Parameters#
- class gammapy.modeling.Parameters(parameters=None)[source]#
Bases:
collections.abc.Sequence
Parameters container.
List of
Parameter
objects.Covariance matrix.
- Parameters
- parameterslist of
Parameter
List of parameters
- parameterslist of
Attributes Summary
List of free parameters
Parameter maxima (
numpy.ndarray
).Parameter mins (
numpy.ndarray
).List of parameter names
Parameter types
Unique parameters (
Parameters
).Parameter values (
numpy.ndarray
).Methods Summary
Autoscale all parameters.
Check parameter limits and emit a warning
copy
()A deep copy
count
(value)Freeze all parameters
from_dict
(data)from_stack
(parameters_list)Create
Parameters
by stacking a list of otherParameters
objects.index
(val)Get position index for a given parameter.
restore_status
([restore_values])Context manager to restore status.
select
([name, type, frozen])Create a mask of models, true if all conditions are verified
set_parameter_factors
(factors)Set factor of all parameters.
to_dict
()to_table
()Convert parameter attributes to
Table
.Unfreeze all parameters (even those frozen by default)
Attributes Documentation
- free_parameters#
List of free parameters
- max#
Parameter maxima (
numpy.ndarray
).
- min#
Parameter mins (
numpy.ndarray
).
- names#
List of parameter names
- types#
Parameter types
- unique_parameters#
Unique parameters (
Parameters
).
- value#
Parameter values (
numpy.ndarray
).
Methods Documentation
- autoscale()[source]#
Autoscale all parameters.
See
autoscale()
- count(value) integer -- return number of occurrences of value #
- classmethod from_stack(parameters_list)[source]#
Create
Parameters
by stacking a list of otherParameters
objects.- Parameters
- parameters_listlist of
Parameters
List of
Parameters
objects
- parameters_listlist of
- index(val)[source]#
Get position index for a given parameter.
The input can be a parameter object, parameter name (str) or if a parameter index (int) is passed in, it is simply returned.
- restore_status(restore_values=True)[source]#
Context manager to restore status.
A copy of the values is made on enter, and those values are restored on exit.
- Parameters
- restore_valuesbool
Restore values if True, otherwise restore only frozen status.
Examples
from gammapy.modeling.models import PowerLawSpectralModel pwl = PowerLawSpectralModel(index=2) with pwl.parameters.restore_status(): pwl.parameters["index"].value = 3 print(pwl.parameters["index"].value)
- select(name=None, type=None, frozen=None)[source]#
Create a mask of models, true if all conditions are verified
- Parameters
- namestr or list
Name of the parameter
- type{None, spatial, spectral, temporal}
type of models
- frozenbool
Select frozen parameters if True, exclude them if False.
- Returns
- parameters
Parameters
Selected parameters
- parameters