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ktofr15loc.py
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ktofr15loc.py
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# PURPOSE: compute temperature profile for a given cluster using all observations
# v2: * if ARF not present, get one, and set it equal to zero
# v3: * correcting ikt vs ktish0 mistake in above version...
# * more complex fitting for case of multiple kT-components in one Z-shell
# v4: * write reduced statistic to file
# * reduce the kT components (for a given Z-shell) to those whose uncertainty ranges
# do not overlap
# v5: * perform the last fit, with the normalizations of the different kT components unlinked.
# * change None to NaN in output files
# ktofr9: * based on zofr5.py
# * normalizations are only linked for spectra that cover 95-105% of the annulus
# ktofr9_norm: * based on ktofr9,
# * only fit norm's while getting kT results from ktofr9.py results
# * OUTPUT IS NOT WELL WRITTEN, ISSUES FIXED IN ktofr9_norm2
# ktofr9_norm2: * writes to ktofr9_norm2.txt the normalization of each CCD in each OBSID
# * also writes the covered area a fraction of the complete shell area
# ktofr10: * #++# stands for changes in this version, from ktofr9_norm2
# * nnec changed, after including the simulations with BGfrac=0.8
# * exclude CCD's which don't have BG files, while making evtrad files.
# * ccdname was = 'i576' instead of 'i567', this was fixed
# * Systematic errors of the hien run not used anymore
# * THIS CHANGE WAS CANCELLED: delete_window replaced by clear as it works when no windows are open
# * define bgxs to contain BG scaling factor, relative to blank-sky BG count rate
# * when linking norms with area almost equal to area of shell, use relative backscal, instead
# of equating them
# ktofr11: * find which CCD's are in an OBSID in the very begining, to set presccdglob early on and avoid
# including data in the analysis which will not be used. For example evtrad file should only
# contain events from OBSIDS which will actually be analyzed. In previous versions, this caused
# bgfrac to be wrongly calculated. This is done by introducing whichccd2, and moving some of
# of region output files from radreg3 to whichccd2, while making radreg4 instead of 3.
# * write nH
# * restrict calculating sclbgct to the CCD's in presccdglob, instead of adding BG
# counts from all CCD's
# * freeze nH! (as done in Vikhlinin)
# * kT for nnec comes from previous shell, unless it's shell 0, then use values in cluname_TZ.txt
# * initial kT and Z for any shell (except ishell=0) comes from previous shell
# ktofr11_fix: * refit the last n bins in the spectra, where n is taken from fix_ktofr11_list.txt
# ktofr12loc: * in the hien scaling, only instrumental BG components are scaled by hienbgscl.
# sky BG components are scaled by bgscl
# * use simple box regions to extract spectra
# * min of .norm param is 0, not emnorm0/1e3
# ktofr13loc: * uses loadbg4z4simple, which uses a re-fitting of the BG spectra. the previous
# BG fits often had offsets from the data
# ktofr14loc: * gal1 and cxb components are obtained from in-field spec fit, when present
# * gal1 and cxb components' normalization is scaled, instead of scaling the entire
# component when the model is set.
# * gal1 and cxb components are scaled by relative backscal and NOT by backscal * exposure
# like was done before, and like is done with instrumental BG components. this finding
# was found using the testing script calibrate_spec_scaling3.py
# * for certain OBSIDs, scale by bgscl and not by high energy scaling to model the BG.
# This is because these observations are missing counts at high energy. Their spectra
# drop to zero, above a certain energy or PHA.
# OUTPUT: ktofrsp/spfix*
# OUTPUT: ktofrsp/warf14_*
# OUTPUT: ktofrsp/kt14an*
# OUTPUT: ktofr14.txt
# OUTPUT: ktofr14_hien.txt
# OUTPUT: ktofr14_norm3.txt
# OUTPUT: fitplots/ktofr14_CLU_OB_ISHELL
from sherpa.astro.ui import *
from pychips.all import *
import os
import commands
import pdb
import gc
import numpy as n
import centradec
import asol6_loc
import radreg4simple3
import rmfarf4bg
import loadbg4z8simple3
import groupzeros
import globmod
import whichccd2z_loc
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' )