def METHOD_NAME(
    n_instances=20,
    n_columns=1,
    n_timepoints=20,
    y=None,
    all_positive=False,
    random_state=None,
    return_mtype="pd-multiindex",
):
    """Generate sktime compatible test data, Panel data formats.
    Parameters
    ----------
    n_instances : int, optional, default=20
        number of instances per series in the panel
    n_columns : int, optional, default=1
        number of variables in the time series
    n_timepoints : int, optional, default=20
        number of time points in each series
    y : None (default), or 1D np.darray or 1D array-like, shape (n_instances, )
        if passed, return will be generated with association to y
    all_positive : bool, optional, default=False
        whether series contain only positive values when generated
    random_state : None (default) or int
        if int is passed, will be used in numpy RandomState for generation
    return_mtype : str, sktime Panel mtype str, default="pd-multiindex"
        see sktime.datatypes.MTYPE_LIST_PANEL for a full list of admissible strings
        see sktime.datatypes.MTYPE_REGISTER for an short explanation of formats
        see examples/AA_datatypes_and_datasets.ipynb for a full specification
    Returns
    -------
    X : an sktime time series data container of mtype return_mtype
        with n_instances instances, n_columns variables, n_timepoints time points
        generating distribution is all values i.i.d. normal with std 0.5
        if y is passed, i-th series values are additively shifted by y[i] * 100
    """
    # If target variable y is given, we ignore n_instances and instead generate as
    # many instances as in the target variable
    if y is not None:
        y = np.asarray(y)
        n_instances = len(y)
    rng = check_random_state(random_state)
    # Generate data as 3d numpy array
    X = rng.normal(scale=0.5, size=(n_instances, n_columns, n_timepoints))
    # Generate association between data and target variable
    if y is not None:
        X = X + (y * 100).reshape(-1, 1, 1)
    if all_positive:
        X = X**2
    X = convert(X, from_type="numpy3D", to_type=return_mtype)
    return X