def extract_flare(obsid_list, times):
count = 1
for obs in obsid_list: # Cycles through obsID's
binlength = raw_input('Select bin length, (usually 200): ') # Bin set to 200
index1 = (count*2)-2 # Gets the start time index of the obsID
index2 = (count*2)-1 # Gets the stop time index of the obsID
start = times[index1] # Selects the start and stop times for the obsID being run
stop = times[index2]
count += 1 # Adds 1 to the count to continue formula ie. obsID number 3 will have count = 3, index1=4, and index2=5 which are its start and stop times in the times list
print "Performing dmextract and deflare on obsID %s" % obs
dmextract(infile="reprojected_data/%s_background.fits[bin time=%s:%s:%s]" % (obs, start, stop, binlength), outfile='reprojected_data/%s_background.lc' % obs, opt='ltc1', clobber='yes')
deflare(infile='reprojected_data/%s_background.lc' % obs, outfile='reprojected_data/%s_bkg_deflare.gti' % obs, method='clean', plot='no', save='reprojected_data/%s_plot' % obs)
def lightcurves_with_exclusion(cluster):
for observation in cluster.observations:
# data_nosrc_hiEfilter = "{}/acisI_nosrc_fullE.fits".format(obs_analysis_dir)
data_nosrc_hiEfilter = "{}/acisI_nosrc_hiEfilter.fits".format(observation.analysis_directory)
print("Creating the image with sources removed")
data = observation.acis_nosrc_filename
image_nosrc = "{}/img_acisI_nosrc_fullE.fits".format(observation.analysis_directory)
if io.file_exists(observation.exclude_file):
print("Removing sources from event file to be used in lightcurve")
infile = "{}[exclude sky=region({})]".format(data_nosrc_hiEfilter, observation.exclude)
outfile = "{}/acisI_lcurve.fits".format(observation.analysis_directory)
clobber = True
rt.dmcopy.punlearn()
rt.dmcopy(infile=infile, outfile=outfile, clobber=clobber)
data_lcurve = "{}/acisI_lcurve.fits".format(observation.analysis_directory)
else:
yes_or_no = io.check_yes_no(
"Are there sources to be excluded from observation {} while making the lightcurve? ".format(observation.id))
if yes_or_no: # yes_or_no == True
print("Create the a region file with the region to be excluded and save it as {}".format(observation.exclude_file))
else:
data_lcurve = data_nosrc_hiEfilter
backbin = 259.28
echo = True
tstart = rt.dmkeypar(infile=data_nosrc_hiEfilter, keyword="TSTART", echo=echo)
tstop = rt.dmkeypar(infile=data_nosrc_hiEfilter, keyword="TSTOP", echo=echo)
print("Creating lightcurve from the events list with dmextract")
infile = "{}[bin time={}:{}:{}]".format(data_lcurve, tstart, tstop, backbin)
outfile = "{}/acisI_lcurve.lc".format(observation.analysis_directory)
opt = "ltc1"
rt.dmextract.punlearn()
rt.dmextract(infile=infile, outfile=outfile, opt=opt, clobber=clobber)
lcurve = outfile
print("Cleaning the lightcurve by removing flares with deflare. Press enter to continue.")
rt.deflare.punlearn()
infile = lcurve
outfile = "{}/acisI_gti.gti".format(observation.analysis_directory)
method = "clean"
save = "{}/acisI_lcurve".format(observation.analysis_directory)
rt.deflare(infile=infile, outfile=outfile, method=method, save=save)
gti = outfile
print("filtering the event list using GTI info just obtained.")
infile = "{}[@{}]".format(data_nosrc_hiEfilter, gti)
outfile = observation.clean
clobber = True
rt.dmcopy(infile=infile, outfile=outfile, clobber=clobber)
data_clean = outfile
print("Don't forget to check the light curves!")
def generate_light_curve(observation):
# filter out high energy background flares
obsid_analysis_dir = observation.analysis_directory
data = observation.acis_nosrc_filename
background = observation.background_nosrc_filename
infile = "{}[energy=9000:12000]".format(data)
outfile = "{}/acisI_hiE.fits".format(obsid_analysis_dir)
clobber = True
rt.dmcopy.punlearn()
rt.dmcopy(infile=infile, outfile=outfile, clobber=clobber)
data_hiE = outfile
infile = "{}[bin sky=8]".format(data_hiE)
outfile = "{}/img_acisI_hiE.fits".format(obsid_analysis_dir)
rt.dmcopy.punlearn()
rt.dmcopy(infile=infile, outfile=outfile, clobber=clobber)
backbin = 259.28
echo = True
tstart = rt.dmkeypar(infile=data_hiE, keyword="TSTART", echo=echo)
tstop = rt.dmkeypar(infile=data_hiE, keyword="TSTOP", echo=echo)
print("Creating a lightcurve from the high energy events list with dmextract")
rt.dmextract.punlearn()
infile = "{}[bin time={}:{}:{}]".format(data_hiE, tstart, tstop, backbin)
outfile = "{}/acisI_lcurve_hiE.lc".format(obsid_analysis_dir)
print('Running dmextract infile={} outfile={} opt=ltc1 clobber=True'.format(infile, outfile))
rt.dmextract(infile=infile,
outfile=outfile,
opt='ltc1', clobber=True)
lcurve_hiE = outfile
print("cleaning the lightcurve for {}, press enter to continue.".format(observation.id))
rt.deflare.punlearn()
outfile = "{}/acisI_gti_hiE.gti".format(obsid_analysis_dir)
method = "clean"
save = "{}/acisI_lcurve_hiE".format(obsid_analysis_dir)
rt.deflare(infile=lcurve_hiE, outfile=outfile, method=method, save=save)
gti_hiE = outfile
print("Filtering the event list using GTI info from high energy flares.")
infile = "{}[@{}]".format(data, gti_hiE)
outfile = "{}/acisI_nosrc_hiEfilter.fits".format(obsid_analysis_dir)
print("running: dmcopy infile={} outfile={} clobber={}".format(infile, outfile, clobber))
rt.dmcopy.punlearn()
rt.dmcopy(infile=infile, outfile=outfile, clobber=clobber)
data_nosrc_hiEfilter = outfile
infile = "{}[bin sky=8]".format(data_nosrc_hiEfilter)
outfile = "{}/img_acisI_nosrc_fullE.fits".format(obsid_analysis_dir)
rt.dmcopy.punlearn()
rt.dmcopy(infile=infile, outfile=outfile, clobber=clobber)