def load_basic_motions(return_X_y=False):
    r"""Load and return the Basic Motions dataset.

    The data was generated as part of a student project where four students
    performed four activities whilst wearing a smart watch. The watch collects
    3D accelerometer and a 3D gyroscope It consists of four classes, which are
    walking, resting, running and badminton. Participants were required to
    record motion a total of five times, and the data is sampled once every
    tenth of a second, for a ten second period.

    ================   ==============
    Training samples               40
    Test samples                   40
    Dimensionality                  6
    Timestamps                    100
    Classes                         4
    ================   ==============

    Parameters
    ----------
    return_X_y : bool (default = False)
        If True, return
        ``(data_train, data_test, target_train, target_test)`` instead of a
        Bunch object.

    Returns
    -------
    data : Bunch
        Dictionary-like object, with attributes:

        data_train : array of floats
            The time series in the training set.
        data_test : array of floats
            The time series in the test set.
        target_train : array of integers
            The classification labels in the training set.
        target_test : array of integers
            The classification labels in the test set.
        DESCR : str
            The full description of the dataset.
        url : str
            The url of the dataset.

    (data_train, data_test, target_train, target_test) : tuple if ``return_X_y`` is True

    References
    ----------
    .. [1] `UCR archive entry for the PigCVP dataset
           <http://www.timeseriesclassification.com/description.php?Dataset=BasicMotions>`_

    Examples
    --------
    >>> from pyts.datasets import load_basic_motions
    >>> bunch = load_basic_motions()
    >>> bunch.data_train.shape
    (40, 6, 100)
    >>> X_train, X_test, y_train, y_test = load_basic_motions(return_X_y=True)
    >>> X_train.shape
    (40, 6, 100)

    """  # noqa: E501
    return _load_dataset('BasicMotions', 'UEA', return_X_y)
Load and return the Basic Motions dataset.

    The data was generated as part of a student project where four students
    performed four activities whilst wearing a smart watch. The watch collects
    3D accelerometer and a 3D gyroscope It consists of four classes, which are
    walking, resting, running and badminton. Participants were required to
    record motion a total of five times, and the data is sampled once every
    tenth of a second, for a ten second period.

    ================   ==============
    Training samples               40
    Test samples                   40
    Dimensionality                  6
    Timestamps                    100
    Classes                         4
    ================   ==============

    Parameters
    ----------
    return_X_y : bool (default = False)
        If True, return
        ``(data_train, data_test, target_train, target_test)`` instead of a
        Bunch object.

    Returns
    -------
    data : Bunch
        Dictionary-like object, with attributes:

        data_train : array of floats
            The time series in the training set.
        data_test : array of floats
            The time series in the test set.
        target_train : array of integers
            The classification labels in the training set.
        target_test : array of integers
            The classification labels in the test set.
        DESCR : str
            The full description of the dataset.
        url : str
            The url of the dataset.

    (data_train, data_test, target_train, target_test) : tuple if ``return_X_y`` is True

    References
    ----------
    .. [1] `UCR archive entry for the PigCVP dataset
           <http://www.timeseriesclassification.com/description.php?Dataset=BasicMotions>`_

    Examples
    --------
    >>> from pyts.datasets import load_basic_motions
    >>> bunch = load_basic_motions()
    >>> bunch.data_train.shape
    (40, 6, 100)
    >>> X_train, X_test, y_train, y_test = load_basic_motions(return_X_y=True)
    >>> X_train.shape
    (40, 6, 100)

    
pyts/datasets/load.py