TemplateNPredModel

class gammapy.modeling.models.TemplateNPredModel

Bases: ModelBase

Background model.

Create a new map by a tilt and normalization on the available map.

Parameters:

mapMap

Background model map.

spectral_modelSpectralModel

Normalized spectral model. Default is PowerLawNormSpectralModel.

copy_databool

Create a deepcopy of the map data or directly use the original. Default is True. Use False to save memory in case of large maps.

spatial_modelSpatialModel

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

Attributes Summary

default_parameters
energy_center	True energy axis bin centers as a Quantity.
evaluation_radius	Evaluation radius as a Angle.
map	A lazy FITS data descriptor.
name
parameters	Parameters as a Parameters object.
parameters_unique_names	List of unique parameter names.
position	Position as a SkyCoord.
spectral_model	Spectral model as a SpectralModel object.
tag

Methods Summary

copy([name, copy_data])	Copy template npred model.
cutout(position, width[, mode, name])	Cutout background model.
evaluate()	Evaluate background model.
freeze([model_type])	Freeze model parameters.
from_dict(data, **kwargs)
slice_by_energy([energy_min, energy_max, name])	Select and slice model template in energy range.
stack(other[, weights, nan_to_num])	Stack background model in place.
to_dict([full_output])	Create dictionary for YAML serialisation.
unfreeze([model_type])	Restore parameters frozen status to default.
write([overwrite])	Write the map.

Attributes Documentation

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

energy_center

True energy axis bin centers as a Quantity.

evaluation_radius

Evaluation radius as a Angle.

map

A lazy FITS data descriptor.

Parameters:

cachebool

Whether to cache the data.

name

parameters

parameters_unique_names

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

position

Position as a SkyCoord.

spectral_model

Spectral model as a SpectralModel object.

tag = 'TemplateNPredModel'

Methods Documentation

copy(name=None, copy_data=False, **kwargs)

Copy template npred model.

Parameters:

namestr, optional

Assign a new name to the copied model. Default is None.

copy_databool, optional

Copy the data arrays attached to models. Default is False.

**kwargsdict

Keyword arguments forwarded to TemplateNPredModel.

Returns:

modelTemplateNPredModel

Copied template npred model.

cutout(position, width, mode='trim', name=None)

Cutout background model.

Parameters:

positionSkyCoord

Center position of the cutout region.

widthtuple of Angle

Angular sizes of the region in (lon, lat) in that specific order. If only one value is passed, a square region is extracted.

mode{‘trim’, ‘partial’, ‘strict’}

Mode option for Cutout2D, for details see Cutout2D. Default is “trim”.

namestr, optional

Name of the returned background model. Default is None.

Returns:

cutoutTemplateNPredModel

Cutout background model.

evaluate()

Evaluate background model.

Returns:

background_mapMap

Background evaluated on the Map.

freeze(model_type='spectral')

Freeze model parameters.

classmethod from_dict(data, **kwargs)

slice_by_energy(energy_min=None, energy_max=None, name=None)

Select and slice model template in energy range.

Parameters:

energy_min, energy_maxQuantity

Energy bounds of the slice. Default is None.

namestr

Name of the sliced model. Default is None.

Returns:

modelTemplateNpredModel

Sliced Model.

stack(other, weights=None, nan_to_num=True)

Stack background model in place.

Stacking the background model resets the current parameters values.

Parameters:

otherTemplateNPredModel

Other background model.

weightsfloat, optional

Weights. Default is None.

nan_to_num: bool, optional

Non-finite values are replaced by zero if True. Default is True.

to_dict(full_output=False)

Create dictionary for YAML serialisation.

unfreeze(model_type='spectral')

Restore parameters frozen status to default.

write(overwrite=False)

Write the map.

Parameters:

overwrite: bool, optional

Overwrite existing file. Default is False, which will raise a warning if the template file exists already.

__init__(map, spectral_model=None, name=None, filename=None, datasets_names=None, copy_data=True, spatial_model=None, covariance_data=None)

classmethod __new__(*args, **kwargs)