TemporalModel¶

class gammapy.modeling.models.TemporalModel(**kwargs)[source]¶

Bases: gammapy.modeling.models.core.Model

Temporal model base class. evaluates on astropy.time.Time objects

Attributes Summary

`covariance`
`default_parameters`
`parameters`	Parameters (`Parameters`)
`type`

Methods Summary

`__call__`(time)	Evaluate model
`copy`()	A deep copy.
`create`(tag[, model_type])	Create a model instance.
`from_dict`(data)
`from_parameters`(parameters, **kwargs)	Create model from parameter list
`plot`(time_range[, ax])	Plot Temporal Model.
`time_sum`(t_min, t_max)	Total time between t_min and t_max
`to_dict`([full_output])	Create dict for YAML serialisation

Attributes Documentation

covariance¶

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

parameters¶: Parameters (Parameters)

type¶

Methods Documentation

__call__(time)[source]¶

Evaluate model

Parameters

timeTime: Time object

copy()¶: A deep copy.

static create(tag, model_type=None, *args, **kwargs)¶

Create a model instance.

Examples

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

classmethod from_dict(data)¶

classmethod from_parameters(parameters, **kwargs)¶

Create model from parameter list

Parameters

parametersParameters: Parameters for init

Returns

modelModel: Model instance

plot(time_range, ax=None)[source]¶

Plot Temporal Model.

Parameters

time_rangeTime: times to plot the model
axAxes, optional: axis

Returns

axAxes, optional: axis

static time_sum(t_min, t_max)[source]¶

Total time between t_min and t_max

Parameters

t_min, t_max: `~astropy.time.Time`: Lower and upper bound of integration range

Returns

time_sumTimeDelta: Summed time in the intervals.

to_dict(full_output=False)¶: Create dict for YAML serialisation