FluxPointsConfig

class gammapy.analysis.FluxPointsConfig

Bases: GammapyBaseConfig

Configuration for the FluxPointsEstimator.

Attributes:

energydict

Energy binning for the light curve. Should contain the following keys ‘min’ and ‘max’ (with energy quantities) and ‘nbins’.

sourcestr

Source name.

parametersdict

Optional parameters such as selection filters, options are: “all”, “errn-errp”, “ul”, “scan”

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)