FitConfig#

class gammapy.analysis.FitConfig[source]#

Bases: GammapyBaseConfig

Configuration for model fitting.

Attributes:
fit_rangedict

Energy range used during the fit. Should contain the following keys ‘min’ and ‘max’ (with energy quantities).

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Attributes Summary

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

Attributes Documentation

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid', 'use_enum_values': True, 'validate_assignment': True, 'validate_default': True}#

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

__init__(**data)#

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

data (Any)

Return type:

None

classmethod __new__(*args, **kwargs)#