def ccd_sort(cluster):
print("Running ccd_sort on {}.".format(cluster.name))
for observation in cluster.observations:
print("Working on {}/{}".format(cluster.name, observation.id))
analysis_path = observation.analysis_directory
os.chdir(analysis_path)
evt1_filename = io.get_path("{}/{}".format(analysis_path,
io.get_filename_matching("acis*evt1.fits")[0]))
evt2_filename = io.get_path("{}/{}".format(analysis_path,
io.get_filename_matching("evt2.fits")[0]))
detname = rt.dmkeypar(infile=evt1_filename, keyword="DETNAM", echo=True)
print("evt1 : {}\nevt2 : {}\ndetname : {}".format(evt1_filename,
evt2_filename,
detname))
assert not isinstance(detname, type(None)), "detname returned nothing!"
detnums = [int(x) for x in detname.split('-')[-1]]
for acis_id in detnums:
print("{cluster}/{observation}: Making level 2 event file for ACIS Chip id: {acis_id}".format(
cluster=cluster.name,
observation=observation.id,
acis_id=acis_id))
rt.dmcopy(infile="{evt2_file}[ccd_id={acis_id}]".format(evt2_file=evt2_filename,
acis_id=acis_id),
outfile="acis_ccd{acis_id}.fits".format(acis_id=acis_id),
clobber=True)
acisI_list = io.get_filename_matching("acis_ccd[0-3].fits")
for i in range(len(acisI_list)):
acisI_list[i] = io.get_path("{obs_analysis_dir}/{file}".format(obs_analysis_dir=observation.analysis_directory,
file=acisI_list[i]))
io.write_contents_to_file("\n".join(acisI_list), observation.ccd_merge_list, binary=False)
merge_data_and_backgrounds(cluster, acisI_list)
return
def copy_event_files(source_dir, destination_dir):
os.chdir(source_dir)
evt2_filename = io.get_filename_matching("{source_dir}/acis*repro_evt2.fits".format(source_dir=source_dir))
if isinstance(evt2_filename, list):
evt2_filename = evt2_filename[-1]
bpix1_filename = io.get_filename_matching("{source_dir}/*repro_bpix1.fits".format(source_dir=source_dir))
if isinstance(bpix1_filename, list):
bpix1_filename = bpix1_filename[-1]
io.copy(evt2_filename, io.get_path("{}/evt2.fits".format(destination_dir)))
io.copy(bpix1_filename, io.get_path("{}/bpix1_new.fits".format(destination_dir)))
print("Copied level 2 event files")
return None
def get_cluster_config(clstr_name):
data_dir = config.data_directory()
config_file = io.get_filename_matching('{0}{1}/{1}_pypeline_config.ini'.format(data_dir, clstr_name))
if len(config_file) >= 1:
return config_file[-1]
else:
return None
def make_pcad_lis(cluster, obsid):
analysis_dir = cluster.obs_analysis_directory(obsid)
search_str = "{}/*asol1.fits".format(analysis_dir)
pcad_files = io.get_filename_matching(search_str)
pcad_list_string = "\n".join(pcad_files)
pcad_filename = "{}/pcad_asol1.lis".format(analysis_dir)
io.write_contents_to_file(pcad_list_string, pcad_filename, binary=False)
return pcad_filename
def merge_data_and_backgrounds(cluster, acis_list):
rt.dmmerge.punlearn()
merged_file = "acisI.fits"
rt.dmmerge(infile="@acisI.lis[subspace -expno]",
outfile=merged_file,
clobber=True)
detname = rt.dmkeypar(infile=io.get_filename_matching("acis*evt1.fits"),
keyword="DETNAM")
# acisI3 = detname.find("3")
# acisS3 = detname.find("7")
rt.dmlist.punlearn()
rt.dmlist(infile=merged_file, opt="header")
return None
def acis_mask(self):
filename = io.get_filename_matching("{analysis_dir}/*_msk1.fits".format(
analysis_dir=self.analysis_directory
))[0]
return filename
def fov_file(self):
return io.get_filename_matching("{}/*{}*fov1.fits".format(
self.analysis_directory,
self.id
))[0]
def create_global_response_file_for(cluster, obsid, region_file):
observation = cluster.observation(obsid)
#min_counts = 525
obs_analysis_dir = observation.analysis_directory
global_response_dir = "{}/globalresponse/".format(obs_analysis_dir)
io.make_directory(global_response_dir)
clean = observation.clean
back = observation.back
pbk0 = io.get_filename_matching("{}/acis*pbk0*.fits".format(obs_analysis_dir))[0]
bad_pixel_file = io.get_filename_matching("{}/bpix1_new.fits".format(obs_analysis_dir))[0]
rt.ardlib.punlearn()
rt.acis_set_ardlib(badpixfile=bad_pixel_file)
mask_file = io.get_filename_matching("{}/*msk1.fits".format(obs_analysis_dir))
make_pcad_lis(cluster, obsid)
infile = "{}[sky=region({})]".format(clean, region_file)
outroot = "{}/acisI_region_0".format(global_response_dir)
weight = True
correct_psf = False
pcad = "@{}/pcad_asol1.lis".format(obs_analysis_dir)
combine = False
bkg_file = ""
bkg_resp = False
group_type = "NUM_CTS"
binspec = 1
clobber = True
rt.specextract(infile=infile, outroot=outroot, weight=weight, correctpsf=correct_psf,
asp=pcad, combine=combine, mskfile=mask_file, bkgfile=bkg_file, bkgresp=bkg_resp,
badpixfile=bad_pixel_file, grouptype=group_type, binspec=binspec, clobber=clobber)
infile = "{}[sky=region({})][bin pi]".format(back, region_file)
outfile = "{}/acisI_back_region_0.pi".format(global_response_dir)
clobber = True
rt.dmextract.punlearn()
print("Running: dmextract infile={}, outfile={}, clobber={}".format(infile, outfile, clobber))
rt.dmextract(infile=infile, outfile=outfile, clobber=clobber)
rt.dmhedit.punlearn()
infile = "{}/acisI_region_0.pi".format(global_response_dir)
filelist = ""
operation = "add"
key = "BACKFILE"
value = outfile
rt.dmhedit(infile=infile, filelist=filelist, operation=operation, key=key, value=value)
observation = cluster.observation(obsid)
aux_response_file = '{global_response_directory}/acisI_region_0.arf'.format(
global_response_directory=observation.global_response_directory)
redist_matrix_file = '{global_response_directory}/acisI_region_0.rmf'.format(
global_response_directory=observation.global_response_directory)
io.copy(aux_response_file, observation.aux_response_file)
io.copy(redist_matrix_file, observation.redistribution_matrix_file)
def ciao_back(cluster, overwrite=False):
print("Running ciao_back on {}.".format(cluster.name))
for observation in cluster.observations:
pcad_file = make_pcad_lis(cluster, observation.id)
backI_lis = []
backS_lis = []
analysis_path = observation.analysis_directory
filelist = io.read_contents_of_file(observation.ccd_merge_list).split('\n')
pcad = io.read_contents_of_file(pcad_file)
for acis_file in filelist:
rt.acis_bkgrnd_lookup.punlearn()
print("Finding background for {}".format(acis_file))
path_to_background = rt.acis_bkgrnd_lookup(infile=acis_file)
print("Found background at {}".format(path_to_background))
acis_id = int(acis_file.split('/')[-1].split('.')[-2][-1])
assert isinstance(acis_id, int), "acis_id = {}".format(acis_id)
assert not isinstance(path_to_background, type(None)), "Cannot find background {}".format(acis_file)
local_background_path = io.get_path("{}/back_ccd{}.fits".format(analysis_path, acis_id))
try:
if io.file_exists(local_background_path) and overwrite:
io.delete(local_background_path)
io.copy(path_to_background, local_background_path)
except OSError:
print("Problem copying background file {}. Do you have the right permissions and a full CALDB?".format(
path_to_background))
raise
acis_gain = rt.dmkeypar(infile=acis_file,
keyword="GAINFILE",
echo=True)
background_gain = rt.dmkeypar(infile=local_background_path,
keyword="GAINFILE",
echo=True)
print("{}/{}/acis_ccd{}.fits gain: {}".format(cluster.name, observation.id, acis_id, acis_gain))
print("{}/{}/back_ccd{}.fits gain: {}".format(cluster.name, observation.id, acis_id, background_gain))
if dates_and_versions_match(acis_gain, background_gain):
print("Date/version numbers don't match on the acis data and background. Reprocessing.")
local_background_path = reprocess(cluster, observation.id, acis_gain, background_gain, acis_id)
print("Reprojecting background")
rt.reproject_events.punlearn()
infile = local_background_path
outfile = io.get_path("{local_path}/back_reproj_ccd{acis_id}.fits".format(local_path=analysis_path,
acis_id=acis_id))
match = acis_file
print(
"Running:\n reproject_events(infile={infile}, outfile={outfile}, aspect={pcad}, match={match})".format(
infile=infile, outfile=outfile, pcad=pcad, match=match)
)
rt.reproject_events(infile=infile,
outfile=outfile,
aspect="{pcad_file}".format(pcad_file=pcad),
match=match,
random=0,
clobber=True)
back_reproject = outfile
datamode = rt.dmkeypar(infile=io.get_filename_matching(io.get_path("{}/acis*evt1*.fits".format(analysis_path))),
keyword="DATAMODE")
if datamode == "VFAINT":
print("VFAINT Mode, resetting setting status bits")
rt.dmcopy.punlearn()
rt.dmcopy(infile="{}[status=0]".format(back_reproject),
outfile=outfile,
clobber=True)
if acis_id <= 3:
backI_lis.append(back_reproject)
else:
backS_lis.append(back_reproject)
merged_back_list = backI_lis + backS_lis
print("writing backI.lis and backS.lis")
io.write_contents_to_file("\n".join(backI_lis), io.get_path("{}/backI.lis".format(analysis_path)),
binary=False)
io.write_contents_to_file("\n".join(backS_lis), io.get_path("{}/backS.lis".format(analysis_path)),
binary=False)
io.write_contents_to_file("\n".join(merged_back_list), observation.merged_back_lis, binary=False)
return
