PointSpatialModel

class gammapy.modeling.models.PointSpatialModel

Bases: SpatialModel

Point Source.

For more information see Point spatial model.

Parameters:

lon_0, lat_0Angle

Center position. Default is “0 deg”, “0 deg”.

frame{“icrs”, “galactic”}

Center position coordinate frame.

Attributes Summary

default_parameters
evaluation_bin_size_min	Minimal evaluation bin size as an Angle.
evaluation_radius	Evaluation radius as an Angle.
is_energy_dependent
lat_0	A model parameter.
lon_0	A model parameter.
tag

Methods Summary

evaluate_geom(geom)	Evaluate model on Geom.
integrate_geom(geom[, oversampling_factor])	Integrate model on Geom.
to_region(**kwargs)	Model outline as a PointSkyRegion.

Attributes Documentation

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

evaluation_bin_size_min

Minimal evaluation bin size as an Angle.

evaluation_radius

Evaluation radius as an Angle.

Set as zero degrees.

is_energy_dependent

lat_0

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 or min and max properties and consider the fact that there is a factor and scale 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 and factor_max properties, i.e. the optimiser “sees” the well-scaled problem.

Parameters:

namestr

Name.

valuefloat or Quantity

Value.

scalefloat, optional

Scale (sometimes used in fitting).

unitUnit or str, optional

Unit. Default is “”.

minfloat, str or quantity, optional

Minimum (sometimes used in fitting). If None, set to numpy.nan. Default is None.

maxfloat, str or quantity, optional

Maximum (sometimes used in fitting). Default is numpy.nan.

frozenbool, optional

Frozen (used in fitting). Default is False.

errorfloat, optional

Parameter error. Default is 0.

scan_minfloat, optional

Minimum value for the parameter scan. Overwrites scan_n_sigma. Default is None.

scan_maxfloat, optional

Maximum value for the parameter scan. Overwrites scan_n_sigma. Default is None.

scan_n_values: int, optional

Number of values to be used for the parameter scan. Default is 11.

scan_n_sigmaint, optional

Number of sigmas to scan. Default is 2.

scan_values: `numpy.array`, optional

Scan values. Overwrites all the scan keywords before. Default is None.

scale_method{‘scale10’, ‘factor1’, None}, optional

Method used to set factor and scale. Default is “scale10”.

interp{“lin”, “sqrt”, “log”}, optional

Parameter scaling to use for the scan. Default is “lin”.

priorPrior, optional

Prior set on the parameter. Default is None.

lon_0

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 or min and max properties and consider the fact that there is a factor and scale 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 and factor_max properties, i.e. the optimiser “sees” the well-scaled problem.

Parameters:

namestr

Name.

valuefloat or Quantity

Value.

scalefloat, optional

Scale (sometimes used in fitting).

unitUnit or str, optional

Unit. Default is “”.

minfloat, str or quantity, optional

Minimum (sometimes used in fitting). If None, set to numpy.nan. Default is None.

maxfloat, str or quantity, optional

Maximum (sometimes used in fitting). Default is numpy.nan.

frozenbool, optional

Frozen (used in fitting). Default is False.

errorfloat, optional

Parameter error. Default is 0.

scan_minfloat, optional

Minimum value for the parameter scan. Overwrites scan_n_sigma. Default is None.

scan_maxfloat, optional

Maximum value for the parameter scan. Overwrites scan_n_sigma. Default is None.

scan_n_values: int, optional

Number of values to be used for the parameter scan. Default is 11.

scan_n_sigmaint, optional

Number of sigmas to scan. Default is 2.

scan_values: `numpy.array`, optional

Scan values. Overwrites all the scan keywords before. Default is None.

scale_method{‘scale10’, ‘factor1’, None}, optional

Method used to set factor and scale. Default is “scale10”.

interp{“lin”, “sqrt”, “log”}, optional

Parameter scaling to use for the scan. Default is “lin”.

priorPrior, optional

Prior set on the parameter. Default is None.

tag = ['PointSpatialModel', 'point']

Methods Documentation

evaluate_geom(geom)

Evaluate model on Geom.

integrate_geom(geom, oversampling_factor=None)

Integrate model on Geom.

Parameters:

geomGeom

Map geometry.

Returns:

fluxMap

Predicted flux map.

to_region(**kwargs)

Model outline as a PointSkyRegion.

__init__(**kwargs)

classmethod __new__(*args, **kwargs)