def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
NAME_FACTORY.update_base_dict(args['data'])
mktime = args['mktimefilter']
for comp in components:
zcut = "zmax%i" % comp.zmax
key = comp.make_key('{ebin_name}_{evtype_name}')
name_keys = dict(zcut=zcut,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
irf_ver=NAME_FACTORY.irf_ver(),
mktime=mktime,
fullpath=True)
outfile = NAME_FACTORY.bexpcube_sun(**name_keys)
ltcube_sun = NAME_FACTORY.ltcube_sun(**name_keys)
job_configs[key] = dict(infile=NAME_FACTORY.ltcube_sun(**name_keys),
outfile=outfile,
irfs=NAME_FACTORY.irfs(**name_keys),
evtype=comp.evtype,
emin=comp.emin,
emax=comp.emax,
enumbins=comp.enumbins,
logfile=make_nfs_path(outfile.replace('.fits', '.log')))
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)
if sim is not None:
raise ValueError("Found 'sim' argument on AnalyzeROI_SG config.")
if targets_yaml is None:
return job_configs
config_yaml = 'config.yaml'
config_override = args.get('config')
if is_not_null(config_override):
config_yaml = config_override
targets = load_yaml(targets_yaml)
base_config = dict(roi_baseline=args['roi_baseline'],
make_plots=args['make_plots'])
for target_name in targets.keys():
name_keys = dict(target_type=ttype,
target_name=target_name,
fullpath=True)
target_dir = NAME_FACTORY.targetdir(**name_keys)
config_path = os.path.join(target_dir, config_yaml)
logfile = make_nfs_path(os.path.join(
target_dir, "%s_%s.log" % (self.linkname, target_name)))
job_config = base_config.copy()
job_config.update(dict(config=config_path,
logfile=logfile))
job_configs[target_name] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
NAME_FACTORY.update_base_dict(args['data'])
models = load_yaml(args['models'])
for modelkey in models:
manifest = os.path.join('analysis', 'model_%s' % modelkey,
'srcmap_manifest_%s.yaml' % modelkey)
for comp in components:
key = comp.make_key('{ebin_name}_{evtype_name}')
fullkey = "%s_%s" % (modelkey, key)
outfile = NAME_FACTORY.merged_srcmaps(
modelkey=modelkey,
component=key,
coordsys=comp.coordsys,
mktime='none',
irf_ver=NAME_FACTORY.irf_ver())
logfile = make_nfs_path(outfile.replace('.fits', '.log'))
job_configs[fullkey] = dict(input=manifest,
compname=key,
logfile=logfile)
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)
if targets_yaml is None:
return job_configs
targets = load_yaml(targets_yaml)
for target_name, target_list in targets.items():
for targ_prof in target_list:
name_keys = dict(target_type=ttype,
target_name=target_name,
profile=targ_prof,
fullpath=True)
targ_key = "%s_%s" % (target_name, targ_prof)
input_path = NAME_FACTORY.sedfile(**name_keys)
output_path = input_path.replace('.fits', '.png')
logfile = make_nfs_path(input_path.replace('.fits', '.log'))
job_config = dict(infile=input_path,
outfile=output_path,
logfile=logfile)
job_configs[targ_key] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
NAME_FACTORY.update_base_dict(args['data'])
mktime = args['mktimefilter']
for comp in components:
zcut = "zmax%i" % comp.zmax
key = comp.make_key('{ebin_name}_{evtype_name}')
name_keys = dict(zcut=zcut,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
irf_ver=NAME_FACTORY.irf_ver(),
mktime=mktime,
fullpath=True)
outfile = NAME_FACTORY.bexpcube_sun(**name_keys)
ltcube_sun = NAME_FACTORY.ltcube_sun(**name_keys)
job_configs[key] = dict(
infile=NAME_FACTORY.ltcube_sun(**name_keys),
outfile=outfile,
irfs=NAME_FACTORY.irfs(**name_keys),
evtype=comp.evtype,
emin=comp.emin,
emax=comp.emax,
enumbins=comp.enumbins,
logfile=make_nfs_path(outfile.replace('.fits', '.log')))
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)
if sim is not None:
raise ValueError("Found 'sim' argument on AnalyzeROI_SG config.")
if targets_yaml is None:
return job_configs
config_yaml = 'config.yaml'
config_override = args.get('config')
if is_not_null(config_override):
config_yaml = config_override
targets = load_yaml(targets_yaml)
base_config = dict(roi_baseline=args['roi_baseline'],
make_plots=args['make_plots'])
for target_name in targets.keys():
name_keys = dict(target_type=ttype,
target_name=target_name,
fullpath=True)
target_dir = NAME_FACTORY.targetdir(**name_keys)
config_path = os.path.join(target_dir, config_yaml)
logfile = make_nfs_path(
os.path.join(target_dir,
"%s_%s.log" % (self.linkname, target_name)))
job_config = base_config.copy()
job_config.update(dict(config=config_path, logfile=logfile))
job_configs[target_name] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)
if targets_yaml is None:
return job_configs
targets = load_yaml(targets_yaml)
for target_name, target_list in targets.items():
for targ_prof in target_list:
name_keys = dict(target_type=ttype,
target_name=target_name,
profile=targ_prof,
fullpath=True)
targ_key = "%s_%s" % (target_name, targ_prof)
input_path = NAME_FACTORY.sedfile(**name_keys)
output_path = input_path.replace('.fits', '.png')
logfile = make_nfs_path(input_path.replace('.fits', '.log'))
job_config = dict(infile=input_path,
outfile=output_path,
logfile=logfile)
job_configs[targ_key] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
NAME_FACTORY.update_base_dict(args['data'])
ret_dict = make_catalog_comp_dict(
library=args['library'], basedir=NAME_FACTORY.base_dict['basedir'])
catalog_info_dict = ret_dict['catalog_info_dict']
for catalog_name in catalog_info_dict:
for comp in components:
zcut = "zmax%i" % comp.zmax
key = comp.make_key('{ebin_name}_{evtype_name}')
name_keys = dict(zcut=zcut,
sourcekey=catalog_name,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
coordsys=comp.coordsys,
irf_ver=NAME_FACTORY.irf_ver(),
mktime='none',
fullpath=True)
outfile = NAME_FACTORY.srcmaps(**name_keys)
outfile_tokens = os.path.splitext(outfile)
infile_regexp = "%s_*.fits" % outfile_tokens[0]
logfile = make_nfs_path(outfile.replace('.fits', '.log'))
job_configs[key] = dict(output=outfile,
args=infile_regexp,
logfile=logfile)
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
NAME_FACTORY.update_base_dict(args['data'])
models = load_yaml(args['models'])
for modelkey in models:
manifest = os.path.join('analysis', 'model_%s' % modelkey,
'srcmap_manifest_%s.yaml' % modelkey)
for comp in components:
key = comp.make_key('{ebin_name}_{evtype_name}')
fullkey = "%s_%s" % (modelkey, key)
outfile = NAME_FACTORY.merged_srcmaps(modelkey=modelkey,
component=key,
coordsys=comp.coordsys,
mktime='none',
irf_ver=NAME_FACTORY.irf_ver())
logfile = make_nfs_path(outfile.replace('.fits', '.log'))
job_configs[fullkey] = dict(input=manifest,
compname=key,
logfile=logfile)
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
NAME_FACTORY.update_base_dict(args['data'])
if self._comp_dict is None or self._comp_dict_file != args['library']:
self._comp_dict_file = args['library']
self._comp_dict = make_catalog_comp_dict(sources=self._comp_dict_file,
basedir=NAME_FACTORY.base_dict['basedir'])
else:
print ("Using cached catalog dict from %s" % args['library'])
catalog_info_dict = self._comp_dict['catalog_info_dict']
comp_info_dict = self._comp_dict['comp_info_dict']
n_src_per_job = args['nsrc']
if args['make_xml']:
SrcmapsCatalog_SG._make_xml_files(catalog_info_dict, comp_info_dict)
for catalog_name, catalog_info in catalog_info_dict.items():
n_cat_src = len(catalog_info.catalog.table)
n_job = int(math.ceil(float(n_cat_src) / n_src_per_job))
for comp in components:
zcut = "zmax%i" % comp.zmax
key = comp.make_key('{ebin_name}_{evtype_name}')
name_keys = dict(zcut=zcut,
sourcekey=catalog_name,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
coordsys=comp.coordsys,
irf_ver=NAME_FACTORY.irf_ver(),
mktime='none',
fullpath=True)
for i_job in range(n_job):
full_key = "%s_%02i" % (key, i_job)
srcmin = i_job * n_src_per_job
srcmax = min(srcmin + n_src_per_job, n_cat_src)
outfile = NAME_FACTORY.srcmaps(
**name_keys).replace('.fits', "_%02i.fits" % (i_job))
logfile = make_nfs_path(outfile.replace('.fits', '.log'))
job_configs[full_key] = dict(cmap=NAME_FACTORY.ccube(**name_keys),
expcube=NAME_FACTORY.ltcube(**name_keys),
irfs=NAME_FACTORY.irfs(**name_keys),
bexpmap=NAME_FACTORY.bexpcube(**name_keys),
outfile=outfile,
logfile=logfile,
srcmdl=catalog_info.srcmdl_name,
evtype=comp.evtype,
srcmin=srcmin,
srcmax=srcmax)
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(roster_yaml, sim) = NAME_FACTORY.resolve_rosterfile(args)
if roster_yaml is None:
return job_configs
roster_dict = load_yaml(roster_yaml)
astro_priors = args['astro_priors']
specs = args['specs']
for roster_name in roster_dict.keys():
rost_specs = specs
for astro_prior in astro_priors:
name_keys = dict(target_type=ttype,
roster_name=roster_name,
astro_prior=astro_prior,
sim_name=sim,
fullpath=True)
for spec in rost_specs:
targ_key = "%s:%s:%s" % (roster_name, astro_prior, spec)
if sim is not None:
seedlist = range(args['seed'],
args['seed'] + args['nsims'])
sim_path = os.path.join('config', 'sim_%s.yaml' % sim)
else:
seedlist = [None]
sim_path = None
for seed in seedlist:
if seed is not None:
name_keys['seed'] = "%06i" % seed
input_path = NAME_FACTORY.sim_stackedlimitsfile(
**name_keys)
full_targ_key = "%s_%06i" % (targ_key, seed)
else:
input_path = NAME_FACTORY.stackedlimitsfile(
**name_keys)
full_targ_key = targ_key
output_path = input_path.replace(
'.fits', '_%s.png' % spec)
logfile = make_nfs_path(
output_path.replace('.png', '.log'))
job_config = dict(infile=input_path,
outfile=output_path,
astro_prior=astro_prior,
logfile=logfile,
sim=sim_path,
spec=spec)
job_configs[full_targ_key] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)
if targets_yaml is None:
return job_configs
config_yaml = 'config.yaml'
config_override = args.get('config')
if is_not_null(config_override):
config_yaml = config_override
targets = load_yaml(targets_yaml)
nsims_job = args['nsims_job']
first_seed = args['seed']
nsims = args['nsims']
last_seed = first_seed + nsims
base_config = dict(sim_profile=args['sim_profile'],
roi_baseline=args['roi_baseline'],
non_null_src=args['non_null_src'],
do_find_src=args['do_find_src'],
sim=sim)
for target_name, target_list in targets.items():
name_keys = dict(target_type=ttype,
target_name=target_name,
sim_name=sim,
fullpath=True)
simdir = NAME_FACTORY.sim_targetdir(**name_keys)
config_path = os.path.join(simdir, config_yaml)
job_config = base_config.copy()
job_config.update(dict(config=config_path, profiles=target_list))
current_seed = first_seed
while current_seed < last_seed:
fullkey = "%s_%06i" % (target_name, current_seed)
logfile = make_nfs_path(
os.path.join(
simdir, "%s_%s_%06i.log" %
(self.linkname, target_name, current_seed)))
if nsims_job <= 0 or current_seed + nsims_job >= last_seed:
nsims_current = last_seed - current_seed
else:
nsims_current = nsims_job
job_config.update(
dict(seed=current_seed,
nsims=nsims_current,
logfile=logfile))
job_configs[fullkey] = job_config.copy()
current_seed += nsims_current
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(roster_yaml, sim) = NAME_FACTORY.resolve_rosterfile(args)
if roster_yaml is None:
return job_configs
roster_dict = load_yaml(roster_yaml)
astro_priors = args['astro_priors']
channels = args['channels']
global_min = args['global_min']
for roster_name in list(roster_dict.keys()):
rost_chans = select_channels(channels, roster_name)
for astro_prior in astro_priors:
name_keys = dict(target_type=ttype,
roster_name=roster_name,
astro_prior=astro_prior,
sim_name=sim,
fullpath=True)
for chan in rost_chans:
targ_key = "%s:%s:%s" % (roster_name, astro_prior, chan)
if sim is not None:
seedlist = list(
range(args['seed'], args['seed'] + args['nsims']))
else:
seedlist = [None]
for seed in seedlist:
if seed is not None:
name_keys['seed'] = "%06i" % seed # pylint: disable=bad-string-format-type
input_path = NAME_FACTORY.sim_resultsfile(
**name_keys)
full_targ_key = "%s_%06i" % (targ_key, seed) # pylint: disable=bad-string-format-type
else:
input_path = NAME_FACTORY.resultsfile(**name_keys)
full_targ_key = targ_key
output_path = input_path.replace(
'.fits', '_%s.png' % chan)
logfile = make_nfs_path(
output_path.replace('.png', '.log'))
job_config = dict(infile=input_path,
outfile=output_path,
astro_prior=astro_prior,
logfile=logfile,
global_min=global_min,
chan=chan)
job_configs[full_targ_key] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml,
sim) = NAME_FACTORY.resolve_targetfile(args, require_sim_name=True)
if targets_yaml is None:
return job_configs
specconfig = NAME_FACTORY.resolve_specconfig(args)
astro_priors = args['astro_priors']
write_full = args.get('write_full', False)
targets = load_yaml(targets_yaml)
base_config = dict(nsims=args['nsims'],
seed=args['seed'],
specconfig=specconfig)
for target_name, profile_list in list(targets.items()):
for profile in profile_list:
for astro_prior in astro_priors:
if is_null(astro_prior):
astro_prior = 'none'
full_key = "%s:%s:%s:%s" % (target_name, profile, sim,
astro_prior)
name_keys = dict(target_type=ttype,
target_name=target_name,
sim_name=sim,
profile=profile,
astro_prior=astro_prior,
fullpath=True)
limitfile = NAME_FACTORY.sim_dmlimitsfile(**name_keys)
first = args['seed']
last = first + args['nsims'] - 1
outfile = limitfile.replace(
'_SEED.fits',
'_collected_%06i_%06i.fits' % (first, last))
logfile = make_nfs_path(outfile.replace('.fits', '.log'))
if not write_full:
outfile = None
summaryfile = limitfile.replace(
'_SEED.fits',
'_summary_%06i_%06i.fits' % (first, last))
job_config = base_config.copy()
job_config.update(
dict(limitfile=limitfile,
astro_prior=astro_prior,
outfile=outfile,
summaryfile=summaryfile,
logfile=logfile))
job_configs[full_key] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)
if targets_yaml is None:
return job_configs
config_yaml = 'config.yaml'
config_override = args.get('config')
if is_not_null(config_override):
config_yaml = config_override
targets = load_yaml(targets_yaml)
nsims_job = args['nsims_job']
first_seed = args['seed']
nsims = args['nsims']
last_seed = first_seed + nsims
base_config = dict(sim_profile=args['sim_profile'],
roi_baseline=args['roi_baseline'],
non_null_src=args['non_null_src'],
sim=sim)
for target_name, target_list in targets.items():
name_keys = dict(target_type=ttype,
target_name=target_name,
sim_name=sim,
fullpath=True)
simdir = NAME_FACTORY.sim_targetdir(**name_keys)
config_path = os.path.join(simdir, config_yaml)
job_config = base_config.copy()
job_config.update(dict(config=config_path,
profiles=target_list))
current_seed = first_seed
while current_seed < last_seed:
fullkey = "%s_%06i" % (target_name, current_seed)
logfile = make_nfs_path(os.path.join(simdir, "%s_%s_%06i.log" % (self.linkname,
target_name, current_seed)))
if nsims_job <= 0 or current_seed + nsims_job >= last_seed:
nsims_current = last_seed - current_seed
else:
nsims_current = nsims_job
job_config.update(dict(seed=current_seed,
nsims=nsims_current,
logfile=logfile))
job_configs[fullkey] = job_config.copy()
current_seed += nsims_current
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
comp_file = args.get('comp', None)
if comp_file is not None:
comp_dict = yaml.safe_load(open(comp_file))
coordsys = comp_dict.pop('coordsys')
for v in comp_dict.values():
v['coordsys'] = coordsys
else:
return job_configs
datafile = args['data']
if datafile is None or datafile == 'None':
return job_configs
NAME_FACTORY.update_base_dict(args['data'])
inputfiles = create_inputlist(args['ft1file'])
outdir_base = os.path.join(NAME_FACTORY.base_dict['basedir'],
'counts_cubes')
ft2file = os.path.join(NAME_FACTORY.base_dict['basedir'],
args['ft2file'])
data_ver = NAME_FACTORY.base_dict['data_ver']
for idx, infile in enumerate(inputfiles):
key = "%06i" % idx
key_scfile = "%03i" % (idx + 1)
output_dir = os.path.join(outdir_base, key)
try:
os.mkdir(output_dir)
except OSError:
pass
scfile = args['ft2file'].replace('.lst', '_%s.fits' % key_scfile)
logfile = make_nfs_path(
os.path.join(output_dir,
'scatter_mk_%s_%s.log' % (data_ver, key)))
job_configs[key] = comp_dict.copy()
job_configs[key].update(
dict(ft1file=infile,
ft2file=ft2file,
data=args['data'],
scfile=scfile,
comp=args['comp'],
hpx_order_max=args['hpx_order_max'],
outdir=outdir_base,
outkey=key,
logfile=logfile,
pfiles=output_dir))
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(roster_yaml, sim) = NAME_FACTORY.resolve_rosterfile(
args, require_sim_name=True)
if roster_yaml is None:
return job_configs
specconfig = NAME_FACTORY.resolve_specconfig(args)
astro_priors = args['astro_priors']
write_full = args['write_full']
first = args['seed']
last = first + args['nsims'] - 1
base_config = dict(nsims=args['nsims'],
seed=args['seed'])
roster_dict = load_yaml(roster_yaml)
for roster_name in roster_dict.keys():
for astro_prior in astro_priors:
if is_null(astro_prior):
astro_prior = 'none'
full_key = "%s:%s:%s" % (roster_name, sim, astro_prior)
name_keys = dict(target_type=ttype,
roster_name=roster_name,
sim_name=sim,
astro_prior=astro_prior,
fullpath=True)
limitfile = NAME_FACTORY.sim_stackedlimitsfile(**name_keys)
outfile = limitfile.replace(
'_SEED.fits', '_collected_%06i_%06i.fits' %
(first, last))
logfile = make_nfs_path(outfile.replace('.fits', '.log'))
if not write_full:
outfile = None
summaryfile = limitfile.replace('_SEED.fits', '_summary.fits')
job_config = base_config.copy()
job_config.update(dict(limitfile=limitfile,
specconfig=specconfig,
astro_prior=astro_prior,
outfile=outfile,
summaryfile=summaryfile,
logfile=logfile))
job_configs[full_key] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
datafile = args['data']
if datafile is None or datafile == 'None':
return job_configs
NAME_FACTORY.update_base_dict(args['data'])
outdir_base = os.path.join(NAME_FACTORY.base_dict['basedir'], 'counts_cubes')
inputfiles = create_inputlist(args['ft1file'])
num_files = len(inputfiles)
for comp in components:
zcut = "zmax%i" % comp.zmax
mktimelist = copy.copy(comp.mktimefilters)
if not mktimelist:
mktimelist.append('none')
evtclasslist_keys = copy.copy(comp.evtclasses)
if not evtclasslist_keys:
evtclasslist_vals = [NAME_FACTORY.base_dict['evclass']]
else:
evtclasslist_vals = copy.copy(evtclasslist_keys)
for mktimekey in mktimelist:
for evtclassval in evtclasslist_vals:
fullkey = comp.make_key(
'%s_%s_{ebin_name}_%s_{evtype_name}' %
(evtclassval, zcut, mktimekey))
name_keys = dict(zcut=zcut,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
coordsys=comp.coordsys,
irf_ver=NAME_FACTORY.irf_ver(),
mktime=mktimekey,
evclass=evtclassval,
fullpath=True)
ccube_name = os.path.basename(NAME_FACTORY.ccube(**name_keys))
outfile = os.path.join(outdir_base, ccube_name)
infiles = _make_input_file_list(outfile, num_files)
logfile = make_nfs_path(outfile.replace('.fits', '.log'))
job_configs[fullkey] = dict(args=infiles,
output=outfile,
logfile=logfile)
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
datafile = args['data']
if datafile is None or datafile == 'None':
return job_configs
NAME_FACTORY.update_base_dict(args['data'])
for comp in components:
zcut = "zmax%i" % comp.zmax
mktimelist = copy.copy(comp.mktimefilters)
if not mktimelist:
mktimelist.append('none')
evtclasslist_keys = copy.copy(comp.evtclasses)
if not evtclasslist_keys:
evtclasslist_vals = [NAME_FACTORY.base_dict['evclass']]
else:
evtclasslist_vals = copy.copy(evtclasslist_keys)
for mktimekey in mktimelist:
for evtclassval in evtclasslist_vals:
fullkey = comp.make_key(
'%s_%s_{ebin_name}_%s_{evtype_name}' %
(evtclassval, zcut, mktimekey))
name_keys = dict(zcut=zcut,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
coordsys=comp.coordsys,
irf_ver=NAME_FACTORY.irf_ver(),
mktime=mktimekey,
evclass=evtclassval,
fullpath=True)
outfile = NAME_FACTORY.bexpcube(**name_keys)
cmap = NAME_FACTORY.ccube(**name_keys)
infile = NAME_FACTORY.ltcube(**name_keys)
logfile = make_nfs_path(outfile.replace('.fits', '.log'))
job_configs[fullkey] = dict(
cmap=cmap,
infile=infile,
outfile=outfile,
irfs=NAME_FACTORY.irfs(**name_keys),
hpx_order=min(comp.hpx_order, args['hpx_order_max']),
evtype=comp.evtype,
logfile=logfile)
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
NAME_FACTORY.update_base_dict(args['data'])
ret_dict = make_diffuse_comp_info_dict(
components=components,
library=args['library'],
basedir=NAME_FACTORY.base_dict['basedir'])
diffuse_comp_info_dict = ret_dict['comp_info_dict']
for diffuse_comp_info_key in sorted(diffuse_comp_info_dict.keys()):
diffuse_comp_info_value = diffuse_comp_info_dict[
diffuse_comp_info_key]
for comp in components:
zcut = "zmax%i" % comp.zmax
key = comp.make_key('{ebin_name}_{evtype_name}')
if diffuse_comp_info_value.components is None:
sub_comp_info = diffuse_comp_info_value
else:
sub_comp_info = diffuse_comp_info_value.get_component_info(
comp)
full_key = "%s_%s" % (sub_comp_info.sourcekey, key)
name_keys = dict(zcut=zcut,
sourcekey=sub_comp_info.sourcekey,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
coordsys=comp.coordsys,
irf_ver=NAME_FACTORY.irf_ver(),
mktime='none',
fullpath=True)
infile = NAME_FACTORY.srcmaps(**name_keys)
outfile = infile.replace('.fits', '.png')
logfile = make_nfs_path(outfile.replace('.png', '_png.log'))
job_configs[full_key] = dict(
input=infile,
output=outfile,
extension=sub_comp_info.source_name,
zscale=args.get('zscale', 'log'),
logfile=logfile)
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
NAME_FACTORY.update_base_dict(args['data'])
ret_dict = make_catalog_comp_dict(sources=args['library'], basedir='.')
comp_info_dict = ret_dict['comp_info_dict']
for split_ver, split_dict in comp_info_dict.items():
for source_key, source_dict in split_dict.items():
full_key = "%s_%s" % (split_ver, source_key)
merged_name = "%s_%s" % (source_dict.catalog_info.catalog_name,
source_key)
if source_dict.model_type != 'CompositeSource':
continue
for comp in components:
zcut = "zmax%i" % comp.zmax
key = "%s_%s" % (
full_key, comp.make_key('{ebin_name}_{evtype_name}'))
name_keys = dict(zcut=zcut,
sourcekey=full_key,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
coordsys=comp.coordsys,
mktime='none',
irf_ver=NAME_FACTORY.irf_ver())
nested_name_keys = dict(
zcut=zcut,
sourcekey=source_dict.catalog_info.catalog_name,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
coordsys=comp.coordsys,
mktime='none',
irf_ver=NAME_FACTORY.irf_ver())
outfile = NAME_FACTORY.srcmaps(**name_keys)
logfile = make_nfs_path(outfile.replace('.fits', '.log'))
job_configs[key] = dict(
srcmaps=NAME_FACTORY.srcmaps(**nested_name_keys),
expcube=NAME_FACTORY.ltcube(**name_keys),
irfs=NAME_FACTORY.irfs(**name_keys),
bexpmap=NAME_FACTORY.bexpcube(**name_keys),
srcmdl=NAME_FACTORY.srcmdl_xml(**name_keys),
merged=merged_name,
outfile=outfile,
outxml=NAME_FACTORY.nested_srcmdl_xml(**name_keys),
logfile=logfile)
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
try:
os.makedirs(os.path.join(ttype, 'results'))
except OSError:
pass
(roster_yaml, sim) = NAME_FACTORY.resolve_rosterfile(args)
if roster_yaml is None:
return job_configs
roster_dict = load_yaml(roster_yaml)
astro_priors = args['astro_priors']
channels = args['channels']
sim_path = os.path.join('config', 'sim_%s.yaml' % sim)
for roster_name in list(roster_dict.keys()):
rost_chans = select_channels(channels, roster_name)
for astro_prior in astro_priors:
name_keys = dict(target_type=ttype,
roster_name=roster_name,
astro_prior=astro_prior,
sim_name=sim,
seed='summary',
fullpath=True)
bands_path = NAME_FACTORY.sim_stackedlimitsfile(**name_keys)
for chan in rost_chans:
targ_key = "%s:%s:%s:%s" % (roster_name, astro_prior, sim,
chan)
output_path = os.path.join(
ttype, 'results', "control_mle_%s_%s_%s_%s.png" %
(roster_name, astro_prior, sim, chan))
logfile = make_nfs_path(output_path.replace(
'.png', '.log'))
job_config = dict(bands=bands_path,
outfile=output_path,
sim=sim_path,
logfile=logfile,
chan=chan)
job_configs[targ_key] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)
if sim is not None:
raise ValueError("Found 'sim' argument on AnalyzeSED_SG config.")
if targets_yaml is None:
return job_configs
targets = load_yaml(targets_yaml)
config_yaml = 'config.yaml'
if is_not_null(args['skydirs']):
skydirs = args['skydirs']
else:
skydirs = None
base_config = dict(roi_baseline=args['roi_baseline'],
make_plots=args['make_plots'],
non_null_src=args['non_null_src'])
for target_name, target_list in targets.items():
name_keys = dict(target_type=ttype,
target_name=target_name,
sim_name='random',
fullpath=True)
if skydirs is None:
target_dir = NAME_FACTORY.targetdir(**name_keys)
skydir_path = None
else:
target_dir = NAME_FACTORY.sim_targetdir(**name_keys)
skydir_path = os.path.join(target_dir, skydirs)
config_path = os.path.join(target_dir, config_yaml)
logfile = make_nfs_path(
os.path.join(target_dir,
"%s_%s.log" % (self.linkname, target_name)))
job_config = base_config.copy()
job_config.update(
dict(config=config_path,
profiles=target_list,
skydirs=skydir_path,
logfile=logfile))
job_configs[target_name] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
NAME_FACTORY.update_base_dict(args['data'])
ret_dict = make_catalog_comp_dict(sources=args['library'], basedir='.')
comp_info_dict = ret_dict['comp_info_dict']
for split_ver, split_dict in comp_info_dict.items():
for source_key, source_dict in split_dict.items():
full_key = "%s_%s" % (split_ver, source_key)
merged_name = "%s_%s" % (source_dict.catalog_info.catalog_name, source_key)
if source_dict.model_type != 'CompositeSource':
continue
for comp in components:
zcut = "zmax%i" % comp.zmax
key = "%s_%s" % (full_key, comp.make_key('{ebin_name}_{evtype_name}'))
name_keys = dict(zcut=zcut,
sourcekey=full_key,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
coordsys=comp.coordsys,
mktime='none',
irf_ver=NAME_FACTORY.irf_ver())
nested_name_keys = dict(zcut=zcut,
sourcekey=source_dict.catalog_info.catalog_name,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
coordsys=comp.coordsys,
mktime='none',
irf_ver=NAME_FACTORY.irf_ver())
outfile = NAME_FACTORY.srcmaps(**name_keys)
logfile = make_nfs_path(outfile.replace('.fits', '.log'))
job_configs[key] = dict(srcmaps=NAME_FACTORY.srcmaps(**nested_name_keys),
expcube=NAME_FACTORY.ltcube(**name_keys),
irfs=NAME_FACTORY.irfs(**name_keys),
bexpmap=NAME_FACTORY.bexpcube(**name_keys),
srcmdl=NAME_FACTORY.srcmdl_xml(**name_keys),
merged=merged_name,
outfile=outfile,
outxml=NAME_FACTORY.nested_srcmdl_xml(**name_keys),
logfile=logfile)
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(roster_yaml, sim) = NAME_FACTORY.resolve_rosterfile(args)
if roster_yaml is None:
return job_configs
if sim is not None:
raise ValueError("Sim argument set of plotting data results")
roster_dict = load_yaml(roster_yaml)
astro_priors = args['astro_priors']
channels = args['channels']
sims = args['sims']
for roster_name in list(roster_dict.keys()):
rost_chans = select_channels(channels, roster_name)
for astro_prior in astro_priors:
name_keys = dict(target_type=ttype,
roster_name=roster_name,
astro_prior=astro_prior,
fullpath=True)
input_path = NAME_FACTORY.stackedlimitsfile(**name_keys)
for sim in sims:
name_keys.update(sim_name=sim, seed='summary')
bands_path = NAME_FACTORY.sim_stackedlimitsfile(
**name_keys)
for chan in rost_chans:
targ_key = "%s:%s:%s:%s" % (roster_name, astro_prior,
sim, chan)
output_path = os.path.join(
ttype, 'results', "final_%s_%s_%s_%s.png" %
(roster_name, astro_prior, sim, chan))
logfile = make_nfs_path(
output_path.replace('.png', '.log'))
job_config = dict(infile=input_path,
outfile=output_path,
bands=bands_path,
logfile=logfile,
chan=chan)
job_configs[targ_key] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(
args, require_sim_name=True)
if targets_yaml is None:
return job_configs
write_full = args['write_full']
targets = load_yaml(targets_yaml)
base_config = dict(config=args['config'],
nsims=args['nsims'],
seed=args['seed'])
first = args['seed']
last = first + args['nsims'] - 1
for target_name, profile_list in targets.items():
for profile in profile_list:
full_key = "%s:%s:%s" % (target_name, profile, sim)
name_keys = dict(target_type=ttype,
target_name=target_name,
sim_name=sim,
profile=profile,
fullpath=True)
sed_file = NAME_FACTORY.sim_sedfile(**name_keys)
outfile = sed_file.replace(
'_SEED.fits', '_collected_%06i_%06i.fits' % (first, last))
logfile = make_nfs_path(outfile.replace('.fits', '.log'))
if not write_full:
outfile = None
summaryfile = sed_file.replace(
'_SEED.fits', '_summary_%06i_%06i.fits' % (first, last))
job_config = base_config.copy()
job_config.update(dict(sed_file=sed_file,
outfile=outfile,
summaryfile=summaryfile,
logfile=logfile))
job_configs[full_key] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)
if sim is not None:
raise ValueError("Found 'sim' argument on AnalyzeSED_SG config.")
if targets_yaml is None:
return job_configs
targets = load_yaml(targets_yaml)
config_yaml = 'config.yaml'
if is_not_null(args['skydirs']):
skydirs = args['skydirs']
else:
skydirs = None
base_config = dict(roi_baseline=args['roi_baseline'],
make_plots=args['make_plots'],
non_null_src=args['non_null_src'])
for target_name, target_list in targets.items():
name_keys = dict(target_type=ttype,
target_name=target_name,
sim_name='random',
fullpath=True)
if skydirs is None:
target_dir = NAME_FACTORY.targetdir(**name_keys)
skydir_path = None
else:
target_dir = NAME_FACTORY.sim_targetdir(**name_keys)
skydir_path = os.path.join(target_dir, skydirs)
config_path = os.path.join(target_dir, config_yaml)
logfile = make_nfs_path(os.path.join(
target_dir, "%s_%s.log" % (self.linkname, target_name)))
job_config = base_config.copy()
job_config.update(dict(config=config_path,
profiles=target_list,
skydirs=skydir_path,
logfile=logfile))
job_configs[target_name] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)
if targets_yaml is None:
return job_configs
astro_priors = args['astro_priors']
channels = args['channels']
base_config = dict(bands=None, sim=sim)
targets = load_yaml(targets_yaml)
for target_name, target_list in list(targets.items()):
for targ_prof in target_list:
prof_chans = select_channels(channels, targ_prof)
for astro_prior in astro_priors:
name_keys = dict(target_type=ttype,
target_name=target_name,
profile=targ_prof,
astro_prior=astro_prior,
fullpath=True)
input_path = NAME_FACTORY.dmlimitsfile(**name_keys)
for chan in prof_chans:
targ_key = "%s:%s:%s:%s" % (target_name, targ_prof,
astro_prior, chan)
output_path = input_path.replace(
'.fits', '_%s.png' % chan)
logfile = make_nfs_path(
output_path.replace('.png', '.log'))
job_config = base_config.copy()
job_config.update(
dict(infile=input_path,
outfile=output_path,
astro_prior=astro_prior,
logfile=logfile,
chan=chan))
job_configs[targ_key] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
targetfile_info = NAME_FACTORY.resolve_targetfile(args)
targets_yaml = targetfile_info[0]
if targets_yaml is None:
return job_configs
targets = load_yaml(targets_yaml)
astro_priors = args['astro_priors']
specs = args['specs']
global_min = args['global_min']
for target_name, target_list in targets.items():
for targ_prof in target_list:
prof_specs = specs
for astro_prior in astro_priors:
name_keys = dict(target_type=ttype,
target_name=target_name,
profile=targ_prof,
astro_prior=astro_prior,
fullpath=True)
input_path = NAME_FACTORY.stack_likefile(**name_keys)
for spec in prof_specs:
targ_key = "%s:%s:%s:%s" % (target_name, targ_prof,
astro_prior, spec)
output_path = input_path.replace(
'.fits', '_%s.png' % spec)
logfile = make_nfs_path(
output_path.replace('.png', '.log'))
job_config = dict(infile=input_path,
outfile=output_path,
astro_prior=astro_prior,
logfile=logfile,
global_min=global_min,
spec=spec)
job_configs[targ_key] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
gmm = make_ring_dicts(library=args['library'], basedir='.')
for galkey in gmm.galkeys():
ring_dict = gmm.ring_dict(galkey)
for ring_key, ring_info in ring_dict.items():
output_file = ring_info.merged_gasmap
file_string = ""
for fname in ring_info.files:
file_string += " %s" % fname
logfile = make_nfs_path(output_file.replace('.fits', '.log'))
job_configs[ring_key] = dict(output=output_file,
args=file_string,
logfile=logfile)
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
comp_file = args.get('comp', None)
if comp_file is not None:
comp_dict = yaml.safe_load(open(comp_file))
coordsys = comp_dict.pop('coordsys')
for v in comp_dict.values():
v['coordsys'] = coordsys
else:
return job_configs
NAME_FACTORY.update_base_dict(args['data'])
inputfiles = create_inputlist(args['ft1file'])
outdir_base = os.path.join(NAME_FACTORY.base_dict['basedir'],
'counts_cubes')
for idx, infile in enumerate(inputfiles):
key = "%06i" % idx
output_dir = os.path.join(outdir_base, key)
try:
os.mkdir(output_dir)
except OSError:
pass
logfile = make_nfs_path(
os.path.join(output_dir, 'scatter_%s.log' % key))
#job_configs[key] = args.copy()
job_configs[key] = args.copy()
job_configs[key].update(
dict(ft1file=infile,
comp=args['comp'],
hpx_order_max=args['hpx_order_max'],
outdir=outdir_base,
outkey=key,
logfile=logfile,
pfiles=output_dir))
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)
if targets_yaml is None:
return job_configs
config_yaml = 'config.yaml'
config_override = args.get('config')
if is_not_null(config_override):
config_yaml = config_override
targets = load_yaml(targets_yaml)
base_config = dict(sim_profile=args['sim_profile'],
roi_baseline=args['roi_baseline'],
sim=sim,
nsims=args['nsims'],
seed=args['seed'])
for target_name, target_list in targets.items():
name_keys = dict(target_type=ttype,
target_name=target_name,
sim_name=sim,
fullpath=True)
simdir = NAME_FACTORY.sim_targetdir(**name_keys)
config_path = os.path.join(simdir, config_yaml)
logfile = make_nfs_path(
os.path.join(simdir,
"%s_%s.log" % (self.linkname, target_name)))
job_config = base_config.copy()
job_config.update(
dict(config=config_path, logfile=logfile,
profiles=target_list))
job_configs[target_name] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)
if targets_yaml is None:
return job_configs
targets = load_yaml(targets_yaml)
first = args['seed']
last = first + args['nsims'] - 1
for target_name, target_list in targets.items():
for targ_prof in target_list:
name_keys = dict(target_type=ttype,
target_name=target_name,
profile=targ_prof,
fullpath=True)
targ_key = "%s_%s" % (target_name, targ_prof)
input_path = NAME_FACTORY.sedfile(**name_keys)
output_path = input_path.replace('.fits', '.png')
logfile = make_nfs_path(input_path.replace('.fits', '.log'))
sed_file = NAME_FACTORY.sim_sedfile(sim_name=args['band_sim'],
**name_keys)
summaryfile = sed_file.replace(
'_SEED.fits', '_summary_%06i_%06i.fits' % (first, last))
job_config = dict(infile=input_path,
outfile=output_path,
summaryfile=summaryfile,
band_sim=args['band_sim'],
logfile=logfile)
job_configs[targ_key] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
NAME_FACTORY.update_base_dict(args['data'])
NAME_FACTORY_CLEAN.update_base_dict(args['data'])
NAME_FACTORY_DIRTY.update_base_dict(args['data'])
NAME_FACTORY_CLEAN.base_dict['evclass'] = args['clean']
NAME_FACTORY_DIRTY.base_dict['evclass'] = args['dirty']
for comp in components:
zcut = "zmax%i" % comp.zmax
key = comp.make_key('{ebin_name}_{evtype_name}')
name_keys = dict(zcut=zcut,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
coordsys=comp.coordsys,
irf_ver=NAME_FACTORY.irf_ver(),
mktime=args['mktimefilter'],
fullpath=True)
outfile = NAME_FACTORY.residual_cr(**name_keys)
if args['hpx_order']:
hpx_order = min(comp.hpx_order, args['hpx_order'])
else:
hpx_order = comp.hpx_order
job_configs[key] = dict(bexpcube_dirty=NAME_FACTORY_DIRTY.bexpcube(**name_keys),
ccube_dirty=NAME_FACTORY_DIRTY.ccube(**name_keys),
bexpcube_clean=NAME_FACTORY_CLEAN.bexpcube(**name_keys),
ccube_clean=NAME_FACTORY_CLEAN.ccube(**name_keys),
outfile=outfile,
hpx_order=hpx_order,
full_output=args['full_output'],
logfile=make_nfs_path(outfile.replace('.fits', '.log')))
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
comp_file = args.get('comp', None)
if comp_file is not None:
comp_dict = yaml.safe_load(open(comp_file))
coordsys = comp_dict.pop('coordsys')
for v in comp_dict.values():
v['coordsys'] = coordsys
else:
return job_configs
NAME_FACTORY.update_base_dict(args['data'])
inputfiles = create_inputlist(args['ft1file'])
outdir_base = os.path.join(NAME_FACTORY.base_dict['basedir'], 'counts_cubes')
for idx, infile in enumerate(inputfiles):
key = "%06i" % idx
output_dir = os.path.join(outdir_base, key)
try:
os.mkdir(output_dir)
except OSError:
pass
logfile = make_nfs_path(os.path.join(output_dir, 'scatter_%s.log' % key))
job_configs[key] = comp_dict.copy()
job_configs[key].update(dict(ft1file=infile,
comp=args['comp'],
hpx_order_max=args['hpx_order_max'],
outdir=outdir_base,
outkey=key,
logfile=logfile,
pfiles=output_dir))
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)
if targets_yaml is None:
return job_configs
config_yaml = 'config.yaml'
config_override = args.get('config')
if is_not_null(config_override):
config_yaml = config_override
rand_yaml = NAME_FACTORY.resolve_randconfig(args)
targets = load_yaml(targets_yaml)
base_config = dict(rand_config=rand_yaml)
for target_name in targets.keys():
name_keys = dict(target_type=ttype,
target_name=target_name,
sim_name=sim,
fullpath=True)
simdir = NAME_FACTORY.sim_targetdir(**name_keys)
config_path = os.path.join(simdir, config_yaml)
outfile = os.path.join(simdir, 'skydirs.yaml')
logfile = make_nfs_path(outfile.replace('yaml', 'log'))
job_config = base_config.copy()
job_config.update(dict(config=config_path,
outfile=outfile,
logfile=logfile))
job_configs[target_name] = job_config
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
ttype = args['ttype']
(targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)
if targets_yaml is None:
return job_configs
config_yaml = 'config.yaml'
config_override = args.get('config')
if is_not_null(config_override):
config_yaml = config_override
rand_yaml = NAME_FACTORY.resolve_randconfig(args)
targets = load_yaml(targets_yaml)
base_config = dict(rand_config=rand_yaml)
for target_name in targets.keys():
name_keys = dict(target_type=ttype,
target_name=target_name,
sim_name=sim,
fullpath=True)
simdir = NAME_FACTORY.sim_targetdir(**name_keys)
config_path = os.path.join(simdir, config_yaml)
outfile = os.path.join(simdir, 'skydirs.yaml')
logfile = make_nfs_path(outfile.replace('yaml', 'log'))
job_config = base_config.copy()
job_config.update(
dict(config=config_path, outfile=outfile, logfile=logfile))
job_configs[target_name] = job_config
return job_configs
def _map_arguments(self, args):
"""Map from the top-level arguments to the arguments provided to
the indiviudal links """
comp_file = args.get('comp', None)
datafile = args.get('data', None)
if is_null(comp_file):
return
if is_null(datafile):
return
NAME_FACTORY.update_base_dict(datafile)
outdir = args.get('outdir', None)
outkey = args.get('outkey', None)
ft1file = args['ft1file']
if is_null(outdir) or is_null(outkey):
return
pfiles = os.path.join(outdir, outkey)
self.comp_dict = yaml.safe_load(open(comp_file))
coordsys = self.comp_dict.pop('coordsys')
full_out_dir = make_nfs_path(os.path.join(outdir, outkey))
for key_e, comp_e in sorted(self.comp_dict.items()):
emin = math.pow(10., comp_e['log_emin'])
emax = math.pow(10., comp_e['log_emax'])
enumbins = comp_e['enumbins']
zmax = comp_e['zmax']
zcut = "zmax%i" % comp_e['zmax']
evclassstr = NAME_FACTORY.base_dict['evclass']
kwargs_select = dict(zcut=zcut,
ebin=key_e,
psftype='ALL',
coordsys=coordsys,
mktime='none')
selectfile_energy = make_full_path(outdir, outkey, NAME_FACTORY.select(**kwargs_select))
linkname = 'select-energy-%s-%s' % (key_e, zcut)
self._set_link(linkname, Gtlink_select,
infile=ft1file,
outfile=selectfile_energy,
zmax=zmax,
emin=emin,
emax=emax,
evclass=NAME_FACTORY.evclassmask(evclassstr),
pfiles=pfiles,
logfile=os.path.join(full_out_dir, "%s.log" % linkname))
if 'evtclasses' in comp_e:
evtclasslist_vals = comp_e['evtclasses']
else:
evtclasslist_vals = [NAME_FACTORY.base_dict['evclass']]
for evtclassval in evtclasslist_vals:
for psf_type, psf_dict in sorted(comp_e['psf_types'].items()):
linkname_select = 'select-type-%s-%s-%s-%s' % (
key_e, zcut, evtclassval, psf_type)
linkname_bin = 'bin-%s-%s-%s-%s' % (key_e, zcut, evtclassval, psf_type)
hpx_order = psf_dict['hpx_order']
kwargs_bin = kwargs_select.copy()
kwargs_bin['psftype'] = psf_type
selectfile_psf = make_full_path(
outdir, outkey, NAME_FACTORY.select(**kwargs_bin))
binfile = make_full_path(outdir, outkey, NAME_FACTORY.ccube(**kwargs_bin))
self._set_link(linkname_select, Gtlink_select,
infile=selectfile_energy,
outfile=selectfile_psf,
zmax=zmax,
emin=emin,
emax=emax,
evtype=EVT_TYPE_DICT[psf_type],
evclass=NAME_FACTORY.evclassmask(evtclassval),
pfiles=pfiles,
logfile=os.path.join(full_out_dir, "%s.log" % linkname_select))
self._set_link(linkname_bin, Gtlink_bin,
coordsys=coordsys,
hpx_order=hpx_order,
evfile=selectfile_psf,
outfile=binfile,
emin=emin,
emax=emax,
enumbins=enumbins,
pfiles=pfiles,
logfile=os.path.join(full_out_dir, "%s.log" % linkname_bin))
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
NAME_FACTORY.update_base_dict(args['data'])
ret_dict = make_diffuse_comp_info_dict(components=components,
library=args['library'],
basedir='.')
diffuse_comp_info_dict = ret_dict['comp_info_dict']
if args['make_xml']:
SrcmapsDiffuse_SG._make_xml_files(diffuse_comp_info_dict)
for diffuse_comp_info_key in sorted(diffuse_comp_info_dict.keys()):
diffuse_comp_info_value = diffuse_comp_info_dict[diffuse_comp_info_key]
no_psf = diffuse_comp_info_value.no_psf
for comp in components:
zcut = "zmax%i" % comp.zmax
key = comp.make_key('{ebin_name}_{evtype_name}')
if diffuse_comp_info_value.components is None:
sub_comp_info = diffuse_comp_info_value
else:
sub_comp_info = diffuse_comp_info_value.get_component_info(comp)
name_keys = dict(zcut=zcut,
sourcekey=sub_comp_info.sourcekey,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
mktime='none',
coordsys=comp.coordsys,
irf_ver=NAME_FACTORY.irf_ver(),
fullpath=True)
kmin = 0
kmax = comp.enumbins + 1
outfile_base = NAME_FACTORY.srcmaps(**name_keys)
kstep = HPX_ORDER_TO_KSTEP[comp.hpx_order]
base_dict = dict(cmap=NAME_FACTORY.ccube(**name_keys),
expcube=NAME_FACTORY.ltcube(**name_keys),
irfs=NAME_FACTORY.irfs(**name_keys),
bexpmap=NAME_FACTORY.bexpcube(**name_keys),
srcmdl=sub_comp_info.srcmdl_name,
source=sub_comp_info.source_name,
no_psf=no_psf,
evtype=comp.evtype)
if kstep < 0:
kstep = kmax
else:
pass
for k in range(kmin, kmax, kstep):
full_key = "%s_%s_%02i" % (diffuse_comp_info_key, key, k)
khi = min(kmax, k + kstep)
full_dict = base_dict.copy()
outfile = outfile_base.replace('.fits', '_%02i.fits' % k)
logfile = make_nfs_path(outfile_base.replace('.fits', '_%02i.log' % k))
full_dict.update(dict(outfile=outfile,
kmin=k, kmax=khi,
logfile=logfile))
job_configs[full_key] = full_dict
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
NAME_FACTORY.update_base_dict(args['data'])
ret_dict = make_diffuse_comp_info_dict(components=components,
library=args['library'],
basedir='.')
diffuse_comp_info_dict = ret_dict['comp_info_dict']
if args['make_xml']:
SrcmapsDiffuse_SG._make_xml_files(diffuse_comp_info_dict)
for diffuse_comp_info_key in sorted(diffuse_comp_info_dict.keys()):
diffuse_comp_info_value = diffuse_comp_info_dict[
diffuse_comp_info_key]
no_psf = diffuse_comp_info_value.no_psf
for comp in components:
zcut = "zmax%i" % comp.zmax
key = comp.make_key('{ebin_name}_{evtype_name}')
if diffuse_comp_info_value.components is None:
sub_comp_info = diffuse_comp_info_value
else:
sub_comp_info = diffuse_comp_info_value.get_component_info(
comp)
name_keys = dict(zcut=zcut,
sourcekey=sub_comp_info.sourcekey,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
mktime='none',
coordsys=comp.coordsys,
irf_ver=NAME_FACTORY.irf_ver(),
fullpath=True)
kmin = 0
kmax = comp.enumbins + 1
outfile_base = NAME_FACTORY.srcmaps(**name_keys)
kstep = HPX_ORDER_TO_KSTEP[comp.hpx_order]
base_dict = dict(cmap=NAME_FACTORY.ccube(**name_keys),
expcube=NAME_FACTORY.ltcube(**name_keys),
irfs=NAME_FACTORY.irfs(**name_keys),
bexpmap=NAME_FACTORY.bexpcube(**name_keys),
srcmdl=sub_comp_info.srcmdl_name,
source=sub_comp_info.source_name,
no_psf=no_psf,
evtype=comp.evtype)
if kstep < 0:
kstep = kmax
else:
pass
for k in range(kmin, kmax, kstep):
full_key = "%s_%s_%02i" % (diffuse_comp_info_key, key, k)
khi = min(kmax, k + kstep)
full_dict = base_dict.copy()
outfile = outfile_base.replace('.fits', '_%02i.fits' % k)
logfile = make_nfs_path(
outfile_base.replace('.fits', '_%02i.log' % k))
full_dict.update(
dict(outfile=outfile,
kmin=k,
kmax=khi,
logfile=logfile))
job_configs[full_key] = full_dict
return job_configs
def build_job_configs(self, args):
"""Hook to build job configurations
"""
job_configs = {}
components = Component.build_from_yamlfile(args['comp'])
NAME_FACTORY.update_base_dict(args['data'])
if self._comp_dict is None or self._comp_dict_file != args['library']:
self._comp_dict_file = args['library']
self._comp_dict = make_catalog_comp_dict(
sources=self._comp_dict_file,
basedir=NAME_FACTORY.base_dict['basedir'])
else:
print("Using cached catalog dict from %s" % args['library'])
catalog_info_dict = self._comp_dict['catalog_info_dict']
comp_info_dict = self._comp_dict['comp_info_dict']
n_src_per_job = args['nsrc']
if args['make_xml']:
SrcmapsCatalog_SG._make_xml_files(catalog_info_dict,
comp_info_dict)
for catalog_name, catalog_info in catalog_info_dict.items():
n_cat_src = len(catalog_info.catalog.table)
n_job = int(math.ceil(float(n_cat_src) / n_src_per_job))
for comp in components:
zcut = "zmax%i" % comp.zmax
key = comp.make_key('{ebin_name}_{evtype_name}')
name_keys = dict(zcut=zcut,
sourcekey=catalog_name,
ebin=comp.ebin_name,
psftype=comp.evtype_name,
coordsys=comp.coordsys,
irf_ver=NAME_FACTORY.irf_ver(),
mktime='none',
fullpath=True)
for i_job in range(n_job):
full_key = "%s_%02i" % (key, i_job)
srcmin = i_job * n_src_per_job
srcmax = min(srcmin + n_src_per_job, n_cat_src)
outfile = NAME_FACTORY.srcmaps(**name_keys).replace(
'.fits', "_%02i.fits" % (i_job))
logfile = make_nfs_path(outfile.replace('.fits', '.log'))
job_configs[full_key] = dict(
cmap=NAME_FACTORY.ccube(**name_keys),
expcube=NAME_FACTORY.ltcube(**name_keys),
irfs=NAME_FACTORY.irfs(**name_keys),
bexpmap=NAME_FACTORY.bexpcube(**name_keys),
outfile=outfile,
logfile=logfile,
srcmdl=catalog_info.srcmdl_name,
evtype=comp.evtype,
srcmin=srcmin,
srcmax=srcmax)
return job_configs
def _map_arguments(self, args):
"""Map from the top-level arguments to the arguments provided to
the indiviudal links """
comp_file = args.get('comp', None)
datafile = args.get('data', None)
if is_null(comp_file):
return
if is_null(datafile):
return
NAME_FACTORY.update_base_dict(args['data'])
outdir = args.get('outdir')
outkey = args.get('outkey')
ft1file = args['ft1file']
ft2file = args['ft2file']
if is_null(outdir) or is_null(outkey):
return
pfiles = os.path.join(outdir, outkey)
self.comp_dict = yaml.safe_load(open(comp_file))
coordsys = self.comp_dict.pop('coordsys')
full_out_dir = make_nfs_path(os.path.join(outdir, outkey))
for key_e, comp_e in sorted(self.comp_dict.items()):
if 'logebins' in comp_e:
ebins_file = make_nfs_path(
os.path.join(full_out_dir, 'energy_bins.fits'))
write_ebins_file(ebins_file, comp_e['logebins'])
else:
ebins_file = None
enumbins = comp_e['enumbins']
emin = math.pow(10., comp_e['log_emin'])
emax = math.pow(10., comp_e['log_emax'])
zmax = comp_e['zmax']
zcut = "zmax%i" % comp_e['zmax']
tmin = comp_e.get('tmin', None)
tmax = comp_e.get('tmax', None)
if is_null(tmin):
tmin = 'INDEF'
if is_null(tmax):
tmax = 'INDEF'
evclassstr = NAME_FACTORY.base_dict['evclass']
kwargs_select = dict(zcut=zcut,
ebin=key_e,
psftype='ALL',
coordsys=coordsys)
linkname = 'select-energy-%s-%s' % (key_e, zcut)
selectfile_energy = make_full_path(
outdir, outkey, NAME_FACTORY.select(**kwargs_select))
self._set_link(linkname,
Gtlink_select,
infile=ft1file,
outfile=selectfile_energy,
zmax=zmax,
tmin=tmin,
tmax=tmax,
emin=emin,
emax=emax,
evclass=NAME_FACTORY.evclassmask(evclassstr),
pfiles=pfiles,
logfile=os.path.join(full_out_dir,
"%s.log" % linkname))
if 'mktimefilters' in comp_e:
mktimefilters = comp_e['mktimefilters']
else:
mktimefilters = ['none']
for mktimekey in mktimefilters:
kwargs_mktime = kwargs_select.copy()
kwargs_mktime['mktime'] = mktimekey
filterstring = MKTIME_DICT[mktimekey]
mktime_file = make_full_path(
outdir, outkey, NAME_FACTORY.mktime(**kwargs_mktime))
ltcube_file = make_full_path(
outdir, outkey, NAME_FACTORY.ltcube(**kwargs_mktime))
linkname_mktime = 'mktime-%s-%s-%s' % (key_e, zcut, mktimekey)
linkname_ltcube = 'ltcube-%s-%s-%s' % (key_e, zcut, mktimekey)
self._set_link(linkname_mktime,
Gtlink_mktime,
evfile=selectfile_energy,
outfile=mktime_file,
scfile=ft2file,
filter=filterstring,
pfiles=pfiles,
logfile=os.path.join(full_out_dir, "%s.log" %
linkname_mktime))
self._set_link(linkname_ltcube,
Gtlink_ltcube,
evfile=mktime_file,
outfile=ltcube_file,
scfile=ft2file,
zmax=zmax,
pfiles=pfiles,
logfile=os.path.join(full_out_dir, "%s.log" %
linkname_ltcube))
if 'evtclasses' in comp_e:
evtclasslist_vals = comp_e['evtclasses']
else:
evtclasslist_vals = [NAME_FACTORY.base_dict['evclass']]
for evtclassval in evtclasslist_vals:
for psf_type, psf_dict in sorted(
comp_e['psf_types'].items()):
linkname_select = 'select-type-%s-%s-%s-%s-%s' % (
key_e, zcut, mktimekey, evtclassval, psf_type)
linkname_bin = 'bin-%s-%s-%s-%s-%s' % (
key_e, zcut, mktimekey, evtclassval, psf_type)
kwargs_bin = kwargs_mktime.copy()
kwargs_bin['psftype'] = psf_type
kwargs_bin['coordsys'] = coordsys
kwargs_bin['evclass'] = evtclassval
selectfile_psf = make_full_path(
outdir, outkey, NAME_FACTORY.select(**kwargs_bin))
binfile_psf = make_full_path(
outdir, outkey, NAME_FACTORY.ccube(**kwargs_bin))
hpx_order_psf = min(args['hpx_order_max'],
psf_dict['hpx_order'])
linkname_select = 'select-type-%s-%s-%s-%s-%s' % (
key_e, zcut, mktimekey, evtclassval, psf_type)
linkname_bin = 'bin-%s-%s-%s-%s-%s' % (
key_e, zcut, mktimekey, evtclassval, psf_type)
self._set_link(
linkname_select,
Gtlink_select,
infile=selectfile_energy,
outfile=selectfile_psf,
zmax=zmax,
emin=emin,
emax=emax,
tmin=tmin,
tmax=tmax,
evtype=EVT_TYPE_DICT[psf_type],
evclass=NAME_FACTORY.evclassmask(evtclassval),
pfiles=pfiles,
logfile=os.path.join(full_out_dir,
"%s.log" % linkname_select))
print("xx", ebins_file)
if ebins_file is None:
self._set_link(linkname_bin,
Gtlink_bin,
coordsys=coordsys,
hpx_order=hpx_order_psf,
evfile=selectfile_psf,
outfile=binfile_psf,
emin=emin,
emax=emax,
enumbins=enumbins,
pfiles=pfiles,
logfile=os.path.join(
full_out_dir,
"%s.log" % linkname_bin))
else:
self._set_link(linkname_bin,
Gtlink_bin,
coordsys=coordsys,
hpx_order=hpx_order_psf,
evfile=selectfile_psf,
outfile=binfile_psf,
ebinalg='FILE',
ebinfile=ebins_file,
pfiles=pfiles,
logfile=os.path.join(
full_out_dir,
"%s.log" % linkname_bin))
