ConstantTemporalModel#
- class gammapy.modeling.models.ConstantTemporalModel(**kwargs)[source]#
Bases:
gammapy.modeling.models.temporal.TemporalModel
Constant temporal model.
For more information see Constant temporal model.
Attributes Summary
Frozen status of a model, True if all parameters are frozen
Parameters (
Parameters
)Methods Summary
__call__
(time)Evaluate model
copy
(**kwargs)evaluate
(time)Evaluate at given times.
freeze
()Freeze all parameters
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, n_points])Plot Temporal Model.
reassign
(datasets_names, new_datasets_names)Reassign a model from one dataset to another
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
unfreeze
()Restore parameters frozen status to default
Attributes Documentation
- covariance#
- default_parameters = <gammapy.modeling.parameter.Parameters object>#
- frozen#
Frozen status of a model, True if all parameters are frozen
- parameters#
Parameters (
Parameters
)
- tag = ['ConstantTemporalModel', 'const']#
- type#
Methods Documentation
- copy(**kwargs)#
- freeze()#
Freeze all parameters
- classmethod from_dict(data)#
- classmethod from_parameters(parameters, **kwargs)#
Create model from parameter list
- Parameters
- parameters
Parameters
Parameters for init
- parameters
- Returns
- model
Model
Model instance
- model
- plot(time_range, ax=None, n_points=100, **kwargs)#
Plot Temporal Model.
- reassign(datasets_names, new_datasets_names)#
Reassign a model from one dataset to another
- Parameters
- datasets_namesstr or list
Name of the datasets where the model is currently defined
- new_datasets_namesstr or list
Name of the datasets where the model should be defined instead. If multiple names are given the two list must have the save length, as the reassignment is element-wise.
- Returns
- model
Model
Reassigned model.
- model
- sample_time(n_events, t_min, t_max, t_delta='1 s', random_state=0)#
Sample arrival times of events.
- Parameters
- n_eventsint
Number of events to sample.
- t_min
Time
Start time of the sampling.
- t_max
Time
Stop time of the sampling.
- t_delta
Quantity
Time step used for sampling of the temporal model.
- random_state{int, ‘random-seed’, ‘global-rng’,
RandomState
} Defines random number generator initialisation. Passed to
get_random_state
.
- Returns
- time
Quantity
Array with times of the sampled events.
- time
- static time_sum(t_min, t_max)#
Total time between t_min and t_max
- to_dict(full_output=False)#
Create dict for YAML serialisation
- unfreeze()#
Restore parameters frozen status to default