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

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])
schema_json(*[, by_alias])
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.

fields

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().

to_string

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.

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) → DictStrAny

classmethod schema_json(*, by_alias: bool = True, **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.