FluxMetaData#

class gammapy.estimators.FluxMetaData[source]#

Bases: MetaData

Metadata containing information about the FluxPoints and FluxMaps.

Attributes:
sed_type{“dnde”, “flux”, “eflux”, “e2dnde”, “likelihood”}, optional

SED type.

sed_type_init{“dnde”, “flux”, “eflux”, “e2dnde”, “likelihood”}, optional

SED type of the initial data.

n_sigmafloat, optional

Significance threshold above which upper limits should be used.

n_sigma_ulfloat, optional

Significance value used for the upper limit computation.

sqrt_ts_threshold_ulfloat, optional

Threshold on the square root of the likelihood value above which upper limits should be used.

n_sigma_sensitivityfloat, optional

Sigma number for which the flux sensitivity is computed

targetTargetMetaData, optional

General metadata information about the target.

creationCreatorMetaData, optional

The creation metadata.

optionaldict, optional

additional optional metadata.

Notethese quantities are serialized in FITS header with the keywords stored in the dictionary FLUX_METADATA_FITS_KEYS

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)#