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fermiPy/fermipy | fermipy/diffuse/catalog_src_manager.py | make_catalog_comp_dict | def make_catalog_comp_dict(**kwargs):
"""Build and return the information about the catalog components
"""
library_yamlfile = kwargs.pop('library', 'models/library.yaml')
csm = kwargs.pop('CatalogSourceManager', CatalogSourceManager(**kwargs))
if library_yamlfile is None or library_yamlfile == 'None... | python | def make_catalog_comp_dict(**kwargs):
"""Build and return the information about the catalog components
"""
library_yamlfile = kwargs.pop('library', 'models/library.yaml')
csm = kwargs.pop('CatalogSourceManager', CatalogSourceManager(**kwargs))
if library_yamlfile is None or library_yamlfile == 'None... | [
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fermiPy/fermipy | fermipy/diffuse/catalog_src_manager.py | CatalogSourceManager.read_catalog_info_yaml | def read_catalog_info_yaml(self, splitkey):
""" Read the yaml file for a particular split key
"""
catalog_info_yaml = self._name_factory.catalog_split_yaml(sourcekey=splitkey,
fullpath=True)
yaml_dict = yaml.safe_load(open... | python | def read_catalog_info_yaml(self, splitkey):
""" Read the yaml file for a particular split key
"""
catalog_info_yaml = self._name_factory.catalog_split_yaml(sourcekey=splitkey,
fullpath=True)
yaml_dict = yaml.safe_load(open... | [
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fermiPy/fermipy | fermipy/diffuse/catalog_src_manager.py | CatalogSourceManager.build_catalog_info | def build_catalog_info(self, catalog_info):
""" Build a CatalogInfo object """
cat = SourceFactory.build_catalog(**catalog_info)
catalog_info['catalog'] = cat
# catalog_info['catalog_table'] =
# Table.read(catalog_info['catalog_file'])
catalog_info['catalog_table'] = c... | python | def build_catalog_info(self, catalog_info):
""" Build a CatalogInfo object """
cat = SourceFactory.build_catalog(**catalog_info)
catalog_info['catalog'] = cat
# catalog_info['catalog_table'] =
# Table.read(catalog_info['catalog_file'])
catalog_info['catalog_table'] = c... | [
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fermiPy/fermipy | fermipy/diffuse/catalog_src_manager.py | CatalogSourceManager.catalog_components | def catalog_components(self, catalog_name, split_ver):
""" Return the set of merged components for a particular split key """
return sorted(self._split_comp_info_dicts["%s_%s" % (catalog_name, split_ver)].keys()) | python | def catalog_components(self, catalog_name, split_ver):
""" Return the set of merged components for a particular split key """
return sorted(self._split_comp_info_dicts["%s_%s" % (catalog_name, split_ver)].keys()) | [
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fermiPy/fermipy | fermipy/diffuse/catalog_src_manager.py | CatalogSourceManager.split_comp_info | def split_comp_info(self, catalog_name, split_ver, split_key):
""" Return the info for a particular split key """
return self._split_comp_info_dicts["%s_%s" % (catalog_name, split_ver)][split_key] | python | def split_comp_info(self, catalog_name, split_ver, split_key):
""" Return the info for a particular split key """
return self._split_comp_info_dicts["%s_%s" % (catalog_name, split_ver)][split_key] | [
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fermiPy/fermipy | fermipy/diffuse/catalog_src_manager.py | CatalogSourceManager.make_catalog_comp_info_dict | def make_catalog_comp_info_dict(self, catalog_sources):
""" Make the information about the catalog components
Parameters
----------
catalog_sources : dict
Dictionary with catalog source defintions
Returns
-------
catalog_ret_dict : dict
... | python | def make_catalog_comp_info_dict(self, catalog_sources):
""" Make the information about the catalog components
Parameters
----------
catalog_sources : dict
Dictionary with catalog source defintions
Returns
-------
catalog_ret_dict : dict
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fermiPy/fermipy | fermipy/tsmap.py | extract_images_from_tscube | def extract_images_from_tscube(infile, outfile):
""" Extract data from table HDUs in TSCube file and convert them to FITS images
"""
inhdulist = fits.open(infile)
wcs = pywcs.WCS(inhdulist[0].header)
map_shape = inhdulist[0].data.shape
t_eng = Table.read(infile, "EBOUNDS")
t_scan = Table.re... | python | def extract_images_from_tscube(infile, outfile):
""" Extract data from table HDUs in TSCube file and convert them to FITS images
"""
inhdulist = fits.open(infile)
wcs = pywcs.WCS(inhdulist[0].header)
map_shape = inhdulist[0].data.shape
t_eng = Table.read(infile, "EBOUNDS")
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fermiPy/fermipy | fermipy/tsmap.py | truncate_array | def truncate_array(array1, array2, position):
"""Truncate array1 by finding the overlap with array2 when the
array1 center is located at the given position in array2."""
slices = []
for i in range(array1.ndim):
xmin = 0
xmax = array1.shape[i]
dxlo = array1.shape[i] // 2
... | python | def truncate_array(array1, array2, position):
"""Truncate array1 by finding the overlap with array2 when the
array1 center is located at the given position in array2."""
slices = []
for i in range(array1.ndim):
xmin = 0
xmax = array1.shape[i]
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fermiPy/fermipy | fermipy/tsmap.py | _sum_wrapper | def _sum_wrapper(fn):
"""
Wrapper to perform row-wise aggregation of list arguments and pass
them to a function. The return value of the function is summed
over the argument groups. Non-list arguments will be
automatically cast to a list.
"""
def wrapper(*args, **kwargs):
v = 0
... | python | def _sum_wrapper(fn):
"""
Wrapper to perform row-wise aggregation of list arguments and pass
them to a function. The return value of the function is summed
over the argument groups. Non-list arguments will be
automatically cast to a list.
"""
def wrapper(*args, **kwargs):
v = 0
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fermiPy/fermipy | fermipy/tsmap.py | _amplitude_bounds | def _amplitude_bounds(counts, bkg, model):
"""
Compute bounds for the root of `_f_cash_root_cython`.
Parameters
----------
counts : `~numpy.ndarray`
Count map.
bkg : `~numpy.ndarray`
Background map.
model : `~numpy.ndarray`
Source template (multiplied with exposure).... | python | def _amplitude_bounds(counts, bkg, model):
"""
Compute bounds for the root of `_f_cash_root_cython`.
Parameters
----------
counts : `~numpy.ndarray`
Count map.
bkg : `~numpy.ndarray`
Background map.
model : `~numpy.ndarray`
Source template (multiplied with exposure).... | [
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fermiPy/fermipy | fermipy/tsmap.py | _root_amplitude_brentq | def _root_amplitude_brentq(counts, bkg, model, root_fn=_f_cash_root):
"""Fit amplitude by finding roots using Brent algorithm.
See Appendix A Stewart (2009).
Parameters
----------
counts : `~numpy.ndarray`
Slice of count map.
bkg : `~numpy.ndarray`
Slice of background map.
... | python | def _root_amplitude_brentq(counts, bkg, model, root_fn=_f_cash_root):
"""Fit amplitude by finding roots using Brent algorithm.
See Appendix A Stewart (2009).
Parameters
----------
counts : `~numpy.ndarray`
Slice of count map.
bkg : `~numpy.ndarray`
Slice of background map.
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fermiPy/fermipy | fermipy/tsmap.py | poisson_log_like | def poisson_log_like(counts, model):
"""Compute the Poisson log-likelihood function for the given
counts and model arrays."""
loglike = np.array(model)
m = counts > 0
loglike[m] -= counts[m] * np.log(model[m])
return loglike | python | def poisson_log_like(counts, model):
"""Compute the Poisson log-likelihood function for the given
counts and model arrays."""
loglike = np.array(model)
m = counts > 0
loglike[m] -= counts[m] * np.log(model[m])
return loglike | [
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fermiPy/fermipy | fermipy/tsmap.py | f_cash | def f_cash(x, counts, bkg, model):
"""
Wrapper for cash statistics, that defines the model function.
Parameters
----------
x : float
Model amplitude.
counts : `~numpy.ndarray`
Count map slice, where model is defined.
bkg : `~numpy.ndarray`
Background map slice, where... | python | def f_cash(x, counts, bkg, model):
"""
Wrapper for cash statistics, that defines the model function.
Parameters
----------
x : float
Model amplitude.
counts : `~numpy.ndarray`
Count map slice, where model is defined.
bkg : `~numpy.ndarray`
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fermiPy/fermipy | fermipy/tsmap.py | _ts_value_newton | def _ts_value_newton(position, counts, bkg, model, C_0_map):
"""
Compute TS value at a given pixel position using the newton
method.
Parameters
----------
position : tuple
Pixel position.
counts : `~numpy.ndarray`
Count map.
bkg : `~numpy.ndarray`
Background ma... | python | def _ts_value_newton(position, counts, bkg, model, C_0_map):
"""
Compute TS value at a given pixel position using the newton
method.
Parameters
----------
position : tuple
Pixel position.
counts : `~numpy.ndarray`
Count map.
bkg : `~numpy.ndarray`
Background ma... | [
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fermiPy/fermipy | fermipy/tsmap.py | TSMapGenerator.tsmap | def tsmap(self, prefix='', **kwargs):
"""Generate a spatial TS map for a source component with
properties defined by the `model` argument. The TS map will
have the same geometry as the ROI. The output of this method
is a dictionary containing `~fermipy.skymap.Map` objects with
... | python | def tsmap(self, prefix='', **kwargs):
"""Generate a spatial TS map for a source component with
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fermiPy/fermipy | fermipy/tsmap.py | TSCubeGenerator.tscube | def tscube(self, prefix='', **kwargs):
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fermiPy/fermipy | fermipy/irfs.py | compute_ps_counts | def compute_ps_counts(ebins, exp, psf, bkg, fn, egy_dim=0, spatial_model='PointSource',
spatial_size=1E-3):
"""Calculate the observed signal and background counts given models
for the exposure, background intensity, PSF, and source flux.
Parameters
----------
ebins : `~numpy.n... | python | def compute_ps_counts(ebins, exp, psf, bkg, fn, egy_dim=0, spatial_model='PointSource',
spatial_size=1E-3):
"""Calculate the observed signal and background counts given models
for the exposure, background intensity, PSF, and source flux.
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ebins : `~numpy.n... | [
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fermiPy/fermipy | fermipy/irfs.py | create_psf | def create_psf(event_class, event_type, dtheta, egy, cth):
"""Create an array of PSF response values versus energy and
inclination angle.
Parameters
----------
egy : `~numpy.ndarray`
Energy in MeV.
cth : `~numpy.ndarray`
Cosine of the incidence angle.
"""
irf = create_... | python | def create_psf(event_class, event_type, dtheta, egy, cth):
"""Create an array of PSF response values versus energy and
inclination angle.
Parameters
----------
egy : `~numpy.ndarray`
Energy in MeV.
cth : `~numpy.ndarray`
Cosine of the incidence angle.
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fermiPy/fermipy | fermipy/irfs.py | create_edisp | def create_edisp(event_class, event_type, erec, egy, cth):
"""Create an array of energy response values versus energy and
inclination angle.
Parameters
----------
egy : `~numpy.ndarray`
Energy in MeV.
cth : `~numpy.ndarray`
Cosine of the incidence angle.
"""
irf = crea... | python | def create_edisp(event_class, event_type, erec, egy, cth):
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Parameters
----------
egy : `~numpy.ndarray`
Energy in MeV.
cth : `~numpy.ndarray`
Cosine of the incidence angle.
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Cosine of the incidence angle. | [
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fermiPy/fermipy | fermipy/irfs.py | create_aeff | def create_aeff(event_class, event_type, egy, cth):
"""Create an array of effective areas versus energy and incidence
angle. Binning in energy and incidence angle is controlled with
the egy and cth input parameters.
Parameters
----------
event_class : str
Event class string (e.g. P8R2_... | python | def create_aeff(event_class, event_type, egy, cth):
"""Create an array of effective areas versus energy and incidence
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Parameters
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Event class string (e.g. P8R2_... | [
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fermiPy/fermipy | fermipy/irfs.py | calc_exp | def calc_exp(skydir, ltc, event_class, event_types,
egy, cth_bins, npts=None):
"""Calculate the exposure on a 2D grid of energy and incidence angle.
Parameters
----------
npts : int
Number of points by which to sample the response in each
incidence angle bin. If None t... | python | def calc_exp(skydir, ltc, event_class, event_types,
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npts : int
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fermiPy/fermipy | fermipy/irfs.py | create_avg_rsp | def create_avg_rsp(rsp_fn, skydir, ltc, event_class, event_types, x,
egy, cth_bins, npts=None):
"""Calculate the weighted response function.
"""
if npts is None:
npts = int(np.ceil(np.max(cth_bins[1:] - cth_bins[:-1]) / 0.05))
wrsp = np.zeros((len(x), len(egy), len(cth_bins) ... | python | def create_avg_rsp(rsp_fn, skydir, ltc, event_class, event_types, x,
egy, cth_bins, npts=None):
"""Calculate the weighted response function.
"""
if npts is None:
npts = int(np.ceil(np.max(cth_bins[1:] - cth_bins[:-1]) / 0.05))
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fermiPy/fermipy | fermipy/irfs.py | create_avg_psf | def create_avg_psf(skydir, ltc, event_class, event_types, dtheta,
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Parameters
----------
egy : `~numpy.ndarray`
Energies in MeV.
cth_bins : `~numpy.ndarray`
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Energies in MeV.
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fermiPy/fermipy | fermipy/irfs.py | create_avg_edisp | def create_avg_edisp(skydir, ltc, event_class, event_types, erec,
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Parameters
----------
egy : `~numpy.ndarray`
True energies in MeV.
cth_bins : `~numpy.ndarray`
... | python | def create_avg_edisp(skydir, ltc, event_class, event_types, erec,
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True energies in MeV.
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fermiPy/fermipy | fermipy/irfs.py | create_wtd_psf | def create_wtd_psf(skydir, ltc, event_class, event_types, dtheta,
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fermiPy/fermipy | fermipy/irfs.py | calc_drm | def calc_drm(skydir, ltc, event_class, event_types,
egy_bins, cth_bins, nbin=64):
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npts = int(np.ceil(128. / bins_per_dec(egy_bins)))
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etrue_bins = 10**np.linspace(1.0, 6.5, nbin * ... | python | def calc_drm(skydir, ltc, event_class, event_types,
egy_bins, cth_bins, nbin=64):
"""Calculate the detector response matrix."""
npts = int(np.ceil(128. / bins_per_dec(egy_bins)))
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fermiPy/fermipy | fermipy/irfs.py | calc_counts | def calc_counts(skydir, ltc, event_class, event_types,
egy_bins, cth_bins, fn, npts=1):
"""Calculate the expected counts vs. true energy and incidence angle
for a source with spectral parameterization ``fn``.
Parameters
----------
skydir : `~astropy.coordinate.SkyCoord`
ltc : `... | python | def calc_counts(skydir, ltc, event_class, event_types,
egy_bins, cth_bins, fn, npts=1):
"""Calculate the expected counts vs. true energy and incidence angle
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fermiPy/fermipy | fermipy/irfs.py | calc_counts_edisp | def calc_counts_edisp(skydir, ltc, event_class, event_types,
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"""Calculate the expected counts vs. observed energy and true
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egy_bins, cth_bins, fn, nbin=16, npts=1):
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fermiPy/fermipy | fermipy/irfs.py | calc_wtd_exp | def calc_wtd_exp(skydir, ltc, event_class, event_types,
egy_bins, cth_bins, fn, nbin=16):
"""Calculate the effective exposure.
Parameters
----------
skydir : `~astropy.coordinates.SkyCoord`
ltc : `~fermipy.irfs.LTCube`
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fermiPy/fermipy | fermipy/irfs.py | PSFModel.eval | def eval(self, ebin, dtheta, scale_fn=None):
"""Evaluate the PSF at the given energy bin index.
Parameters
----------
ebin : int
Index of energy bin.
dtheta : array_like
Array of angular separations in degrees.
scale_fn : callable
... | python | def eval(self, ebin, dtheta, scale_fn=None):
"""Evaluate the PSF at the given energy bin index.
Parameters
----------
ebin : int
Index of energy bin.
dtheta : array_like
Array of angular separations in degrees.
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fermiPy/fermipy | fermipy/irfs.py | PSFModel.interp | def interp(self, energies, dtheta, scale_fn=None):
"""Evaluate the PSF model at an array of energies and angular
separations.
Parameters
----------
energies : array_like
Array of energies in MeV.
dtheta : array_like
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"""Evaluate the PSF model at an array of energies and angular
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fermiPy/fermipy | fermipy/irfs.py | PSFModel.interp_bin | def interp_bin(self, egy_bins, dtheta, scale_fn=None):
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Parameters
----------
egy_bins : array_like
Energy bin edges in MeV.
dtheta : array_like
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"""Evaluate the bin-averaged PSF model over the energy bins ``egy_bins``.
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egy_bins : array_like
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fermiPy/fermipy | fermipy/irfs.py | PSFModel.containment_angle | def containment_angle(self, energies=None, fraction=0.68, scale_fn=None):
"""Evaluate the PSF containment angle at a sequence of energies."""
if energies is None:
energies = self.energies
vals = self.interp(energies[np.newaxis, :], self.dtheta[:, np.newaxis],
... | python | def containment_angle(self, energies=None, fraction=0.68, scale_fn=None):
"""Evaluate the PSF containment angle at a sequence of energies."""
if energies is None:
energies = self.energies
vals = self.interp(energies[np.newaxis, :], self.dtheta[:, np.newaxis],
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fermiPy/fermipy | fermipy/irfs.py | PSFModel.containment_angle_bin | def containment_angle_bin(self, egy_bins, fraction=0.68, scale_fn=None):
"""Evaluate the PSF containment angle averaged over energy bins."""
vals = self.interp_bin(egy_bins, self.dtheta, scale_fn=scale_fn)
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"""Evaluate the PSF containment angle averaged over energy bins."""
vals = self.interp_bin(egy_bins, self.dtheta, scale_fn=scale_fn)
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fermiPy/fermipy | fermipy/irfs.py | PSFModel.create | def create(cls, skydir, ltc, event_class, event_types, energies, cth_bins=None,
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fermiPy/fermipy | fermipy/jobs/sys_interface.py | remove_file | def remove_file(filepath, dry_run=False):
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fermiPy/fermipy | fermipy/jobs/sys_interface.py | clean_job | def clean_job(logfile, outfiles, dry_run=False):
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remove_file(logfile, dry_run)
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remove_file(logfile, dry_run)
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fermiPy/fermipy | fermipy/jobs/sys_interface.py | check_log | def check_log(logfile, exited='Exited with exit code',
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Often logfile doesn't exist because the job hasn't begun
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fermiPy/fermipy | fermipy/jobs/sys_interface.py | SysInterface.check_job | def check_job(cls, job_details):
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Link object that sendes the job
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Key used to identify this particular job
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Parameters
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link : `Link`
Link object that sendes the job
key : str
Key used to identify this particular job
job_archive : `JobArchive`
Archive used to keep track of jobs
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fermiPy/fermipy | fermipy/jobs/sys_interface.py | SysInterface.submit_jobs | def submit_jobs(self, link, job_dict=None, job_archive=None, stream=sys.stdout):
"""Run the `Link` with all of the items job_dict as input.
If job_dict is None, the job_dict will be take from link.jobs
Returns a `JobStatus` enum
"""
failed = False
if job_dict is None:
... | python | def submit_jobs(self, link, job_dict=None, job_archive=None, stream=sys.stdout):
"""Run the `Link` with all of the items job_dict as input.
If job_dict is None, the job_dict will be take from link.jobs
Returns a `JobStatus` enum
"""
failed = False
if job_dict is None:
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fermiPy/fermipy | fermipy/jobs/sys_interface.py | SysInterface.clean_jobs | def clean_jobs(self, link, job_dict=None, clean_all=False):
""" Clean up all the jobs associated with this link.
Returns a `JobStatus` enum
"""
failed = False
if job_dict is None:
job_dict = link.jobs
for job_details in job_dict.values():
# clean... | python | def clean_jobs(self, link, job_dict=None, clean_all=False):
""" Clean up all the jobs associated with this link.
Returns a `JobStatus` enum
"""
failed = False
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job_dict = link.jobs
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fermiPy/fermipy | fermipy/model_utils.py | get_spatial_type | def get_spatial_type(spatial_model):
"""Translate a spatial model string to a spatial type."""
if spatial_model in ['SkyDirFunction', 'PointSource',
'Gaussian']:
return 'SkyDirFunction'
elif spatial_model in ['SpatialMap']:
return 'SpatialMap'
elif spatial_model... | python | def get_spatial_type(spatial_model):
"""Translate a spatial model string to a spatial type."""
if spatial_model in ['SkyDirFunction', 'PointSource',
'Gaussian']:
return 'SkyDirFunction'
elif spatial_model in ['SpatialMap']:
return 'SpatialMap'
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fermiPy/fermipy | fermipy/model_utils.py | create_pars_from_dict | def create_pars_from_dict(name, pars_dict, rescale=True, update_bounds=False):
"""Create a dictionary for the parameters of a function.
Parameters
----------
name : str
Name of the function.
pars_dict : dict
Existing parameter dict that will be merged with the
default d... | python | def create_pars_from_dict(name, pars_dict, rescale=True, update_bounds=False):
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Parameters
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Name of the function.
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Update a parameter dictionary. This function will automatically
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fermiPy/fermipy | fermipy/model_utils.py | cast_pars_dict | def cast_pars_dict(pars_dict):
"""Cast the bool and float elements of a parameters dict to
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for pname, pdict in pars_dict.items():
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"""Cast the bool and float elements of a parameters dict to
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fermiPy/fermipy | fermipy/scripts/gather_srcmaps.py | do_gather | def do_gather(flist):
""" Gather all the HDUs from a list of files"""
hlist = []
nskip = 3
for fname in flist:
fin = fits.open(fname)
if len(hlist) == 0:
if fin[1].name == 'SKYMAP':
nskip = 4
start = 0
else:
start = nskip
... | python | def do_gather(flist):
""" Gather all the HDUs from a list of files"""
hlist = []
nskip = 3
for fname in flist:
fin = fits.open(fname)
if len(hlist) == 0:
if fin[1].name == 'SKYMAP':
nskip = 4
start = 0
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start = nskip
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fermiPy/fermipy | fermipy/jobs/job_archive.py | main_browse | def main_browse():
"""Entry point for command line use for browsing a JobArchive """
parser = argparse.ArgumentParser(usage="job_archive.py [options]",
description="Browse a job archive")
parser.add_argument('--jobs', action='store', dest='job_archive_table',
... | python | def main_browse():
"""Entry point for command line use for browsing a JobArchive """
parser = argparse.ArgumentParser(usage="job_archive.py [options]",
description="Browse a job archive")
parser.add_argument('--jobs', action='store', dest='job_archive_table',
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobStatusVector.n_waiting | def n_waiting(self):
"""Return the number of jobs in various waiting states"""
return self._counters[JobStatus.no_job] +\
self._counters[JobStatus.unknown] +\
self._counters[JobStatus.not_ready] +\
self._counters[JobStatus.ready] | python | def n_waiting(self):
"""Return the number of jobs in various waiting states"""
return self._counters[JobStatus.no_job] +\
self._counters[JobStatus.unknown] +\
self._counters[JobStatus.not_ready] +\
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobStatusVector.n_failed | def n_failed(self):
"""Return the number of failed jobs"""
return self._counters[JobStatus.failed] + self._counters[JobStatus.partial_failed] | python | def n_failed(self):
"""Return the number of failed jobs"""
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobStatusVector.get_status | def get_status(self):
"""Return an overall status based
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"""
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return JobStatus.no_job
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# If more... | python | def get_status(self):
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobDetails.make_tables | def make_tables(job_dict):
"""Build and return an `astropy.table.Table' to store `JobDetails`"""
col_dbkey = Column(name='dbkey', dtype=int)
col_jobname = Column(name='jobname', dtype='S64')
col_jobkey = Column(name='jobkey', dtype='S64')
col_appname = Column(name='appname', dtyp... | python | def make_tables(job_dict):
"""Build and return an `astropy.table.Table' to store `JobDetails`"""
col_dbkey = Column(name='dbkey', dtype=int)
col_jobname = Column(name='jobname', dtype='S64')
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobDetails.get_file_ids | def get_file_ids(self, file_archive, creator=None, status=FileStatus.no_file):
"""Fill the file id arrays from the file lists
Parameters
----------
file_archive : `FileArchive`
Used to look up file ids
creator : int
A unique key for the job that created... | python | def get_file_ids(self, file_archive, creator=None, status=FileStatus.no_file):
"""Fill the file id arrays from the file lists
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----------
file_archive : `FileArchive`
Used to look up file ids
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobDetails.get_file_paths | def get_file_paths(self, file_archive, file_id_array):
"""Get the full paths of the files used by this object from the the id arrays
Parameters
----------
file_archive : `FileArchive`
Used to look up file ids
file_id_array : `numpy.array`
Array that rema... | python | def get_file_paths(self, file_archive, file_id_array):
"""Get the full paths of the files used by this object from the the id arrays
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----------
file_archive : `FileArchive`
Used to look up file ids
file_id_array : `numpy.array`
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobDetails._fill_array_from_list | def _fill_array_from_list(the_list, the_array):
"""Fill an `array` from a `list`"""
for i, val in enumerate(the_list):
the_array[i] = val
return the_array | python | def _fill_array_from_list(the_list, the_array):
"""Fill an `array` from a `list`"""
for i, val in enumerate(the_list):
the_array[i] = val
return the_array | [
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobDetails.make_dict | def make_dict(cls, table):
"""Build a dictionary map int to `JobDetails` from an `astropy.table.Table`"""
ret_dict = {}
for row in table:
job_details = cls.create_from_row(row)
ret_dict[job_details.dbkey] = job_details
return ret_dict | python | def make_dict(cls, table):
"""Build a dictionary map int to `JobDetails` from an `astropy.table.Table`"""
ret_dict = {}
for row in table:
job_details = cls.create_from_row(row)
ret_dict[job_details.dbkey] = job_details
return ret_dict | [
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobDetails.check_status_logfile | def check_status_logfile(self, checker_func):
"""Check on the status of this particular job using the logfile"""
self.status = checker_func(self.logfile)
return self.status | python | def check_status_logfile(self, checker_func):
"""Check on the status of this particular job using the logfile"""
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobArchive._read_table_file | def _read_table_file(self, table_file):
"""Read an `astropy.table.Table` from table_file to set up the `JobArchive`"""
self._table_file = table_file
if os.path.exists(self._table_file):
self._table = Table.read(self._table_file, hdu='JOB_ARCHIVE')
self._table_ids = Table.... | python | def _read_table_file(self, table_file):
"""Read an `astropy.table.Table` from table_file to set up the `JobArchive`"""
self._table_file = table_file
if os.path.exists(self._table_file):
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobArchive.get_details | def get_details(self, jobname, jobkey):
"""Get the `JobDetails` associated to a particular job instance"""
fullkey = JobDetails.make_fullkey(jobname, jobkey)
return self._cache[fullkey] | python | def get_details(self, jobname, jobkey):
"""Get the `JobDetails` associated to a particular job instance"""
fullkey = JobDetails.make_fullkey(jobname, jobkey)
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobArchive.register_job | def register_job(self, job_details):
"""Register a job in this `JobArchive` """
# check to see if the job already exists
try:
job_details_old = self.get_details(job_details.jobname,
job_details.jobkey)
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"""Register a job in this `JobArchive` """
# check to see if the job already exists
try:
job_details_old = self.get_details(job_details.jobname,
job_details.jobkey)
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobArchive.register_jobs | def register_jobs(self, job_dict):
"""Register a bunch of jobs in this archive"""
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sys.stdout.write("Registering %i total jobs: " % njobs)
for i, job_details in enumerate(job_dict.values()):
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"""Register a bunch of jobs in this archive"""
njobs = len(job_dict)
sys.stdout.write("Registering %i total jobs: " % njobs)
for i, job_details in enumerate(job_dict.values()):
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobArchive.register_job_from_link | def register_job_from_link(self, link, key, **kwargs):
"""Register a job in the `JobArchive` from a `Link` object """
job_config = kwargs.get('job_config', None)
if job_config is None:
job_config = link.args
status = kwargs.get('status', JobStatus.unknown)
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"""Register a job in the `JobArchive` from a `Link` object """
job_config = kwargs.get('job_config', None)
if job_config is None:
job_config = link.args
status = kwargs.get('status', JobStatus.unknown)
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobArchive.update_job | def update_job(self, job_details):
"""Update a job in the `JobArchive` """
other = self.get_details(job_details.jobname,
job_details.jobkey)
other.timestamp = job_details.timestamp
other.status = job_details.status
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"""Update a job in the `JobArchive` """
other = self.get_details(job_details.jobname,
job_details.jobkey)
other.timestamp = job_details.timestamp
other.status = job_details.status
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobArchive.remove_jobs | def remove_jobs(self, mask):
"""Mark all jobs that match a mask as 'removed' """
jobnames = self.table[mask]['jobname']
jobkey = self.table[mask]['jobkey']
self.table[mask]['status'] = JobStatus.removed
for jobname, jobkey in zip(jobnames, jobkey):
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"""Mark all jobs that match a mask as 'removed' """
jobnames = self.table[mask]['jobname']
jobkey = self.table[mask]['jobkey']
self.table[mask]['status'] = JobStatus.removed
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobArchive.build_temp_job_archive | def build_temp_job_archive(cls):
"""Build and return a `JobArchive` using defualt locations of
persistent files. """
try:
os.unlink('job_archive_temp.fits')
os.unlink('file_archive_temp.fits')
except OSError:
pass
cls._archive = cls(job_archiv... | python | def build_temp_job_archive(cls):
"""Build and return a `JobArchive` using defualt locations of
persistent files. """
try:
os.unlink('job_archive_temp.fits')
os.unlink('file_archive_temp.fits')
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobArchive.update_job_status | def update_job_status(self, checker_func):
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njobs = len(self.cache.keys())
status_vect = np.zeros((8), int)
sys.stdout.write("Updating status of %i jobs: " % njobs)
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"""Update the status of all the jobs in the archive"""
njobs = len(self.cache.keys())
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fermiPy/fermipy | fermipy/jobs/job_archive.py | JobArchive.build_archive | def build_archive(cls, **kwargs):
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if cls._archive is None:
cls._archive = cls(**kwargs)
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if cls._archive is None:
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fermiPy/fermipy | fermipy/timing.py | Timer.elapsed_time | def elapsed_time(self):
"""Get the elapsed time."""
# Timer is running
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fermiPy/fermipy | fermipy/diffuse/source_factory.py | make_spatialmap_source | def make_spatialmap_source(name, Spatial_Filename, spectrum):
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"""
data = dict(Spatial_Filename=Spatial_Filename,
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fermiPy/fermipy | fermipy/diffuse/source_factory.py | make_mapcube_source | def make_mapcube_source(name, Spatial_Filename, spectrum):
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data = dict(Spatial_Filename=Spatial_Filename)
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"""Construct and return a `fermipy.roi_model.MapCubeSource` object
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data = dict(Spatial_Filename=Spatial_Filename)
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fermiPy/fermipy | fermipy/diffuse/source_factory.py | make_isotropic_source | def make_isotropic_source(name, Spectrum_Filename, spectrum):
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data = dict(Spectrum_Filename=Spectrum_Filename)
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return roi_model.IsoSource(name, data) | python | def make_isotropic_source(name, Spectrum_Filename, spectrum):
"""Construct and return a `fermipy.roi_model.IsoSource` object
"""
data = dict(Spectrum_Filename=Spectrum_Filename)
if spectrum is not None:
data.update(spectrum)
return roi_model.IsoSource(name, data) | [
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fermiPy/fermipy | fermipy/diffuse/source_factory.py | make_composite_source | def make_composite_source(name, spectrum):
"""Construct and return a `fermipy.roi_model.CompositeSource` object
"""
data = dict(SpatialType='CompositeSource',
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"""Construct and return a `fermipy.roi_model.CompositeSource` object
"""
data = dict(SpatialType='CompositeSource',
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fermiPy/fermipy | fermipy/diffuse/source_factory.py | make_catalog_sources | def make_catalog_sources(catalog_roi_model, source_names):
"""Construct and return dictionary of sources that are a subset of sources
in catalog_roi_model.
Parameters
----------
catalog_roi_model : dict or `fermipy.roi_model.ROIModel`
Input set of sources
source_names : list
N... | python | def make_catalog_sources(catalog_roi_model, source_names):
"""Construct and return dictionary of sources that are a subset of sources
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Parameters
----------
catalog_roi_model : dict or `fermipy.roi_model.ROIModel`
Input set of sources
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fermiPy/fermipy | fermipy/diffuse/source_factory.py | make_sources | def make_sources(comp_key, comp_dict):
"""Make dictionary mapping component keys to a source
or set of sources
Parameters
----------
comp_key : str
Key used to access sources
comp_dict : dict
Information used to build sources
return `OrderedDict` maping comp_key to `fermi... | python | def make_sources(comp_key, comp_dict):
"""Make dictionary mapping component keys to a source
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Parameters
----------
comp_key : str
Key used to access sources
comp_dict : dict
Information used to build sources
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fermiPy/fermipy | fermipy/diffuse/source_factory.py | SourceFactory.add_sources | def add_sources(self, source_info_dict):
"""Add all of the sources in source_info_dict to this factory
"""
self._source_info_dict.update(source_info_dict)
for key, value in source_info_dict.items():
self._sources.update(make_sources(key, value)) | python | def add_sources(self, source_info_dict):
"""Add all of the sources in source_info_dict to this factory
"""
self._source_info_dict.update(source_info_dict)
for key, value in source_info_dict.items():
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fermiPy/fermipy | fermipy/diffuse/source_factory.py | SourceFactory.build_catalog | def build_catalog(**kwargs):
"""Build a `fermipy.catalog.Catalog` object
Parameters
----------
catalog_type : str
Specifies catalog type, options include 2FHL | 3FGL | 4FGLP
catalog_file : str
FITS file with catalog tables
catalog_extdir : str
... | python | def build_catalog(**kwargs):
"""Build a `fermipy.catalog.Catalog` object
Parameters
----------
catalog_type : str
Specifies catalog type, options include 2FHL | 3FGL | 4FGLP
catalog_file : str
FITS file with catalog tables
catalog_extdir : str
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fermiPy/fermipy | fermipy/diffuse/source_factory.py | SourceFactory.make_fermipy_roi_model_from_catalogs | def make_fermipy_roi_model_from_catalogs(cataloglist):
"""Build and return a `fermipy.roi_model.ROIModel object from
a list of fermipy.catalog.Catalog` objects
"""
data = dict(catalogs=cataloglist,
src_roiwidth=360.)
return roi_model.ROIModel(data, skydir=SkyC... | python | def make_fermipy_roi_model_from_catalogs(cataloglist):
"""Build and return a `fermipy.roi_model.ROIModel object from
a list of fermipy.catalog.Catalog` objects
"""
data = dict(catalogs=cataloglist,
src_roiwidth=360.)
return roi_model.ROIModel(data, skydir=SkyC... | [
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fermiPy/fermipy | fermipy/diffuse/source_factory.py | SourceFactory.make_roi | def make_roi(cls, sources=None):
"""Build and return a `fermipy.roi_model.ROIModel` object from
a dict with information about the sources
"""
if sources is None:
sources = {}
src_fact = cls()
src_fact.add_sources(sources)
ret_model = roi_model.ROIModel... | python | def make_roi(cls, sources=None):
"""Build and return a `fermipy.roi_model.ROIModel` object from
a dict with information about the sources
"""
if sources is None:
sources = {}
src_fact = cls()
src_fact.add_sources(sources)
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fermiPy/fermipy | fermipy/diffuse/source_factory.py | SourceFactory.copy_selected_sources | def copy_selected_sources(cls, roi, source_names):
"""Build and return a `fermipy.roi_model.ROIModel` object
by copying selected sources from another such object
"""
roi_new = cls.make_roi()
for source_name in source_names:
try:
src_cp = roi.copy_sourc... | python | def copy_selected_sources(cls, roi, source_names):
"""Build and return a `fermipy.roi_model.ROIModel` object
by copying selected sources from another such object
"""
roi_new = cls.make_roi()
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fermiPy/fermipy | fermipy/diffuse/timefilter.py | MktimeFilterDict.build_from_yamlfile | def build_from_yamlfile(yamlfile):
""" Build a list of components from a yaml file
"""
d = yaml.load(open(yamlfile))
return MktimeFilterDict(d['aliases'], d['selections']) | python | def build_from_yamlfile(yamlfile):
""" Build a list of components from a yaml file
"""
d = yaml.load(open(yamlfile))
return MktimeFilterDict(d['aliases'], d['selections']) | [
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fermiPy/fermipy | fermipy/scripts/dispatch.py | collect_jobs | def collect_jobs(dirs, runscript, overwrite=False, max_job_age=90):
"""Construct a list of job dictionaries."""
jobs = []
for dirname in sorted(dirs):
o = dict(cfgfile=os.path.join(dirname, 'config.yaml'),
logfile=os.path.join(
dirname, os.path.splitext(runsc... | python | def collect_jobs(dirs, runscript, overwrite=False, max_job_age=90):
"""Construct a list of job dictionaries."""
jobs = []
for dirname in sorted(dirs):
o = dict(cfgfile=os.path.join(dirname, 'config.yaml'),
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fermiPy/fermipy | fermipy/srcmap_utils.py | delete_source_map | def delete_source_map(srcmap_file, names, logger=None):
"""Delete a map from a binned analysis source map file if it exists.
Parameters
----------
srcmap_file : str
Path to the source map file.
names : list
List of HDU keys of source maps to be deleted.
"""
with fits.open(sr... | python | def delete_source_map(srcmap_file, names, logger=None):
"""Delete a map from a binned analysis source map file if it exists.
Parameters
----------
srcmap_file : str
Path to the source map file.
names : list
List of HDU keys of source maps to be deleted.
"""
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fermiPy/fermipy | fermipy/srcmap_utils.py | MapInterpolator.get_offsets | def get_offsets(self, pix):
"""Get offset of the first pixel in each dimension in the
global coordinate system.
Parameters
----------
pix : `~numpy.ndarray`
Pixel coordinates in global coordinate system.
"""
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pix : `~numpy.ndarray`
Pixel coordinates in global coordinate system.
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fermiPy/fermipy | fermipy/srcmap_utils.py | MapInterpolator.shift_to_coords | def shift_to_coords(self, pix, fill_value=np.nan):
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pix_offset = self.get_offsets(pix)
dpix = np.zeros(len(self.shape) - 1)
for i in range(len(self.shape) - 1):
x = self.rebin * (pix[i] - pix_off... | python | def shift_to_coords(self, pix, fill_value=np.nan):
"""Create a new map that is shifted to the pixel coordinates
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pix_offset = self.get_offsets(pix)
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fermiPy/fermipy | fermipy/srcmap_utils.py | SourceMapCache.create_map | def create_map(self, pix):
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pix : `~numpy.ndarray`
Reference pixel of new map.
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Reference pixel of new map.
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"""Convert git release tag into a form that is PEP440 compliant."""
if vcs is None:
return None
tags = vcs.split('-')
# Bare version number
if len(tags) == 1:
return tags[0]
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"""Convert git release tag into a form that is PEP440 compliant."""
if vcs is None:
return None
tags = vcs.split('-')
# Bare version number
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fermiPy/fermipy | fermipy/version.py | read_release_version | def read_release_version():
"""Read the release version from ``_version.py``."""
import re
dirname = os.path.abspath(os.path.dirname(__file__))
try:
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for line in f.readlines():
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"""Read the release version from ``_version.py``."""
import re
dirname = os.path.abspath(os.path.dirname(__file__))
try:
f = open(os.path.join(dirname, "_version.py"), "rt")
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fermiPy/fermipy | fermipy/version.py | write_release_version | def write_release_version(version):
"""Write the release version to ``_version.py``."""
dirname = os.path.abspath(os.path.dirname(__file__))
f = open(os.path.join(dirname, "_version.py"), "wt")
f.write("__version__ = '%s'\n" % version)
f.close() | python | def write_release_version(version):
"""Write the release version to ``_version.py``."""
dirname = os.path.abspath(os.path.dirname(__file__))
f = open(os.path.join(dirname, "_version.py"), "wt")
f.write("__version__ = '%s'\n" % version)
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fermiPy/fermipy | fermipy/diffuse/gt_split_and_mktime.py | make_full_path | def make_full_path(basedir, outkey, origname):
"""Make a full file path by combining tokens
Parameters
-----------
basedir : str
The top level output area
outkey : str
The key for the particular instance of the analysis
origname : str
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"""Make a full file path by combining tokens
Parameters
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basedir : str
The top level output area
outkey : str
The key for the particular instance of the analysis
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fermiPy/fermipy | fermipy/utils.py | init_matplotlib_backend | def init_matplotlib_backend(backend=None):
"""This function initializes the matplotlib backend. When no
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Parameters
----------
backend : str
matplotlib backend name.
"""
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"""This function initializes the matplotlib backend. When no
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backend : str
matplotlib backend name.
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fermiPy/fermipy | fermipy/utils.py | load_data | def load_data(infile, workdir=None):
"""Load python data structure from either a YAML or numpy file. """
infile = resolve_path(infile, workdir=workdir)
infile, ext = os.path.splitext(infile)
if os.path.isfile(infile + '.npy'):
infile += '.npy'
elif os.path.isfile(infile + '.yaml'):
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"""Load python data structure from either a YAML or numpy file. """
infile = resolve_path(infile, workdir=workdir)
infile, ext = os.path.splitext(infile)
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fermiPy/fermipy | fermipy/utils.py | resolve_file_path_list | def resolve_file_path_list(pathlist, workdir, prefix='',
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"""Resolve the path of each file name in the file ``pathlist`` and
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"""
files = []
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files = [line.strip() for line in f]
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"""Resolve the path of each file name in the file ``pathlist`` and
write the updated paths to a new file.
"""
files = []
with open(pathlist, 'r') as f:
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fermiPy/fermipy | fermipy/utils.py | collect_dirs | def collect_dirs(path, max_depth=1, followlinks=True):
"""Recursively find directories under the given path."""
if not os.path.isdir(path):
return []
o = [path]
if max_depth == 0:
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subdir = os.path.join(path, subdir)
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"""Recursively find directories under the given path."""
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if max_depth == 0:
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fermiPy/fermipy | fermipy/utils.py | match_regex_list | def match_regex_list(patterns, string):
"""Perform a regex match of a string against a list of patterns.
Returns true if the string matches at least one pattern in the
list."""
for p in patterns:
if re.findall(p, string):
return True
return False | python | def match_regex_list(patterns, string):
"""Perform a regex match of a string against a list of patterns.
Returns true if the string matches at least one pattern in the
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for p in patterns:
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fermiPy/fermipy | fermipy/utils.py | find_rows_by_string | def find_rows_by_string(tab, names, colnames=['assoc']):
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strings in ``names``. This method ignores whitespace and case
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Parameters
----------
tab : `astropy.table.Table`
Table that will be searched.... | python | def find_rows_by_string(tab, names, colnames=['assoc']):
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fermiPy/fermipy | fermipy/utils.py | separation_cos_angle | def separation_cos_angle(lon0, lat0, lon1, lat1):
"""Evaluate the cosine of the angular separation between two
direction vectors."""
return (np.sin(lat1) * np.sin(lat0) + np.cos(lat1) * np.cos(lat0) *
np.cos(lon1 - lon0)) | python | def separation_cos_angle(lon0, lat0, lon1, lat1):
"""Evaluate the cosine of the angular separation between two
direction vectors."""
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fermiPy/fermipy | fermipy/utils.py | angle_to_cartesian | def angle_to_cartesian(lon, lat):
"""Convert spherical coordinates to cartesian unit vectors."""
theta = np.array(np.pi / 2. - lat)
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"""Convert spherical coordinates to cartesian unit vectors."""
theta = np.array(np.pi / 2. - lat)
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fermiPy/fermipy | fermipy/utils.py | cov_to_correlation | def cov_to_correlation(cov):
"""Compute the correlation matrix given the covariance matrix.
Parameters
----------
cov : `~numpy.ndarray`
N x N matrix of covariances among N parameters.
Returns
-------
corr : `~numpy.ndarray`
N x N matrix of correlations among N parameters.
... | python | def cov_to_correlation(cov):
"""Compute the correlation matrix given the covariance matrix.
Parameters
----------
cov : `~numpy.ndarray`
N x N matrix of covariances among N parameters.
Returns
-------
corr : `~numpy.ndarray`
N x N matrix of correlations among N parameters.
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fermiPy/fermipy | fermipy/utils.py | ellipse_to_cov | def ellipse_to_cov(sigma_maj, sigma_min, theta):
"""Compute the covariance matrix in two variables x and y given
the std. deviation along the semi-major and semi-minor axes and
the rotation angle of the error ellipse.
Parameters
----------
sigma_maj : float
Std. deviation along major ax... | python | def ellipse_to_cov(sigma_maj, sigma_min, theta):
"""Compute the covariance matrix in two variables x and y given
the std. deviation along the semi-major and semi-minor axes and
the rotation angle of the error ellipse.
Parameters
----------
sigma_maj : float
Std. deviation along major ax... | [
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"+... | Compute the covariance matrix in two variables x and y given
the std. deviation along the semi-major and semi-minor axes and
the rotation angle of the error ellipse.
Parameters
----------
sigma_maj : float
Std. deviation along major axis of error ellipse.
sigma_min : float
Std.... | [
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"erro... | 9df5e7e3728307fd58c5bba36fd86783c39fbad4 | https://github.com/fermiPy/fermipy/blob/9df5e7e3728307fd58c5bba36fd86783c39fbad4/fermipy/utils.py#L516-L537 | train |
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