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