ConstantTemporalModel¶

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

Bases: gammapy.modeling.models.TemporalModel

Constant temporal model.

Attributes Summary

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

Methods Summary

`__call__`(time)	Evaluate model
`copy`()	A deep copy.
`create`(tag[, model_type])	Create a model instance.
`evaluate`(time)	Evaluate at given times.
`from_dict`(data)
`from_parameters`(parameters, **kwargs)	Create model from parameter list
`integral`(t_min, t_max)	Evaluate the integrated flux within the given time intervals
`plot`(time_range[, ax])	Plot Temporal Model.
`sample_time`(n_events, t_min, t_max[, …])	Sample arrival times of events.
`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)

tag = ['ConstantTemporalModel', 'const']¶

type¶

Methods Documentation

__call__(time)¶

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

static evaluate(time)[source]¶: Evaluate at given times.

classmethod from_dict(data)¶

classmethod from_parameters(parameters, **kwargs)¶

Create model from parameter list

Parameters

parametersParameters: Parameters for init

Returns

modelModel: Model instance

integral(t_min, t_max)[source]¶

Evaluate the integrated flux within the given time intervals

Parameters

t_min: `~astropy.time.Time`: Start times of observation
t_max: `~astropy.time.Time`: Stop times of observation

Returns

normQuantity: Integrated flux norm on the given time intervals

plot(time_range, ax=None)¶

Plot Temporal Model.

Parameters

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

Returns

axAxes, optional: axis

static sample_time(n_events, t_min, t_max, random_state=0)[source]¶

Sample arrival times of events.

Parameters

n_eventsint: Number of events to sample.
t_minTime: Start time of the sampling.
t_maxTime: Stop time of the sampling.
random_state{int, ‘random-seed’, ‘global-rng’, RandomState}: Defines random number generator initialisation. Passed to get_random_state.

Returns

timeQuantity: Array with times of the sampled events.

static time_sum(t_min, t_max)¶

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