_bmutils.py 文件源码

def find_centers_gmm(data, gridpoints, n_components=2):
    r""" Provided 1D data and a grid of points, return the indices of the points closest to
    the centers of an assumed n-modal distribution behind "data"

    data : 1D data ndarray, of shape (N, 1)
    gridpoints: 1D gridpoints

    returns: idxs, igmm
    idxs: 1D ndarray
            INDICES of gridpoints that are closest to the centers of the gaussians

    igmm: gaussian mixture model (sklearn type)

    tested = true
    """
    igmm = _GMM(n_components=n_components)
    igmm.fit(data)
    return _np.abs(gridpoints-_np.sort(igmm.means_, 0)).argmin(1), igmm