AnalysisConfig

class gammapy.analysis.AnalysisConfig

Bases: gammapy.analysis.config.GammapyBaseConfig

Gammapy analysis configuration.

Attributes Summary

copy(self, \*, include, ForwardRef] = None, …)	Duplicate a model, optionally choose which fields to include, exclude and change.
dict(self, \*, include, ForwardRef] = None, …)	Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
fields
json(self, \*, include, ForwardRef] = None, …)	Generate a JSON representation of the model, include and exclude arguments as per dict().
to_string(self, pretty)

Methods Summary

construct(_fields_set, NoneType] = None, …)	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, pathlib.Path], \*, …)
parse_obj(obj)
parse_raw(b, bytes], \*, content_type, …)
read(path)	Reads from YAML file.
schema(by_alias)
schema_json(\*, by_alias, \*\*dumps_kwargs)
set_logging(self)	Set logging config.
to_yaml(self)	Convert to YAML string.
update(self[, 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(self, path[, overwrite])	Write to YAML file.

Attributes Documentation

copy(self: 'Model', *, include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('DictIntStrAny')] = None, exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('DictIntStrAny')] = None, update: 'DictStrAny' = None, deep: bool = False) → 'Model'

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(self, *, include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('DictIntStrAny')] = None, exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('DictIntStrAny')] = None, by_alias: bool = False, skip_defaults: bool = None, exclude_unset: bool = False, exclude_defaults: bool = False) → 'DictStrAny'

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

fields

json(self, *, include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('DictIntStrAny')] = None, exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('DictIntStrAny')] = None, by_alias: bool = False, skip_defaults: bool = None, exclude_unset: bool = False, exclude_defaults: bool = False, encoder: Union[Callable[[Any], Any], NoneType] = None, **dumps_kwargs: Any) → 'unicode'

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(self, pretty: bool = False) → 'unicode'

Methods Documentation

classmethod construct(_fields_set: Union[ForwardRef('SetStr'), NoneType] = 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(self)

Set logging config.

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

to_yaml(self)

Convert to YAML string.

update(self, 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(self, path, overwrite=False)

Write to YAML file.