load_unit_test¶
- load_unit_test(split=None, return_type='numpy3d')[source]¶
Load UnitTest data.
This is an equal length univariate time series classification problem. It is a stripped down version of the ChinaTown problem that is used in correctness tests for classification.
- Parameters:
- split: None or one of “TRAIN”, “TEST”, default=None
Whether to load the train or test instances of the problem. By default it loads both train and test instances into a single array.
- return_type: string, default=”numpy3d”
Data structure containing series, should be either “numpy2d” or “numpy3d”.
- Returns:
- X: np.ndarray
shape (n_cases, 1, 24) (return_type=”numpy3d) or shape (n_cases, 24) (return_type=”numpy2d), where n_cases where n_cases is either 20 (split = “train”) 22 (split=”test”) or 42.
- y: np.ndarray
1D array of length 20, 22 or 42 The class labels for each time series instance in X
- Raises:
- ValueError is raised if the data cannot be stored in the requested return_type.
Examples
>>> from aeon.datasets import load_unit_test >>> X, y = load_unit_test()