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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis._fit_newton
def _fit_newton(self, fitcache=None, ebin=None, **kwargs): """Fast fitting method using newton fitter.""" tol = kwargs.get('tol', self.config['optimizer']['tol']) max_iter = kwargs.get('max_iter', self.config['optimizer']['max_iter']) init_lambda = kwargs.g...
python
def _fit_newton(self, fitcache=None, ebin=None, **kwargs): """Fast fitting method using newton fitter.""" tol = kwargs.get('tol', self.config['optimizer']['tol']) max_iter = kwargs.get('max_iter', self.config['optimizer']['max_iter']) init_lambda = kwargs.g...
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Fast fitting method using newton fitter.
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.load_xml
def load_xml(self, xmlfile): """Load model definition from XML. Parameters ---------- xmlfile : str Name of the input XML file. """ self.logger.info('Loading XML') for c in self.components: c.load_xml(xmlfile) for name in self....
python
def load_xml(self, xmlfile): """Load model definition from XML. Parameters ---------- xmlfile : str Name of the input XML file. """ self.logger.info('Loading XML') for c in self.components: c.load_xml(xmlfile) for name in self....
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.load_parameters_from_yaml
def load_parameters_from_yaml(self, yamlfile, update_sources=False): """Load model parameters from yaml Parameters ---------- yamlfile : str Name of the input yaml file. """ d = utils.load_yaml(yamlfile) for src, src_pars in d.items(): for...
python
def load_parameters_from_yaml(self, yamlfile, update_sources=False): """Load model parameters from yaml Parameters ---------- yamlfile : str Name of the input yaml file. """ d = utils.load_yaml(yamlfile) for src, src_pars in d.items(): for...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis._restore_counts_maps
def _restore_counts_maps(self): """ Revert counts maps to their state prior to injecting any simulated components. """ for c in self.components: c.restore_counts_maps() if hasattr(self.like.components[0].logLike, 'setCountsMap'): self._init_roi_m...
python
def _restore_counts_maps(self): """ Revert counts maps to their state prior to injecting any simulated components. """ for c in self.components: c.restore_counts_maps() if hasattr(self.like.components[0].logLike, 'setCountsMap'): self._init_roi_m...
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Revert counts maps to their state prior to injecting any simulated components.
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.simulate_source
def simulate_source(self, src_dict=None): """ Inject simulated source counts into the data. Parameters ---------- src_dict : dict Dictionary defining the spatial and spectral properties of the source that will be injected. """ self._fitcac...
python
def simulate_source(self, src_dict=None): """ Inject simulated source counts into the data. Parameters ---------- src_dict : dict Dictionary defining the spatial and spectral properties of the source that will be injected. """ self._fitcac...
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Inject simulated source counts into the data. Parameters ---------- src_dict : dict Dictionary defining the spatial and spectral properties of the source that will be injected.
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.simulate_roi
def simulate_roi(self, name=None, randomize=True, restore=False): """Generate a simulation of the ROI using the current best-fit model and replace the data counts cube with this simulation. The simulation is created by generating an array of Poisson random numbers with expectation value...
python
def simulate_roi(self, name=None, randomize=True, restore=False): """Generate a simulation of the ROI using the current best-fit model and replace the data counts cube with this simulation. The simulation is created by generating an array of Poisson random numbers with expectation value...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.write_model_map
def write_model_map(self, model_name, name=None): """Save the counts model map to a FITS file. Parameters ---------- model_name : str String that will be append to the name of the output file. name : str Name of the component. Returns ---...
python
def write_model_map(self, model_name, name=None): """Save the counts model map to a FITS file. Parameters ---------- model_name : str String that will be append to the name of the output file. name : str Name of the component. Returns ---...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.write_weight_map
def write_weight_map(self, model_name): """Save the counts model map to a FITS file. Parameters ---------- model_name : str String that will be append to the name of the output file. Returns ------- """ maps = [c.write_weight_map(model_name)...
python
def write_weight_map(self, model_name): """Save the counts model map to a FITS file. Parameters ---------- model_name : str String that will be append to the name of the output file. Returns ------- """ maps = [c.write_weight_map(model_name)...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.print_roi
def print_roi(self, loglevel=logging.INFO): """Print information about the spectral and spatial properties of the ROI (sources, diffuse components).""" self.logger.log(loglevel, '\n' + str(self.roi))
python
def print_roi(self, loglevel=logging.INFO): """Print information about the spectral and spatial properties of the ROI (sources, diffuse components).""" self.logger.log(loglevel, '\n' + str(self.roi))
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.print_params
def print_params(self, allpars=False, loglevel=logging.INFO): """Print information about the model parameters (values, errors, bounds, scale).""" pars = self.get_params() o = '\n' o += '%4s %-20s%10s%10s%10s%10s%10s%5s\n' % ( 'idx', 'parname', 'value', 'error', ...
python
def print_params(self, allpars=False, loglevel=logging.INFO): """Print information about the model parameters (values, errors, bounds, scale).""" pars = self.get_params() o = '\n' o += '%4s %-20s%10s%10s%10s%10s%10s%5s\n' % ( 'idx', 'parname', 'value', 'error', ...
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Print information about the model parameters (values, errors, bounds, scale).
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.load_roi
def load_roi(self, infile, reload_sources=False, params=None, mask=None): """This function reloads the analysis state from a previously saved instance generated with `~fermipy.gtanalysis.GTAnalysis.write_roi`. Parameters ---------- infile : str reload_sources :...
python
def load_roi(self, infile, reload_sources=False, params=None, mask=None): """This function reloads the analysis state from a previously saved instance generated with `~fermipy.gtanalysis.GTAnalysis.write_roi`. Parameters ---------- infile : str reload_sources :...
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This function reloads the analysis state from a previously saved instance generated with `~fermipy.gtanalysis.GTAnalysis.write_roi`. Parameters ---------- infile : str reload_sources : bool Regenerate source maps for non-diffuse sources. params : st...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.write_roi
def write_roi(self, outfile=None, save_model_map=False, **kwargs): """Write current state of the analysis to a file. This method writes an XML model definition, a ROI dictionary, and a FITS source catalog file. A previously saved analysis state can be reloaded from th...
python
def write_roi(self, outfile=None, save_model_map=False, **kwargs): """Write current state of the analysis to a file. This method writes an XML model definition, a ROI dictionary, and a FITS source catalog file. A previously saved analysis state can be reloaded from th...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.make_plots
def make_plots(self, prefix, mcube_map=None, **kwargs): """Make diagnostic plots using the current ROI model.""" #mcube_maps = kwargs.pop('mcube_maps', None) if mcube_map is None: mcube_map = self.model_counts_map() plotter = plotting.AnalysisPlotter(self.config['plotting']...
python
def make_plots(self, prefix, mcube_map=None, **kwargs): """Make diagnostic plots using the current ROI model.""" #mcube_maps = kwargs.pop('mcube_maps', None) if mcube_map is None: mcube_map = self.model_counts_map() plotter = plotting.AnalysisPlotter(self.config['plotting']...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.curvature
def curvature(self, name, **kwargs): """Test whether a source shows spectral curvature by comparing the likelihood ratio of PowerLaw and LogParabola spectral models. Parameters ---------- name : str Source name. """ name = self.roi.get_sourc...
python
def curvature(self, name, **kwargs): """Test whether a source shows spectral curvature by comparing the likelihood ratio of PowerLaw and LogParabola spectral models. Parameters ---------- name : str Source name. """ name = self.roi.get_sourc...
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Test whether a source shows spectral curvature by comparing the likelihood ratio of PowerLaw and LogParabola spectral models. Parameters ---------- name : str Source name.
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.bowtie
def bowtie(self, name, fd=None, loge=None): """Generate a spectral uncertainty band (bowtie) for the given source. This will create an uncertainty band on the differential flux as a function of energy by propagating the errors on the global fit parameters. Note that this band only ...
python
def bowtie(self, name, fd=None, loge=None): """Generate a spectral uncertainty band (bowtie) for the given source. This will create an uncertainty band on the differential flux as a function of energy by propagating the errors on the global fit parameters. Note that this band only ...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.update_source
def update_source(self, name, paramsonly=False, reoptimize=False, **kwargs): """Update the dictionary for this source. Parameters ---------- name : str paramsonly : bool reoptimize : bool Re-fit background parameters in likelihood scan. """ ...
python
def update_source(self, name, paramsonly=False, reoptimize=False, **kwargs): """Update the dictionary for this source. Parameters ---------- name : str paramsonly : bool reoptimize : bool Re-fit background parameters in likelihood scan. """ ...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.get_src_model
def get_src_model(self, name, paramsonly=False, reoptimize=False, npts=None, **kwargs): """Compose a dictionary for a source with the current best-fit parameters. Parameters ---------- name : str paramsonly : bool Skip computing TS and ...
python
def get_src_model(self, name, paramsonly=False, reoptimize=False, npts=None, **kwargs): """Compose a dictionary for a source with the current best-fit parameters. Parameters ---------- name : str paramsonly : bool Skip computing TS and ...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTAnalysis.compute_srcprob
def compute_srcprob(self,xmlfile=None, overwrite=False): """Run the gtsrcprob app with the current model or a user provided xmlfile""" for i,c in enumerate(self.components): # compute diffuse response, necessary for srcprob c._diffrsp_app(xmlfile=xmlfile) # compute s...
python
def compute_srcprob(self,xmlfile=None, overwrite=False): """Run the gtsrcprob app with the current model or a user provided xmlfile""" for i,c in enumerate(self.components): # compute diffuse response, necessary for srcprob c._diffrsp_app(xmlfile=xmlfile) # compute s...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.reload_source
def reload_source(self, name): """Recompute the source map for a single source in the model. """ src = self.roi.get_source_by_name(name) if hasattr(self.like.logLike, 'loadSourceMap'): self.like.logLike.loadSourceMap(str(name), True, False) srcmap_utils.delete_s...
python
def reload_source(self, name): """Recompute the source map for a single source in the model. """ src = self.roi.get_source_by_name(name) if hasattr(self.like.logLike, 'loadSourceMap'): self.like.logLike.loadSourceMap(str(name), True, False) srcmap_utils.delete_s...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.reload_sources
def reload_sources(self, names): """Recompute the source map for a list of sources in the model. """ try: self.like.logLike.loadSourceMaps(names, True, True) # loadSourceMaps doesn't overwrite the header so we need # to ignore EXPSCALE by setting check_header...
python
def reload_sources(self, names): """Recompute the source map for a list of sources in the model. """ try: self.like.logLike.loadSourceMaps(names, True, True) # loadSourceMaps doesn't overwrite the header so we need # to ignore EXPSCALE by setting check_header...
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train
https://github.com/fermiPy/fermipy/blob/9df5e7e3728307fd58c5bba36fd86783c39fbad4/fermipy/gtanalysis.py#L4547-L4559
fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.add_source
def add_source(self, name, src_dict, free=None, save_source_maps=True, use_pylike=True, use_single_psf=False): """Add a new source to the model. Source properties (spectrum, spatial model) are set with the src_dict argument. Parameters ---------- name : str...
python
def add_source(self, name, src_dict, free=None, save_source_maps=True, use_pylike=True, use_single_psf=False): """Add a new source to the model. Source properties (spectrum, spatial model) are set with the src_dict argument. Parameters ---------- name : str...
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Add a new source to the model. Source properties (spectrum, spatial model) are set with the src_dict argument. Parameters ---------- name : str Source name. src_dict : dict or `~fermipy.roi_model.Source` object Dictionary or Source object defining the...
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train
https://github.com/fermiPy/fermipy/blob/9df5e7e3728307fd58c5bba36fd86783c39fbad4/fermipy/gtanalysis.py#L4561-L4627
fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis._create_source
def _create_source(self, src): """Create a pyLikelihood Source object from a `~fermipy.roi_model.Model` object.""" if src['SpatialType'] == 'SkyDirFunction': pylike_src = pyLike.PointSource(self.like.logLike.observation()) pylike_src.setDir(src.skydir.ra.deg, src.skydir....
python
def _create_source(self, src): """Create a pyLikelihood Source object from a `~fermipy.roi_model.Model` object.""" if src['SpatialType'] == 'SkyDirFunction': pylike_src = pyLike.PointSource(self.like.logLike.observation()) pylike_src.setDir(src.skydir.ra.deg, src.skydir....
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.set_exposure_scale
def set_exposure_scale(self, name, scale=None): """Set the exposure correction of a source. Parameters ---------- name : str Source name. scale : factor Exposure scale factor (1.0 = nominal exposure). """ name = self.roi.get_source_by_na...
python
def set_exposure_scale(self, name, scale=None): """Set the exposure correction of a source. Parameters ---------- name : str Source name. scale : factor Exposure scale factor (1.0 = nominal exposure). """ name = self.roi.get_source_by_na...
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Set the exposure correction of a source. Parameters ---------- name : str Source name. scale : factor Exposure scale factor (1.0 = nominal exposure).
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train
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.set_edisp_flag
def set_edisp_flag(self, name, flag=True): """Enable/Disable the energy dispersion correction for a source.""" src = self.roi.get_source_by_name(name) name = src.name self.like[name].src.set_edisp_flag(flag)
python
def set_edisp_flag(self, name, flag=True): """Enable/Disable the energy dispersion correction for a source.""" src = self.roi.get_source_by_name(name) name = src.name self.like[name].src.set_edisp_flag(flag)
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.set_energy_range
def set_energy_range(self, logemin, logemax): """Set the energy range of the analysis. Parameters ---------- logemin: float Lower end of energy range in log10(E/MeV). logemax : float Upper end of energy range in log10(E/MeV). """ if logem...
python
def set_energy_range(self, logemin, logemax): """Set the energy range of the analysis. Parameters ---------- logemin: float Lower end of energy range in log10(E/MeV). logemax : float Upper end of energy range in log10(E/MeV). """ if logem...
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Set the energy range of the analysis. Parameters ---------- logemin: float Lower end of energy range in log10(E/MeV). logemax : float Upper end of energy range in log10(E/MeV).
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.counts_map
def counts_map(self): """Return 3-D counts map for this component as a Map object. Returns ------- map : `~fermipy.skymap.MapBase` """ try: if isinstance(self.like, gtutils.SummedLikelihood): cmap = self.like.components[0].logLike.countsMap()...
python
def counts_map(self): """Return 3-D counts map for this component as a Map object. Returns ------- map : `~fermipy.skymap.MapBase` """ try: if isinstance(self.like, gtutils.SummedLikelihood): cmap = self.like.components[0].logLike.countsMap()...
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Return 3-D counts map for this component as a Map object. Returns ------- map : `~fermipy.skymap.MapBase`
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.weight_map
def weight_map(self): """Return 3-D weights map for this component as a Map object. Returns ------- map : `~fermipy.skymap.MapBase` """ # EAC we need the try blocks b/c older versions of the ST don't have some of these functions if isinstance(self.like, gtutils....
python
def weight_map(self): """Return 3-D weights map for this component as a Map object. Returns ------- map : `~fermipy.skymap.MapBase` """ # EAC we need the try blocks b/c older versions of the ST don't have some of these functions if isinstance(self.like, gtutils....
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Return 3-D weights map for this component as a Map object. Returns ------- map : `~fermipy.skymap.MapBase`
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.model_counts_map
def model_counts_map(self, name=None, exclude=None, use_mask=False): """Return the model expectation map for a single source, a set of sources, or all sources in the ROI. The map will be computed using the current model parameters. Parameters ---------- name : str ...
python
def model_counts_map(self, name=None, exclude=None, use_mask=False): """Return the model expectation map for a single source, a set of sources, or all sources in the ROI. The map will be computed using the current model parameters. Parameters ---------- name : str ...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.model_counts_spectrum
def model_counts_spectrum(self, name, logemin, logemax, weighted=False): """Return the model counts spectrum of a source. Parameters ---------- name : str Source name. """ # EAC, we need this b/c older version of the ST don't have the right signature ...
python
def model_counts_spectrum(self, name, logemin, logemax, weighted=False): """Return the model counts spectrum of a source. Parameters ---------- name : str Source name. """ # EAC, we need this b/c older version of the ST don't have the right signature ...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.setup
def setup(self, overwrite=False, **kwargs): """Run pre-processing step for this component. This will generate all of the auxiliary files needed to instantiate a likelihood object. By default this function will skip any steps for which the output file already exists. Parameters...
python
def setup(self, overwrite=False, **kwargs): """Run pre-processing step for this component. This will generate all of the auxiliary files needed to instantiate a likelihood object. By default this function will skip any steps for which the output file already exists. Parameters...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis._scale_srcmap
def _scale_srcmap(self, scale_map, check_header=True, names=None): """Apply exposure corrections to the source map file. Parameters ---------- scale_map : dict Dictionary of exposure corrections. check_header : bool Check EXPSCALE header keyword to see i...
python
def _scale_srcmap(self, scale_map, check_header=True, names=None): """Apply exposure corrections to the source map file. Parameters ---------- scale_map : dict Dictionary of exposure corrections. check_header : bool Check EXPSCALE header keyword to see i...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis._make_scaled_srcmap
def _make_scaled_srcmap(self): """Make an exposure cube with the same binning as the counts map.""" self.logger.info('Computing scaled source map.') bexp0 = fits.open(self.files['bexpmap_roi']) bexp1 = fits.open(self.config['gtlike']['bexpmap']) srcmap = fits.open(self.config['...
python
def _make_scaled_srcmap(self): """Make an exposure cube with the same binning as the counts map.""" self.logger.info('Computing scaled source map.') bexp0 = fits.open(self.files['bexpmap_roi']) bexp1 = fits.open(self.config['gtlike']['bexpmap']) srcmap = fits.open(self.config['...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.simulate_roi
def simulate_roi(self, name=None, clear=True, randomize=True): """Simulate the whole ROI or inject a simulation of one or more model components into the data. Parameters ---------- name : str Name of the model component to be simulated. If None then the wh...
python
def simulate_roi(self, name=None, clear=True, randomize=True): """Simulate the whole ROI or inject a simulation of one or more model components into the data. Parameters ---------- name : str Name of the model component to be simulated. If None then the wh...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.write_model_map
def write_model_map(self, model_name=None, name=None): """Save counts model map to a FITS file. """ if model_name is None: suffix = self.config['file_suffix'] else: suffix = '_%s%s' % (model_name, self.config['file_suffix']) self.logger.info('Generating...
python
def write_model_map(self, model_name=None, name=None): """Save counts model map to a FITS file. """ if model_name is None: suffix = self.config['file_suffix'] else: suffix = '_%s%s' % (model_name, self.config['file_suffix']) self.logger.info('Generating...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.write_weight_map
def write_weight_map(self, model_name=None): """Save counts model map to a FITS file. """ if model_name is None: suffix = self.config['file_suffix'] else: suffix = '_%s%s' % (model_name, self.config['file_suffix']) self.logger.info('Generating model map...
python
def write_weight_map(self, model_name=None): """Save counts model map to a FITS file. """ if model_name is None: suffix = self.config['file_suffix'] else: suffix = '_%s%s' % (model_name, self.config['file_suffix']) self.logger.info('Generating model map...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis._update_srcmap_file
def _update_srcmap_file(self, sources, overwrite=True): """Check the contents of the source map file and generate source maps for any components that are not present.""" if not os.path.isfile(self.files['srcmap']): return hdulist = fits.open(self.files['srcmap']) hd...
python
def _update_srcmap_file(self, sources, overwrite=True): """Check the contents of the source map file and generate source maps for any components that are not present.""" if not os.path.isfile(self.files['srcmap']): return hdulist = fits.open(self.files['srcmap']) hd...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis._create_srcmap
def _create_srcmap(self, name, src, **kwargs): """Generate the source map for a source.""" psf_scale_fn = kwargs.get('psf_scale_fn', None) skydir = src.skydir spatial_model = src['SpatialModel'] spatial_width = src['SpatialWidth'] xpix, ypix = self.geom.to_image().coord_...
python
def _create_srcmap(self, name, src, **kwargs): """Generate the source map for a source.""" psf_scale_fn = kwargs.get('psf_scale_fn', None) skydir = src.skydir spatial_model = src['SpatialModel'] spatial_width = src['SpatialWidth'] xpix, ypix = self.geom.to_image().coord_...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis._update_srcmap
def _update_srcmap(self, name, src, **kwargs): """Update the source map for an existing source in memory.""" k = self._create_srcmap(name, src, **kwargs) scale = self._src_expscale.get(name, 1.0) k *= scale # Force the source map to be cached # FIXME: No longer necessar...
python
def _update_srcmap(self, name, src, **kwargs): """Update the source map for an existing source in memory.""" k = self._create_srcmap(name, src, **kwargs) scale = self._src_expscale.get(name, 1.0) k *= scale # Force the source map to be cached # FIXME: No longer necessar...
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Update the source map for an existing source in memory.
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train
https://github.com/fermiPy/fermipy/blob/9df5e7e3728307fd58c5bba36fd86783c39fbad4/fermipy/gtanalysis.py#L5594-L5609
fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.generate_model
def generate_model(self, model_name=None, outfile=None): """Generate a counts model map from an XML model file using gtmodel. Parameters ---------- model_name : str Name of the model. If no name is given it will use the baseline model. outfile :...
python
def generate_model(self, model_name=None, outfile=None): """Generate a counts model map from an XML model file using gtmodel. Parameters ---------- model_name : str Name of the model. If no name is given it will use the baseline model. outfile :...
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Generate a counts model map from an XML model file using gtmodel. Parameters ---------- model_name : str Name of the model. If no name is given it will use the baseline model. outfile : str Override the name of the output model file.
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train
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.write_xml
def write_xml(self, xmlfile): """Write the XML model for this analysis component.""" xmlfile = self.get_model_path(xmlfile) self.logger.info('Writing %s...', xmlfile) self.like.writeXml(str(xmlfile))
python
def write_xml(self, xmlfile): """Write the XML model for this analysis component.""" xmlfile = self.get_model_path(xmlfile) self.logger.info('Writing %s...', xmlfile) self.like.writeXml(str(xmlfile))
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Write the XML model for this analysis component.
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train
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis.get_model_path
def get_model_path(self, name): """Infer the path to the XML model name.""" name, ext = os.path.splitext(name) ext = '.xml' xmlfile = name + self.config['file_suffix'] + ext xmlfile = utils.resolve_path(xmlfile, workdir=self.config['fileio'][...
python
def get_model_path(self, name): """Infer the path to the XML model name.""" name, ext = os.path.splitext(name) ext = '.xml' xmlfile = name + self.config['file_suffix'] + ext xmlfile = utils.resolve_path(xmlfile, workdir=self.config['fileio'][...
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Infer the path to the XML model name.
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train
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis._tscube_app
def _tscube_app(self, xmlfile): """Run gttscube as an application.""" xmlfile = self.get_model_path(xmlfile) outfile = os.path.join(self.config['fileio']['workdir'], 'tscube%s.fits' % (self.config['file_suffix'])) kw = dict(cmap=self.files['ccube'], ...
python
def _tscube_app(self, xmlfile): """Run gttscube as an application.""" xmlfile = self.get_model_path(xmlfile) outfile = os.path.join(self.config['fileio']['workdir'], 'tscube%s.fits' % (self.config['file_suffix'])) kw = dict(cmap=self.files['ccube'], ...
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Run gttscube as an application.
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train
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis._diffrsp_app
def _diffrsp_app(self,xmlfile=None, **kwargs): """ Compute the diffuse response """ loglevel = kwargs.get('loglevel', self.loglevel) self.logger.log(loglevel, 'Computing diffuse repsonce for component %s.', self.name) # set the srcmdl sr...
python
def _diffrsp_app(self,xmlfile=None, **kwargs): """ Compute the diffuse response """ loglevel = kwargs.get('loglevel', self.loglevel) self.logger.log(loglevel, 'Computing diffuse repsonce for component %s.', self.name) # set the srcmdl sr...
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fermiPy/fermipy
fermipy/gtanalysis.py
GTBinnedAnalysis._srcprob_app
def _srcprob_app(self,xmlfile=None, overwrite=False, **kwargs): """ Run srcprob for an analysis component as an application """ loglevel = kwargs.get('loglevel', self.loglevel) self.logger.log(loglevel, 'Computing src probability for component %s.', self...
python
def _srcprob_app(self,xmlfile=None, overwrite=False, **kwargs): """ Run srcprob for an analysis component as an application """ loglevel = kwargs.get('loglevel', self.loglevel) self.logger.log(loglevel, 'Computing src probability for component %s.', self...
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fermiPy/fermipy
fermipy/jobs/chain.py
purge_dict
def purge_dict(idict): """Remove null items from a dictionary """ odict = {} for key, val in idict.items(): if is_null(val): continue odict[key] = val return odict
python
def purge_dict(idict): """Remove null items from a dictionary """ odict = {} for key, val in idict.items(): if is_null(val): continue odict[key] = val return odict
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train
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fermiPy/fermipy
fermipy/jobs/chain.py
Chain.main
def main(cls): """Hook to run this `Chain` from the command line """ chain = cls.create() args = chain._run_argparser(sys.argv[1:]) chain._run_chain(sys.stdout, args.dry_run) chain._finalize(args.dry_run)
python
def main(cls): """Hook to run this `Chain` from the command line """ chain = cls.create() args = chain._run_argparser(sys.argv[1:]) chain._run_chain(sys.stdout, args.dry_run) chain._finalize(args.dry_run)
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fermiPy/fermipy
fermipy/jobs/chain.py
Chain._latch_file_info
def _latch_file_info(self): """Internal function to update the dictionaries keeping track of input and output files """ self._map_arguments(self.args) self.files.latch_file_info(self.args) self.sub_files.file_dict.clear() self.sub_files.update(self.files.file_dict...
python
def _latch_file_info(self): """Internal function to update the dictionaries keeping track of input and output files """ self._map_arguments(self.args) self.files.latch_file_info(self.args) self.sub_files.file_dict.clear() self.sub_files.update(self.files.file_dict...
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train
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fermiPy/fermipy
fermipy/jobs/chain.py
Chain._set_link
def _set_link(self, linkname, cls, **kwargs): """Transfer options kwargs to a `Link` object, optionally building the `Link if needed. Parameters ---------- linkname : str Unique name of this particular link cls : type Type of `Link` being create...
python
def _set_link(self, linkname, cls, **kwargs): """Transfer options kwargs to a `Link` object, optionally building the `Link if needed. Parameters ---------- linkname : str Unique name of this particular link cls : type Type of `Link` being create...
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Transfer options kwargs to a `Link` object, optionally building the `Link if needed. Parameters ---------- linkname : str Unique name of this particular link cls : type Type of `Link` being created or managed
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fermiPy/fermipy
fermipy/jobs/chain.py
Chain._set_links_job_archive
def _set_links_job_archive(self): """Pass self._job_archive along to links""" for link in self._links.values(): link._job_archive = self._job_archive
python
def _set_links_job_archive(self): """Pass self._job_archive along to links""" for link in self._links.values(): link._job_archive = self._job_archive
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train
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fermiPy/fermipy
fermipy/jobs/chain.py
Chain._run_chain
def _run_chain(self, stream=sys.stdout, dry_run=False, stage_files=True, force_run=False, resubmit_failed=False): """Run all the links in the chain Parameters ----------- stream : `file` ...
python
def _run_chain(self, stream=sys.stdout, dry_run=False, stage_files=True, force_run=False, resubmit_failed=False): """Run all the links in the chain Parameters ----------- stream : `file` ...
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train
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fermiPy/fermipy
fermipy/jobs/chain.py
Chain.clear_jobs
def clear_jobs(self, recursive=True): """Clear a dictionary with all the jobs If recursive is True this will include jobs from all internal `Link` """ if recursive: for link in self._links.values(): link.clear_jobs(recursive) self.jobs.clear()
python
def clear_jobs(self, recursive=True): """Clear a dictionary with all the jobs If recursive is True this will include jobs from all internal `Link` """ if recursive: for link in self._links.values(): link.clear_jobs(recursive) self.jobs.clear()
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train
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fermiPy/fermipy
fermipy/jobs/chain.py
Chain.get_jobs
def get_jobs(self, recursive=True): """Return a dictionary with all the jobs If recursive is True this will include jobs from all internal `Link` """ if recursive: ret_dict = self.jobs.copy() for link in self._links.values(): ret_dict.update(link....
python
def get_jobs(self, recursive=True): """Return a dictionary with all the jobs If recursive is True this will include jobs from all internal `Link` """ if recursive: ret_dict = self.jobs.copy() for link in self._links.values(): ret_dict.update(link....
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fermiPy/fermipy
fermipy/jobs/chain.py
Chain.missing_input_files
def missing_input_files(self): """Make and return a dictionary of the missing input files. This returns a dictionary mapping filepath to list of `Link` that use the file as input. """ ret_dict = OrderedDict() for link in self._links.values(): link_dict = link...
python
def missing_input_files(self): """Make and return a dictionary of the missing input files. This returns a dictionary mapping filepath to list of `Link` that use the file as input. """ ret_dict = OrderedDict() for link in self._links.values(): link_dict = link...
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train
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fermiPy/fermipy
fermipy/jobs/chain.py
Chain.check_links_status
def check_links_status(self, fail_running=False, fail_pending=False): """"Check the status of all the jobs run from the `Link` objects in this `Chain` and return a status flag that summarizes that. Parameters ---------- ...
python
def check_links_status(self, fail_running=False, fail_pending=False): """"Check the status of all the jobs run from the `Link` objects in this `Chain` and return a status flag that summarizes that. Parameters ---------- ...
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fermiPy/fermipy
fermipy/jobs/chain.py
Chain.run
def run(self, stream=sys.stdout, dry_run=False, stage_files=True, resubmit_failed=False): """Runs this `Chain`. Parameters ----------- stream : `file` Stream that this `Link` will print to, Must have 'write' function dry_run : bool ...
python
def run(self, stream=sys.stdout, dry_run=False, stage_files=True, resubmit_failed=False): """Runs this `Chain`. Parameters ----------- stream : `file` Stream that this `Link` will print to, Must have 'write' function dry_run : bool ...
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train
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fermiPy/fermipy
fermipy/jobs/chain.py
Chain.update_args
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python
def update_args(self, override_args): """Update the argument used to invoke the application Note that this will also update the dictionary of input and output files. Parameters ----------- override_args : dict dictionary passed to the links """ ...
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train
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fermiPy/fermipy
fermipy/jobs/chain.py
Chain.print_status
def print_status(self, indent="", recurse=False): """Print a summary of the job status for each `Link` in this `Chain`""" print ("%s%30s : %15s : %20s" % (indent, "Linkname", "Link Status", "Jobs Status")) for link in self._links.values(): if hasattr(link, 'check_statu...
python
def print_status(self, indent="", recurse=False): """Print a summary of the job status for each `Link` in this `Chain`""" print ("%s%30s : %15s : %20s" % (indent, "Linkname", "Link Status", "Jobs Status")) for link in self._links.values(): if hasattr(link, 'check_statu...
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fermiPy/fermipy
fermipy/jobs/chain.py
Chain.print_summary
def print_summary(self, stream=sys.stdout, indent="", recurse_level=2): """Print a summary of the activity done by this `Chain`. Parameters ----------- stream : `file` Stream to print to, must have 'write' method. indent : str Indentation at start of li...
python
def print_summary(self, stream=sys.stdout, indent="", recurse_level=2): """Print a summary of the activity done by this `Chain`. Parameters ----------- stream : `file` Stream to print to, must have 'write' method. indent : str Indentation at start of li...
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train
https://github.com/fermiPy/fermipy/blob/9df5e7e3728307fd58c5bba36fd86783c39fbad4/fermipy/jobs/chain.py#L390-L412
fermiPy/fermipy
fermipy/diffuse/solar.py
register_classes
def register_classes(): """Register these classes with the `LinkFactory` """ Gtlink_exphpsun.register_class() Gtlink_suntemp.register_class() Gtexphpsun_SG.register_class() Gtsuntemp_SG.register_class() SunMoonChain.register_class()
python
def register_classes(): """Register these classes with the `LinkFactory` """ Gtlink_exphpsun.register_class() Gtlink_suntemp.register_class() Gtexphpsun_SG.register_class() Gtsuntemp_SG.register_class() SunMoonChain.register_class()
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fermiPy/fermipy
fermipy/diffuse/solar.py
Gtexpcube2wcs_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']) mktime = args['mktimefilter'] base_config = dict(nxpix=args['nxpix']...
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']) mktime = args['mktimefilter'] base_config = dict(nxpix=args['nxpix']...
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fermiPy/fermipy
fermipy/diffuse/solar.py
Gtexphpsun_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']) mktime = args['mktimefilter'] for comp in components: zc...
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']) mktime = args['mktimefilter'] for comp in components: zc...
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fermiPy/fermipy
fermipy/diffuse/solar.py
Gtsuntemp_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']) # FIXME mktime = args['mktimefilter'] for comp in components...
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']) # FIXME mktime = args['mktimefilter'] for comp in components...
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fermiPy/fermipy
fermipy/diffuse/solar.py
SunMoonChain._map_arguments
def _map_arguments(self, input_dict): """Map from the top-level arguments to the arguments provided to the indiviudal links """ config_yaml = input_dict['config'] config_dict = load_yaml(config_yaml) data = config_dict.get('data') comp = config_dict.get('comp') ...
python
def _map_arguments(self, input_dict): """Map from the top-level arguments to the arguments provided to the indiviudal links """ config_yaml = input_dict['config'] config_dict = load_yaml(config_yaml) data = config_dict.get('data') comp = config_dict.get('comp') ...
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fermiPy/fermipy
fermipy/diffuse/model_component.py
ModelComponentInfo.get_component_info
def get_component_info(self, comp): """Return the information about sub-component specific to a particular data selection Parameters ---------- comp : `binning.Component` object Specifies the sub-component Returns `ModelComponentInfo` object """ if ...
python
def get_component_info(self, comp): """Return the information about sub-component specific to a particular data selection Parameters ---------- comp : `binning.Component` object Specifies the sub-component Returns `ModelComponentInfo` object """ if ...
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fermiPy/fermipy
fermipy/diffuse/model_component.py
ModelComponentInfo.add_component_info
def add_component_info(self, compinfo): """Add sub-component specific information to a particular data selection Parameters ---------- compinfo : `ModelComponentInfo` object Sub-component being added """ if self.components is None: self.component...
python
def add_component_info(self, compinfo): """Add sub-component specific information to a particular data selection Parameters ---------- compinfo : `ModelComponentInfo` object Sub-component being added """ if self.components is None: self.component...
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fermiPy/fermipy
fermipy/diffuse/model_component.py
ModelComponentInfo.clone_and_merge_sub
def clone_and_merge_sub(self, key): """Clones self and merges clone with sub-component specific information Parameters ---------- key : str Key specifying which sub-component Returns `ModelComponentInfo` object """ new_comp = copy.deepcopy(self) ...
python
def clone_and_merge_sub(self, key): """Clones self and merges clone with sub-component specific information Parameters ---------- key : str Key specifying which sub-component Returns `ModelComponentInfo` object """ new_comp = copy.deepcopy(self) ...
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fermiPy/fermipy
fermipy/catalog.py
add_columns
def add_columns(t0, t1): """Add columns of table t1 to table t0.""" for colname in t1.colnames: col = t1.columns[colname] if colname in t0.columns: continue new_col = Column(name=col.name, length=len(t0), dtype=col.dtype) # , # shape=col.shape) t0.add_column...
python
def add_columns(t0, t1): """Add columns of table t1 to table t0.""" for colname in t1.colnames: col = t1.columns[colname] if colname in t0.columns: continue new_col = Column(name=col.name, length=len(t0), dtype=col.dtype) # , # shape=col.shape) t0.add_column...
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fermiPy/fermipy
fermipy/catalog.py
join_tables
def join_tables(left, right, key_left, key_right, cols_right=None): """Perform a join of two tables. Parameters ---------- left : `~astropy.Table` Left table for join. right : `~astropy.Table` Right table for join. key_left : str Key used to match eleme...
python
def join_tables(left, right, key_left, key_right, cols_right=None): """Perform a join of two tables. Parameters ---------- left : `~astropy.Table` Left table for join. right : `~astropy.Table` Right table for join. key_left : str Key used to match eleme...
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fermiPy/fermipy
fermipy/catalog.py
strip_columns
def strip_columns(tab): """Strip whitespace from string columns.""" for colname in tab.colnames: if tab[colname].dtype.kind in ['S', 'U']: tab[colname] = np.core.defchararray.strip(tab[colname])
python
def strip_columns(tab): """Strip whitespace from string columns.""" for colname in tab.colnames: if tab[colname].dtype.kind in ['S', 'U']: tab[colname] = np.core.defchararray.strip(tab[colname])
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fermiPy/fermipy
fermipy/catalog.py
row_to_dict
def row_to_dict(row): """Convert a table row to a dictionary.""" o = {} for colname in row.colnames: if isinstance(row[colname], np.string_) and row[colname].dtype.kind in ['S', 'U']: o[colname] = str(row[colname]) else: o[colname] = row[colname] return o
python
def row_to_dict(row): """Convert a table row to a dictionary.""" o = {} for colname in row.colnames: if isinstance(row[colname], np.string_) and row[colname].dtype.kind in ['S', 'U']: o[colname] = str(row[colname]) else: o[colname] = row[colname] return o
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fermiPy/fermipy
fermipy/diffuse/gt_merge_srcmaps.py
GtMergeSrcmaps.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.srcmaps, ...
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.srcmaps, ...
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fermiPy/fermipy
fermipy/diffuse/gt_merge_srcmaps.py
MergeSrcmaps_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']) ret_dict = make_catalog_comp_dict(sources=args['library'], basedir='.') ...
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']) ret_dict = make_catalog_comp_dict(sources=args['library'], basedir='.') ...
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fermiPy/fermipy
fermipy/batch.py
check_log
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python
def check_log(logfile, exited='Exited with exit code', successful='Successfully completed', exists=True): """ Often logfile doesn't exist because the job hasn't begun to run. It is unclear what you want to do in that case... Parameters ---------- logfile : str String with path...
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fermiPy/fermipy
fermipy/batch.py
dispatch_job
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python
def dispatch_job(jobname, exe, args, opts, batch_opts, dry_run=True): """Dispatch an LSF job. Parameters ---------- exe : str Execution string. args : list Positional arguments. opts : dict Dictionary of command-line options. """ batch_opts.setdefault('W', 300...
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fermiPy/fermipy
fermipy/diffuse/gt_coadd_split.py
_make_input_file_list
def _make_input_file_list(binnedfile, num_files): """Make the list of input files for a particular energy bin X psf type """ outdir_base = os.path.abspath(os.path.dirname(binnedfile)) outbasename = os.path.basename(binnedfile) filelist = "" for i in range(num_files): split_key = "%06i" % i ...
python
def _make_input_file_list(binnedfile, num_files): """Make the list of input files for a particular energy bin X psf type """ outdir_base = os.path.abspath(os.path.dirname(binnedfile)) outbasename = os.path.basename(binnedfile) filelist = "" for i in range(num_files): split_key = "%06i" % i ...
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fermiPy/fermipy
fermipy/diffuse/gt_coadd_split.py
CoaddSplit._map_arguments
def _map_arguments(self, args): """Map from the top-level arguments to the arguments provided to the indiviudal links """ comp_file = args.get('comp', None) datafile = args.get('data', None) do_ltsum = args.get('do_ltsum', False) NAME_FACTORY.update_base_dict(datafile) ...
python
def _map_arguments(self, args): """Map from the top-level arguments to the arguments provided to the indiviudal links """ comp_file = args.get('comp', None) datafile = args.get('data', None) do_ltsum = args.get('do_ltsum', False) NAME_FACTORY.update_base_dict(datafile) ...
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fermiPy/fermipy
fermipy/diffuse/gt_coadd_split.py
CoaddSplit_SG.build_job_configs
def build_job_configs(self, args): """Hook to build job configurations """ job_configs = {} components = Component.build_from_yamlfile(args['comp']) datafile = args['data'] if datafile is None or datafile == 'None': return job_configs NAME_FACTORY.up...
python
def build_job_configs(self, args): """Hook to build job configurations """ job_configs = {} components = Component.build_from_yamlfile(args['comp']) datafile = args['data'] if datafile is None or datafile == 'None': return job_configs NAME_FACTORY.up...
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fermiPy/fermipy
fermipy/spectrum.py
SpectralFunction.create_from_flux
def create_from_flux(cls, params, emin, emax, flux, scale=1.0): """Create a spectral function instance given its flux.""" params = params.copy() params[0] = 1.0 params[0] = flux / cls.eval_flux(emin, emax, params, scale=scale) return cls(params, scale)
python
def create_from_flux(cls, params, emin, emax, flux, scale=1.0): """Create a spectral function instance given its flux.""" params = params.copy() params[0] = 1.0 params[0] = flux / cls.eval_flux(emin, emax, params, scale=scale) return cls(params, scale)
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fermiPy/fermipy
fermipy/spectrum.py
SpectralFunction.create_from_eflux
def create_from_eflux(cls, params, emin, emax, eflux, scale=1.0): """Create a spectral function instance given its energy flux.""" params = params.copy() params[0] = 1.0 params[0] = eflux / cls.eval_eflux(emin, emax, params, scale=scale) return cls(params, scale)
python
def create_from_eflux(cls, params, emin, emax, eflux, scale=1.0): """Create a spectral function instance given its energy flux.""" params = params.copy() params[0] = 1.0 params[0] = eflux / cls.eval_eflux(emin, emax, params, scale=scale) return cls(params, scale)
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fermiPy/fermipy
fermipy/spectrum.py
SpectralFunction._integrate
def _integrate(cls, fn, emin, emax, params, scale=1.0, extra_params=None, npt=20): """Fast numerical integration method using mid-point rule.""" emin = np.expand_dims(emin, -1) emax = np.expand_dims(emax, -1) params = copy.deepcopy(params) for i, p in enumera...
python
def _integrate(cls, fn, emin, emax, params, scale=1.0, extra_params=None, npt=20): """Fast numerical integration method using mid-point rule.""" emin = np.expand_dims(emin, -1) emax = np.expand_dims(emax, -1) params = copy.deepcopy(params) for i, p in enumera...
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fermiPy/fermipy
fermipy/spectrum.py
SpectralFunction.dnde
def dnde(self, x, params=None): """Evaluate differential flux.""" params = self.params if params is None else params return np.squeeze(self.eval_dnde(x, params, self.scale, self.extra_params))
python
def dnde(self, x, params=None): """Evaluate differential flux.""" params = self.params if params is None else params return np.squeeze(self.eval_dnde(x, params, self.scale, self.extra_params))
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fermiPy/fermipy
fermipy/spectrum.py
SpectralFunction.ednde
def ednde(self, x, params=None): """Evaluate E times differential flux.""" params = self.params if params is None else params return np.squeeze(self.eval_ednde(x, params, self.scale, self.extra_params))
python
def ednde(self, x, params=None): """Evaluate E times differential flux.""" params = self.params if params is None else params return np.squeeze(self.eval_ednde(x, params, self.scale, self.extra_params))
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fermiPy/fermipy
fermipy/spectrum.py
SpectralFunction.e2dnde
def e2dnde(self, x, params=None): """Evaluate E^2 times differential flux.""" params = self.params if params is None else params return np.squeeze(self.eval_e2dnde(x, params, self.scale, self.extra_params))
python
def e2dnde(self, x, params=None): """Evaluate E^2 times differential flux.""" params = self.params if params is None else params return np.squeeze(self.eval_e2dnde(x, params, self.scale, self.extra_params))
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fermiPy/fermipy
fermipy/spectrum.py
SpectralFunction.dnde_deriv
def dnde_deriv(self, x, params=None): """Evaluate derivative of the differential flux with respect to E.""" params = self.params if params is None else params return np.squeeze(self.eval_dnde_deriv(x, params, self.scale, self.extra_params))
python
def dnde_deriv(self, x, params=None): """Evaluate derivative of the differential flux with respect to E.""" params = self.params if params is None else params return np.squeeze(self.eval_dnde_deriv(x, params, self.scale, self.extra_params))
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fermiPy/fermipy
fermipy/spectrum.py
SpectralFunction.ednde_deriv
def ednde_deriv(self, x, params=None): """Evaluate derivative of E times differential flux with respect to E.""" params = self.params if params is None else params return np.squeeze(self.eval_ednde_deriv(x, params, self.scale, self.extra_pa...
python
def ednde_deriv(self, x, params=None): """Evaluate derivative of E times differential flux with respect to E.""" params = self.params if params is None else params return np.squeeze(self.eval_ednde_deriv(x, params, self.scale, self.extra_pa...
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fermiPy/fermipy
fermipy/spectrum.py
SpectralFunction.e2dnde_deriv
def e2dnde_deriv(self, x, params=None): """Evaluate derivative of E^2 times differential flux with respect to E.""" params = self.params if params is None else params return np.squeeze(self.eval_e2dnde_deriv(x, params, self.scale, self.ext...
python
def e2dnde_deriv(self, x, params=None): """Evaluate derivative of E^2 times differential flux with respect to E.""" params = self.params if params is None else params return np.squeeze(self.eval_e2dnde_deriv(x, params, self.scale, self.ext...
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fermiPy/fermipy
fermipy/spectrum.py
SpectralFunction.flux
def flux(self, emin, emax, params=None): """Evaluate the integral flux.""" params = self.params if params is None else params return np.squeeze(self.eval_flux(emin, emax, params, self.scale, self.extra_params))
python
def flux(self, emin, emax, params=None): """Evaluate the integral flux.""" params = self.params if params is None else params return np.squeeze(self.eval_flux(emin, emax, params, self.scale, self.extra_params))
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fermiPy/fermipy
fermipy/spectrum.py
SpectralFunction.eflux
def eflux(self, emin, emax, params=None): """Evaluate the integral energy flux.""" params = self.params if params is None else params return np.squeeze(self.eval_eflux(emin, emax, params, self.scale, self.extra_params))
python
def eflux(self, emin, emax, params=None): """Evaluate the integral energy flux.""" params = self.params if params is None else params return np.squeeze(self.eval_eflux(emin, emax, params, self.scale, self.extra_params))
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fermiPy/fermipy
fermipy/extension.py
ExtensionFit.extension
def extension(self, name, **kwargs): """Test this source for spatial extension with the likelihood ratio method (TS_ext). This method will substitute an extended spatial model for the given source and perform a one-dimensional scan of the spatial extension parameter over the ran...
python
def extension(self, name, **kwargs): """Test this source for spatial extension with the likelihood ratio method (TS_ext). This method will substitute an extended spatial model for the given source and perform a one-dimensional scan of the spatial extension parameter over the ran...
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fermiPy/fermipy
fermipy/sed_plotting.py
plotNLL_v_Flux
def plotNLL_v_Flux(nll, fluxType, nstep=25, xlims=None): """ Plot the (negative) log-likelihood as a function of normalization nll : a LnLFN object nstep : Number of steps to plot xlims : x-axis limits, if None, take tem from the nll object returns fig,ax, which are matplotlib figure and axes o...
python
def plotNLL_v_Flux(nll, fluxType, nstep=25, xlims=None): """ Plot the (negative) log-likelihood as a function of normalization nll : a LnLFN object nstep : Number of steps to plot xlims : x-axis limits, if None, take tem from the nll object returns fig,ax, which are matplotlib figure and axes o...
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fermiPy/fermipy
fermipy/sed_plotting.py
plotCastro_base
def plotCastro_base(castroData, ylims, xlabel, ylabel, nstep=25, zlims=None, global_min=False): """ Make a color plot (castro plot) of the log-likelihood as a function of energy and flux normalization castroData : A CastroData_Base object, with the log-li...
python
def plotCastro_base(castroData, ylims, xlabel, ylabel, nstep=25, zlims=None, global_min=False): """ Make a color plot (castro plot) of the log-likelihood as a function of energy and flux normalization castroData : A CastroData_Base object, with the log-li...
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fermiPy/fermipy
fermipy/sed_plotting.py
plotCastro
def plotCastro(castroData, ylims, nstep=25, zlims=None): """ Make a color plot (castro plot) of the delta log-likelihood as a function of energy and flux normalization castroData : A CastroData object, with the log-likelihood v. normalization for each energy bin ylims ...
python
def plotCastro(castroData, ylims, nstep=25, zlims=None): """ Make a color plot (castro plot) of the delta log-likelihood as a function of energy and flux normalization castroData : A CastroData object, with the log-likelihood v. normalization for each energy bin ylims ...
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fermiPy/fermipy
fermipy/sed_plotting.py
plotSED
def plotSED(castroData, ylims, TS_thresh=4.0, errSigma=1.0, specVals=[]): """ Make a color plot (castro plot) of the (negative) log-likelihood as a function of energy and flux normalization castroData : A CastroData object, with the log-likelihood v. normalization for each energy bin...
python
def plotSED(castroData, ylims, TS_thresh=4.0, errSigma=1.0, specVals=[]): """ Make a color plot (castro plot) of the (negative) log-likelihood as a function of energy and flux normalization castroData : A CastroData object, with the log-likelihood v. normalization for each energy bin...
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fermiPy/fermipy
fermipy/sed_plotting.py
compare_SED
def compare_SED(castroData1, castroData2, ylims, TS_thresh=4.0, errSigma=1.0, specVals=[]): """ Compare two SEDs castroData1: A CastroData object, with the log-likelihood v. normalization for each energy bin castroData2: A CastroData object, with the log...
python
def compare_SED(castroData1, castroData2, ylims, TS_thresh=4.0, errSigma=1.0, specVals=[]): """ Compare two SEDs castroData1: A CastroData object, with the log-likelihood v. normalization for each energy bin castroData2: A CastroData object, with the log...
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fermiPy/fermipy
fermipy/diffuse/diffuse_src_manager.py
make_ring_dicts
def make_ring_dicts(**kwargs): """Build and return the information about the Galprop rings """ library_yamlfile = kwargs.get('library', 'models/library.yaml') gmm = kwargs.get('GalpropMapManager', GalpropMapManager(**kwargs)) if library_yamlfile is None or library_yamlfile == 'None': return ...
python
def make_ring_dicts(**kwargs): """Build and return the information about the Galprop rings """ library_yamlfile = kwargs.get('library', 'models/library.yaml') gmm = kwargs.get('GalpropMapManager', GalpropMapManager(**kwargs)) if library_yamlfile is None or library_yamlfile == 'None': return ...
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fermiPy/fermipy
fermipy/diffuse/diffuse_src_manager.py
make_diffuse_comp_info_dict
def make_diffuse_comp_info_dict(**kwargs): """Build and return the information about the diffuse components """ library_yamlfile = kwargs.pop('library', 'models/library.yaml') components = kwargs.pop('components', None) if components is None: comp_yamlfile = kwargs.pop('comp', 'config/binnin...
python
def make_diffuse_comp_info_dict(**kwargs): """Build and return the information about the diffuse components """ library_yamlfile = kwargs.pop('library', 'models/library.yaml') components = kwargs.pop('components', None) if components is None: comp_yamlfile = kwargs.pop('comp', 'config/binnin...
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fermiPy/fermipy
fermipy/diffuse/diffuse_src_manager.py
GalpropMapManager.read_galprop_rings_yaml
def read_galprop_rings_yaml(self, galkey): """ Read the yaml file for a partiuclar galprop key """ galprop_rings_yaml = self._name_factory.galprop_rings_yaml(galkey=galkey, fullpath=True) galprop_rings = yaml.safe_load(op...
python
def read_galprop_rings_yaml(self, galkey): """ Read the yaml file for a partiuclar galprop key """ galprop_rings_yaml = self._name_factory.galprop_rings_yaml(galkey=galkey, fullpath=True) galprop_rings = yaml.safe_load(op...
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https://github.com/fermiPy/fermipy/blob/9df5e7e3728307fd58c5bba36fd86783c39fbad4/fermipy/diffuse/diffuse_src_manager.py#L50-L56
fermiPy/fermipy
fermipy/diffuse/diffuse_src_manager.py
GalpropMapManager.make_ring_filename
def make_ring_filename(self, source_name, ring, galprop_run): """ Make the name of a gasmap file for a single ring Parameters ---------- source_name : str The galprop component, used to define path to gasmap files ring : int The ring index galpro...
python
def make_ring_filename(self, source_name, ring, galprop_run): """ Make the name of a gasmap file for a single ring Parameters ---------- source_name : str The galprop component, used to define path to gasmap files ring : int The ring index galpro...
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https://github.com/fermiPy/fermipy/blob/9df5e7e3728307fd58c5bba36fd86783c39fbad4/fermipy/diffuse/diffuse_src_manager.py#L77-L94
fermiPy/fermipy
fermipy/diffuse/diffuse_src_manager.py
GalpropMapManager.make_merged_name
def make_merged_name(self, source_name, galkey, fullpath): """ Make the name of a gasmap file for a set of merged rings Parameters ---------- source_name : str The galprop component, used to define path to gasmap files galkey : str A short key identifyin...
python
def make_merged_name(self, source_name, galkey, fullpath): """ Make the name of a gasmap file for a set of merged rings Parameters ---------- source_name : str The galprop component, used to define path to gasmap files galkey : str A short key identifyin...
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Make the name of a gasmap file for a set of merged rings Parameters ---------- source_name : str The galprop component, used to define path to gasmap files galkey : str A short key identifying the galprop parameters fullpath : bool Return the...
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train
https://github.com/fermiPy/fermipy/blob/9df5e7e3728307fd58c5bba36fd86783c39fbad4/fermipy/diffuse/diffuse_src_manager.py#L96-L113
fermiPy/fermipy
fermipy/diffuse/diffuse_src_manager.py
GalpropMapManager.make_xml_name
def make_xml_name(self, source_name, galkey, fullpath): """ Make the name of an xml file for a model definition for a set of merged rings Parameters ---------- source_name : str The galprop component, used to define path to gasmap files galkey : str A sh...
python
def make_xml_name(self, source_name, galkey, fullpath): """ Make the name of an xml file for a model definition for a set of merged rings Parameters ---------- source_name : str The galprop component, used to define path to gasmap files galkey : str A sh...
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https://github.com/fermiPy/fermipy/blob/9df5e7e3728307fd58c5bba36fd86783c39fbad4/fermipy/diffuse/diffuse_src_manager.py#L115-L132