ConstantFluxSpatialModel#

class gammapy.modeling.models.ConstantFluxSpatialModel(**kwargs)[source]#

Bases: SpatialModel

Spatially constant flux spatial model.

For more information see Constant spatial model.

Attributes Summary

`covariance`
`default_parameters`
`evaluation_bin_size_min`
`evaluation_radius`
`evaluation_region`	Evaluation region.
`frame`
`frozen`	Frozen status of a model, True if all parameters are frozen.
`is_energy_dependent`
`parameters`	Parameters as a `Parameters` object.
`phi_0`
`position`
`position_error`	Get 95% containment position error as `EllipseSkyRegion`.
`position_lonlat`	Spatial model center position `(lon, lat)` in radians and frame of the model.
`tag`
`type`

Methods Summary

`__call__`(lon, lat[, energy])	Call evaluate method.
`copy`(**kwargs)	Deep copy.
`evaluate`(lon, lat)	Evaluate model.
`evaluate_geom`(geom)	Evaluate model.
`freeze`()	Freeze all parameters.
`from_dict`(data, **kwargs)	Create a spatial model from a dictionary.
`from_parameters`(parameters, **kwargs)	Create model from parameter list.
`from_position`(position, **kwargs)	Define the position of the model using a `SkyCoord`.
`integrate_geom`(geom[, oversampling_factor])	Evaluate model.
`plot`([ax, geom])	Plot spatial model.
`plot_error`([ax, which, kwargs_position, ...])	Plot the errors of the spatial model.
`plot_grid`([geom])	Plot spatial model energy slices in a grid.
`plot_interactive`([ax, geom])	Plot spatial model.
`plot_position_error`([ax])	Plot position error.
`reassign`(datasets_names, new_datasets_names)	Reassign a model from one dataset to another.
`to_dict`([full_output])	Create dictionary for YAML serilisation.
`to_region`(**kwargs)	Model outline as a `RectangleSkyRegion`.
`unfreeze`()	Restore parameters frozen status to default.

Attributes Documentation

covariance#

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

evaluation_bin_size_min#

evaluation_radius = None#

evaluation_region#: Evaluation region.

frame = 'icrs'#

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

is_energy_dependent#

parameters#: Parameters as a Parameters object.

phi_0#

position = None#

position_error#: Get 95% containment position error as EllipseSkyRegion.

position_lonlat#: Spatial model center position (lon, lat) in radians and frame of the model.

tag = ['ConstantFluxSpatialModel', 'const-flux']#

type#

Methods Documentation

__call__(lon, lat, energy=None)#: Call evaluate method.

copy(**kwargs)#: Deep copy.

static evaluate(lon, lat)[source]#: Evaluate model.

static evaluate_geom(geom)[source]#: Evaluate model.

freeze()#: Freeze all parameters.

classmethod from_dict(data, **kwargs)#

Create a spatial model from a dictionary.

Parameters:

datadict: Dictionary containing model parameters.
kwargsdict: Keyword arguments passed to from_parameters.

classmethod from_parameters(parameters, **kwargs)#

Create model from parameter list.

Parameters:

parametersParameters: Parameters for init.

Returns:

modelModel: Model instance.

classmethod from_position(position, **kwargs)#

Define the position of the model using a SkyCoord.

The model will be created in the frame of the SkyCoord.

Parameters:

positionSkyCoord: Position.

Returns:

modelSpatialModel: Spatial model.

static integrate_geom(geom, oversampling_factor=None)[source]#: Evaluate model.

plot(ax=None, geom=None, **kwargs)#

Plot spatial model.

Parameters:

axAxes, optional: Matplotlib axes. Default is None.
geomWcsGeom, optional: Geometry to use for plotting. Default is None.
**kwargsdict: Keyword arguments passed to plot().

Returns:

axAxes, optional: Matplotlib axes.

plot_error(ax=None, which='position', kwargs_position=None, kwargs_extension=None)#

Plot the errors of the spatial model.

Parameters:

axAxes, optional

Matplotlib axes to plot the errors on. Default is None.

which: list of str

Which errors to plot. Available options are:

“all”: all the optional steps are plotted

“position”: plot the position error of the spatial model

“extension”: plot the extension error of the spatial model

kwargs_positiondict, optional

Keyword arguments passed to plot_position_error. Default is None.

kwargs_extensiondict, optional

Keyword arguments passed to plot_extension_error. Default is None.

Returns:

axAxes, optional: Matplotlib axes.

plot_grid(geom=None, **kwargs)#

Plot spatial model energy slices in a grid.

Parameters:

geomWcsGeom, optional: Geometry to use for plotting. Default is None.
**kwargsdict: Keyword arguments passed to plot().

Returns:

axAxes, optional: Matplotlib axes.

plot_interactive(ax=None, geom=None, **kwargs)#

Plot spatial model.

Parameters:

axAxes, optional: Matplotlib axes. Default is None.
geomWcsGeom, optional: Geom to use for plotting. Default is None.
**kwargsdict: Keyword arguments passed to plot().

Returns:

axAxes, optional: Matplotlib axes.

plot_position_error(ax=None, **kwargs)#

Plot position error.

Parameters:

axAxes, optional: Matplotlib axes to plot the position error on. Default is None.
**kwargsdict: Keyword arguments passed to plot().

Returns:

axAxes, optional: Matplotlib axes.

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.

to_dict(full_output=False)[source]#: Create dictionary for YAML serilisation.

to_region(**kwargs)[source]#: Model outline as a RectangleSkyRegion.

unfreeze()#: Restore parameters frozen status to default.