def set_up_roi(self):
'''Loads fermipy GTAnalysis object, sets up sources,
loads some dictionaries of values for later use.
'''
self.gta = GTAnalysis.create(self.roi_file, config=self.config_path)
self.gta.free_sources(free=False)
self.gta.free_source(self.name)
self.src_model = self.gta.get_src_model(self.name)
self.init_like = -self.gta.like()
self.gta.set_source_spectrum(self.name, spectrum_type='FileFunction')
self.logEMeV, self.init_dnde = self.gta.get_source_dnde(self.name)
self.EMeV = np.power(10., self.logEMeV)
self.get_init_vals()
def main():
# Argument defintion
usage = "usage: %(prog)s [options]"
description = "Load a fermipy configuration and snapshot"
parser = argparse.ArgumentParser(usage, description=description)
parser.add_argument('-c',
"--config",
type=argparse.FileType('r'),
default="config.yaml",
help="Config file")
parser.add_argument('-i',
"--input",
type=argparse.FileType('r'),
default="baseline.npy",
help="Input file")
parser.add_argument('-o',
"--output",
type=str,
default=None,
help="Output file")
parser.add_argument('-p',
"--pars",
type=str,
default=None,
help="Parameter file")
parser.add_argument('-m',
"--mask",
type=str,
default=None,
help="Mask file")
args = parser.parse_args(sys.argv[1:])
gta = GTAnalysis.create(args.input.name,
args.config.name,
params=args.pars,
mask=args.mask)
for name in gta.like.sourceNames():
print('Initializing source %s' % name)
gta._init_source(name)
gta._update_roi()
gta.write_roi(args.output, save_model_map=True, save_weight_map=True)
return gta
def load_roi(roi_file):
with open(cwd + '/config_local.yaml', 'r') as i:
config = yaml.safe_load(i)
config['fileio']['workdir'] = cwd + '/fits'
config['fileio']['outdir'] = cwd + '/fits'
config['fileio']['logfile'] = cwd + '/fits/fermipy.log'
config['data']['ltcube'] = cwd + '/fits/ltcube_00.fits'
config['model'][
'galdiff'] = path_to_conda + '/share/fermitools/refdata/fermi/galdiffuse/gll_iem_v07.fits'
config['model'][
'isodiff'] = path_to_conda + '/share/fermitools/refdata/fermi/galdiffuse/iso_P8R3_SOURCE_V3_v1.txt'
config['logging']['verbosity'] = 4
source = config['selection']['target']
with open(cwd + '/config_modified.yaml', 'w') as o:
yaml.dump(config, o)
gta = GTAnalysis.create(roi_file, config=f'{cwd}/config_modified.yaml')
return gta
def run_analysis(self, argv):
"""Run this analysis"""
args = self._parser.parse_args(argv)
if not HAVE_ST:
raise RuntimeError(
"Trying to run fermipy analysis, but don't have ST")
if is_not_null(args.roi_baseline):
gta = GTAnalysis.create(args.roi_baseline, args.config)
else:
gta = GTAnalysis(args.config,
logging={'verbosity': 3},
fileio={'workdir_regex': '\.xml$|\.npy$'})
gta.print_roi()
test_source = args.target
gta.sed(test_source, outfile='sed_%s.fits' % 'FL8Y', make_plots=True)
gta.extension(test_source, make_plots=True)
return gta
data = np.zeros((100, 3), dtype=float)
np.savetxt(
f"/nfs/astrop/n1/kuhlmann/NGC_1275/ts_limit/grid_ts/outdata/roi_{which_roi}/out_{which_gm:03}.dat",
data)
start = which_range * nsim
end = (which_range + 1) * nsim
indices = [i for i in range(start, end)]
else:
start = which_range * nsim
end = (which_range + 1) * nsim
indices = [i for i in range(start, end)]
print(indices)
# sys.exit()
gta = GTAnalysis.create(roi_file, config=cwd + '/config_modified.yaml')
roi_numpy = np.load(roi_file, allow_pickle=True).flat[0]
print('fermipy loglike:', -gta.like())
print('numpy loglike:', roi_numpy['roi']['loglike'])
test = janitor(source, gta)
setrlimit(RLIMIT_AS, (2048 * 1024 * 1024, hard))
print(getrlimit(RLIMIT_AS))
test.indices = indices
for i in indices:
test.index = i
print('doing simulation number', str(i))
test.fit()
test.write_outdata()
def run_analysis(self, argv):
"""Run this analysis"""
args = self._parser.parse_args(argv)
if not HAVE_ST:
raise RuntimeError(
"Trying to run fermipy analysis, but don't have ST")
if args.load_baseline:
gta = GTAnalysis.create(args.roi_baseline, args.config)
else:
gta = GTAnalysis(args.config,
logging={'verbosity': 3},
fileio={'workdir_regex': '\.xml$|\.npy$'})
gta.setup()
if is_not_null(args.input_pars):
gta.load_parameters_from_yaml(args.input_pars)
gta.write_roi(args.roi_baseline,
save_model_map=True,
save_weight_map=True,
make_plots=args.make_plots)
src_list = get_src_names(gta)
plotter = plotting.AnalysisPlotter(gta.config['plotting'],
fileio=gta.config['fileio'],
logging=gta.config['logging'])
if is_null(args.fit_strategy):
return
fit_strategy = load_yaml(args.fit_strategy)
npred_current = None
npred_prev = None
plots_only = False
for fit_stage in fit_strategy:
mask = fit_stage.get('mask', None)
npred_threshold = fit_stage.get('npred_threshold', 1.0e4)
frac_threshold = fit_stage.get('frac_threshold', 0.5)
npred_frac = fit_stage.get('npred_frac', 0.9999)
if plots_only:
gta.load_roi("%s.npy" % fit_stage['key'])
npred_current = set_wts_get_npred_wt(gta, mask)
skip_list_region = get_unchanged(src_list,
npred_current,
npred_prev,
frac_threshold=frac_threshold)
else:
npred_current = set_wts_get_npred_wt(gta, mask)
skip_list_region = get_unchanged(src_list,
npred_current,
npred_prev,
frac_threshold=frac_threshold)
gta.optimize(npred_frac=npred_frac,
npred_threshold=npred_threshold,
skip=skip_list_region)
snapshot(gta,
plotter,
fit_stage['key'],
make_plots=args.make_plots)
npred_prev = npred_current
npred_current = build_srcdict(gta, 'npred_wt')
def run_analysis(self, argv):
"""Run this analysis"""
args = self._parser.parse_args(argv)
if not HAVE_ST:
raise RuntimeError(
"Trying to run fermipy analysis, but don't have ST")
if args.load_baseline:
gta = GTAnalysis.create(args.roi_baseline,
args.config)
else:
gta = GTAnalysis(args.config,
logging={'verbosity': 3},
fileio={'workdir_regex': '\.xml$|\.npy$'})
gta.setup()
if is_not_null(args.input_pars):
gta.load_parameters_from_yaml(args.input_pars)
gta.write_roi(args.roi_baseline,
save_model_map=True,
save_weight_map=True,
make_plots=args.make_plots)
src_list = get_src_names(gta)
plotter = plotting.AnalysisPlotter(gta.config['plotting'],
fileio=gta.config['fileio'],
logging=gta.config['logging'])
if is_null(args.fit_strategy):
return
fit_strategy = load_yaml(args.fit_strategy)
npred_current = None
npred_prev = None
plots_only = False
for fit_stage in fit_strategy:
mask = fit_stage.get('mask', None)
npred_threshold = fit_stage.get('npred_threshold', 1.0e4)
frac_threshold = fit_stage.get('frac_threshold', 0.5)
npred_frac = fit_stage.get('npred_frac', 0.9999)
if plots_only:
gta.load_roi("%s.npy" % fit_stage['key'])
npred_current = set_wts_get_npred_wt(gta, mask)
skip_list_region = get_unchanged(src_list,
npred_current,
npred_prev,
frac_threshold=frac_threshold)
else:
npred_current = set_wts_get_npred_wt(gta, mask)
skip_list_region = get_unchanged(src_list,
npred_current,
npred_prev,
frac_threshold=frac_threshold)
gta.optimize(npred_frac=npred_frac,
npred_threshold=npred_threshold,
skip=skip_list_region)
snapshot(gta, plotter, fit_stage['key'], make_plots=args.make_plots)
npred_prev = npred_current
npred_current = build_srcdict(gta, 'npred_wt')
config['fileio']['logfile'] = cwd+'/fits/fermipy.log'
config['data']['ltcube'] = cwd+'/fits/ltcube_00.fits'
config['model']['galdiff'] = path_to_conda+'/share/fermitools/refdata/fermi/galdiffuse/gll_iem_v07.fits'
config['model']['isodiff'] = path_to_conda+'/share/fermitools/refdata/fermi/galdiffuse/iso_P8R3_SOURCE_V3_v1.txt'
config['logging']['verbosity'] = 4
source = config['selection']['target']
with open(cwd+'/config_modified.yaml', 'w') as o:
yaml.dump(config, o)
if roi == 0:
roi_file = 'fully_optimized.npy'
elif roi == 1:
roi_file = 'simulation_base_roi.npy'
gta = GTAnalysis.create(f'fits/{roi_file}', config='config_modified.yaml')
init_like = - gta.like()
src_model = gta.get_src_model(source)
norm = src_model['param_values'][0] * 1.0e11
alpha = src_model['param_values'][1]
beta = src_model['param_values'][2] * 1.0e1
norm_err = src_model['param_errors'][0] * 1.0e11
alpha_err = src_model['param_errors'][1]
beta_err = src_model['param_errors'][2] * 1.0e1
Eb = src_model['param_values'][3]
gta.set_source_spectrum(source, spectrum_type='FileFunction')
log10MeV, dnde = gta.get_source_dnde(source)
x = np.power(10, log10MeV)
loglikes = np.zeros((nsim, 5))
for i in gm_vals:
prob = np.loadtxt(f'{photon_base_path}/prob{i:03.0f}.dat')
try:
os.mkdir(workdir)
except FileExistsError:
print('output directory already exists')
sys.exit()
roi_path = workdir
print(roi_path)
files = os.listdir(master_loc)
print('files at master loc:', files)
for f in files:
shutil.copy2(f'{master_loc}/{f}',
f'{workdir}') # copying from master file location
else:
roi_path = f'{cwd}/fits_01'
gta = GTAnalysis.create(f'{roi_path}/fit_newminuit',
cwd + '/config_modified.yaml')
print('loaded loglike:', -gta.like())
roi_npy = np.load(f'{roi_path}/fit_newminuit.npy', allow_pickle=True).flat[0]
print('numpy loglike:', roi_npy['roi']['loglike'])
like_save_path = f'{workdir}/loglike_H0_{input_arg}.dat' # loglike of null hypothesis (no alps)
gta.free_sources(free=False)
gta.simulate_roi()
for j in range(5):
gta.optimize()
# print("loglike of saved roi", -gta.like())
# gta.write_roi(f'sim_{input_arg}')
gta.free_source(source)
# gta.fit(optimizer='NEWMINUIT', reoptimize=True)
# gta.free_source(source, free=False)
# gta.free_source(source, pars='norm')
gta.free_source('isodiff')
