TimesfmHyperparams

timesfm_model.TimesfmHyperparams · inherits PydanticBaseModel

A container for TimesFM model hyperparameters.

__init__(self, **data)

Initializes the Pydantic model.

Parameter	Type	Default	Description

TimesfmModel

timesfm_model.TimesfmModel · inherits BaseModel

Initialize TimesFM model.

__init__(self, params, settings)

Initialize TimesFM model.

Parameter	Type	Default	Description
params	Dict[str, Any]	-	Model parameters dictionary
settings	Dict[str, Any]	-	Settings dictionary containing device, python_version, etc.

train(self, y_context, y_target, timestamps_context, timestamps_target, **kwargs) -> TimesfmModel

Foundation model: no training needed. Mark as fitted and return self.

Parameters:

Parameter	Type	Default	Description
y_context	np.ndarray	-	(undocumented)
y_target	np.ndarray	-	(undocumented)
timestamps_context	np.ndarray	-	(undocumented)
timestamps_target	np.ndarray	-	(undocumented)
**kwargs		-	(undocumented)

Returns: TimesfmModel (the fitted model).

predict(self, y_context, timestamps_context, timestamps_target, **kwargs)

Make predictions using the trained TimesFM model.

Parameters:

Parameter	Type	Default	Description
y_context	np.ndarray	-	(undocumented)
timestamps_context	np.ndarray	-	(undocumented)
timestamps_target	np.ndarray	-	(undocumented)
**kwargs		-	(undocumented)

Returns: np.ndarray (The predicted values). Raises: ValueError (If TimesFMModel is not fitted. Call train() first.)