metrics.py 文件源码

def gamma_soft_dtw(dataset, n_samples=100, random_state=None):
    """Compute gamma value to be used for GAK/Soft-DTW.

    This method was originally presented in [1]_.

    Parameters
    ----------
    dataset
        A dataset of time series
    n_samples : int (default: 100)
        Number of samples on which median distance should be estimated
    random_state : integer or numpy.RandomState or None (default: None)
        The generator used to draw the samples. If an integer is given, it fixes the seed. Defaults to the global
        numpy random number generator.

    Returns
    -------
    float
        Suggested :math:`\\gamma` parameter for the Soft-DTW

    Example
    -------
    >>> dataset = [[1, 2, 2, 3], [1., 2., 3., 4.]]
    >>> gamma_soft_dtw(dataset=dataset, n_samples=200, random_state=0)  # doctest: +ELLIPSIS
    8.0...

    See Also
    --------
    sigma_gak : Compute sigma parameter for Global Alignment kernel

    References
    ----------
    .. [1] M. Cuturi, "Fast global alignment kernels," ICML 2011.
    """
    return 2. * sigma_gak(dataset=dataset, n_samples=n_samples, random_state=random_state) ** 2