def repevt(clu,obsid):
print
print 'Reprocessing evt file for OBSID '+obsid+' ------------------------'
print
if not os.access('mfe_'+clu+'/repro3_evt'+obsid+'.fits', os.F_OK) :
acao = asol6_loc.asol(obsid, 'asol')
bpix = asol6_loc.asol(obsid,'bpix')
evt1 = asol6_loc.asol(obsid,'evt1')
flt1 = asol6_loc.asol(obsid,'flt1')
mtl = asol6_loc.asol(obsid,'mtl')
readmode = commands.getoutput('dmkeypar '+evt1+' readmode echo+')
datamode = commands.getoutput('dmkeypar '+evt1+' datamode echo+')
if readmode == 'TIMED' :
if datamode == 'VFAINT' or datamode == 'FAINT' : edef = 'stdlev1'
if datamode == 'GRADED' : edef = 'grdlev1'
if readmode == 'CONTINUOUS' :
if 'FAINT' in datamode : edef = 'cclev1'
if 'GRADED' in datamode : edef = 'ccgrdlev1'
# ACIS_PROCESS_EVENTS
os.system('punlearn acis_process_events')
os.system('pset acis_process_events infile='+evt1)
os.system('pset acis_process_events outfile=mfe_'+clu+'/repro3_evt1_'+obsid+'.fits')
os.system('pset acis_process_events badpixfile='+bpix)
os.system('pset acis_process_events acaofffile='+acao)
os.system('pset acis_process_events eventdef=")'+edef+'"')
#os.system('pset acis_process_events rand_pix_size=0.5') # deprecated keyword
os.system('pset acis_process_events rand_pha=yes')
os.system('pset acis_process_events apply_tgain=yes')
os.system('pset acis_process_events apply_cti=yes')
os.system('pset acis_process_events mtlfile='+mtl)
os.system('pset acis_process_events mode=h')
if datamode == 'VFAINT' : os.system('pset acis_process_events check_vf_pha=yes')
os.system('acis_process_events clobber=yes') # clobber=yes here is permanent
# Grade and Status filtering
if datamode == 'VFAINT' : sstat='0'
elif datamode == 'FAINT' : sstat='00000000x00000000000000000000000'
# this status string chosen so that we stay consistent with blank sky file filtering
# even if for FAINT mode, this status filtering is the same as status=0
os.system('punlearn dmcopy')
os.system('dmcopy "mfe_'+clu+'/repro3_evt1_'+obsid+'.fits[EVENTS][grade=0,2,3,4,6,status='+sstat+']" mfe_'+clu+'/repro3_flt_evt1_'+obsid+'.fits clobber=yes') # clobber=yes here is permanent
# More filtering
os.system('punlearn dmcopy')
os.system('dmcopy "mfe_'+clu+'/repro3_flt_evt1_'+obsid+'.fits[EVENTS][@'+flt1+'][cols -pha]" mfe_'+clu+'/repro3_evt'+obsid+'.fits')
else : print 'The repro3cessed file already exists'
print '------ End of repevt for cluster ' + clu + ', OBSID ' + obsid + ' ----------------'
print
print
def arf (clu, ob, i, ccdname) :
locclu = 'mfe_'+clu
origclu= 'orig_'+clu
# MKWARF --------------
pbk = asol6_loc.asol(ob,'pbk')
acao = asol6_loc.asol(ob, 'asol')
os.system('punlearn mkwarf')
os.system('pset mkwarf infile="'+locclu+'/radp'+ob+'/sp'+str(i)+'_ccd'+ccdname+'.fits[WMAP]"')
os.system('pset mkwarf outfile='+locclu+'/radp'+ob+'/warf'+str(i)+'_ccd'+ccdname+'.fits')
os.system('pset mkwarf weightfile='+locclu+'/radp'+ob+'/wfef'+str(i)+'_ccd'+ccdname+'.fits')
#os.system('pset mkwarf pbkfile='+pbk)
os.system('pset mkwarf egridspec="0.3:11.0:0.01"')
os.system('pset mkwarf asolfile='+acao)
os.system('mkwarf verbose=1 mode=h')
def arf(clu, ob, isp, ccd):
locclu = 'mfe_' + clu
# MKWARF --------------
pbk = asol6_loc.asol(ob, 'pbk')
acao = asol6_loc.asol(ob, 'asol')
os.system('punlearn mkwarf')
os.system('pset mkwarf infile="' + locclu + '/zofr/sp10simple' + ob + '_' +
str(isp) + '_ccd' + ccd + '.fits[WMAP]"')
os.system('pset mkwarf outfile=' + locclu + '/zofr/warf10_' + ob + '_' +
str(isp) + '_ccd' + ccd + '.fits')
os.system('pset mkwarf weightfile=' + locclu + '/zofr/wfef10_' + ob + '_' +
str(isp) + '_ccd' + ccd + '.fits')
# os.system('pset mkwarf pbkfile='+pbk)
os.system('pset mkwarf egridspec="0.3:11.0:0.01"')
os.system('pset mkwarf asolfile=' + acao)
os.system('mkwarf verbose=1 mode=h clobber=yes')
os.system('rm ' + locclu + '/zofr/wfef10_' + ob + '_' + str(isp) + '_ccd' +
ccd + '.fits')
def ktofr(clu, obsids, zz, nnhhlab, checkfit):
print ' -----------> checkbgfit4 for ' + clu
clean()
gc.collect()
set_stat('cstat')
locclu = 'mfe_' + clu
(rac, decc) = centradec.getrd(locclu)
if not os.path.exists(locclu + '/bginfield/'):
os.mkdir(locclu + '/bginfield/')
if not os.path.exists(locclu + '/reg/'): os.mkdir(locclu + '/reg/')
if not os.path.exists(locclu + '/spec/'): os.mkdir(locclu + '/spec/')
if not os.path.exists(locclu + '/ktofrsp/'): os.mkdir(locclu + '/ktofrsp/')
ccdname = 'i567'
ccdlist = ['0,1,2,3', '5', '6', '7']
ccdindex = {'i': 0, '5': 1, '6': 2, '7': 3}
# dataplot = ChipsCurve()
# modelplot = ChipsHistogram()
# dataplot.symbol.style='plus'
# dataplot.symbol.size=3
# dataplot.line.style='none'
# modelplot.line.color = "red"
# modelplot.line.thickness = 3
# create simplechipsreg regions.
for ob in obsids:
os.system('punlearn skyfov')
os.system('skyfov ' + locclu + '/clean' + ob + '.fits ' + locclu +
'/reg/simplechipsreg' + ob + '.fits clobber=yes')
# which CCD's are present in each OBSID
presccdglob = []
for iob in range(len(obsids)):
presccdglob.append(whichccd2z_loc.find(clu, obsids[iob]))
# Remove OBSID's which do not have any good CCD's:
emptyobs = []
for iob in range(len(obsids)):
ob = obsids[iob]
for ccd in str(presccdglob[iob]):
if not os.path.exists(locclu+'/spec/sp'+ob+'_ccd'+ccd+'_center.wrmf') \
or not os.path.exists(locclu+'/spec/bgarf'+ob+'_ccd'+ccd+'.fits') \
or not os.path.exists(locclu+'/spec/bgspsimple'+ob+'_ccd'+ccd+'.fits') \
or not os.path.exists(locclu+'/spec/bgrmf'+ob+'_ccd'+ccd+'.fits') :
presccdglob[iob] = presccdglob[iob].replace(ccd, '')
if presccdglob[iob] == '': emptyobs.append(iob)
emptyobs.reverse()
for iob in emptyobs:
del obsids[iob]
del presccdglob[iob]
anfile = open(locclu + '/bginfield_all.reg', 'r')
anline = anfile.readline()
anline = anfile.readline()
pbg1 = float(anline.split(',')[2][0:-1]) * 60 / 0.492
pbg2 = float(anline.split(',')[3][0:-3]) * 60 / 0.492
anfile.close()
# Create BG annulus for each OBSIDS, which excludes the pt srcs
# Get presccd
presccd = []
for iob in range(len(obsids)):
ob = obsids[iob]
intermed1 = radreg4simple2.radreg(clu, ob, pbg1, pbg2,
locclu + '/bginfield/outer' + ob)
presccd.append(intermed1)
# Make sure that some needed files were created. If not, remove from prescccd
# any CCD wich is missing PI, ARF or RMF file
for iob in range(len(obsids)):
ob = obsids[iob]
for ccd in str(presccd[iob]):
if not os.path.exists(
locclu + '/spec/sp' + ob + '_ccd' + ccd +
'_center.wrmf') or ccd not in presccdglob[iob]:
presccd[iob] = presccd[iob].replace(ccd, '')
#if not os.path.exists(locclu+'/spec/sp'+ob+'_ccd'+ccd+'_center.wrmf') : presccd[iob] = presccd[iob].replace(ccd, '')
srcstr = ''
for iob in range(len(obsids)):
ob = obsids[iob]
for iccd in range(len(presccd[iob])):
ccd = presccd[iob][iccd]
os.system('punlearn dmextract')
os.system(
'dmextract "' + locclu + '/clean' + ob + '.fits[ccd_id=' +
ccdlist[ccdindex[ccd]] + '][sky=region(' + locclu +
'/bginfield/outer' + ob + '_ccd' + ccd +
'_xfov_pt_simple.reg)][bin PI]" ' + locclu + '/bginfield/sp' +
ob + '_ccd' + ccd +
'.fits opt=pha1 wmap="[energy=300:2000][bin det=8]" clobber=yes'
)
# Make ARF given the WMAP from the above spectrum file
#pbk = asol6_loc.asol(ob,'pbk')
acao = asol6_loc.asol(ob, 'asol')
os.system('punlearn mkwarf')
os.system('pset mkwarf infile="' + locclu + '/bginfield/sp' + ob +
'_ccd' + ccd + '.fits[WMAP]"')
os.system('pset mkwarf outfile=' + locclu + '/bginfield/warf' +
ob + '_ccd' + ccd + '.fits')
os.system('pset mkwarf weightfile=' + locclu + '/bginfield/wfef' +
ob + '_ccd' + ccd + '.fits')
#os.system('pset mkwarf pbkfile='+pbk)
os.system('pset mkwarf egridspec="0.3:11.0:0.01"')
os.system('pset mkwarf asolfile=' + acao)
os.system('mkwarf verbose=1 mode=h clobber=yes')
os.system('rm ' + locclu + '/bginfield/wfef' + ob + '_ccd' + ccd +
'.fits')
# Make sure (AGAIN) that all the needed files were created. If not, remove from prescccd
# any CCD wich is missing PI, ARF or RMF file
for iob in range(len(obsids)):
ob = obsids[iob]
for ccd in str(presccd[iob]):
if not os.path.exists(locclu + '/bginfield/warf' + ob + '_ccd' +
ccd + '.fits') or not os.path.exists(
locclu + '/bginfield/sp' + ob + '_ccd' +
ccd +
'.fits') or ccd not in presccdglob[iob]:
presccd[iob] = presccd[iob].replace(ccd, '')
if not os.path.exists(locclu + '/spec/sp' + ob + '_ccd' + ccd +
'_center.wrmf'):
presccdglob[iob] = presccdglob[iob].replace(ccd, '')
presccd[iob] = presccd[iob].replace(ccd, '')
# load infield BG
for iob in range(len(obsids)):
ob = obsids[iob]
for iccd in range(len(presccd[iob])):
ccd = presccd[iob][iccd]
load_pha(ob + '.' + ccd,
locclu + '/bginfield/sp' + ob + '_ccd' + ccd + '.fits')
load_rmf(ob + '.' + ccd,
locclu + '/spec/sp' + ob + '_ccd' + ccd + '_center.wrmf')
load_arf(ob + '.' + ccd,
locclu + '/bginfield/warf' + ob + '_ccd' + ccd + '.fits')
srcstr = srcstr + '"' + ob + '.' + ccd + '",'
# Fit the BG using blank sky AND infield BG data
loadbg4z8simple2_write.bg(clu, obsids, presccdglob, presccd, srcstr, zz,
nnhhlab, checkfit)
# Make and save plots
for iob in range(len(obsids)):
ob = obsids[iob]
for iccd in range(len(presccdglob[iob])):
ccd = presccdglob[iob][iccd]
if ccd in presccd[iob]:
plot_fit_resid(ob + '.' + ccd)
if os.path.exists('fitplots/checkbgfit4infield_' + clu + '_' +
ob + '_ccd' + ccd + '.eps'):
os.remove('fitplots/checkbgfit4infield_' + clu + '_' + ob +
'_ccd' + ccd + '.eps')
print_window(
'fitplots/checkbgfit4infield_' + clu + '_' + ob + '_ccd' +
ccd, ['format', 'eps', 'orientation', 'landscape'])
delete_window('all')
plot_fit_resid('bg' + ob + '.' + ccd)
if os.path.exists('fitplots/checkbgfit4blanksky_' + clu + '_' +
ob + '_ccd' + ccd + '.eps'):
os.remove('fitplots/checkbgfit4blanksky_' + clu + '_' + ob +
'_ccd' + ccd + '.eps')
print_window(
'fitplots/checkbgfit4blanksky_' + clu + '_' + ob + '_ccd' +
ccd, ['format', 'eps', 'orientation', 'landscape'])
delete_window('all')
def sp(clu, ob, r1mpc):
locclu = 'mfe_' + clu
origclu = 'orig_' + clu
os.system('punlearn ardlib')
acao = asol6_loc.asol(ob, 'asol')
if not os.path.exists(locclu + '/spec'): os.mkdir(locclu + '/spec')
(rac, decc) = centradec.getrd(locclu)
# simple in, out and bg regions (w/o point source exclusion)
reginfile = open(locclu + '/reg/in.reg', 'w')
reginfile.write('circle(' + rac + ',' + decc + ',' + str(r1mpc / 10) +
'")\n')
reginfile.close()
regoutfile = open(locclu + '/reg/out.reg', 'w')
regoutfile.write('annulus(' + rac + ',' + decc + ',' + str(r1mpc / 10) +
'",' + str(r1mpc) + '")\n')
regoutfile.close()
regbgfile = open(locclu + '/reg/bg.reg', 'w')
regbgfile.write('circle(' + rac + ',' + decc + ',' + str(r1mpc) + '")\n')
regbgfile.close()
# make chip regions using skyfov
os.system('punlearn skyfov')
os.system('skyfov ' + locclu + '/clean' + ob + '.fits ' + locclu +
'/reg/chipsreg' + ob + '.fits aspect=' + acao + ' mskfile=' +
asol6_loc.asol(ob, 'msk1'))
pbk = asol6_loc.asol(ob, 'pbk')
regv = ['in2', 'out2']
ctsin0 = commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu +
'/reg/in.reg)][ccd_id=0]" counts')
ctsin1 = commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu +
'/reg/in.reg)][ccd_id=1]" counts')
ctsin2 = commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu +
'/reg/in.reg)][ccd_id=2]" counts')
ctsin3 = commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu +
'/reg/in.reg)][ccd_id=3]" counts')
ctsin5 = commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu +
'/reg/in.reg)][ccd_id=5]" counts')
ctsin6 = commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu +
'/reg/in.reg)][ccd_id=6]" counts')
ctsin7 = commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu +
'/reg/in.reg)][ccd_id=7]" counts')
ctsout0 = commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu +
'/reg/out.reg)][ccd_id=0]" counts')
ctsout1 = commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu +
'/reg/out.reg)][ccd_id=1]" counts')
ctsout2 = commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu +
'/reg/out.reg)][ccd_id=2]" counts')
ctsout3 = commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu +
'/reg/out.reg)][ccd_id=3]" counts')
ctsout5 = commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu +
'/reg/out.reg)][ccd_id=5]" counts')
ctsout6 = commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu +
'/reg/out.reg)][ccd_id=6]" counts')
ctsout7 = commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu +
'/reg/out.reg)][ccd_id=7]" counts')
# Create regions file combining field-of-view regions and point source exclusion regions
chipreg.make(clu, ob, r1mpc, float(ctsin0), float(ctsin1), float(ctsin2),
float(ctsin3), float(ctsin5), float(ctsin6), float(ctsin7),
float(ctsout0), float(ctsout1), float(ctsout2),
float(ctsout3), float(ctsout5), float(ctsout6),
float(ctsout7))
ccdv = ['i', '5', '6', '7']
ccdlist = ['0,1,2,3', '5', '6', '7']
for iccd in range(len(ccdv)):
# RMF -----------------------
#if not os.path.exists(locclu+'/spec/sp'+ob+'_ccd'+ccdv[iccd]+'_center.wrmf') and
#if float(commands.getoutput('dmlist "'+locclu+'/clean'+ob+'.fits[ccd_id='+ccdlist[iccd]+']" counts')) > 0
if os.path.exists(locclu + '/bg/bg' + ob + '_ccd' + ccdv[iccd] +
'r.fits'):
rmf4ent5.rmf(locclu, ob, ccdv[iccd])
for ireg in range(len(regv)):
for iccd in range(len(ccdv)):
# the region file, below, is created if there are enough counts in the region
# of interest.
if os.path.exists(locclu + '/reg/' + regv[ireg] + '_' + ob +
'_ccd' + ccdv[iccd] + '.reg') and os.path.exists(
locclu + '/bg/bg' + ob + '_ccd' +
ccdv[iccd] + 'r.fits'):
# DMEXTRACT -----------
os.system('punlearn dmextract')
os.system('pset dmextract infile="' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu + '/reg/' + regv[ireg] +
'_' + ob + '_ccd' + ccdv[iccd] + '.reg)][bin PI]"')
os.system('pset dmextract outfile=' + locclu + '/spec/sp' +
ob + '_' + regv[ireg] + '_ccd' + ccdv[iccd] + '.pi')
os.system('pset dmextract opt=pha1')
os.system('pset dmextract wmap="[energy=300:2000][bin det=8]"')
os.system('dmextract verbose=1 mode=h')
# DMGROUP -----------
os.system('punlearn dmgroup')
os.system('pset dmgroup infile=' + locclu + '/spec/sp' + ob +
'_' + regv[ireg] + '_ccd' + ccdv[iccd] + '.pi')
os.system('pset dmgroup outfile=' + locclu + '/spec/sp' + ob +
'_' + regv[ireg] + '_ccd' + ccdv[iccd] + '_grp.pi')
os.system('pset dmgroup grouptype=ADAPTIVE grouptypeval=30')
os.system('pset dmgroup xcolumn="channel" ycolumn="counts"')
os.system('pset dmgroup binspec=""')
os.system('dmgroup verbose=1 mode=h')
# MKWARF --------------
os.system('punlearn mkwarf')
os.system('pset mkwarf infile="' + locclu + '/spec/sp' + ob +
'_' + regv[ireg] + '_ccd' + ccdv[iccd] +
'.pi[WMAP]"')
os.system('pset mkwarf outfile=' + locclu + '/spec/sp' + ob +
'_' + regv[ireg] + '_ccd' + ccdv[iccd] + '.warf')
os.system('pset mkwarf weightfile=' + locclu + '/spec/sp' +
ob + '_' + regv[ireg] + '_ccd' + ccdv[iccd] +
'.wfef')
#os.system('pset mkwarf pbkfile='+pbk)
os.system('pset mkwarf egridspec="0.3:11.0:0.01"')
os.system('pset mkwarf asolfile=' + acao)
os.system('mkwarf verbose=1 mode=h')
# DMEXTRACT BG -----------
os.system('punlearn dmextract')
os.system('pset dmextract infile="' + locclu + '/bg/bg' + ob +
'_ccd' + ccdv[iccd] + 'r.fits[sky=region(' + locclu +
'/reg/' + regv[ireg] + '_' + ob + '_ccd' +
ccdv[iccd] + '.reg)][bin PI]"')
os.system('pset dmextract outfile=' + locclu + '/spec/sp' +
ob + '_' + regv[ireg] + '_ccd' + ccdv[iccd] +
'_bgbg2.pi')
os.system('pset dmextract opt=pha1')
os.system('dmextract verbose=1 mode=h')
def radreg(clu, ob, rlo, rhi, prefix) :
locclu = 'mfe_'+clu
(rac, decc) = centradec.getrd(locclu)
badskyfovob = ['3182', '897', '11708']
acao = asol6_loc.asol(ob,'asol')
ccdname='i567'
ccdlist=['0,1,2,3','5','6','7']
# Get the SKY coodinates of the center.
os.system('punlearn dmcoords')
os.system('dmcoords '+locclu+'/clean'+ob+'.fits asolfile="'+acao+'" option=cel ra='+rac+' dec='+decc+' celfmt=hms')
xc = commands.getoutput('pget dmcoords x')
yc = commands.getoutput('pget dmcoords y')
xcf = float(xc)
ycf = float(yc)
# ra, dec in degrees
os.system('punlearn dmcoords')
os.system('dmcoords '+locclu+'/clean'+ob+'.fits asolfile="'+acao+'" option=sky x='+xc+' y='+yc+' celfmt=deg')
racd = float(commands.getoutput('pget dmcoords ra'))
decd = float(commands.getoutput('pget dmcoords dec'))
# Make a list of point sources, to be able to choose which ones are close
# to a given shell for it to be excluded.
ptfile = open(locclu+'/reg/pt0mfe_wcs.reg', 'r')
regline = ptfile.readline()
regv = []
ptr=[] # how far from (rac,decc) in pixels
ptdr=[] # 'radius' of circle/ellipse in pixels
while regline != '\n' and regline != '' :
if regline[0] != '#' :
regv.append(regline)
s1=regline.partition('(')
s2=s1[2].partition(':')
hh=float(s2[0])
s3=s2[2].partition(':')
mm=float(s3[0])
s4=s3[2].partition(',')
ss=float(s4[0])
ptra = 15.*(hh+mm/60.+ss/3600.)
s5=s4[2].partition(':')
dd=float(s5[0])
if s5[0][0]=='+' : ff=1.
elif s5[0][0]=='-' : ff=-1.
s6=s5[2].partition(':')
am=float(s6[0])
s7=s6[2].partition(',')
ac=float(s7[0])
ptdec= dd + ff * (am/60. + ac/3600.)
d2 = ( ( (ptra-racd) * numpy.cos(decd/180.*numpy.pi) ) ** 2. + (ptdec-decd) ** 2. ) * (3600./0.492)**2.
ptr.append( d2**0.5 )
if s1[0] == 'ellipse' :
s8=s7[2].partition("',")
s9=s8[2].partition("',")
ptdr.append(60./0.492*max(float(s8[0]),float(s9[0])))
elif s1[0] == 'circle' :
s8=s7[2].partition("'")
ptdr.append(60./0.492*float(s8[0]))
else :
print
print 'BAAAAAAAAAAAAAD REGIOOOOOOOOOOOON'
print
regline = ptfile.readline()
ptfile.close()
# get CCD regions
chipx=commands.getoutput('dmlist "'+locclu+'/reg/simplechipsreg'+ob+'.fits[cols x]" data,clean')
t1 = chipx.split('\n')
t1.remove(t1[0])
chipy=commands.getoutput('dmlist "'+locclu+'/reg/simplechipsreg'+ob+'.fits[cols y]" data,clean')
u1 = chipy.split('\n')
u1.remove(u1[0])
ccdid=commands.getoutput('dmlist "'+locclu+'/reg/simplechipsreg'+ob+'.fits[cols ccd_id]" data,clean')
c1 = ccdid.split('\n')
c1.remove(c1[0])
# goodchips[0] contains indices to u1, t1 or c1 that pertain to chip I (ie ACIS-I)
# goodchips[1] contains indices to u1, t1 or c1 that pertain to chip 5
# goodchips[2] contains indices to u1, t1 or c1 that pertain to chip 6
# goodchips[3] contains indices to u1, t1 or c1 that pertain to chip 7
goodchips=[[],[],[],[]]
# I 5 6 7
for i in range(len(c1)) :
if int(c1[i]) in (0,1,2,3) : goodchips[0].append(i)
if int(c1[i]) == 5 : goodchips[1].append(i)
if int(c1[i]) == 6 : goodchips[2].append(i)
if int(c1[i]) == 7 : goodchips[3].append(i)
# ccdreg will contain the regions (in string format) corresponding to
# the CCD's I, 5, 6 and 7
ccdreg=[[],[],[],[]]
ccdregfileappend=[False,False,False,False]
for iccd in range(4) :
if len(goodchips[iccd]) > 0 :
for igood in range(len(goodchips[iccd])) :
i = goodchips[iccd][igood]
polyx = []
t2=t1[i]
t3=t2.lstrip()
t4=t3.partition(' ')
while ('NaN' not in t4[0]) and (t4[1] != '') :
polyx.append(float(t4[0]))
t2=t4[2]
t3=t2.lstrip()
t4=t3.partition(' ')
polyy = []
u2=u1[i]
u3=u2.lstrip()
u4=u3.partition(' ')
while ('NaN' not in u4[0]) and (u4[1] != '') :
polyy.append(float(u4[0]))
u2=u4[2]
u3=u2.lstrip()
u4=u3.partition(' ')
ccdreg[iccd].append('polygon(')
for j in range(len(polyx)) :
ccdreg[iccd][igood] = ccdreg[iccd][igood] + str(polyx[j]) + ',' + str(polyy[j]) + ','
ccdreg[iccd][igood] = ccdreg[iccd][igood][0:-1]
ccdreg[iccd][igood] = ccdreg[iccd][igood] + ')'
if not os.path.exists(locclu+'/reg/obsimple'+ob+'ccd'+ccdname[iccd]+'.reg') and \
ob not in badskyfovob : # <--- list of obsids where ccd region was created mannually, because
# skyfov returned wrong region
ccdregfile = open(locclu+'/reg/obsimple'+ob+'ccd'+ccdname[iccd]+'.reg', 'w')
for igood in range(len(goodchips[iccd])) : ccdregfile.write(' +'+ccdreg[iccd][igood])
ccdregfile.close()
ccdregfileappend[iccd]=True
# Hi BG corner region
if os.path.exists(locclu+'/reg/hibgcorner'+ob+'.reg') :
hibgfile = open(locclu+'/reg/hibgcorner'+ob+'.reg','r')
hibgstr = hibgfile.readline()
hibgfile.close()
hibgx = float( hibgstr[7:-1].split(',')[0] )
hibgy = float( hibgstr[7:-1].split(',')[1] )
hibgr = ( (hibgx-xcf)**2. + (hibgy-ycf)**2. )**0.5
# make region of intersection of annulus with chip regions MINUS PTSRCs
presccd=''
for iccd in range(4) :
if len(ccdreg[iccd]) > 0 :
# write region to file
if ob not in badskyfovob :
fovptfile = open(prefix+'_ccd'+str(ccdname[iccd])+'_xfov_pt_simple.reg', 'w')
for ii in range(len(ccdreg[iccd])) :
fovptfile.write('+annulus('+xc+','+yc+','+str(rlo)+','+str(rhi)+') * '+ccdreg[iccd][ii]+'\n')
for jj in range(len(ptr)) : # add point source regions which lie within this annulus
if ptr[jj]-ptdr[jj] <= rhi and ptr[jj]+ptdr[jj] >= rlo : fovptfile.write('-'+regv[jj][0:-1]+' ')
if iccd == 0 and os.path.exists(locclu+'/reg/hibgcorner'+ob+'.reg') and hibgr-1095. <= rhi and hibgr+1095. >= rlo : fovptfile.write( '-'+hibgstr[0:-1] )
fovptfile.write('\n')
fovptfile.close()
elif os.path.exists(locclu+'/reg/obsimple'+ob+'ccd'+ccdname[iccd]+'.reg') :
fovptfile = open(prefix+'_ccd'+str(ccdname[iccd])+'_xfov_pt_simple.reg', 'w')
for ii in range(len(ccdreg[iccd])) :
obsimplefile = open(locclu+'/reg/obsimple'+ob+'ccd'+ccdname[iccd]+'.reg', 'r')
obsimpleline = obsimplefile.readline().replace('\n','').replace(' +',' ')
fovptfile.write('+annulus('+xc+','+yc+','+str(rlo)+','+str(rhi)+') * '+obsimpleline+'\n')
for jj in range(len(ptr)) : # add point source regions which lie within this annulus
if ptr[jj]-ptdr[jj] <= rhi and ptr[jj]+ptdr[jj] >= rlo : fovptfile.write('-'+regv[jj][0:-1]+' ')
if iccd == 0 and os.path.exists(locclu+'/reg/hibgcorner'+ob+'.reg') and hibgr-1095. <= rhi and hibgr+1095. >= rlo : fovptfile.write( '-'+hibgstr[0:-1] )
fovptfile.write('\n')
obsimplefile.close()
fovptfile.close()
# add a good CCD to presccd (radial shell dependent
if float(commands.getoutput('dmlist "'+locclu+'/clean'+ob+'.fits[ccd_id='+ccdlist[iccd]+'][sky=region('+prefix+'_ccd'+str(ccdname[iccd])+'_xfov_pt_simple.reg)]" counts')) > 0 and os.path.exists(locclu+'/bg/bg'+ob+'_ccd'+ccdname[iccd]+'r_en.fits') : presccd=presccd+ccdname[iccd]
else :
if ob not in badskyfovob : os.remove(prefix+'_ccd'+str(ccdname[iccd])+'_xfov_pt_simple.reg')
# presccd is a string containing the CCD's found in this range rlo -> rhi
return presccd
def bg(clu, ob):
print
print 'Making BG files for OBSID ' + ob + ' ---------------------------'
print
locclu = 'mfe_' + clu
acao = asol6_loc.asol(ob, 'asol')
datamode = commands.getoutput('dmkeypar ' + locclu + '/clean' + ob +
'.fits datamode echo+')
sd = commands.getoutput('dmkeypar ' + locclu + '/clean' + ob +
'.fits date-obs echo+')
intdat = int(sd[0:4] + sd[5:7] + sd[8:10])
if intdat < 19990916:
bgd = 'period a' # period A : BG too uncertain because CTI rapidly increasing!
elif 19990916 <= intdat and intdat <= 20000128:
bgd = '1999-09-16' # period B
elif 20000129 <= intdat and intdat <= 20001130:
if datamode == 'FAINT':
bgd = '2000-01-29' # period C
elif datamode == 'VFAINT':
bgd = '2000-12-01' # period C by date, but assign to period D because no VFAINT mode in period C blank-sky files
elif 20001201 <= intdat and intdat <= 20050831:
bgd = '2000-12-01' # period D
elif 20050901 <= intdat:
bgd = '2005-09-01' # period E
hardob = hardsoft3.hardsoft(clu, [ob], 'h')
softob = hardsoft3.hardsoft(clu, [ob], 's')
if len(hardob) == 1: bgaim = 'i'
elif len(softob) == 1: bgaim = 's'
else:
print '------------ CANT DETERMINE AIM POINT -----------------'
print
bgaim = 'unknown'
chipnum = []
allchips = '0123567'
for c in allchips:
if float(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[ccd_id=' + c + ']" counts')) > 0:
chipnum.append(c)
####### Make region for the high-BG corner
if '1' in chipnum:
os.system('punlearn dmcoords')
os.system('dmcoords ' + locclu + '/clean' + ob +
'.fits option=chip chip_id=1 chipx=900 chipy=512 asol=' +
acao)
hibgx = commands.getoutput('pget dmcoords x')
hibgy = commands.getoutput('pget dmcoords y')
roll = float(
commands.getoutput('dmkeypar ' + locclu + '/clean' + ob +
'.fits roll_pnt echo+'))
hibgfile = open(locclu + '/reg/hibgcorner' + ob + '.reg', 'w')
hibgfile.write('rotbox(' + hibgx + ',' + hibgy + ',1050,300,' +
str(360. - roll) + ')\n')
hibgfile.close()
############################################3
if commands.getoutput('dmkeypar ' + locclu + '/clean' + ob +
'.fits cti_corr echo+') == '1':
bgcti = '_cti'
elif commands.getoutput('dmkeypar ' + locclu + '/clean' + ob +
'.fits cti_corr echo+') == '0':
bgcti = ''
ciaodir = commands.getoutput('echo $ASCDS_INSTALL')
bgf = ciaodir + '/CALDB/data/chandra/acis/bkgrnd'
if bgaim != 'unknown' and bgd != 'period a':
for c in chipnum:
bgfound = glob.glob(bgf + '/acis' + c + bgaim + 'D' + bgd +
'bkgrnd' + bgcti + 'N000*.fits')
bgfound.sort()
if len(bgfound) == 0:
print "---- no BG files found for cluster " + clu + ", OBSID " + ob + ", chip# " + c + " ------------------ "
print 'The following was not found: '
print bgf + '/acis' + c + bgaim + 'D' + bgd + 'bkgrnd' + bgcti + 'N000*.fits'
print
elif len(bgfound) == 1:
if os.path.exists(locclu + '/bg/bg' + ob + '_ccd' + c +
'.fits'):
os.remove(locclu + '/bg/bg' + ob + '_ccd' + c + '.fits')
os.symlink(bgfound[0],
locclu + '/bg/bg' + ob + '_ccd' + c + '.fits')
elif len(bgfound) > 1:
print
print ' -------------- MANY BG FILES FOUND FOR cluster ' + clu + ', OBSID ' + ob + ', CCD ' + c
print ' -------------- CHOOSING THE LATEST: ' + bgfound[-1]
print
if os.path.exists(locclu + '/bg/bg' + ob + '_ccd' + c +
'.fits'):
os.remove(locclu + '/bg/bg' + ob + '_ccd' + c + '.fits')
os.symlink(bgfound[-1],
locclu + '/bg/bg' + ob + '_ccd' + c + '.fits')
chipnums = []
for s in ['5', '6', '7']:
if s in chipnum: chipnums.append(s)
chipnumi = []
for s in ['0', '1', '2', '3']:
if s in chipnum: chipnumi.append(s)
if len(chipnumi) > 0:
makebgi(ob, locclu, datamode, bgd, acao)
if len(chipnums) > 0:
makebgs(ob, locclu, chipnums, datamode, bgd, acao)
print
print
def mrg( clu, obsids, longest ) :
origclu = 'orig_' + clu
locclu = 'mfe_' + clu
acao = asol6_loc.asol(longest, 'asol')
if not os.path.exists(locclu+'/mrgevt.fits') :
print
print 'Merging evt files for cluster '+clu+' ------------------------'
print
hardob = hardsoft3.hardsoft(clu, [longest], 'h')
softob = hardsoft3.hardsoft(clu, [longest], 's')
# determining which chips to use in computing the centroid
if len(hardob)==1 : chipstr0 = '[ccd_id=0,1,2,3]' # ACIS-I: straightforward: chips 0,1,2,3
else :
# choose the soft chip with most count to compute centroid
chipcount=numpy.zeros(3)
softchip=['5','6','7']
for ichip in range(3) : chipcount[ichip] = int(commands.getoutput('dmlist "mfe_'+clu+'/repro3_evt'+longest+'.fits[ccd_id='+softchip[ichip]+']" counts'))
chipstr0='[ccd_id='+softchip[numpy.argmax(chipcount)]+']'
# (x1, y1)
os.system('punlearn dmstat')
os.system('dmstat "mfe_'+clu+'/repro3_evt'+longest+'.fits'+chipstr0+'[energy=300:7000][cols x]" median=yes')
x1=commands.getoutput('pget dmstat out_median')
sx1=commands.getoutput('pget dmstat out_sigma')
os.system('punlearn dmstat')
os.system('dmstat "mfe_'+clu+'/repro3_evt'+longest+'.fits'+chipstr0+'[energy=300:7000][cols y]" median=yes')
y1=commands.getoutput('pget dmstat out_median')
sy1=commands.getoutput('pget dmstat out_sigma')
# (x2, y2)
os.system('punlearn dmstat')
os.system('dmstat "mfe_'+clu+'/repro3_evt'+longest+'.fits'+chipstr0+'[energy=300:7000][sky=ellipse('+x1+','+y1+','+str(2.*float(sx1))+','+str(2.*float(sy1))+',0)][cols x]" median=yes')
x2=commands.getoutput('pget dmstat out_median')
sx2=commands.getoutput('pget dmstat out_sigma')
os.system('punlearn dmstat')
os.system('dmstat "mfe_'+clu+'/repro3_evt'+longest+'.fits'+chipstr0+'[energy=300:7000][sky=ellipse('+x1+','+y1+','+str(2.*float(sx1))+','+str(2.*float(sy1))+',0)][cols y]" median=yes')
y2=commands.getoutput('pget dmstat out_median')
sy2=commands.getoutput('pget dmstat out_sigma')
# (x3, y3)
os.system('punlearn dmstat')
os.system('dmstat "mfe_'+clu+'/repro3_evt'+longest+'.fits'+chipstr0+'[energy=300:7000][sky=ellipse('+x2+','+y2+','+str(1.*float(sx2))+','+str(1.*float(sy2))+',0)][cols x]" median=yes')
x3=commands.getoutput('pget dmstat out_median')
sx3=commands.getoutput('pget dmstat out_sigma')
os.system('punlearn dmstat')
os.system('dmstat "mfe_'+clu+'/repro3_evt'+longest+'.fits'+chipstr0+'[energy=300:7000][sky=ellipse('+x2+','+y2+','+str(1.*float(sx2))+','+str(1.*float(sy2))+',0)][cols y]" median=yes')
y3=commands.getoutput('pget dmstat out_median')
sy3=commands.getoutput('pget dmstat out_sigma')
# (x4, y4)
os.system('punlearn dmstat')
os.system('dmstat "mfe_'+clu+'/repro3_evt'+longest+'.fits'+chipstr0+'[energy=300:7000][sky=ellipse('+x3+','+y3+','+str(0.75*float(sx3))+','+str(0.75*float(sy3))+',0)][cols x]" median=yes')
x4=commands.getoutput('pget dmstat out_median')
sx4=commands.getoutput('pget dmstat out_sigma')
os.system('punlearn dmstat')
os.system('dmstat "mfe_'+clu+'/repro3_evt'+longest+'.fits'+chipstr0+'[energy=300:7000][sky=ellipse('+x3+','+y3+','+str(0.75*float(sx3))+','+str(0.75*float(sy3))+',0)][cols y]" median=yes')
y4=commands.getoutput('pget dmstat out_median')
sy4=commands.getoutput('pget dmstat out_sigma')
if len(obsids) > 1 :
os.system('punlearn merge_obs')
evtstr = ''
asolstr= ''
for j in range(len(obsids)) :
evtstr = evtstr + ','+locclu+'/repro3_evt_nophas'+obsids[j]+'.fits'
asolstr= asolstr+ ','+asol6_loc.asol(obsids[j], 'asol')
os.system('dmcopy "mfe_'+clu+'/repro3_evt'+obsids[j]+'.fits[ccd_id=0,1,2,3,5,6,7][col -phas]" '+locclu+'/repro3_evt_nophas'+obsids[j]+'.fits')
evtstr = evtstr[1:]
asolstr= asolstr[1:]
os.system('pset merge_obs infiles="'+evtstr+'"')
#os.system('pset merge_all chip="0,1,2,3,5,6,7" \n')
os.system('pset merge_obs refcoord=mfe_'+clu+'/repro3_evt'+longest+'.fits')
os.system('pset merge_obs outroot='+locclu+'/mrgevt')
os.system('pset merge_obs asolfiles='+asolstr)
os.system('merge_obs mode=h ')
os.system('cp '+locclu+'/mrgevt_merged_evt.fits '+locclu+'/mrgevt.fits')
#mrg_cmd_file.close()
#os.system('source temp_merge_all.csh')
#os.remove('temp_merge_all.csh')
elif len(obsids) == 1 : shutil.copy('mfe_'+clu+'/repro3_evt'+obsids[0]+'.fits', locclu+'/mrgevt.fits')
# (xc, yc)
os.system('punlearn dmstat')
os.system('dmstat "'+locclu+'/mrgevt.fits[sky=ellipse('+x4+','+y4+','+sx4+','+sy4+',0.)][cols x]" median=yes')
xc=commands.getoutput('pget dmstat out_median')
xcf = float(xc)
os.system('punlearn dmstat')
os.system('dmstat "'+locclu+'/mrgevt.fits[sky=ellipse('+x4+','+y4+','+sx4+','+sy4+',0.)][cols y]" median=yes')
yc=commands.getoutput('pget dmstat out_median')
ycf=float(yc)
# (rac, decc)
os.system('punlearn dmcoords')
os.system('dmcoords '+locclu+'/mrgevt.fits asolfile='+acao+' option=sky x='+xc+' y='+yc+' celfmt=hms')
rac = commands.getoutput('pget dmcoords ra')
decc = commands.getoutput('pget dmcoords dec')
# writing rac, dec to file
racfile = open(locclu+'/rac.txt', 'w')
racfile.write(rac+'\n')
racfile.close()
deccfile = open(locclu+'/decc.txt', 'w')
deccfile.write(decc+'\n')
deccfile.close()
else :
print
print '------- Merged file exists already, skipping mrg procedure'
print
print
def preradial(clu, obsids, r1mpc):
locclu = 'mfe_' + clu
exptime = numpy.zeros(len(obsids))
for j in range(len(obsids)):
exptime[j] = float(
commands.getoutput('dmkeypar ' + locclu + '/clean' + obsids[j] +
'.fits livetime echo+'))
longob = obsids[numpy.argmax(exptime)]
if not os.path.exists(locclu + '/ctofr'): os.mkdir(locclu + '/ctofr')
if len(obsids) > 1:
os.system('punlearn obs')
evtstr = ''
asolstr = ''
for j in range(len(obsids)):
evtstr = evtstr + ',' + locclu + '/clean_nophas' + obsids[
j] + '_en.fits'
asolstr = asolstr + ',' + asol6_loc.asol(obsids[j], 'asol')
os.system('punlearn dmcopy')
os.system(
'dmcopy "' + locclu + '/clean' + obsids[j] +
'.fits[energy=300:7000][ccd_id=0,1,2,3,5,6,7][col -phas]" ' +
locclu + '/clean_nophas' + obsids[j] + '_en.fits')
evtstr = evtstr[1:]
asolstr = asolstr[1:]
os.system('pset merge_obs infiles="' + evtstr + '"')
os.system('pset merge_obs asolfiles=' + asolstr)
os.system('pset merge_obs refcoord=' + locclu + '/clean' + longob +
'.fits')
os.system('pset merge_obs outroot=' + locclu + '/mrgclean_en')
os.system('merge_obs mode=h ')
os.system('cp ' + locclu + '/mrgclean_en_merged_evt.fits ' + locclu +
'/mrgclean_en.fits')
# clean up
os.system('rm ' + locclu + '/clean_nophas[1-9]*_en.fits')
else:
os.system('punlearn dmcopy')
os.system('dmcopy "' + locclu + '/clean' + obsids[0] +
'.fits[ccd_id=0,1,2,3,5,6,7][energy=300:7000][col -phas]" ' +
locclu + '/mrgclean_en.fits')
acao = asol6_loc.asol(longob, 'asol')
# get the coordinates of the center in SKY units
os.system('punlearn dmcoords')
os.system('dmcoords ' + locclu + '/mrgclean_en.fits asolfile=' + acao +
' ra=`more ' + locclu + '/rac.txt` dec=`more ' + locclu +
'/decc.txt` option=cel celfmt=hms')
xs = commands.getoutput('pget dmcoords x')
ys = commands.getoutput('pget dmcoords y')
centerccd = int(commands.getoutput('pget dmcoords chip_id'))
# Make file with the radial coordinate of each photon count
os.system('punlearn dmtcalc')
os.system(
'dmtcalc "' + locclu +
'/mrgclean_en.fits[col -time,-ccd_id,-node_id,-expno,-chip,-tdet,-det,-phas,-pha_ro,-energy,-pi,-fltgrade,-grade,-status][exclude sky=region('
+ locclu + '/reg/pt0mfe_wcs.reg)]" "' + locclu +
'/evtrad_mrgclean.txt[opt kernel=text/simple]" expr="r2=((' + xs +
'-sky[0])^2)+((' + ys + '-sky[1])^2)" clobber=no')
r2 = []
rfile = open(locclu + '/evtrad_mrgclean.txt', 'r')
intermed = rfile.readline()
intermed = rfile.readline()
intermed = rfile.readline() # first data-containing line
while intermed != '' and intermed != '\n':
r2.append(float(intermed.split(' ')[2][0:-1]))
intermed = rfile.readline()
rfile.close()
rmax = (max(r2))**0.5
os.system('rm ' + locclu + '/radbins5.txt' + ' ' + locclu + '/hienrlo.txt')
for ob in obsids:
radial10.radial(clu, ob, r1mpc / 0.492, rmax, obsids)
def ktofr(clu, obsids, r1mpc, zz, nnhhlab):
print ' -----------> ktofr14loc for ' + clu
clean()
gc.collect()
set_stat('cstat')
# local directory for this cluster
locclu = 'mfe_' + clu
# coords of center of the cluster
(rac, decc) = centradec.getrd(locclu)
# don't use these observations
badhienobs = [
'7686', '7688', '7689', '7690', '7692', '7693', '7694', '7696', '7701'
]
if not os.path.exists(locclu + '/ktofrsp/'): os.mkdir(locclu + '/ktofrsp/')
# Chandra CCDs to look for data in
ccdname = 'i567'
ccdlist = ['0,1,2,3', '5', '6', '7']
# Plotting settings
dataplot = ChipsCurve()
modelplot = ChipsHistogram()
dataplot.symbol.style = 'plus'
dataplot.symbol.size = 3
dataplot.line.style = 'none'
modelplot.line.color = "red"
modelplot.line.thickness = 3
# create simplechipsreg regions.
for ob in obsids:
os.system('punlearn skyfov')
os.system('skyfov ' + locclu + '/clean' + ob + '.fits ' + locclu +
'/reg/simplechipsreg' + ob + '.fits clobber=yes')
# which CCD's are present in each OBSID
presccdglob = []
for iob in range(len(obsids)):
presccdglob.append(whichccd2z_loc.find(clu, obsids[iob]))
# Reset these global variables
globmod.globstr1 = ''
globmod.globstr2 = ''
for iob in range(len(obsids)):
ob = obsids[iob]
# Make file with only counts in energy range .3-7keV
os.system('punlearn dmcopy')
os.system('dmcopy "' + locclu + '/clean' + ob +
'.fits[energy=300:7000]" ' + locclu + '/evt' + ob +
'_b.fits')
# get the coordinates of the center in SKY units
os.system('punlearn dmcoords')
os.system('dmcoords ' + locclu + '/clean' + ob + '.fits asolfile=' +
asol6_loc.asol(ob, 'asol') + ' ra=' + rac + ' dec=' + decc +
' option=cel celfmt=hms')
xs = commands.getoutput('pget dmcoords x')
ys = commands.getoutput('pget dmcoords y')
# Make region containing all ptsrcs and hi-BG corner region
os.system('cp ' + locclu + '/reg/pt0mfe_wcs.reg ' + locclu +
'/reg/pt_hibg' + ob + '.reg')
if os.path.exists(locclu + '/reg/hibgcorner' + ob + '.reg'):
os.system('more ' + locclu + '/reg/hibgcorner' + ob + '.reg >> ' +
locclu + '/reg/pt_hibg' + ob + '.reg')
# Make file with the radial coordinate of each photon count
os.system(
'dmtcalc "' + locclu + '/evt' + ob +
'_b.fits[col -time,-ccd_id,-node_id,-expno,-chip,-tdet,-det,-phas,-pha_ro,-energy,-pi,-fltgrade,-grade,-status][exclude sky=region('
+ locclu + '/reg/pt_hibg' + ob + '.reg)]" "' + locclu + '/evtrad' +
ob + '.txt[opt kernel=text/simple]" expr="r2=((' + xs +
'-sky[0])^2)+((' + ys + '-sky[1])^2)"')
# Get the radial coord of EACH photon count!
# To be used to determine if we have enough counts
# for a given radial bin to get 10% error on best-fit
# kT value.
r = [] # in Mpc
for ob in obsids:
rfile = open(locclu + '/evtrad' + ob + '.txt', 'r')
intermed = rfile.readline()
intermed = rfile.readline()
intermed = rfile.readline() # first data-containing line
while intermed != '' and intermed != '\n':
r.append(0.492 / r1mpc * float(intermed.split(' ')[2][0:-1])**0.5)
intermed = rfile.readline()
rfile.close()
r.sort()
# Define rmin and rmax
rmax = r[-1]
rmin = 1.2 / r1mpc
# The first radius, defined by rmin
for imin in range(len(r)):
if r[imin] >= rmin: break # imin is the index where r >= rmin
# Read abundance from cluname_TZ.txt
tzfile = open('cluname_TZ.txt', 'r')
intermed = 'init'
while intermed != '':
intermed = tzfile.readline()
if intermed.split()[0] == clu:
abin = float(intermed.split()[2])
about = float(intermed.split()[4])
ktin = float(intermed.split()[1])
ktout = float(intermed.split()[3])
break
tzfile.close()
# Bin the radial data
rbnd = [rmin] # the 1st radius
ct1bin = 100
i = imin + ct1bin
while i < len(r):
rbnd.append(r[i])
i = i + ct1bin
rbnd = n.array(rbnd)
# Load Hi-energy count in losrc regions
losrchienct = n.ones((len(obsids), 4)) * -1
for iob in range(len(obsids)):
ob = obsids[iob]
sclfile = open(locclu + '/ctofr/scl' + ob + '.txt', 'r')
for iccd in range(4):
intermed = sclfile.readline()
if intermed.split()[2].lower() != 'nan':
losrchienct[iob, iccd] = float(intermed.split()[2])
sclfile.close()
# Load string containing exculsion of all point sources
excstr = []
for ob in obsids:
excfile = open(locclu + '/reg/exclpt' + ob + '.reg', 'r')
excstr.append(excfile.readline())
excfile.close()
################### make radial bins which contain enough counts for a best-fit kT with 10% error ########################
ccdindex = {'i': 0, '5': 1, '6': 2, '7': 3}
vrstat = []
vkt = []
vktp = []
vktm = []
ishell = 0
rz1 = []
rz2 = []
ishell = 0 # the index of everything created new, in this loop. only increases, when we get a satisfactory fit.
i1 = 0 # index to rbnd indicating inner radius
i2 = 1 # index to rbnd indicating outer radius
while i2 <= len(rbnd) - 1:
ct = 1
while ct <= 10:
print '======== loop ct =', ct
# get annulus temperature from cluname_TZ.txt, based on in/out regions
if ishell == 0:
if (rbnd[i1] + rbnd[i2]) / 2 <= 0.1 and ktin > 0: tshell = ktin
elif (rbnd[i1] + rbnd[i2]) / 2 > 0.1 and ktout > 0:
tshell = ktout
if ktin < 0 and ktout > 0: tshell = ktout
elif ktout < 0 and ktin > 0: tshell = ktin
else: tshell = 5.
else: tshell = vkt[ishell - 1]
# Calculate BG fraction in the annulus
sclbgct = 0
for iob in range(len(obsids)):
ob = obsids[iob]
annfile = open('antemp.reg', 'w')
annfile.write('annulus(' + rac + ',' + decc + ',' +
str(rbnd[i1] * r1mpc) + '",' +
str(rbnd[i2] * r1mpc) + '")\n')
annfile.write(excstr[iob])
annfile.close()
for ccd in presccdglob[iob]:
sclbgct = sclbgct + float(
commands.getoutput(
'dmlist "' + locclu + '/bg/bg' + ob + '_ccd' +
ccd + 'r_en.fits[sky=region(antemp.reg)]" counts')
) / float(
commands.getoutput(
'dmkeypar ' + locclu + '/bg/bg' + ob + '_ccd' +
ccd + 'r_en.fits exposure echo+')) * float(
commands.getoutput('dmkeypar ' + locclu +
'/evt' + ob +
'_b.fits exposure echo+'))
os.remove('antemp.reg')
bgfrac = sclbgct / float(i2 - i1) / ct1bin
# given approx. kT and BGfrac, how many counts do we need for 10% error?
nnec = (500 * 10.**(1.976 * bgfrac)) * (tshell / 2.)**1.7
nnec = max(nnec, 153.) # 153counts is the value at BGf=0, kT=1keV.
# We take this as the min number of counts for making a kT bin
inec0 = min(int(nnec / ct1bin) + i1 + 1, len(rbnd) - 1)
# making sure that rhi/rlo >= 1.25:
i125 = n.where(rbnd >= 1.25 * rbnd[i1])
if len(i125[0]) == 0: i125 = [[len(rbnd) - 1]]
inec = max(inec0, i125[0][0])
if inec <= i2 or inec == len(rbnd) - 1:
i2 = inec
break
else:
i2 = inec
ct = ct + 1
if ct >= 11:
os.system('echo ' + str(ishell) + ' >> ' + locclu +
'/shells_nocnvg.txt')
rz1.append(rbnd[i1])
rz2.append(rbnd[i2])
################# make spec and fit ####################################
# Get the CCD's present in this shell
presccd = [] # the ccd's that are present in this SHELL!
for iob in range(len(obsids)):
ob = obsids[iob]
# radreg4 returns the ccd's that are present in this SHELL!
# and makes the regions necessary for them to be used in fits..
intermed1 = radreg4simple3.radreg(
clu, ob, rz1[-1] * r1mpc / .492, rz2[-1] * r1mpc / .492,
locclu + '/ktofrsp/kt14an' + ob + '_' + str(ishell))
presccd.append(intermed1)
for ccd in str(presccd[iob]):
# Make the spectra for SHELL x CCD
os.system('punlearn dmextract')
os.system(
'dmextract "' + locclu + '/clean' + ob + '.fits[ccd_id=' +
ccdlist[ccdindex[ccd]] + '][sky=region(' + locclu +
'/ktofrsp/kt14an' + ob + '_' + str(ishell) + '_ccd' + ccd +
'_xfov_pt_simple.reg)][bin PI]" ' + locclu +
'/ktofrsp/sp14_' + ob + '_' + str(ishell) + '_ccd' + ccd +
'.fits opt=pha1 wmap="[energy=300:2000][bin det=8]" clobber=yes'
)
# Make ARF given the WMAP from the above spectrum file
#pbk = asol6_loc.asol(ob,'pbk')
acao = asol6_loc.asol(ob, 'asol')
os.system('punlearn mkwarf')
os.system('pset mkwarf infile="' + locclu + '/ktofrsp/sp14_' +
ob + '_' + str(ishell) + '_ccd' + ccd +
'.fits[WMAP]"')
os.system('pset mkwarf outfile=' + locclu +
'/ktofrsp/warf14_' + ob + '_' + str(ishell) +
'_ccd' + ccd + '.fits')
os.system('pset mkwarf weightfile=' + locclu +
'/ktofrsp/wfef14_' + ob + '_' + str(ishell) +
'_ccd' + ccd + '.fits')
#os.system('pset mkwarf pbkfile='+pbk)
os.system('pset mkwarf egridspec="0.3:11.0:0.01"')
os.system('pset mkwarf asolfile=' + acao)
os.system('mkwarf verbose=1 mode=h clobber=yes')
os.system('rm ' + locclu + '/ktofrsp/wfef14_' + ob + '_' +
str(ishell) + '_ccd' + ccd + '.fits')
# Make BG spectra and load them, only once for ishell=0
# This is here because it uses ktofrsp/ktan14*.reg, created just
# above in radreg4simple2.radreg()
if ishell == 0:
infieldccd, infieldgalperbs, infieldcxbperbs = loadbg4z8simple3.bg(
clu, obsids, presccdglob)
for iob in range(len(obsids)):
ob = obsids[iob]
for ccd in str(presccdglob[iob]):
exec 'gal1bg_' + ob + '_' + ccd + '_normval = float( gal1bg_' + ob + '_' + ccd + '.norm.val )'
exec 'cxbbg_' + ob + '_' + ccd + '_amplval = float( cxbbg_' + ob + '_' + ccd + '.ampl.val )'
bginf_present = False
iob_in = -1
for iob in range(len(obsids)):
if len(infieldccd[iob]) > 0:
bginf_present = True
iob_in = iob
# Make sure that all the needed files were created. If not, remove from prescccd
# any CCD wich is missing PI, ARF or RMF file
firstiob = -1
for iob in range(len(obsids)):
ob = obsids[iob]
for ccd in str(presccd[iob]):
if not os.path.exists(locclu+'/ktofrsp/warf14_'+ob+'_'+str(ishell)+'_ccd'+ccd+'.fits') \
or not os.path.exists(locclu+'/spec/sp'+ob+'_ccd'+ccd+'_center.wrmf') \
or not os.path.exists(locclu+'/ktofrsp/sp14_'+ob+'_'+str(ishell)+'_ccd'+ccd+'.fits') \
or ccd not in presccdglob[iob] :
presccd[iob] = presccd[iob].replace(ccd, '')
if len(presccd[iob]) > 0 and firstiob == -1: firstiob = iob
print
print '))))))))))))) clu = ', clu
print '))))))))))))) obsids = ', obsids
print '))))))))))))) ishell = ', ishell
print '))))))))))))) presccdglob = ', presccdglob
print '))))))))))))) presccd = ', presccd
print
# Load data we just made
srcstr = ''
for iob in range(len(obsids)):
ob = obsids[iob]
for ccd in presccd[iob]:
load_pha(
ob + '.' + str(ishell) + '.' + ccd,
locclu + '/ktofrsp/sp14_' + ob + '_' + str(ishell) +
'_ccd' + ccd + '.fits')
load_rmf(
ob + '.' + str(ishell) + '.' + ccd,
locclu + '/spec/sp' + ob + '_ccd' + ccd + '_center.wrmf')
load_arf(
ob + '.' + str(ishell) + '.' + ccd,
locclu + '/ktofrsp/warf14_' + ob + '_' + str(ishell) +
'_ccd' + ccd + '.fits')
bgscl = get_data(ob + '.' + str(ishell) + '.' +
ccd).backscal * get_data(ob + '.' + str(
ishell) + '.' + ccd).exposure / get_data(
'bg' + ob + '.' +
ccd).backscal / get_data('bg' + ob +
'.' +
ccd).exposure
newhienbgscl = calc_data_sum(
id=ob + '.' + str(ishell) + '.' + ccd, lo=9.5,
hi=12) / calc_data_sum(
id='bg' + ob + '.' + ccd, lo=9.5, hi=12)
srcstr = srcstr + '"' + ob + '.' + str(
ishell) + '.' + ccd + '",'
# the source model
rsp = get_response(ob + '.' + str(ishell) + '.' + ccd)
bgrsp = get_response('bg' + ob + '.' + ccd)
groupzeros.grp(ob + '.' + str(ishell) + '.' + ccd, ':.3,7:')
if ob not in badhienobs:
exec 'set_full_model( "' + ob + '.' + str(
ishell
) + '.' + ccd + '", rsp(xsphabs.ab * xsapec.em' + str(
ishell
) + '_' + ob + '_' + ccd + ' ) + newhienbgscl * bgrsp( powlaw1d.p1_' + ob + '_' + ccd + ' + powlaw1d.p2_' + ob + '_' + ccd + ' + exp.e1_' + ob + '_' + ccd + ' + gauss1d.g1_' + ob + '_' + ccd + ' + gauss1d.g2_' + ob + '_' + ccd + ' + gauss1d.g3_' + ob + '_' + ccd + ' + gauss1d.g5_' + ob + '_' + ccd + ' ) + rsp( xsphabs.ab * powlaw1d.cxbbg_' + ob + '_' + ccd + ' + xsapec.gal1bg_' + ob + '_' + ccd + ' ) )'
else:
exec 'set_full_model( "' + ob + '.' + str(
ishell
) + '.' + ccd + '", rsp(xsphabs.ab * xsapec.em' + str(
ishell
) + '_' + ob + '_' + ccd + ' ) + bgscl * bgrsp( powlaw1d.p1_' + ob + '_' + ccd + ' + powlaw1d.p2_' + ob + '_' + ccd + ' + exp.e1_' + ob + '_' + ccd + ' + gauss1d.g1_' + ob + '_' + ccd + ' + gauss1d.g2_' + ob + '_' + ccd + ' + gauss1d.g3_' + ob + '_' + ccd + ' + gauss1d.g5_' + ob + '_' + ccd + ' ) + rsp( xsphabs.ab * powlaw1d.cxbbg_' + ob + '_' + ccd + ' + xsapec.gal1bg_' + ob + '_' + ccd + ' ) )'
# If we fit the in-field BG, then obtain gal1 and cxb components from it
if bginf_present:
exec 'set_par( gal1bg_' + ob + '_' + ccd + '.norm, val=infieldgalperbs[iob_in][0]*get_data("' + ob + '.' + str(
ishell) + '.' + ccd + '").backscal )'
exec 'set_par( cxbbg_' + ob + '_' + ccd + '.ampl, val=infieldcxbperbs[iob_in][0]*get_data("' + ob + '.' + str(
ishell) + '.' + ccd + '").backscal )'
# if no in-field BG, then scale down the values of gal1 and cxb, which were already
# read by loadbg4z8simple. scaling is according to ratio of backscal of source spec
# to backscal of BG spec
else:
exec 'set_par( gal1bg_' + ob + '_' + ccd + '.norm, val=get_data("' + ob + '.' + str(
ishell
) + '.' + ccd + '").backscal * gal1bg_' + ob + '_' + ccd + '_normval )'
exec 'set_par( cxbbg_' + ob + '_' + ccd + '.ampl, val=get_data("' + ob + '.' + str(
ishell
) + '.' + ccd + '").backscal * cxbbg_' + ob + '_' + ccd + '_amplval )'
# Setting abundance parameter, kT and redshift
for ccd in presccd[iob]:
exec 'set_par( em' + str(
ishell) + '_' + ob + '_' + ccd + '.redshift, val=' + str(
zz) + ')'
exec 'set_par( em' + str(
ishell
) + '_' + ob + '_' + ccd + '.abundanc, val=0.3, min=0, max=5, frozen=False)'
exec 'set_par( em' + str(
ishell
) + '_' + ob + '_' + ccd + '.kt, val=5, min=0, max=40, frozen=False)'
if iob != firstiob or ccd != presccd[firstiob][0]:
exec 'link( em' + str(
ishell) + '_' + ob + '_' + ccd + '.kt, em' + str(
ishell) + '_' + obsids[firstiob] + '_' + presccd[
firstiob][0] + '.kt )'
exec 'link( em' + str(
ishell) + '_' + ob + '_' + ccd + '.abundanc, em' + str(
ishell) + '_' + obsids[firstiob] + '_' + presccd[
firstiob][0] + '.abundanc )'
if srcstr[0:-1] != '': # if there is data to fit:
# Set nH
if clu != 'a478':
set_par(ab.nh,
val=nnhhlab,
min=nnhhlab / 10.,
max=nnhhlab * 10.,
frozen=True)
else:
set_par(ab.nh,
val=nnhhlab * 1.1,
min=nnhhlab,
max=nnhhlab * 100.,
frozen=False)
# Setting normalizations, link norms if backscal covers 95-105 % of annulus area
iobiccd1 = [-1, -1]
anarea = n.pi * ((rz2[-1] * r1mpc / .492)**2. -
(rz1[-1] * r1mpc / .492)**2.)
for iob in range(len(obsids)):
ob = obsids[iob]
for iccd in range(len(presccd[iob])):
ccd = presccd[iob][iccd]
bspix2 = float(
commands.getoutput(
'dmkeypar ' + locclu + '/ktofrsp/sp14_' + ob +
'_' + str(ishell) + '_ccd' + ccd +
'.fits backscal echo+')) * 64.0 * 1024.**2.
if iobiccd1 == [
-1, -1
] or bspix2 / anarea < 0.95 or bspix2 / anarea > 1.05:
exec 'set_par(em' + str(
ishell
) + '_' + ob + '_' + ccd + '.norm, val=0.02, min=2e-4, max=2.)'
exec 'emnorm0=abs(float(em' + str(
ishell
) + '_' + ob + '_' + ccd + '.norm.val)*calc_data_sum(id="' + ob + '.' + str(
ishell
) + '.' + ccd + '",lo=0.3,hi=7.0)/calc_model_sum(id="' + ob + '.' + str(
ishell) + '.' + ccd + '",lo=0.3,hi=7.0))'
exec 'set_par(em' + str(
ishell
) + '_' + ob + '_' + ccd + '.norm, val=float(emnorm0), min=0., max=float(emnorm0*1e3) )'
if iobiccd1 == [
-1, -1
] and bspix2 / anarea >= 0.95 and bspix2 / anarea <= 1.05:
iobiccd1 = [iob, iccd]
else: #link to first norm value
relbs = bspix2 / float(
commands.getoutput(
'dmkeypar ' + locclu + '/ktofrsp/sp14_' +
obsids[iobiccd1[0]] + '_' + str(ishell) +
'_ccd' + presccd[iobiccd1[0]][iobiccd1[1]] +
'.fits backscal echo+')) / (64.0 * 1024.**2.)
exec 'link(em' + str(
ishell) + '_' + ob + '_' + ccd + '.norm, em' + str(
ishell) + '_' + obsids[
iobiccd1[0]] + '_' + presccd[iobiccd1[0]][
iobiccd1[1]] + '.norm * relbs )'
# Fitting
exec 'fit(' + srcstr[0:-1] + ')'
# plotting
if ishell != 0: delete_window('all')
x1 = [0., 0.5, 0., 0.5]
y1 = [0.5, 0.5, 0., 0.]
for iob in range(len(obsids)):
ob = obsids[iob]
if len(presccd[iob]) > 0:
add_window(8.5, 8.5, 'inches')
for iccd in range(len(presccd[iob])):
ccd = presccd[iob][iccd]
add_frame(x1[iccd], y1[iccd], x1[iccd] + 0.5,
y1[iccd] + 0.5)
add_curve(
get_data_plot(ob + '.' + str(ishell) + '.' + ccd).x,
get_data_plot(ob + '.' + str(ishell) + '.' + ccd).y,
dataplot)
add_histogram(
get_model_plot(ob + '.' + str(ishell) + '.' + ccd).xlo,
get_model_plot(ob + '.' + str(ishell) + '.' + ccd).xhi,
get_model_plot(ob + '.' + str(ishell) + '.' + ccd).y,
modelplot)
set_plot_title(clu + ' OB' + ob + ' CCD' + ccd)
split(2)
add_curve(
get_resid_plot(ob + '.' + str(ishell) + '.' + ccd).x,
get_resid_plot(ob + '.' + str(ishell) + '.' + ccd).y,
dataplot)
add_hline(0)
if os.path.exists('fitplots/ktofr14_' + clu + '_' + ob + '_' +
str(ishell) + '_hien.eps'):
os.remove('fitplots/ktofr14_' + clu + '_' + ob + '_' +
str(ishell) + '_hien.eps')
if len(presccd[iob]) > 0:
print_window(
'fitplots/ktofr14_' + clu + '_' + ob + '_' +
str(ishell) + '_hien',
['format', 'eps', 'orientation', 'landscape'])
normv = -1 * n.ones((len(obsids), 4))
if get_fit_results().rstat < 3:
# Error calculation
exec 'proj(' + srcstr + ' em' + str(ishell) + '_' + obsids[
firstiob] + '_' + presccd[firstiob][0] + '.kt )'
#15 if get_proj_results().parmaxes[0]!=None or ishell2==len(r1)-1 :
vkt.append(get_proj_results().parvals[0])
vktp.append(get_proj_results().parmaxes[0])
vktm.append(get_proj_results().parmins[0])
vrstat.append(get_fit_results().rstat)
# save normalizations
for iob in range(len(obsids)):
ob = obsids[iob]
for iccd in range(len(presccd[iob])):
ccd = presccd[iob][iccd]
exec 'normv[iob,ccdindex[ccd]]=em' + str(
ishell) + '_' + ob + '_' + ccd + '.norm.val'
# best-fit Z
exec 'bestfitz = em' + str(ishell) + '_' + obsids[
firstiob] + '_' + presccd[firstiob][0] + '.abundanc.val'
# best-fit nH
bestfitnh = ab.nh.val
else:
# No error calculation for bad fits
vkt.append(n.nan)
vktp.append(n.nan)
vktm.append(n.nan)
vrstat.append(get_fit_results().rstat)
# save normalizations
for iob in range(len(obsids)):
ob = obsids[iob]
for iccd in range(len(presccd[iob])):
ccd = presccd[iob][iccd]
normv[iob, ccdindex[ccd]] = n.nan
# best-fit Z
bestfitz = n.nan
# best-fit nH
bestfitnh = n.nan
globmod.globstr1 = globmod.globstr1 + str(rz1[-1]) + ' ' + str(
rz2[-1]) + ' ' + str(vkt[-1]) + ' ' + str(
vktm[-1]) + ' ' + str(vktp[-1]) + ' ' + str(
vrstat[-1]) + ' ' + str(-1) + ' ' + str(
-1) + ' ' + str(-1) + ' ' + str(
bestfitz) + ' ' + str(bestfitnh) + '\n'
# save normalization results:
# rin, rout
globmod.globstr3 = globmod.globstr3 + str(rz1[-1]) + '\t' + str(
rz2[-1]) + '\t'
# the normalization for each (ob,ccd)
for iob in range(len(obsids)):
ob = obsids[iob]
for ccd in presccd[iob]:
globmod.globstr3 = globmod.globstr3 + '-1' + ' ' #13 used to be: +str(normv[iob,ccdindex[ccd]]) +' '
globmod.globstr3 = globmod.globstr3 + '\t'
# the solid angle covered by dataset as a fraction of total
# annulus solid angle, PI (Rout^2-Rin^2)
for iob in range(len(obsids)):
ob = obsids[iob]
for ccd in presccd[iob]:
bspix2 = float(
commands.getoutput(
'dmkeypar ' + locclu + '/ktofrsp/sp14_' + ob +
'_' + str(ishell) + '_ccd' + ccd +
'.fits backscal echo+')) * 64.0 * 1024.**2.
globmod.globstr3 = globmod.globstr3 + str(
bspix2 / anarea) + ' '
# Reduced statistic
globmod.globstr3 = globmod.globstr3 + '\t' + '-1' + '\t' #13 used too be: str(vrstat[-1]) + '\t'
# Number of net counts, using backscal scaling
for iob in range(len(obsids)):
ob = obsids[iob]
for ccd in presccd[iob]:
bgct = get_data(ob + '.' + str(
ishell) + '.' + ccd).backscal * get_data(
ob + '.' + str(ishell) + '.' +
ccd).exposure / get_data(
'bg' + ob + '.' + ccd).backscal / get_data(
'bg' + ob + '.' + ccd
).exposure * calc_data_sum(
id='bg' + ob + '.' + ccd, lo=0.3, hi=7.0
) # the number of BG counts to be subtracted
globmod.globstr3 = globmod.globstr3 + str(
max(
calc_data_sum(
id=ob + '.' + str(ishell) + '.' + ccd,
lo=0.3,
hi=7.0) - bgct, 1.)) + " "
globmod.globstr3 = globmod.globstr3 + '\t'
# the --HE-- normalization for each (ob,ccd)
for iob in range(len(obsids)):
ob = obsids[iob]
for ccd in presccd[iob]:
globmod.globstr3 = globmod.globstr3 + str(normv[
iob,
ccdindex[ccd]]) + ' ' #13 normv used to be normhev
globmod.globstr3 = globmod.globstr3 + '\t'
# Reduced statistic -- HE --
globmod.globstr3 = globmod.globstr3 + '\t' + str(
vrstat[-1]) #13 vrstat used to be vrstathien
globmod.globstr3 = globmod.globstr3 + '\n'
############### end of fitting if statement ############################
# For the next ishell loop:
i1 = i2
i2 = i1 + 1
ishell = ishell + 1
########################### end of ishell loop ##############################
kthfile = open(locclu + '/ktofr14_hien.txt', 'w')
kthfile.write(globmod.globstr1)
kthfile.close()
normfile = open(locclu + '/ktofr14_norm3.txt', 'w')
normfile.write(globmod.globstr3)
normfile.close()
os.system('sed -i s/None/Nan/g ' + locclu + '/ktofr14_hien.txt')
os.system('sed -i s/None/Nan/g ' + locclu + '/ktofr14_norm3.txt')
def radial(clu, ob, r1mpcpix, rmax, obsids):
# obsids param only used to get bg count to compare with counts from merged file.
# all operations done on ob, which is one element of obsids.
locclu = 'mfe_' + clu
if not os.path.exists(locclu + '/radp' + ob):
os.mkdir(locclu + '/radp' + ob)
# create high-energy photons only event file, to use to estimate BG level
os.system('punlearn dmcopy')
os.system('dmcopy "' + locclu + '/clean' + ob +
'.fits[energy=9500:12000]" ' + locclu + '/hien' + ob + '.fits')
# center of the cluster
acao = asol6_loc.asol(ob, 'asol')
(rac, decc) = centradec.getrd(locclu)
os.system('punlearn dmcoords')
os.system('dmcoords ' + locclu + '/clean' + ob + '.fits asolfile="' +
acao + '" option=cel ra=' + rac + ' dec=' + decc + ' celfmt=hms')
xc = commands.getoutput('pget dmcoords x')
yc = commands.getoutput('pget dmcoords y')
xcf = float(xc)
ycf = float(yc)
# ra, dec in degrees
os.system('punlearn dmcoords')
os.system('dmcoords ' + locclu + '/clean' + ob + '.fits asolfile="' +
acao + '" option=sky x=' + xc + ' y=' + yc + ' celfmt=deg')
racd = float(commands.getoutput('pget dmcoords ra'))
decd = float(commands.getoutput('pget dmcoords dec'))
# read all point source areas to subtract them later from observed area
ptfile = open(locclu + '/reg/pt0mfe_wcs.reg', 'r')
regline = ptfile.readline()
regv = []
ptr = [] # how far from (rac,decc) in pixels
ptdr = [] # 'radius' of circle/ellipse in pixels
while regline != '\n' and regline != '':
if regline[0] != '#':
regv.append(regline)
s1 = regline.partition('(')
s2 = s1[2].partition(':')
hh = float(s2[0])
s3 = s2[2].partition(':')
mm = float(s3[0])
s4 = s3[2].partition(',')
ss = float(s4[0])
ptra = 15. * (hh + mm / 60. + ss / 3600.)
s5 = s4[2].partition(':')
dd = float(s5[0])
if s5[0][0] == '+': ff = 1.
elif s5[0][0] == '-': ff = -1.
s6 = s5[2].partition(':')
am = float(s6[0])
s7 = s6[2].partition(',')
ac = float(s7[0])
ptdec = dd + ff * (am / 60. + ac / 3600.)
d2 = (((ptra - racd) * numpy.cos(decd / 180. * numpy.pi))**2. +
(ptdec - decd)**2.) * (3600. / 0.492)**2.
ptr.append(d2**0.5)
if s1[0] == 'ellipse':
s8 = s7[2].partition("',")
s9 = s8[2].partition("',")
ptdr.append(60. / 0.492 * max(float(s8[0]), float(s9[0])))
elif s1[0] == 'circle':
s8 = s7[2].partition("'")
ptdr.append(60. / 0.492 * float(s8[0]))
else:
print
print 'BAAAAAAAAAAAAAD REGIOOOOOOOOOOOON'
print
regline = ptfile.readline()
ptfile.close()
# get chip regions
chipx = commands.getoutput('dmlist "' + locclu + '/reg/chipsreg' + ob +
'.fits[cols x]" data,clean')
t1 = chipx.split('\n')
t1.remove(t1[0])
chipy = commands.getoutput('dmlist "' + locclu + '/reg/chipsreg' + ob +
'.fits[cols y]" data,clean')
u1 = chipy.split('\n')
u1.remove(u1[0])
# find chips 0,1,2,3
ccdid = commands.getoutput('dmlist "' + locclu + '/reg/chipsreg' + ob +
'.fits[cols ccd_id]" data,clean')
c1 = ccdid.split('\n')
c1.remove(c1[0])
goodchips = [[], [], [], []]
# I 5 6 7
for i in range(len(c1)):
if int(c1[i]) in (0, 1, 2, 3): goodchips[0].append(i)
if int(c1[i]) == 5: goodchips[1].append(i)
if int(c1[i]) == 6: goodchips[2].append(i)
if int(c1[i]) == 7: goodchips[3].append(i)
ccdreg = [[], [], [], []]
for iccd in range(4):
if len(goodchips[iccd]) > 0:
for igood in range(len(goodchips[iccd])):
i = goodchips[iccd][igood]
polyx = []
t2 = t1[i]
t3 = t2.lstrip()
t4 = t3.partition(' ')
while ('NaN' not in t4[0]) and (t4[1] != ''):
polyx.append(float(t4[0]))
t2 = t4[2]
t3 = t2.lstrip()
t4 = t3.partition(' ')
polyy = []
u2 = u1[i]
u3 = u2.lstrip()
u4 = u3.partition(' ')
while ('NaN' not in u4[0]) and (u4[1] != ''):
polyy.append(float(u4[0]))
u2 = u4[2]
u3 = u2.lstrip()
u4 = u3.partition(' ')
ccdreg[iccd].append('polygon(')
for j in range(len(polyx)):
ccdreg[iccd][igood] = ccdreg[iccd][igood] + str(
polyx[j]) + ',' + str(polyy[j]) + ','
ccdreg[iccd][igood] = ccdreg[iccd][igood][0:-1]
ccdreg[iccd][igood] = ccdreg[iccd][igood] + ')'
ccdname = ['i', '5', '6', '7']
for iccd in range(4):
if len(ccdreg[iccd]) > 0:
os.system('punlearn dmcopy')
os.system('dmcopy "' + locclu + '/bg/bg' + ob + '_ccd' +
ccdname[iccd] + 'r.fits[energy=300:7000]" ' + locclu +
'/bg/bg' + ob + '_ccd' + ccdname[iccd] + 'r_en.fits')
if not os.path.exists(locclu + '/bg/bg' + ob + '_ccd' +
ccdname[iccd] + 'r_en.fits'):
ccdreg[iccd] = []
exposure = float(
commands.getoutput('dmkeypar ' + locclu + '/evt' + ob +
'_c.fits exposure echo+'))
# Making radbins5.txt
vrlo = []
vrhi = []
if not os.path.exists(locclu + '/radbins5.txt'):
rmin = 1.2 / .492 # in pixels. 1.2" = angular size of 10kpc at z=1
rlo = rmin
rhi = rmin * 1.25
hienrlo1 = -1
hienrlo2 = -1
hienrlo3 = -1
ct1 = 0
ct2 = 0
ct3 = 0
print 'rmax ', rmax
while rhi <= rmax:
# make annulus-minus-ptsrc region for the shell between rlo and rhi.
regfile = open(locclu + '/an_test.reg', 'w')
regfile.write('annulus(' + xc + ',' + yc + ',' + str(rlo) + ',' +
str(rhi) + ')\n')
for ii in range(len(ptr)):
if ptr[ii] - ptdr[ii] <= rhi and ptr[ii] + ptdr[ii] >= rlo:
regfile.write('-' + regv[ii])
regfile.close()
ct = float(
commands.getoutput('dmlist "' + locclu +
'/mrgclean_en.fits[sky=region(' + locclu +
'/an_test.reg)]" counts'))
sclbgct = 0.
for oobb in obsids:
for ccdn in ['i', '5', '6', '7']:
if os.path.exists(locclu + '/bg/bg' + oobb + '_ccd' +
ccdn + 'r_en.fits'):
sclbgct = sclbgct + float(
commands.getoutput('dmkeypar ' + locclu +
'/clean' + oobb +
'.fits exposure echo+')
) / float(
commands.getoutput(
'dmkeypar ' + locclu + '/bg/bg' + oobb +
'_ccd' + ccdn + 'r_en.fits exposure echo+'
)) * float(
commands.getoutput(
'dmlist "' + locclu + '/bg/bg' + oobb +
'_ccd' + ccdn + 'r_en.fits[sky=region(' +
locclu + '/an_test.reg)]" counts'))
shellct = ct - sclbgct
os.remove(locclu + '/an_test.reg')
print rlo, rhi, shellct
# shell has enough counts, OR we've reached rmax
if shellct > 100 or rhi > 0.99 * rmax:
vrlo.append(rlo)
vrhi.append(rhi)
if rhi > 0.99 * rmax: break
# radius where we start measuring hi-energy counts
if ct <= 1.5 * sclbgct:
if ct1 == 0: hienrlo1 = float(rlo) # first choice
ct1 = ct1 + int(ct)
if ct <= 2.0 * sclbgct:
if ct2 == 0:
hienrlo2 = float(
rlo) # second choice, in case 1st doesnt exist
ct2 = ct2 + int(ct)
if ct <= 3.0 * sclbgct:
if ct3 == 0: hienrlo3 = float(rlo) # 3rd choice
ct3 = ct3 + int(ct)
rlo = float(rhi)
rhi = rhi * 1.25
else:
if ct == 0 and len(vrlo) == 0: rlo = float(rhi)
rhi = rhi * 1.25
if rhi > rmax: rhi = rmax
hienrlofile = open(locclu + '/hienrlo.txt', 'w')
hienrlofile.write('1.5 ' + str(hienrlo1) + ' ' + str(ct1) + '\n')
hienrlofile.write('2 ' + str(hienrlo2) + ' ' + str(ct2) + '\n')
hienrlofile.write('3 ' + str(hienrlo3) + ' ' + str(ct3) + '\n')
hienrlofile.close()
binfile = open(locclu + '/radbins5.txt', 'w')
for ir in range(len(vrlo)):
binfile.write(str(vrlo[ir]) + ' ' + str(vrhi[ir]) + '\n')
binfile.close()
xinfile = open(locclu + '/ctofr/xin.txt', 'w')
for ir in range(len(vrlo)):
xinfile.write(str(vrlo[ir] / r1mpcpix) + '\n')
xinfile.close()
xoutfile = open(locclu + '/ctofr/xout.txt', 'w')
for ir in range(len(vrhi)):
xoutfile.write(str(vrhi[ir] / r1mpcpix) + '\n')
xoutfile.close()
# the case where radbins5.txt has been created in a previous ob:
else:
# Loading radial bin edges, from radbins5.txt
binfile = open(locclu + '/radbins5.txt', 'r')
linestr = binfile.readline()
while linestr != '':
intermed = linestr.split(' ')
vrlo.append(float(intermed[0]))
vrhi.append(float(intermed[1][0:-1]))
linestr = binfile.readline()
binfile.close()
# Hi BG corner region
if os.path.exists(locclu + '/reg/hibgcorner' + ob + '.reg'):
hibgfile = open(locclu + '/reg/hibgcorner' + ob + '.reg', 'r')
hibgstr = hibgfile.readline()
hibgfile.close()
hibgx = float(hibgstr[7:-1].split(',')[0])
hibgy = float(hibgstr[7:-1].split(',')[1])
hibgr = ((hibgx - xcf)**2. + (hibgy - ycf)**2.)**0.5
hien = [[], [], [], []]
bghien = [[], [], [], []]
hienomega = [[], [], [], []]
ccdlist = ['0,1,2,3', '5', '6', '7']
scl = [-1, -1, -1, -1]
for iccd in range(4):
if len(ccdreg[iccd]) > 0:
scl[iccd] = exposure / float(
commands.getoutput('dmkeypar "' + locclu + '/bg/bg' + ob +
'_ccd' + ccdname[iccd] +
'r_en.fits" exposure echo+'))
radintfile2err = open(
locclu + '/ctofr/srcprof' + ob + '_ccd' + ccdname[iccd] +
'.txt',
'w') # poisson and systematic errors added in quadrature
radintfile2err.write("# R1 R2 SB SBERR\n")
bgfile = open(
locclu + '/ctofr/bkgprof' + ob + '_ccd' + ccdname[iccd] +
'.txt', 'w')
bsfile = open(
locclu + '/ctofr/omega' + ob + '_ccd' + ccdname[iccd] + '.txt',
'w')
bgexp = float(
commands.getoutput('dmkeypar ' + locclu + '/bg/bg' + ob +
'_ccd' + ccdname[iccd] +
'r_en.fits exposure echo+'))
for i in range(len(vrlo)):
# make region of intersection of annulus with chip regions
fovfile = open(
locclu + '/radp' + ob + '/an' + str(i) + '_ccd' +
ccdname[iccd] + '_xfov.reg', 'w')
for ii in range(len(ccdreg[iccd])):
fovfile.write('+annulus(' + xc + ',' + yc + ',' +
str(vrlo[i]) + ',' + str(vrhi[i]) + ') * ' +
ccdreg[iccd][ii] + '\n')
fovfile.close()
# make region of intersection of annulus with chip regions MINUS PTSRCs
fovptfile = open(
locclu + '/radp' + ob + '/an' + str(i) + '_ccd' +
ccdname[iccd] + '_xfov_pt.reg', 'w')
for ii in range(len(ccdreg[iccd])):
fovptfile.write('+annulus(' + xc + ',' + yc + ',' +
str(vrlo[i]) + ',' + str(vrhi[i]) +
') * ' + ccdreg[iccd][ii] + '\n')
for jj in range(len(ptr)):
if ptr[jj] - ptdr[jj] <= vrhi[
i] and ptr[jj] + ptdr[jj] >= vrlo[i]:
fovptfile.write('-' + regv[jj][0:-1] + ' ')
if os.path.exists(locclu + '/reg/hibgcorner' + ob +
'.reg') and hibgr - 1095. <= vrhi[
i] and hibgr + 1095. >= vrlo[i]:
fovptfile.write('-' + hibgstr[0:-1])
fovptfile.write('\n')
fovptfile.close()
# calculate counts/area/solidangle/second
ct = float(
commands.getoutput('dmlist "' + locclu + '/evt' + ob +
'_c.fits[sky=region(' + locclu +
'/radp' + ob + '/an' + str(i) + '_ccd' +
ccdname[iccd] +
'_xfov_pt.reg)]" counts'))
bgct = float(
commands.getoutput(
'dmlist "' + locclu + '/bg/bg' + ob + '_ccd' +
ccdname[iccd] +
'r_en.fits[energy=700:2000][sky=region(' + locclu +
'/radp' + ob + '/an' + str(i) + '_ccd' +
ccdname[iccd] + '_xfov_pt.reg)]" counts')
) # more exact than above (deleted) line, but could be slower if many ptsrcs
#netct = ct - bgct * scl[iccd]
# make spectrum of annulus
os.system('punlearn dmextract')
os.system('dmextract "' + locclu + '/clean' + ob +
'.fits[ccd_id=' + ccdlist[iccd] + '][sky=region(' +
locclu + '/radp' + ob + '/an' + str(i) + '_ccd' +
ccdname[iccd] + '_xfov_pt.reg)][bin PI]" ' + locclu +
'/radp' + ob + '/sp' + str(i) + '_ccd' +
ccdname[iccd] +
'.fits opt=pha1 wmap="[energy=700:2000][bin det=8]"')
# calculate hi-energy SB
hien[iccd].append(
float(
commands.getoutput('dmlist "' + locclu + '/hien' + ob +
'.fits[ccd_id=' + ccdlist[iccd] +
'][sky=region(' + locclu + '/radp' +
ob + '/an' + str(i) + '_ccd' +
ccdname[iccd] +
'_xfov_pt.reg)]" counts')))
bghien[iccd].append(
float(
commands.getoutput(
'dmlist "' + locclu + '/bg/bg' + ob + '_ccd' +
ccdname[iccd] +
'r.fits[energy=9500:12000][sky=region(' + locclu +
'/radp' + ob + '/an' + str(i) + '_ccd' +
ccdname[iccd] + '_xfov_pt.reg)]" counts')))
hienomega[iccd].append(
float(
commands.getoutput('dmkeypar ' + locclu + '/radp' +
ob + '/sp' + str(i) + '_ccd' +
ccdname[iccd] +
'.fits backscal echo+')))
# make ARF for radial bin
arf4radp4.arf(clu, ob, i, ccdname[iccd])
# calculate solid angle from BACKSCAL keyword in spectrum file
bs = float(
commands.getoutput('dmkeypar ' + locclu + '/radp' + ob +
'/sp' + str(i) + '_ccd' +
ccdname[iccd] + '.fits backscal echo+'))
# calculate effective area
os.system('punlearn dmstat')
# this if statement handles the case when the annulus thickness is less than a pixel,
# which causes dmstat to return area=0
if vrhi[i] - vrlo[i] > 1.5:
if vrhi[i] <= 0.1 * r1mpcpix:
os.system('dmstat "' + locclu + '/instmap/expmap' +
ob + '_ccd' + ccdname[iccd] +
'_in.fits[sky=region(' + locclu + '/radp' +
ob + '/an' + str(i) + '_ccd' +
ccdname[iccd] + '_xfov.reg)]" centroid=no')
else:
os.system('dmstat "' + locclu + '/instmap/expmap' +
ob + '_ccd' + ccdname[iccd] +
'_out.fits[sky=region(' + locclu + '/radp' +
ob + '/an' + str(i) + '_ccd' +
ccdname[iccd] + '_xfov.reg)]" centroid=no')
else:
if vrhi[i] <= 0.1 * r1mpcpix:
os.system('dmstat "' + locclu + '/instmap/expmap' +
ob + '_ccd' + ccdname[iccd] +
'_in.fits[sky=circle(' + xc + ',' + yc +
',' + str(vrhi[i]) + ')]" centroid=no')
else:
os.system('dmstat "' + locclu + '/instmap/expmap' +
ob + '_ccd' + ccdname[iccd] +
'_out.fits[sky=circle(' + xc + ',' + yc +
',' + str(vrhi[i]) + ')]" centroid=no')
try:
area = float(commands.getoutput('pget dmstat out_mean'))
except ValueError:
area = 0
# the above try-exept is for the case, where the expmap needed to calulate area doesnt exist.
# this can happen when the there is no intersection between the in/out region and a ccd.
if bs != 0 and area != 0 and ct != 0:
sb = ct / bs / area / exposure
#sberr = ( ct + scl**2.*bgct )**.5 / bs / area / exposure # poisson error
sberr = ct**.5 / bs / area / exposure # poisson error
radintfile2err.write(
str(vrlo[i] / r1mpcpix) + ' ' +
str(vrhi[i] / r1mpcpix) + ' ' + str(sb) + ' ' + str(
(sberr**2. + sb**2. / 25.)**0.5) +
'\n') # poisson and 1/5 fraction, added in quadrature
bgsb = bgct / bs / area / bgexp
bgsberr = bgct**0.5 / bs / area / bgexp
bgfile.write(
str(vrlo[i] / r1mpcpix) + ' ' +
str(vrhi[i] / r1mpcpix) + ' ' + str(bgsb) + ' ' +
str(bgsberr) + '\n')
bsfile.write(
str(vrlo[i] / r1mpcpix) + ' ' + str(bs) + ' ' +
str(bs * 64.0 * 1024.**2. / (numpy.pi) /
(vrhi[i]**2 - vrlo[i]**2)) + '\n')
radintfile2err.close()
bgfile.close()
bsfile.close()
# write BG scaling factors from hi-energy counts
# get the 1000 outermost counts, and save their region
hientot = [0., 0., 0., 0.]
bghientot = [0., 0., 0., 0.]
hienomegatot = [0., 0., 0., 0.]
sclfile = open(locclu + '/ctofr/scl' + ob + '.txt', 'w')
for iccd in range(4):
if len(ccdreg[iccd]) > 0:
irlo = len(vrlo) - 1
while hientot[iccd] < 1e3 and irlo >= 0:
hientot[iccd] = hientot[iccd] + hien[iccd][irlo]
bghientot[iccd] = bghientot[iccd] + bghien[iccd][irlo]
hienomegatot[iccd] = hienomegatot[iccd] + hienomega[iccd][irlo]
irlo = irlo - 1
irlo = irlo + 1
if bghientot[iccd] != 0:
# write the BG counts and backscales
sclfile.write(
str(scl[iccd]) + ' ' +
str(hientot[iccd] / bghientot[iccd]) + ' ' +
str(hientot[iccd]) + ' ' + str(bghientot[iccd]) + ' ' +
str(hienomegatot[iccd]) + ' ' + str(irlo) + ' ' +
str(vrlo[irlo]) + '\n')
# make region out of which we estimate the Hi-energy cts in the src dataset
losrcregfile = open(
locclu + '/reg/losrc' + ob + '_ccd' + ccdname[iccd] +
'.reg', 'w')
for polyg in ccdreg[iccd]:
losrcregfile.write('+annulus(' + xc + ',' + yc + ',' +
str(vrlo[irlo]) + ',' + str(vrhi[-1]) +
') * ' + polyg + '\n')
for jj in range(len(ptr)):
if ptr[jj] - ptdr[jj] <= vrhi[
-1] and ptr[jj] + ptdr[jj] >= vrlo[irlo]:
losrcregfile.write('-' + regv[jj][0:-1] + ' ')
if iccd == 0 and os.path.exists(
locclu + '/reg/hibgcorner' + ob +
'.reg') and hibgr - 1095. <= vrhi[
-1] and hibgr + 1095. >= vrlo[irlo]:
losrcregfile.write('-' + hibgstr[0:-1])
losrcregfile.write('\n')
losrcregfile.close()
# extract spectrum from the above region, to get the BACKSCAL value from the spectrum
os.system('punlearn dmextract')
os.system('dmextract "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu + '/reg/losrc' + ob +
'_ccd' + ccdname[iccd] + '.reg)][bin PI]" ' +
locclu + '/spec/losrc' + ob + '_ccd' +
ccdname[iccd] +
'.fits opt=pha1 wmap="[energy=700:2000][bin det=8]"')
else:
sclfile.write(
str(scl[iccd]) + ' ' + 'NaN ' + str(hientot[iccd]) + ' ' +
str(bghientot[iccd]) + ' ' + str(hienomegatot[iccd]) +
' ' + str(irlo) + ' ' + str(vrlo[irlo]) + '\n')
# if this ccd is not in this obsid
else:
sclfile.write('-1 -1 -1 -1 -1 -1 -1\n')
sclfile.close()
def rmf(locclu, ob, ccdstr):
acao = asol6_loc.asol(ob, 'asol')
(rac, decc) = centradec.getrd(locclu)
caldbfolder = commands.getoutput('echo $CALDB')
if ccdstr == 'i': ccdlist = '0,1,2,3'
else: ccdlist = ccdstr
os.system('punlearn dmcoords')
os.system('dmcoords ' + locclu + '/clean' + ob + '.fits ' + acao + ' ra=' +
rac + ' dec=' + decc + ' option=cel celfmt=hms mode=h')
chipx = commands.getoutput('pget dmcoords chipx')
chipy = commands.getoutput('pget dmcoords chipy')
centerccd = commands.getoutput('pget dmcoords chip_id')
if centerccd not in ccdlist:
os.system('punlearn dmstat')
os.system('dmstat "' + locclu + '/clean' + ob + '.fits[ccd_id=' +
ccdlist + '][cols x]" median=yes')
xx = commands.getoutput('pget dmstat out_median')
os.system('punlearn dmstat')
os.system('dmstat "' + locclu + '/clean' + ob + '.fits[ccd_id=' +
ccdlist + '][cols y]" median=yes')
yy = commands.getoutput('pget dmstat out_median')
os.system('punlearn dmcoords')
os.system('dmcoords ' + locclu + '/clean' + ob + '.fits ' + acao +
' x=' + xx + ' y=' + yy + ' option=sky mode=h')
chipx = commands.getoutput('pget dmcoords chipx')
chipy = commands.getoutput('pget dmcoords chipy')
centerccd = commands.getoutput('pget dmcoords chip_id')
if float(chipx) < 1: chipx = '1'
if float(chipx) > 1024: chipx = '1024'
if float(chipy) < 1: chipy = '1'
if float(chipy) > 1024: chipy = '1024'
# RMF -----------------------
fptemp = float(
commands.getoutput('dmkeypar ' + locclu + '/clean' + ob +
'.fits fp_temp echo+'))
tgaincor = commands.getoutput('dmkeypar ' + locclu + '/clean' + ob +
'.fits tgaincor echo+')
cticor = commands.getoutput('dmkeypar ' + locclu + '/clean' + ob +
'.fits cti_corr echo+')
ctiapp = commands.getoutput('dmkeypar ' + locclu + '/clean' + ob +
'.fits cti_app echo+')
# using mkacisrmf or...
if (fptemp < 158. or (fptemp >= 158. and ccdstr in ['5', '7'])) and (
ctiapp != 'NNNNNNNNNN' or cticor == 'TRUE'
or cticor == '1') and (tgaincor == 'T'):
gainfile = commands.getoutput('dmkeypar ' + locclu + '/clean' + ob +
'.fits gainfile echo+')
gainver = gainfile.split('.fits')[0][-1]
caldbls = commands.getoutput('ls $CALDB/data/chandra/acis/p2_resp/' +
gainfile[0:15] + '*' + gainver + '.fits')
caldbresp = caldbls.split('\n')
if len(caldbresp) != 1:
print
print
print ' ############### MORE OR LESS THAN ONE P2RESP FILES FOUND !!!!!!!!!! ###################'
print
print
os.system('punlearn mkacisrmf')
os.system('pset mkacisrmf infile=' + caldbresp[0])
os.system('pset mkacisrmf outfile=' + locclu + '/spec/sp' + ob +
'_ccd' + ccdstr + '_center.wrmf')
os.system('pset mkacisrmf energy="0.3:11.0:0.01" channel="1:1024:1"')
os.system('pset mkacisrmf chantype="PI"')
os.system('pset mkacisrmf wmap=none')
os.system('pset mkacisrmf chipx=' + chipx)
os.system('pset mkacisrmf chipy=' + chipy)
os.system('pset mkacisrmf ccd_id=' + centerccd)
os.system('pset mkacisrmf gain=' + caldbfolder +
'/data/chandra/acis/det_gain/' + gainfile)
os.system('pset mkacisrmf asolfile=none')
os.system('mkacisrmf mode=h verbose=1')
# using mkrmf
else:
os.system('punlearn acis_fef_lookup')
os.system('acis_fef_lookup ' + locclu + '/clean' + ob +
'.fits chipx=' + chipx + ' chipy=' + chipy + ' chipid=' +
centerccd)
os.system('punlearn mkrmf')
os.system('pset mkrmf infile=' +
commands.getoutput('pget acis_fef_lookup outfile'))
os.system('pset mkrmf outfile=' + locclu + '/spec/sp' + ob + '_ccd' +
ccdstr + '_center.wrmf')
os.system('pset mkrmf axis1="energy=0.3:11.0:0.01"')
os.system('pset mkrmf axis2="pi=1:1024:1"')
os.system('pset mkrmf weights=none')
os.system('mkrmf verbose=1 mode=h')
def exp(clu, obsids, inorout):
locclu = 'mfe_' + clu
origclu = 'orig_' + clu
#os.system( 'echo "binsrc2, \''+clu+'\' , \'src'+inorout+'.txt\' " | idl' )
binsrc2.bin(clu, 'src' + inorout + '.txt')
(rac, decc) = centradec.getrd(locclu)
if not os.path.exists(locclu + '/instmap'): os.mkdir(locclu + '/instmap')
hardobs = hardsoft3.hardsoft(clu, obsids, 'h')
softobs = hardsoft3.hardsoft(clu, obsids, 's')
for i in range(len(obsids)):
ob = obsids[i]
acao = asol6_loc.asol(ob, 'asol')
os.system('punlearn ardlib')
os.system('acis_set_ardlib ' + asol6_loc.asol(ob, 'bpix'))
ccds = ''
# if this is the in region, then check if there are counts in in region
# but if it's the out region, only check if there are counts in the ccd of interest:
# the reason is we want to include data that is beyond the out region, which stops
# at 1Mpc
if inorout == 'in':
if int(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu + '/reg/' +
inorout +
'.reg)][ccd_id=0]" counts')) > 0:
ccds = ccds + '0'
if int(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu + '/reg/' +
inorout +
'.reg)][ccd_id=1]" counts')) > 0:
ccds = ccds + '1'
if int(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu + '/reg/' +
inorout +
'.reg)][ccd_id=2]" counts')) > 0:
ccds = ccds + '2'
if int(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu + '/reg/' +
inorout +
'.reg)][ccd_id=3]" counts')) > 0:
ccds = ccds + '3'
if int(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu + '/reg/' +
inorout +
'.reg)][ccd_id=5]" counts')) > 0:
ccds = ccds + '5'
if int(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu + '/reg/' +
inorout +
'.reg)][ccd_id=6]" counts')) > 0:
ccds = ccds + '6'
if int(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[sky=region(' + locclu + '/reg/' +
inorout +
'.reg)][ccd_id=7]" counts')) > 0:
ccds = ccds + '7'
else:
if int(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[ccd_id=0]" counts')) > 0:
ccds = ccds + '0'
if int(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[ccd_id=1]" counts')) > 0:
ccds = ccds + '1'
if int(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[ccd_id=2]" counts')) > 0:
ccds = ccds + '2'
if int(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[ccd_id=3]" counts')) > 0:
ccds = ccds + '3'
if int(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[ccd_id=5]" counts')) > 0:
ccds = ccds + '5'
if int(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[ccd_id=6]" counts')) > 0:
ccds = ccds + '6'
if int(
commands.getoutput('dmlist "' + locclu + '/clean' + ob +
'.fits[ccd_id=7]" counts')) > 0:
ccds = ccds + '7'
# ccdscoma=''
# for j in range(len(ccds)-1) : ccdscoma=ccdscoma+ccds[j]+','
# ccdscoma=ccdscoma+ccds[-1]
if not os.path.exists(locclu + '/evt' + ob + '_c.fits'):
os.system('punlearn dmcopy')
os.system('dmcopy "' + locclu + '/clean' + ob +
'.fits[energy=700:2000]" ' + locclu + '/evt' + ob +
'_c.fits')
#[ccd_id='+ccdscoma+']
for j in range(len(ccds)):
if not os.path.exists(locclu + '/instmap/asphist' + ob + '_ccd' +
ccds[j] + '.fits'):
os.system('punlearn asphist')
os.system('pset asphist infile=' + acao)
os.system('pset asphist outfile=' + locclu +
'/instmap/asphist' + ob + '_ccd' + ccds[j] + '.fits')
os.system('pset asphist evtfile="' + locclu + '/clean' + ob +
'.fits[ccd_id=' + ccds[j] + ']"')
os.system('asphist verbose=1 mode=h')
# Make instrument map
for j in range(len(ccds)):
os.system('punlearn mkinstmap')
os.system('pset mkinstmap pixelgrid="1:1024:#1024,1:1024:#1024"')
os.system('pset mkinstmap maskfile=' + asol6_loc.asol(ob, 'msk1'))
#os.system('pset mkinstmap pbkfile='+asol6_loc.asol(ob,'pbk'))
os.system('pset mkinstmap dafile=CALDB')
os.system('pset mkinstmap spectrumfile=' + locclu +
'/spec/binsrc' + inorout + '.txt')
os.system('pset mkinstmap obsfile=' + locclu + '/clean' + ob +
'.fits')
os.system('pset mkinstmap detsubsys=ACIS-' + ccds[j])
os.system('pset mkinstmap outfile=' + locclu +
'/instmap/winstmap' + ob + '_ccd' + ccds[j] + '_' +
inorout + '.fits')
os.system('mkinstmap mode=h verbose=1')
os.system('punlearn dmcoords')
os.system('dmcoords ' + locclu + '/clean' + ob + '.fits asolfile=' +
acao + ' option=cel ra=' + rac + ' dec=' + decc +
' celfmt=hms')
xc = commands.getoutput('pget dmcoords x')
yc = commands.getoutput('pget dmcoords y')
xcf = float(xc)
ycf = float(yc)
xs = commands.getoutput('dmlist "' + locclu + '/evt' + ob +
'_c.fits[cols x]" data,clean')
xsv = xs.split('\n')
xsv.remove(xsv[0])
for ii in range(len(xsv)):
xsv[ii] = float(xsv[ii])
ys = commands.getoutput('dmlist "' + locclu + '/evt' + ob +
'_c.fits[cols y]" data,clean')
ysv = ys.split('\n')
ysv.remove(ysv[0])
for ii in range(len(ysv)):
ysv[ii] = float(ysv[ii])
xmin = min(xsv)
xmax = max(xsv)
ymin = min(ysv)
ymax = max(ysv)
# Make exposure map
os.system('punlearn mkexpmap')
os.system('pset mkexpmap normalize=yes')
os.system('pset mkexpmap xygrid=' + str(xmin) + ':' + str(xmax) +
':4,' + str(ymin) + ':' + str(ymax) + ':4')
os.system('pset mkexpmap useavgaspect=no')
os.system('pset mkexpmap mode=h')
for j in range(len(ccds)):
os.system('mkexpmap instmapfile=' + locclu + '/instmap/winstmap' +
ob + '_ccd' + ccds[j] + '_' + inorout +
'.fits outfile=' + locclu + '/instmap/expmap' + ob +
'_ccd' + ccds[j] + '_' + inorout + '.fits asphistfile=' +
locclu + '/instmap/asphist' + ob + '_ccd' + ccds[j] +
'.fits verbose=1')
# if ACIS-I ccd's are preset, merge them.
if '0' in ccds or '1' in ccds or '2' in ccds or '3' in ccds:
# Reproject exposure map
hmrgstr = ''
for ccd in '0123':
if ccd in ccds:
hmrgstr = hmrgstr + ',' + locclu + '/instmap/expmap' + ob + '_ccd' + ccd + '_' + inorout + '.fits'
hmrgstr = hmrgstr[1:]
os.system('punlearn reproject_image')
os.system('pset reproject_image infile="' + hmrgstr + '"')
os.system('pset reproject_image outfile=' + locclu +
'/instmap/expmap' + ob + '_ccdi_' + inorout + '.fits')
os.system('pset reproject_image matchfile=' + locclu +
'/instmap/expmap' + ob + '_ccd' + ccds[0] + '_' +
inorout + '.fits')
os.system('pset reproject_image method=average')
os.system('reproject_image mode=h')
os.system(
'dmhedit ' + locclu + '/instmap/expmap' + ob + '_ccdi_' +
inorout +
'.fits filelist="" op=add key=BUNIT value="cm**2" mode=h')
# clean up files not needed
for j in range(len(ccds)):
os.remove(locclu + '/instmap/winstmap' + ob + '_ccd' + ccds[j] +
'_' + inorout + '.fits')
# more cleanup
os.system('rm ' + locclu + '/instmap/expmap*_ccd[0123]_*.fits')
