SkyDiffuseCube¶
-
class
gammapy.modeling.models.
SkyDiffuseCube
(map, norm=<Quantity 1.>, tilt=<Quantity 0.>, reference=<Quantity 1. TeV>, meta=None, interp_kwargs=None, name='diffuse', filename=None)[source]¶ Bases:
gammapy.modeling.models.SkyModelBase
Cube sky map template model (3D).
This is for a 3D map with an energy axis. Use
TemplateSpatialModel
for 2D maps.- Parameters
- map
Map
Map template
- normfloat
Norm parameter (multiplied with map values)
- tiltfloat
Additional tilt in the spectrum
- reference
Quantity
Reference energy of the tilt.
- metadict, optional
Meta information, meta[‘filename’] will be used for serialization
- interp_kwargsdict
Interpolation keyword arguments passed to
gammapy.maps.Map.interp_by_coord
. Default arguments are {‘interp’: ‘linear’, ‘fill_value’: 0}.
- map
Attributes Summary
A model parameter.
Parameters (
Parameters
)A model parameter.
A model parameter.
Methods Summary
__call__
(self, lon, lat, energy)Call self as a function.
copy
(self)A shallow copy
create
(tag, \*args, \*\*kwargs)Create a model instance.
evaluate
(self, lon, lat, energy)Evaluate model.
evaluate_geom
(self, geom)from_dict
(data)read
(filename, \*\*kwargs)Read map from FITS file.
to_dict
(self)Create dict for YAML serialisation
Attributes Documentation
-
default_parameters
= <gammapy.modeling.parameter.Parameters object>¶
-
frame
¶
-
norm
¶ A model parameter.
Note that the parameter value has been split into a factor and scale like this:
value = factor x scale
Users should interact with the
value
,quantity
ormin
andmax
properties and consider the fact that there is afactor`
andscale
an implementation detail.That was introduced for numerical stability in parameter and error estimation methods, only in the Gammapy optimiser interface do we interact with the
factor
,factor_min
andfactor_max
properties, i.e. the optimiser “sees” the well-scaled problem.
-
parameters
¶ Parameters (
Parameters
)
-
reference
¶ A model parameter.
Note that the parameter value has been split into a factor and scale like this:
value = factor x scale
Users should interact with the
value
,quantity
ormin
andmax
properties and consider the fact that there is afactor`
andscale
an implementation detail.That was introduced for numerical stability in parameter and error estimation methods, only in the Gammapy optimiser interface do we interact with the
factor
,factor_min
andfactor_max
properties, i.e. the optimiser “sees” the well-scaled problem.
-
tag
= 'SkyDiffuseCube'¶
-
tilt
¶ A model parameter.
Note that the parameter value has been split into a factor and scale like this:
value = factor x scale
Users should interact with the
value
,quantity
ormin
andmax
properties and consider the fact that there is afactor`
andscale
an implementation detail.That was introduced for numerical stability in parameter and error estimation methods, only in the Gammapy optimiser interface do we interact with the
factor
,factor_min
andfactor_max
properties, i.e. the optimiser “sees” the well-scaled problem.
Methods Documentation
-
__call__
(self, lon, lat, energy)¶ Call self as a function.
-
static
create
(tag, *args, **kwargs)¶ Create a model instance.
Examples
>>> from gammapy.modeling 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_geom
(self, geom)¶