FoVBackgroundModel#

class gammapy.modeling.models.FoVBackgroundModel(dataset_name, spectral_model=None, spatial_model=None, covariance_data=None)[source]#

Bases: ModelBase

Field of view background model.

The background model holds the correction parameters applied to the instrumental background attached to a MapDataset or SpectrumDataset.

Parameters:
dataset_namestr

Dataset name.

spectral_modelSpectralModel, Optional

Normalized spectral model. Default is PowerLawNormSpectralModel

spatial_modelSpatialModel, Optional

Unitless Spatial model (unit is dropped on evaluation if defined). Default is None.

Attributes Summary

covariance

default_parameters

frozen

Frozen status of a model, True if all parameters are frozen.

name

Model name.

parameters

Model parameters.

parameters_unique_names

List of unique parameter names.

spatial_model

Spatial norm model.

spectral_model

Spectral norm model.

tag

type

Methods Summary

contributes(*args, **kwargs)

FoV background models always contribute.

copy([name, copy_data])

Copy the FoVBackgroundModel instance.

evaluate(energy[, lon, lat])

Evaluate model.

evaluate_geom(geom)

Evaluate map.

freeze([model_type])

Freeze model parameters.

from_dict(data, **kwargs)

Create model from dictionary.

from_parameters(parameters, **kwargs)

Create model from parameter list.

reassign(datasets_names, new_datasets_names)

Reassign a model from one dataset to another.

reset_to_default()

Reset parameter values to default.

to_dict([full_output])

Create dictionary for YAML serialisation.

unfreeze([model_type])

Restore parameters frozen status to default.

Attributes Documentation

covariance#
default_parameters = <gammapy.modeling.parameter.Parameters object>#
frozen#

Frozen status of a model, True if all parameters are frozen.

name#

Model name.

parameters#

Model parameters.

parameters_unique_names#

List of unique parameter names. Return formatted as par_type.par_name.

spatial_model#

Spatial norm model.

spectral_model#

Spectral norm model.

tag = ['FoVBackgroundModel', 'fov-bkg']#
type#

Methods Documentation

static contributes(*args, **kwargs)[source]#

FoV background models always contribute.

copy(name=None, copy_data=False, **kwargs)[source]#

Copy the FoVBackgroundModel instance.

Parameters:
namestr, optional

Ignored, present for API compatibility. Default is None.

copy_databool, optional

Ignored, present for API compatibility. Default is False.

**kwargsdict

Keyword arguments forwarded to FoVBackgroundModel.

Returns:
modelFoVBackgroundModel

Copied FoV background model.

evaluate(energy, lon=None, lat=None)[source]#

Evaluate model.

evaluate_geom(geom)[source]#

Evaluate map.

freeze(model_type='spectral')[source]#

Freeze model parameters.

classmethod from_dict(data, **kwargs)[source]#

Create model from dictionary.

Parameters:
datadict

Data dictionary.

classmethod from_parameters(parameters, **kwargs)#

Create model from parameter list.

Parameters:
parametersParameters

Parameters for init.

Returns:
modelModel

Model instance.

reassign(datasets_names, new_datasets_names)#

Reassign a model from one dataset to another.

Parameters:
datasets_namesstr or list

Name of the datasets where the model is currently defined.

new_datasets_namesstr or list

Name of the datasets where the model should be defined instead. If multiple names are given the two list must have the save length, as the reassignment is element-wise.

Returns:
modelModel

Reassigned model.

reset_to_default()[source]#

Reset parameter values to default.

to_dict(full_output=False)[source]#

Create dictionary for YAML serialisation.

unfreeze(model_type='spectral')[source]#

Restore parameters frozen status to default.