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

Attributes Summary

`free_parameters`	List of free parameters
`names`	List of parameter names
`restore_values`	Context manager to restore values.
`unique_parameters`	Unique parameters (`Parameters`).
`values`	Parameter values (`numpy.ndarray`).

Methods Summary

`autoscale`(self[, method])	Autoscale all parameters.
`copy`(self)	A deep copy
`count`(self, value)
`freeze_all`(self)	Freeze all parameters
`from_dict`(data)
`from_stack`(parameters_list)	Create `Parameters` by stacking a list of other `Parameters` objects.
`index`(self, val)	Get position index for a given parameter.
`set_parameter_factors`(self, factors)	Set factor of all parameters.
`to_dict`(self)
`to_table`(self)	Convert parameter attributes to `Table`.

Attributes Documentation

free_parameters¶: List of free parameters

names¶: List of parameter names

restore_values¶

Context manager to restore values.

A copy of the values is made on enter, and those values are restored on exit.

Examples

from gammapy.modeling.models import PowerLawSpectralModel
pwl = PowerLawSpectralModel(index=2)
with pwl.parameters.restore_values:
    pwl.parameters["index"].value = 3
print(pwl.parameters["index"].value)

unique_parameters¶: Unique parameters (Parameters).

values¶: Parameter values (numpy.ndarray).

Methods Documentation

autoscale(self, method='scale10')[source]¶

Autoscale all parameters.

See autoscale()

Parameters

method{‘factor1’, ‘scale10’}: Method to apply

copy(self)[source]¶: A deep copy

count(self, value)¶

freeze_all(self)[source]¶: Freeze all parameters

classmethod from_dict(data)[source]¶

classmethod from_stack(parameters_list)[source]¶

Create Parameters by stacking a list of other Parameters objects.

Parameters

parameters_listlist of Parameters: List of Parameters objects

index(self, 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.

set_parameter_factors(self, factors)[source]¶

Set factor of all parameters.

Used in the optimizer interface.

to_dict(self)[source]¶

to_table(self)[source]¶: Convert parameter attributes to Table.