common.py 文件源码

def __init__(self, signal, smoothness_param, deriv_order=1):
        self.y = signal
        assert deriv_order > 0, 'deriv_order must be an int > 0'
        # Compute the fixed derivative of identity (D).
        d = np.zeros(deriv_order * 2 + 1, dtype=int)
        d[deriv_order] = 1
        d = np.diff(d, n=deriv_order)
        n = self.y.shape[0]
        k = len(d)
        s = float(smoothness_param)

        # Here be dragons: essentially we're faking a big banded matrix D,
        # doing s * D.T.dot(D) with it, then taking the upper triangular bands.
        diag_sums = np.vstack([
            np.pad(s * np.cumsum(d[-i:] * d[:i]), ((k - i, 0),), 'constant')
            for i in range(1, k + 1)])
        upper_bands = np.tile(diag_sums[:, -1:], n)
        upper_bands[:, :k] = diag_sums
        for i, ds in enumerate(diag_sums):
            upper_bands[i, -i - 1:] = ds[::-1][:i + 1]
        self.upper_bands = upper_bands