AnalysisConfig

class gammapy.analysis.AnalysisConfig

Bases: gammapy.analysis.config.GammapyBaseConfig

Gammapy analysis configuration.

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

Raises ValidationError if the input data cannot be parsed to form a valid model.

Attributes Summary

copy	Duplicate a model, optionally choose which fields to include, exclude and change.
dict	Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
json	Generate a JSON representation of the model, include and exclude arguments as per dict().

Methods Summary

construct([_fields_set])	Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
from_orm(obj)
from_yaml(config_str)	Create from YAML string.
parse_file(path, *[, content_type, …])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, …])
read(path)	Reads from YAML file.
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
set_logging()	Set logging config.
to_yaml()	Convert to YAML string.
update([config])	Update config with provided settings.
update_forward_refs(**localns)	Try to update ForwardRefs on fields based on this Model, globalns and localns.
validate(value)
write(path[, overwrite])	Write to YAML file.

Attributes Documentation

copy

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters

• include – fields to include in new model

• exclude – fields to exclude from new model, as with values this takes precedence over include

• update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data

• deep – set to True to make a deep copy of the model

Returns

new model instance

dict

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

json

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

Methods Documentation

classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

classmethod from_orm(obj: Any) → Model

classmethod from_yaml(config_str)

Create from YAML string.

classmethod parse_file(path: Union[str, pathlib.Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model

classmethod parse_obj(obj: Any) → Model

classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model

classmethod read(path)

Reads from YAML file.

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode

set_logging()

Set logging config.

Calls logging.basicConfig, i.e. adjusts global logging state.

to_yaml()

Convert to YAML string.

update(config=None)

Update config with provided settings.

Parameters

configstring dict or AnalysisConfig object

Configuration settings provided in dict() syntax.

classmethod update_forward_refs(**localns: Any) → None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) → Model

write(path, overwrite=False)

Write to YAML file.