
mc = re.search('SKY', ent)
if mc is not None:
atemp = re.split('\s+', ent)
skyx = atemp[1]
skyy = atemp[2]
break
#
#-- keep the record of the source position for the later use (e.g. used for evt1 processing);
#
o_fits = fits.replace('.gz', '')
coord_file = o_fits.replace('.fits', '_source_coord')
ofile = './Reg_files/' + coord_file
line = str(skyx) + ':' + str(skyy) + '\n'
fo = open(ofile, 'w')
fo.write(line)
fo.close()
#
#-- remove the 200 pix radius area around the source
#
cmd = ' dmcopy "' + fits + '[exclude sky=circle(' + skyx + ',' + skyy + ',200)]" '
cmd = cmd + ' outfile=source_removed.fits clobber="yes"'
scf.run_ascds(cmd)
#
#--- get a file size: will be used to measure the size of removed area later.
#--- assumption here is the x-ray hit ccd evenly, but of course it is not,
#--- but this is the best guess we canget
#
size = {}
for ccd in ccd_list:
cmd = ' dmcopy "' + fits + '[ccd_id=' + str(ccd) + ']" outfile=test.fits clobber=yes'
scf.run_ascds(cmd)
cmd = 'ls -l test.fits > ' + zspace
os.system(cmd)
data = scf.read_file(zspace, remove=1)
for line in data:
atemp = re.split('\s+', line)
if mcf.chkNumeric(atemp[4]):
size[ccd] = int(float(atemp[4]))
else:
size[ccd] = int(float(atemp[3]))
mcf.rm_file('test.fits')
#
#--- now separate observations to indivisual ccds
#
file_list = []
for ccd in ccd_list:
tail = '_ccd' + str(ccd) + '.fits'
out = o_fits.replace('.fits', tail)
file_list.append(out)
cmd = ' dmcopy "source_removed.fits[ccd_id=' + ccd + ']" outfile= ' + out + ' clobber=yes'
scf.run_ascds(cmd)
mcf.rm_file('source_removed.fits')
#
#--- process each ccd
#
for pfits in file_list:
reg_file = pfits.replace('.fits', '_block_src.reg')
#
#--- find point sources
#
cmd = ' celldetect infile=' + pfits
cmd = cmd + ' outfile=acisi_block_src.fits regfile=acisi_block_src.reg clobber=yes'
scf.run_ascds(cmd)
data = scf.read_file('acisi_block_src.reg')
exclude = []
for ent in data:
atemp = re.split('\,', ent)
#
#--- increase the area covered around the sources 3time to make sure leaks from a bright source is minimized
#
val2 = float(atemp[2]) * 3
val3 = float(atemp[3]) * 3
line = atemp[0] + ',' + atemp[1] + ',' + str(val2) + ',' + str(val3) +',' + atemp[4]
exclude.append(line)
out_name = pfits.replace('.gz','')
out_name = out_name.replace('.fits', '_cleaned.fits')
#
#--- if we actually found point sources, remove them from the ccds
#
e_cnt = len(exclude)
if e_cnt > 0:
cnt = 0
chk = 0
round = 0
line = ''
while cnt < e_cnt:
#
#--- remove 6 sources at a time so that it won't tax memory too much
#
for i in range(cnt, cnt + 6):
if i >= e_cnt:
chk += 1
break
if line == '':
line = exclude[i]
else:
line = line + '+' + exclude[i]
cnt += 6
if round == 0:
cmd = ' dmcopy "' + pfits + '[exclude sky=' + line +']" outfile=out.fits clobber="yes"'
scf.run_ascds(cmd)
round += 1
else:
cmd = 'mv out.fits temp.fits'
os.system(cmd)
cmd = ' dmcopy "temp.fits[exclude sky=' + line +']" outfile=out.fits clobber="yes"'
scf.run_ascds(cmd)
round += 1
if chk > 0:
break
else:
line = ''
mcf.rm_file('temp.fits')
cmd = 'mv out.fits ' + out_name
os.system(cmd)
else:
cmd = 'cp ' + pfits + ' ' + out_name
os.system(cmd)
#
#--- find the size of cleaned up file size
#
cmd = 'ls -l ' + out_name + '>' + zspace
os.system(cmd)
data = scf.read_file(zspace, remove=1)
for line in data:
atemp = re.split('\s+', line)
if mcf.chkNumeric(atemp[4]):
asize = float(atemp[4])
else:
asize = float(atempp[3])
for pccd in range(0, 10):
check = 'ccd' + str(pccd)
mc = re.search(check, out_name)
if mc is not None:
break
#
#--- compute the ratio of the cleaned to the original file; 1 - ratio is the potion that we removed
#--- from the original data
#
ratio = asize / float(size[str(pccd)])
#
#--- record the ratio for later use
#
fo = open('./Reg_files/ratio_table', 'a')
line = reg_file + ': ' + str(ratio) + '\n'
fo.write(line)
fo.close()
cmd = 'mv acisi_block_src.reg ./Reg_files/' + reg_file
os.system(cmd)
mcf.rm_file('acisi_block_src.fits')