ObservationMetaData

class gammapy.data.ObservationMetaData

Bases: MetaData

Metadata containing information about the Observation.

Parameters:

obs_infoObsInfoMetaData

The general observation information.

pointingPointingInfoMetaData

The pointing metadata.

targetTargetMetaData

The target metadata.

creationCreatorMetaData

The creation metadata.

locationEarthLocation or str, optional

The observatory location.

deadtime_fractionfloat

The observation deadtime fraction. Default is 0.

optionaldict, optional

Additional optional metadata.

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].

Methods Summary

from_header(header[, format])

Create and fill the observation metadata from the event list metadata.

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].

Methods Documentation

classmethod from_header(header, format='gadf')

Create and fill the observation metadata from the event list metadata.

Parameters:

headerdict

Input FITS header.

formatstr

The header data format. Default is gadf.

__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)