SkyModel

class gammapy.modeling.models.SkyModel(spectral_model, spatial_model=None, temporal_model=None, name=None, apply_irf=None, datasets_names=None)

Bases: gammapy.modeling.models.SkyModelBase

Sky model component.

This model represents a factorised sky model. It has Parameters combining the spatial and spectral parameters.

Parameters

spectral_modelSpectralModel

Spectral model

spatial_modelSpatialModel

Spatial model (must be normalised to integrate to 1)

temporal_modeltemporalModel

Temporal model

namestr

Model identifier

Attributes Summary

covariance
default_parameters
evaluation_radius	Angle
frame
name
parameters	Parameters (Parameters)
position	SkyCoord
spatial_model	SpatialModel
spectral_model	SpectralModel
tag
temporal_model	TemporalModel

Methods Summary

__call__(self, lon, lat, energy[, time])	Call self as a function.
copy(self[, name])	Copy SkyModel
create(tag, \*args, \*\*kwargs)	Create a model instance.
evaluate(self, lon, lat, energy[, time])	Evaluate the model at given points.
evaluate_geom(self, geom[, gti])	Evaluate model on Geom.
from_dict(data)	Create SkyModel from dict
from_parameters(parameters, \*\*kwargs)	Create model from parameter list
integrate_geom(self, geom[, gti])	Integrate model on Geom.
to_dict(self)	Create dict for YAML serilisation

Attributes Documentation

covariance

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

evaluation_radius

Angle

frame

name

parameters

Parameters (Parameters)

position

SkyCoord

spatial_model

SpatialModel

spectral_model

SpectralModel

tag = 'SkyModel'

temporal_model

TemporalModel

Methods Documentation

__call__(self, lon, lat, energy, time=None)

Call self as a function.

copy(self, name=None, **kwargs)

Copy SkyModel

static create(tag, *args, **kwargs)

Create a model instance.

Examples

>>> from gammapy.modeling.models import Model
>>> spectral_model = Model.create("PowerLaw2SpectralModel", amplitude="1e-10 cm-2 s-1", index=3)
>>> type(spectral_model)
gammapy.modeling.models.spectral.PowerLaw2SpectralModel

evaluate(self, lon, lat, energy, time=None)

Evaluate the model at given points.

The model evaluation follows numpy broadcasting rules.

Return differential surface brightness cube. At the moment in units: cm-2 s-1 TeV-1 deg-2

Parameters

lon, latQuantity

Spatial coordinates

energyQuantity

Energy coordinate

time: `~astropy.time.Time`

Time co-ordinate

Returns

valueQuantity

Model value at the given point.

evaluate_geom(self, geom, gti=None)

Evaluate model on Geom.

classmethod from_dict(data)

Create SkyModel from dict

classmethod from_parameters(parameters, **kwargs)

Create model from parameter list

Parameters

parametersParameters

Parameters for init

Returns

modelModel

Model instance

integrate_geom(self, geom, gti=None)

Integrate model on Geom.

Parameters

geomGeom

Map geometry

gtiGTI

GIT table

Returns

fluxMap

Predicted flux map

to_dict(self)

Create dict for YAML serilisation