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fermiPy/fermipy | fermipy/wcs_utils.py | offset_to_sky | def offset_to_sky(skydir, offset_lon, offset_lat,
coordsys='CEL', projection='AIT'):
"""Convert a cartesian offset (X,Y) in the given projection into
a pair of spherical coordinates."""
offset_lon = np.array(offset_lon, ndmin=1)
offset_lat = np.array(offset_lat, ndmin=1)
w = crea... | python | def offset_to_sky(skydir, offset_lon, offset_lat,
coordsys='CEL', projection='AIT'):
"""Convert a cartesian offset (X,Y) in the given projection into
a pair of spherical coordinates."""
offset_lon = np.array(offset_lon, ndmin=1)
offset_lat = np.array(offset_lat, ndmin=1)
w = crea... | [
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fermiPy/fermipy | fermipy/wcs_utils.py | sky_to_offset | def sky_to_offset(skydir, lon, lat, coordsys='CEL', projection='AIT'):
"""Convert sky coordinates to a projected offset. This function
is the inverse of offset_to_sky."""
w = create_wcs(skydir, coordsys, projection)
skycrd = np.vstack((lon, lat)).T
if len(skycrd) == 0:
return skycrd
... | python | def sky_to_offset(skydir, lon, lat, coordsys='CEL', projection='AIT'):
"""Convert sky coordinates to a projected offset. This function
is the inverse of offset_to_sky."""
w = create_wcs(skydir, coordsys, projection)
skycrd = np.vstack((lon, lat)).T
if len(skycrd) == 0:
return skycrd
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fermiPy/fermipy | fermipy/wcs_utils.py | offset_to_skydir | def offset_to_skydir(skydir, offset_lon, offset_lat,
coordsys='CEL', projection='AIT'):
"""Convert a cartesian offset (X,Y) in the given projection into
a SkyCoord."""
offset_lon = np.array(offset_lon, ndmin=1)
offset_lat = np.array(offset_lat, ndmin=1)
w = create_wcs(skydir, ... | python | def offset_to_skydir(skydir, offset_lon, offset_lat,
coordsys='CEL', projection='AIT'):
"""Convert a cartesian offset (X,Y) in the given projection into
a SkyCoord."""
offset_lon = np.array(offset_lon, ndmin=1)
offset_lat = np.array(offset_lat, ndmin=1)
w = create_wcs(skydir, ... | [
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fermiPy/fermipy | fermipy/wcs_utils.py | skydir_to_pix | def skydir_to_pix(skydir, wcs):
"""Convert skydir object to pixel coordinates.
Gracefully handles 0-d coordinate arrays.
Parameters
----------
skydir : `~astropy.coordinates.SkyCoord`
wcs : `~astropy.wcs.WCS`
Returns
-------
xp, yp : `numpy.ndarray`
The pixel coordinates
... | python | def skydir_to_pix(skydir, wcs):
"""Convert skydir object to pixel coordinates.
Gracefully handles 0-d coordinate arrays.
Parameters
----------
skydir : `~astropy.coordinates.SkyCoord`
wcs : `~astropy.wcs.WCS`
Returns
-------
xp, yp : `numpy.ndarray`
The pixel coordinates
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fermiPy/fermipy | fermipy/wcs_utils.py | pix_to_skydir | def pix_to_skydir(xpix, ypix, wcs):
"""Convert pixel coordinates to a skydir object.
Gracefully handles 0-d coordinate arrays.
Always returns a celestial coordinate.
Parameters
----------
xpix : `numpy.ndarray`
ypix : `numpy.ndarray`
wcs : `~astropy.wcs.WCS`
"""
xpix = np.ar... | python | def pix_to_skydir(xpix, ypix, wcs):
"""Convert pixel coordinates to a skydir object.
Gracefully handles 0-d coordinate arrays.
Always returns a celestial coordinate.
Parameters
----------
xpix : `numpy.ndarray`
ypix : `numpy.ndarray`
wcs : `~astropy.wcs.WCS`
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fermiPy/fermipy | fermipy/wcs_utils.py | wcs_to_axes | def wcs_to_axes(w, npix):
"""Generate a sequence of bin edge vectors corresponding to the
axes of a WCS object."""
npix = npix[::-1]
x = np.linspace(-(npix[0]) / 2., (npix[0]) / 2.,
npix[0] + 1) * np.abs(w.wcs.cdelt[0])
y = np.linspace(-(npix[1]) / 2., (npix[1]) / 2.,
... | python | def wcs_to_axes(w, npix):
"""Generate a sequence of bin edge vectors corresponding to the
axes of a WCS object."""
npix = npix[::-1]
x = np.linspace(-(npix[0]) / 2., (npix[0]) / 2.,
npix[0] + 1) * np.abs(w.wcs.cdelt[0])
y = np.linspace(-(npix[1]) / 2., (npix[1]) / 2.,
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fermiPy/fermipy | fermipy/wcs_utils.py | wcs_to_coords | def wcs_to_coords(w, shape):
"""Generate an N x D list of pixel center coordinates where N is
the number of pixels and D is the dimensionality of the map."""
if w.naxis == 2:
y, x = wcs_to_axes(w, shape)
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z, y, x = wcs_to_axes(w, shape)
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raise Exception... | python | def wcs_to_coords(w, shape):
"""Generate an N x D list of pixel center coordinates where N is
the number of pixels and D is the dimensionality of the map."""
if w.naxis == 2:
y, x = wcs_to_axes(w, shape)
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fermiPy/fermipy | fermipy/wcs_utils.py | get_cel_to_gal_angle | def get_cel_to_gal_angle(skydir):
"""Calculate the rotation angle in radians between the longitude
axes of a local projection in celestial and galactic coordinates.
Parameters
----------
skydir : `~astropy.coordinates.SkyCoord`
Direction of projection center.
Returns
-------
an... | python | def get_cel_to_gal_angle(skydir):
"""Calculate the rotation angle in radians between the longitude
axes of a local projection in celestial and galactic coordinates.
Parameters
----------
skydir : `~astropy.coordinates.SkyCoord`
Direction of projection center.
Returns
-------
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fermiPy/fermipy | fermipy/wcs_utils.py | extract_mapcube_region | def extract_mapcube_region(infile, skydir, outfile, maphdu=0):
"""Extract a region out of an all-sky mapcube file.
Parameters
----------
infile : str
Path to mapcube file.
skydir : `~astropy.coordinates.SkyCoord`
"""
h = fits.open(os.path.expandvars(infile))
npix = 200
... | python | def extract_mapcube_region(infile, skydir, outfile, maphdu=0):
"""Extract a region out of an all-sky mapcube file.
Parameters
----------
infile : str
Path to mapcube file.
skydir : `~astropy.coordinates.SkyCoord`
"""
h = fits.open(os.path.expandvars(infile))
npix = 200
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fermiPy/fermipy | fermipy/wcs_utils.py | WCSProj.distance_to_edge | def distance_to_edge(self, skydir):
"""Return the angular distance from the given direction and
the edge of the projection."""
xpix, ypix = skydir.to_pixel(self.wcs, origin=0)
deltax = np.array((xpix - self._pix_center[0]) * self._pix_size[0],
ndmin=1)
... | python | def distance_to_edge(self, skydir):
"""Return the angular distance from the given direction and
the edge of the projection."""
xpix, ypix = skydir.to_pixel(self.wcs, origin=0)
deltax = np.array((xpix - self._pix_center[0]) * self._pix_size[0],
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fermiPy/fermipy | fermipy/diffuse/utils.py | readlines | def readlines(arg):
"""Read lines from a file into a list.
Removes whitespace and lines that start with '#'
"""
fin = open(arg)
lines_in = fin.readlines()
fin.close()
lines_out = []
for line in lines_in:
line = line.strip()
if not line or line[0] == '#':
cont... | python | def readlines(arg):
"""Read lines from a file into a list.
Removes whitespace and lines that start with '#'
"""
fin = open(arg)
lines_in = fin.readlines()
fin.close()
lines_out = []
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fermiPy/fermipy | fermipy/diffuse/utils.py | create_inputlist | def create_inputlist(arglist):
"""Read lines from a file and makes a list of file names.
Removes whitespace and lines that start with '#'
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"""
lines = []
if isinstance(arglist, list):
for arg in arglist:
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lines = []
if isinstance(arglist, list):
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fermiPy/fermipy | fermipy/validate/tools.py | Validator.init | def init(self):
"""Initialize histograms."""
evclass_shape = [16, 40, 10]
evtype_shape = [16, 16, 40, 10]
evclass_psf_shape = [16, 40, 10, 100]
evtype_psf_shape = [16, 16, 40, 10, 100]
self._hists_eff = dict()
self._hists = dict(evclass_on=np.zeros(evclass_shape... | python | def init(self):
"""Initialize histograms."""
evclass_shape = [16, 40, 10]
evtype_shape = [16, 16, 40, 10]
evclass_psf_shape = [16, 40, 10, 100]
evtype_psf_shape = [16, 16, 40, 10, 100]
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self._hists = dict(evclass_on=np.zeros(evclass_shape... | [
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fermiPy/fermipy | fermipy/validate/tools.py | Validator.create_hist | def create_hist(self, evclass, evtype, xsep, energy, ctheta,
fill_sep=False, fill_evtype=False):
"""Load into a histogram."""
nevt = len(evclass)
ebin = utils.val_to_bin(self._energy_bins, energy)
scale = self._psf_scale[ebin]
vals = [energy, ctheta]
... | python | def create_hist(self, evclass, evtype, xsep, energy, ctheta,
fill_sep=False, fill_evtype=False):
"""Load into a histogram."""
nevt = len(evclass)
ebin = utils.val_to_bin(self._energy_bins, energy)
scale = self._psf_scale[ebin]
vals = [energy, ctheta]
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fermiPy/fermipy | fermipy/validate/tools.py | Validator.calc_eff | def calc_eff(self):
"""Calculate the efficiency."""
hists = self.hists
hists_out = self._hists_eff
cth_axis_idx = dict(evclass=2, evtype=3)
for k in ['evclass', 'evtype']:
if k == 'evclass':
ns0 = hists['evclass_on'][4][None, ...]
nb... | python | def calc_eff(self):
"""Calculate the efficiency."""
hists = self.hists
hists_out = self._hists_eff
cth_axis_idx = dict(evclass=2, evtype=3)
for k in ['evclass', 'evtype']:
if k == 'evclass':
ns0 = hists['evclass_on'][4][None, ...]
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fermiPy/fermipy | fermipy/validate/tools.py | Validator.calc_containment | def calc_containment(self):
"""Calculate PSF containment."""
hists = self.hists
hists_out = self._hists_eff
quantiles = [0.34, 0.68, 0.90, 0.95]
cth_axis_idx = dict(evclass=2, evtype=3)
for k in ['evclass']: # ,'evtype']:
print(k)
non = hists['... | python | def calc_containment(self):
"""Calculate PSF containment."""
hists = self.hists
hists_out = self._hists_eff
quantiles = [0.34, 0.68, 0.90, 0.95]
cth_axis_idx = dict(evclass=2, evtype=3)
for k in ['evclass']: # ,'evtype']:
print(k)
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fermiPy/fermipy | fermipy/config.py | create_default_config | def create_default_config(schema):
"""Create a configuration dictionary from a schema dictionary.
The schema defines the valid configuration keys and their default
values. Each element of ``schema`` should be a tuple/list
containing (default value,docstring,type) or a dict containing a
nested schem... | python | def create_default_config(schema):
"""Create a configuration dictionary from a schema dictionary.
The schema defines the valid configuration keys and their default
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fermiPy/fermipy | fermipy/config.py | update_from_schema | def update_from_schema(cfg, cfgin, schema):
"""Update configuration dictionary ``cfg`` with the contents of
``cfgin`` using the ``schema`` dictionary to determine the valid
input keys.
Parameters
----------
cfg : dict
Configuration dictionary to be updated.
cfgin : dict
New... | python | def update_from_schema(cfg, cfgin, schema):
"""Update configuration dictionary ``cfg`` with the contents of
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input keys.
Parameters
----------
cfg : dict
Configuration dictionary to be updated.
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fermiPy/fermipy | fermipy/config.py | Configurable.write_config | def write_config(self, outfile):
"""Write the configuration dictionary to an output file."""
utils.write_yaml(self.config, outfile, default_flow_style=False) | python | def write_config(self, outfile):
"""Write the configuration dictionary to an output file."""
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fermiPy/fermipy | fermipy/config.py | ConfigManager.create | def create(cls, configfile):
"""Create a configuration dictionary from a yaml config file.
This function will first populate the dictionary with defaults
taken from pre-defined configuration files. The configuration
dictionary is then updated with the user-defined configuration
... | python | def create(cls, configfile):
"""Create a configuration dictionary from a yaml config file.
This function will first populate the dictionary with defaults
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fermiPy/fermipy | fermipy/merge_utils.py | update_null_primary | def update_null_primary(hdu_in, hdu=None):
""" 'Update' a null primary HDU
This actually just checks hdu exists and creates it from hdu_in if it does not.
"""
if hdu is None:
hdu = fits.PrimaryHDU(header=hdu_in.header)
else:
hdu = hdu_in
hdu.header.remove('FILENAME')
ret... | python | def update_null_primary(hdu_in, hdu=None):
""" 'Update' a null primary HDU
This actually just checks hdu exists and creates it from hdu_in if it does not.
"""
if hdu is None:
hdu = fits.PrimaryHDU(header=hdu_in.header)
else:
hdu = hdu_in
hdu.header.remove('FILENAME')
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fermiPy/fermipy | fermipy/merge_utils.py | update_primary | def update_primary(hdu_in, hdu=None):
""" 'Update' a primary HDU
This checks hdu exists and creates it from hdu_in if it does not.
If hdu does exist, this adds the data in hdu_in to hdu
"""
if hdu is None:
hdu = fits.PrimaryHDU(data=hdu_in.data, header=hdu_in.header)
else:
hdu.d... | python | def update_primary(hdu_in, hdu=None):
""" 'Update' a primary HDU
This checks hdu exists and creates it from hdu_in if it does not.
If hdu does exist, this adds the data in hdu_in to hdu
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if hdu is None:
hdu = fits.PrimaryHDU(data=hdu_in.data, header=hdu_in.header)
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fermiPy/fermipy | fermipy/merge_utils.py | update_image | def update_image(hdu_in, hdu=None):
""" 'Update' an image HDU
This checks hdu exists and creates it from hdu_in if it does not.
If hdu does exist, this adds the data in hdu_in to hdu
"""
if hdu is None:
hdu = fits.ImageHDU(
data=hdu_in.data, header=hdu_in.header, name=hdu_in.nam... | python | def update_image(hdu_in, hdu=None):
""" 'Update' an image HDU
This checks hdu exists and creates it from hdu_in if it does not.
If hdu does exist, this adds the data in hdu_in to hdu
"""
if hdu is None:
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fermiPy/fermipy | fermipy/merge_utils.py | update_ebounds | def update_ebounds(hdu_in, hdu=None):
""" 'Update' the EBOUNDS HDU
This checks hdu exists and creates it from hdu_in if it does not.
If hdu does exist, this raises an exception if it doesn not match hdu_in
"""
if hdu is None:
hdu = fits.BinTableHDU(
data=hdu_in.data, header=hdu_... | python | def update_ebounds(hdu_in, hdu=None):
""" 'Update' the EBOUNDS HDU
This checks hdu exists and creates it from hdu_in if it does not.
If hdu does exist, this raises an exception if it doesn not match hdu_in
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hdu = fits.BinTableHDU(
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fermiPy/fermipy | fermipy/merge_utils.py | merge_all_gti_data | def merge_all_gti_data(datalist_in, nrows, first):
""" Merge together all the GTI data
Parameters
-------
datalist_in : list of `astropy.io.fits.BinTableHDU` data
The GTI data that is being merged
nrows : `~numpy.ndarray` of ints
Array with the number of nrows for each object in da... | python | def merge_all_gti_data(datalist_in, nrows, first):
""" Merge together all the GTI data
Parameters
-------
datalist_in : list of `astropy.io.fits.BinTableHDU` data
The GTI data that is being merged
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fermiPy/fermipy | fermipy/merge_utils.py | extract_gti_data | def extract_gti_data(hdu_in):
""" Extract some GTI related data
Parameters
-------
hdu_in : `astropy.io.fits.BinTableHDU`
The GTI data
Returns
-------
data : `astropy.io.fits.BinTableHDU` data
exposure : float
Exposure value taken from FITS header
tstop : float
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""" Extract some GTI related data
Parameters
-------
hdu_in : `astropy.io.fits.BinTableHDU`
The GTI data
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data : `astropy.io.fits.BinTableHDU` data
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Exposure value taken from FITS header
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fermiPy/fermipy | fermipy/merge_utils.py | update_hpx_skymap_allsky | def update_hpx_skymap_allsky(map_in, map_out):
""" 'Update' a HEALPix skymap
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If map_out does exist, this adds the data in map_in to map_out
"""
if map_out is None:
in_hpx = map_in.hpx
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""" 'Update' a HEALPix skymap
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fermiPy/fermipy | fermipy/merge_utils.py | merge_wcs_counts_cubes | def merge_wcs_counts_cubes(filelist):
""" Merge all the files in filelist, assuming that they WCS counts cubes
"""
out_prim = None
out_ebounds = None
datalist_gti = []
exposure_sum = 0.
nfiles = len(filelist)
ngti = np.zeros(nfiles, int)
for i, filename in enumerate(filelist):
... | python | def merge_wcs_counts_cubes(filelist):
""" Merge all the files in filelist, assuming that they WCS counts cubes
"""
out_prim = None
out_ebounds = None
datalist_gti = []
exposure_sum = 0.
nfiles = len(filelist)
ngti = np.zeros(nfiles, int)
for i, filename in enumerate(filelist):
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fermiPy/fermipy | fermipy/merge_utils.py | merge_hpx_counts_cubes | def merge_hpx_counts_cubes(filelist):
""" Merge all the files in filelist, assuming that they HEALPix counts cubes
"""
out_prim = None
out_skymap = None
out_ebounds = None
datalist_gti = []
exposure_sum = 0.
nfiles = len(filelist)
ngti = np.zeros(nfiles, int)
out_name = None
... | python | def merge_hpx_counts_cubes(filelist):
""" Merge all the files in filelist, assuming that they HEALPix counts cubes
"""
out_prim = None
out_skymap = None
out_ebounds = None
datalist_gti = []
exposure_sum = 0.
nfiles = len(filelist)
ngti = np.zeros(nfiles, int)
out_name = None
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fermiPy/fermipy | fermipy/diffuse/gt_srcmaps_catalog.py | GtSrcmapsCatalog.run_analysis | def run_analysis(self, argv):
"""Run this analysis"""
args = self._parser.parse_args(argv)
obs = BinnedAnalysis.BinnedObs(irfs=args.irfs,
expCube=args.expcube,
srcMaps=args.cmap,
... | python | def run_analysis(self, argv):
"""Run this analysis"""
args = self._parser.parse_args(argv)
obs = BinnedAnalysis.BinnedObs(irfs=args.irfs,
expCube=args.expcube,
srcMaps=args.cmap,
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fermiPy/fermipy | fermipy/diffuse/gt_srcmaps_catalog.py | SrcmapsCatalog_SG._make_xml_files | def _make_xml_files(catalog_info_dict, comp_info_dict):
"""Make all the xml file for individual components
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val.roi_model.write_xml(val.srcmdl_name)
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for val2 in val.values():
... | python | def _make_xml_files(catalog_info_dict, comp_info_dict):
"""Make all the xml file for individual components
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val.roi_model.write_xml(val.srcmdl_name)
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fermiPy/fermipy | fermipy/diffuse/gt_srcmaps_catalog.py | SrcmapsCatalog_SG.build_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']:
... | python | 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']:
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fermiPy/fermipy | fermipy/jobs/target_plotting.py | PlotCastro.run_analysis | def run_analysis(self, argv):
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args = self._parser.parse_args(argv)
exttype = splitext(args.infile)[-1]
if exttype in ['.fits', '.npy']:
castro_data = CastroData.create_from_sedfile(args.infile)
elif exttype in ['.yaml']:
castro_dat... | python | def run_analysis(self, argv):
"""Run this analysis"""
args = self._parser.parse_args(argv)
exttype = splitext(args.infile)[-1]
if exttype in ['.fits', '.npy']:
castro_data = CastroData.create_from_sedfile(args.infile)
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fermiPy/fermipy | fermipy/jobs/target_plotting.py | PlotCastro_SG.build_job_configs | def build_job_configs(self, args):
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job_configs = {}
ttype = args['ttype']
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"""Hook to build job configurations
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job_configs = {}
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fermiPy/fermipy | fermipy/sed.py | SEDGenerator.sed | def sed(self, name, **kwargs):
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fermiPy/fermipy | fermipy/diffuse/gt_srcmap_partial.py | GtSrcmapsDiffuse.run_analysis | def run_analysis(self, argv):
"""Run this analysis"""
args = self._parser.parse_args(argv)
obs = BinnedAnalysis.BinnedObs(irfs=args.irfs,
expCube=args.expcube,
srcMaps=args.cmap,
... | python | def run_analysis(self, argv):
"""Run this analysis"""
args = self._parser.parse_args(argv)
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expCube=args.expcube,
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fermiPy/fermipy | fermipy/diffuse/gt_srcmap_partial.py | SrcmapsDiffuse_SG._write_xml | def _write_xml(xmlfile, srcs):
"""Save the ROI model as an XML """
root = ElementTree.Element('source_library')
root.set('title', 'source_library')
for src in srcs:
src.write_xml(root)
output_file = open(xmlfile, 'w')
output_file.write(utils.prettify_xml(roo... | python | def _write_xml(xmlfile, srcs):
"""Save the ROI model as an XML """
root = ElementTree.Element('source_library')
root.set('title', 'source_library')
for src in srcs:
src.write_xml(root)
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fermiPy/fermipy | fermipy/diffuse/gt_srcmap_partial.py | SrcmapsDiffuse_SG._handle_component | def _handle_component(sourcekey, comp_dict):
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if comp_dict.comp_key is None:
fullkey = sourcekey
else:
fullkey = "%s_%s" % (sourcekey, comp_dict.comp_key)
srcdict = make_sources(fullkey, comp_... | python | def _handle_component(sourcekey, comp_dict):
"""Make the source objects and write the xml for a component
"""
if comp_dict.comp_key is None:
fullkey = sourcekey
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fullkey = "%s_%s" % (sourcekey, comp_dict.comp_key)
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fermiPy/fermipy | fermipy/diffuse/gt_srcmap_partial.py | SrcmapsDiffuse_SG._make_xml_files | def _make_xml_files(diffuse_comp_info_dict):
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try:
os.makedirs('srcmdls')
except OSError:
pass
for sourcekey in sorted(diffuse_comp_info_dict.keys()):
comp_info = diffuse_comp_info_dict[sou... | python | def _make_xml_files(diffuse_comp_info_dict):
"""Make all the xml file for individual components
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try:
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job_configs = {}
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ret_dict = make_diffuse_comp_info_dict(components=components,
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job_configs = {}
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fermiPy/fermipy | fermipy/sourcefind_utils.py | fit_error_ellipse | def fit_error_ellipse(tsmap, xy=None, dpix=3, zmin=None):
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fermiPy/fermipy | fermipy/sourcefind_utils.py | find_peaks | def find_peaks(input_map, threshold, min_separation=0.5):
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peak of larger amplitude. The implementation of this method uses
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... | python | def find_peaks(input_map, threshold, min_separation=0.5):
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fermiPy/fermipy | fermipy/sourcefind_utils.py | estimate_pos_and_err_parabolic | def estimate_pos_and_err_parabolic(tsvals):
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fermiPy/fermipy | fermipy/sourcefind_utils.py | refine_peak | def refine_peak(tsmap, pix):
"""Solve for the position and uncertainty of source assuming that you
are near the maximum and the errors are parabolic
Parameters
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tsmap : `~numpy.ndarray`
Array with the TS data.
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-------
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fermiPy/fermipy | fermipy/roi_model.py | create_source_table | def create_source_table(scan_shape):
"""Create an empty source table.
Returns
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tab : `~astropy.table.Table`
"""
cols_dict = collections.OrderedDict()
cols_dict['Source_Name'] = dict(dtype='S48', format='%s')
cols_dict['name'] = dict(dtype='S48', format='%s')
cols_dict['class... | python | def create_source_table(scan_shape):
"""Create an empty source table.
Returns
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tab : `~astropy.table.Table`
"""
cols_dict = collections.OrderedDict()
cols_dict['Source_Name'] = dict(dtype='S48', format='%s')
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fermiPy/fermipy | fermipy/roi_model.py | get_skydir_distance_mask | def get_skydir_distance_mask(src_skydir, skydir, dist, min_dist=None,
square=False, coordsys='CEL'):
"""Retrieve sources within a certain angular distance of an
(ra,dec) coordinate. This function supports two types of
geometric selections: circular (square=False) and square
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fermiPy/fermipy | fermipy/roi_model.py | spectral_pars_from_catalog | def spectral_pars_from_catalog(cat):
"""Create spectral parameters from 3FGL catalog columns."""
spectrum_type = cat['SpectrumType']
pars = get_function_defaults(cat['SpectrumType'])
par_idxs = {k: i for i, k in
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for k in pars:... | python | def spectral_pars_from_catalog(cat):
"""Create spectral parameters from 3FGL catalog columns."""
spectrum_type = cat['SpectrumType']
pars = get_function_defaults(cat['SpectrumType'])
par_idxs = {k: i for i, k in
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fermiPy/fermipy | fermipy/roi_model.py | Model.is_free | def is_free(self):
""" returns True if any of the spectral model parameters is set to free, else False
"""
return bool(np.array([int(value.get("free", False)) for key, value in self.spectral_pars.items()]).sum()) | python | def is_free(self):
""" returns True if any of the spectral model parameters is set to free, else False
"""
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fermiPy/fermipy | fermipy/roi_model.py | Source.set_position | def set_position(self, skydir):
"""
Set the position of the source.
Parameters
----------
skydir : `~astropy.coordinates.SkyCoord`
"""
if not isinstance(skydir, SkyCoord):
skydir = SkyCoord(ra=skydir[0], dec=skydir[1], unit=u.deg)
if not s... | python | def set_position(self, skydir):
"""
Set the position of the source.
Parameters
----------
skydir : `~astropy.coordinates.SkyCoord`
"""
if not isinstance(skydir, SkyCoord):
skydir = SkyCoord(ra=skydir[0], dec=skydir[1], unit=u.deg)
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fermiPy/fermipy | fermipy/roi_model.py | Source.skydir | def skydir(self):
"""Return a SkyCoord representation of the source position.
Returns
-------
skydir : `~astropy.coordinates.SkyCoord`
"""
return SkyCoord(self.radec[0] * u.deg, self.radec[1] * u.deg) | python | def skydir(self):
"""Return a SkyCoord representation of the source position.
Returns
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skydir : `~astropy.coordinates.SkyCoord`
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fermiPy/fermipy | fermipy/roi_model.py | Source.create_from_dict | def create_from_dict(cls, src_dict, roi_skydir=None, rescale=False):
"""Create a source object from a python dictionary.
Parameters
----------
src_dict : dict
Dictionary defining the properties of the source.
"""
src_dict = copy.deepcopy(src_dict)
src... | python | def create_from_dict(cls, src_dict, roi_skydir=None, rescale=False):
"""Create a source object from a python dictionary.
Parameters
----------
src_dict : dict
Dictionary defining the properties of the source.
"""
src_dict = copy.deepcopy(src_dict)
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fermiPy/fermipy | fermipy/roi_model.py | Source.create_from_xmlfile | def create_from_xmlfile(cls, xmlfile, extdir=None):
"""Create a Source object from an XML file.
Parameters
----------
xmlfile : str
Path to XML file.
extdir : str
Path to the extended source archive.
"""
root = ElementTree.ElementTree(fil... | python | def create_from_xmlfile(cls, xmlfile, extdir=None):
"""Create a Source object from an XML file.
Parameters
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xmlfile : str
Path to XML file.
extdir : str
Path to the extended source archive.
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fermiPy/fermipy | fermipy/roi_model.py | Source.create_from_xml | def create_from_xml(root, extdir=None):
"""Create a Source object from an XML node.
Parameters
----------
root : `~xml.etree.ElementTree.Element`
XML node containing the source.
extdir : str
Path to the extended source archive.
"""
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"""Create a Source object from an XML node.
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root : `~xml.etree.ElementTree.Element`
XML node containing the source.
extdir : str
Path to the extended source archive.
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fermiPy/fermipy | fermipy/roi_model.py | Source.write_xml | def write_xml(self, root):
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.clear | def clear(self):
"""Clear the contents of the ROI."""
self._srcs = []
self._diffuse_srcs = []
self._src_dict = collections.defaultdict(list)
self._src_radius = [] | python | def clear(self):
"""Clear the contents of the ROI."""
self._srcs = []
self._diffuse_srcs = []
self._src_dict = collections.defaultdict(list)
self._src_radius = [] | [
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel._create_diffuse_src_from_xml | def _create_diffuse_src_from_xml(self, config, src_type='FileFunction'):
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.create_source | def create_source(self, name, src_dict, build_index=True,
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----------
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.load_sources | def load_sources(self, sources):
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.load_source | def load_source(self, src, build_index=True, merge_sources=True,
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"""
Load a single source.
Parameters
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src : `~fermipy.roi_model.Source`
Source object that will be added to the ROI.
merge_sources : bool
... | python | def load_source(self, src, build_index=True, merge_sources=True,
**kwargs):
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Load a single source.
Parameters
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src : `~fermipy.roi_model.Source`
Source object that will be added to the ROI.
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.match_source | def match_source(self, src):
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"""
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.load | def load(self, **kwargs):
"""Load both point source and diffuse components."""
coordsys = kwargs.get('coordsys', 'CEL')
extdir = kwargs.get('extdir', self.extdir)
srcname = kwargs.get('srcname', None)
self.clear()
self.load_diffuse_srcs()
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.create_from_roi_data | def create_from_roi_data(cls, datafile):
"""Create an ROI model."""
data = np.load(datafile).flat[0]
roi = cls()
roi.load_sources(data['sources'].values())
return roi | python | def create_from_roi_data(cls, datafile):
"""Create an ROI model."""
data = np.load(datafile).flat[0]
roi = cls()
roi.load_sources(data['sources'].values())
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.create | def create(cls, selection, config, **kwargs):
"""Create an ROIModel instance."""
if selection['target'] is not None:
return cls.create_from_source(selection['target'],
config, **kwargs)
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"""Create an ROIModel instance."""
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.create_from_position | def create_from_position(cls, skydir, config, **kwargs):
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Parameters
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skydir : `~astropy.coordinates.SkyCoord`
Sky direction on which the ROI will be centered.
config : dict
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Sky direction on which the ROI will be centered.
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.create_from_source | def create_from_source(cls, name, config, **kwargs):
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coordsys = kwargs.pop('coordsys', 'CEL')
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.get_source_by_name | def get_source_by_name(self, name):
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.get_sources_by_name | def get_sources_by_name(self, name):
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.get_sources | def get_sources(self, skydir=None, distance=None, cuts=None,
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.load_fits_catalog | def load_fits_catalog(self, name, **kwargs):
"""Load sources from a FITS catalog file.
Parameters
----------
name : str
Catalog name or path to a catalog FITS file.
"""
# EAC split this function to make it easier to load an existing catalog
cat = cat... | python | def load_fits_catalog(self, name, **kwargs):
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name : str
Catalog name or path to a catalog FITS file.
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.load_existing_catalog | def load_existing_catalog(self, cat, **kwargs):
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cat : `~fermipy.catalog.Catalog`
Catalog object.
"""
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.load_xml | def load_xml(self, xmlfile, **kwargs):
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extdir = kwargs.get('extdir', self.extdir)
coordsys = kwargs.get('coordsys', 'CEL')
if not os.path.isfile(xmlfile):
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root = E... | python | def load_xml(self, xmlfile, **kwargs):
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extdir = kwargs.get('extdir', self.extdir)
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel._build_src_index | def _build_src_index(self):
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.write_xml | def write_xml(self, xmlfile, config=None):
"""Save the ROI model as an XML file."""
root = ElementTree.Element('source_library')
root.set('title', 'source_library')
for s in self._srcs:
s.write_xml(root)
if config is not None:
srcs = self.create_diffuse... | python | def write_xml(self, xmlfile, config=None):
"""Save the ROI model as an XML file."""
root = ElementTree.Element('source_library')
root.set('title', 'source_library')
for s in self._srcs:
s.write_xml(root)
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.create_table | def create_table(self, names=None):
"""Create an astropy Table object with the contents of the ROI model.
"""
scan_shape = (1,)
for src in self._srcs:
scan_shape = max(scan_shape, src['dloglike_scan'].shape)
tab = create_source_table(scan_shape)
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"""Create an astropy Table object with the contents of the ROI model.
"""
scan_shape = (1,)
for src in self._srcs:
scan_shape = max(scan_shape, src['dloglike_scan'].shape)
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.write_fits | def write_fits(self, fitsfile):
"""Write the ROI model to a FITS file."""
tab = self.create_table()
hdu_data = fits.table_to_hdu(tab)
hdus = [fits.PrimaryHDU(), hdu_data]
fits_utils.write_hdus(hdus, fitsfile) | python | def write_fits(self, fitsfile):
"""Write the ROI model to a FITS file."""
tab = self.create_table()
hdu_data = fits.table_to_hdu(tab)
hdus = [fits.PrimaryHDU(), hdu_data]
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.to_ds9 | def to_ds9(self, free='box',fixed='cross',frame='fk5',color='green',header=True):
"""Returns a list of ds9 region definitions
Parameters
----------
free: bool
one of the supported ds9 point symbols, used for free sources, see here: http://ds9.si.edu/doc/ref/region.html
... | python | def to_ds9(self, free='box',fixed='cross',frame='fk5',color='green',header=True):
"""Returns a list of ds9 region definitions
Parameters
----------
free: bool
one of the supported ds9 point symbols, used for free sources, see here: http://ds9.si.edu/doc/ref/region.html
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fermiPy/fermipy | fermipy/roi_model.py | ROIModel.write_ds9region | def write_ds9region(self, region, *args, **kwargs):
"""Create a ds9 compatible region file from the ROI.
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All other parameters will be forwarded to the `to_ds9` method, see the documentation of... | python | def write_ds9region(self, region, *args, **kwargs):
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fermiPy/fermipy | fermipy/scripts/select_data.py | main | def main():
gtselect_keys = ['tmin', 'tmax', 'emin', 'emax', 'zmax', 'evtype', 'evclass',
'phasemin', 'phasemax', 'convtype', 'rad', 'ra', 'dec']
gtmktime_keys = ['roicut', 'filter']
usage = "usage: %(prog)s [options] "
description = "Run gtselect and gtmktime on one or more FT1 ... | python | def main():
gtselect_keys = ['tmin', 'tmax', 'emin', 'emax', 'zmax', 'evtype', 'evclass',
'phasemin', 'phasemax', 'convtype', 'rad', 'ra', 'dec']
gtmktime_keys = ['roicut', 'filter']
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fermiPy/fermipy | fermipy/diffuse/catalog_src_manager.py | select_extended | def select_extended(cat_table):
"""Select only rows representing extended sources from a catalog table
"""
try:
l = [len(row.strip()) > 0 for row in cat_table['Extended_Source_Name'].data]
return np.array(l, bool)
except KeyError:
return cat_table['Extended'] | python | def select_extended(cat_table):
"""Select only rows representing extended sources from a catalog table
"""
try:
l = [len(row.strip()) > 0 for row in cat_table['Extended_Source_Name'].data]
return np.array(l, bool)
except KeyError:
return cat_table['Extended'] | [
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fermiPy/fermipy | fermipy/diffuse/catalog_src_manager.py | make_mask | def make_mask(cat_table, cut):
"""Mask a bit mask selecting the rows that pass a selection
"""
cut_var = cut['cut_var']
min_val = cut.get('min_val', None)
max_val = cut.get('max_val', None)
nsrc = len(cat_table)
if min_val is None:
min_mask = np.ones((nsrc), bool)
else:
... | python | def make_mask(cat_table, cut):
"""Mask a bit mask selecting the rows that pass a selection
"""
cut_var = cut['cut_var']
min_val = cut.get('min_val', None)
max_val = cut.get('max_val', None)
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fermiPy/fermipy | fermipy/diffuse/catalog_src_manager.py | select_sources | def select_sources(cat_table, cuts):
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full_mask = np.ones((nsrc), bool)
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"""
nsrc = len(cat_table)
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fermiPy/fermipy | fermipy/diffuse/catalog_src_manager.py | make_catalog_comp_dict | def make_catalog_comp_dict(**kwargs):
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"""
library_yamlfile = kwargs.pop('library', 'models/library.yaml')
csm = kwargs.pop('CatalogSourceManager', CatalogSourceManager(**kwargs))
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"""Build and return the information about the catalog components
"""
library_yamlfile = kwargs.pop('library', 'models/library.yaml')
csm = kwargs.pop('CatalogSourceManager', CatalogSourceManager(**kwargs))
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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,
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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
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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
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fermiPy/fermipy | fermipy/diffuse/catalog_src_manager.py | CatalogSourceManager.catalog_components | def catalog_components(self, catalog_name, split_ver):
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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):
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fermiPy/fermipy | fermipy/diffuse/catalog_src_manager.py | CatalogSourceManager.make_catalog_comp_info | def make_catalog_comp_info(self, full_cat_info, split_key, rule_key, rule_val, sources):
""" Make the information about a single merged component
Parameters
----------
full_cat_info : `_model_component.CatalogInfo`
Information about the full catalog
split_key : str
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full_cat_info : `_model_component.CatalogInfo`
Information about the full catalog
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] | train | https://github.com/fermiPy/fermipy/blob/9df5e7e3728307fd58c5bba36fd86783c39fbad4/fermipy/diffuse/catalog_src_manager.py#L149-L183 |
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 | convert_tscube_old | def convert_tscube_old(infile, outfile):
"""Convert between old and new TSCube formats."""
inhdulist = fits.open(infile)
# If already in the new-style format just write and exit
if 'DLOGLIKE_SCAN' in inhdulist['SCANDATA'].columns.names:
if infile != outfile:
inhdulist.writeto(outfil... | python | def convert_tscube_old(infile, outfile):
"""Convert between old and new TSCube formats."""
inhdulist = fits.open(infile)
# If already in the new-style format just write and exit
if 'DLOGLIKE_SCAN' in inhdulist['SCANDATA'].columns.names:
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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]
dxlo = array1.shape[i] // 2
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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.
"""
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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 | _f_cash_root | def _f_cash_root(x, counts, bkg, model):
"""
Function to find root of. Described in Appendix A, Stewart (2009).
Parameters
----------
x : float
Model amplitude.
counts : `~numpy.ndarray`
Count map slice, where model is defined.
bkg : `~numpy.ndarray`
Background map s... | python | def _f_cash_root(x, counts, bkg, model):
"""
Function to find root of. Described in Appendix A, Stewart (2009).
Parameters
----------
x : float
Model amplitude.
counts : `~numpy.ndarray`
Count map slice, where model is defined.
bkg : `~numpy.ndarray`
Background map s... | [
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Background map slice, where model is defined.
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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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bkg : `~numpy.ndarray`
Slice of background map.
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Model template to fit.
Returns
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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`
Background map slice, where... | [
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Model amplitude.
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Count map slice, where model is defined.
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Background map slice, where model is defined.
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fermiPy/fermipy | fermipy/tsmap.py | _ts_value | def _ts_value(position, counts, bkg, model, C_0_map):
"""
Compute TS value at a given pixel position using the approach described
in Stewart (2009).
Parameters
----------
position : tuple
Pixel position.
counts : `~numpy.ndarray`
Count map.
bkg : `~numpy.ndarray`
... | python | def _ts_value(position, counts, bkg, model, C_0_map):
"""
Compute TS value at a given pixel position using the approach described
in Stewart (2009).
Parameters
----------
position : tuple
Pixel position.
counts : `~numpy.ndarray`
Count map.
bkg : `~numpy.ndarray`
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Count map.
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Background map.
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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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Count map.
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Background map.
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Source model map.
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