MMMIdataSchema

class pymc_marketing.data.idata.schema.MMMIdataSchema(**data)

Complete schema for multidimensional MMM InferenceData.

Defines expected groups and variables for a fitted MMM model, with configuration based on model settings.

Parameters:

model_typeLiteral[“mmm”], default “mmm”

Model type (currently only MMM supported)

groupsdict of str to InferenceDataGroupSchema

Schema for each InferenceData group

custom_dimstuple of str, default ()

Custom dimensions beyond standard (date, channel)

Examples

>>> schema = MMMIdataSchema.from_model_config(
...     custom_dims=("country",),
...     has_controls=True,
...     has_seasonality=False,
...     time_varying=False,
... )
>>> errors = schema.validate(mmm.idata)
>>> if errors:
...     print("Validation errors:", errors)

Methods

MMMIdataSchema.__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
MMMIdataSchema.construct([_fields_set])
MMMIdataSchema.copy(*[, include, exclude, ...])	Returns a copy of the model.
MMMIdataSchema.dict(*[, include, exclude, ...])
MMMIdataSchema.from_model_config([...])	Create schema based on model configuration.
MMMIdataSchema.from_orm(obj)
MMMIdataSchema.json(*[, include, exclude, ...])
MMMIdataSchema.model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
MMMIdataSchema.model_copy(*[, update, deep])	!!! abstract "Usage Documentation"
MMMIdataSchema.model_dump(*[, mode, ...])	!!! abstract "Usage Documentation"
MMMIdataSchema.model_dump_json(*[, indent, ...])	!!! abstract "Usage Documentation"
MMMIdataSchema.model_json_schema([by_alias, ...])	Generates a JSON schema for a model class.
MMMIdataSchema.model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
MMMIdataSchema.model_post_init(context, /)	Override this method to perform additional initialization after __init__ and model_construct.
MMMIdataSchema.model_rebuild(*[, force, ...])	Try to rebuild the pydantic-core schema for the model.
MMMIdataSchema.model_validate(obj, *[, ...])	Validate a pydantic model instance.
MMMIdataSchema.model_validate_json(json_data, *)	!!! abstract "Usage Documentation"
MMMIdataSchema.model_validate_strings(obj, *)	Validate the given object with string data against the Pydantic model.
MMMIdataSchema.parse_file(path, *[, ...])
MMMIdataSchema.parse_obj(obj)
MMMIdataSchema.parse_raw(b, *[, ...])
MMMIdataSchema.schema([by_alias, ref_template])
MMMIdataSchema.schema_json(*[, by_alias, ...])
MMMIdataSchema.update_forward_refs(**localns)
MMMIdataSchema.validate(idata)	Validate InferenceData against schema.
MMMIdataSchema.validate_or_raise(idata)	Validate InferenceData, raising detailed exception if invalid.

Attributes

model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
model_type
groups
custom_dims