将序列转换为相同长度

 

 

def transform_to_same_length(x, n_var, max_length):
    n = x.shape[0]

    # the new set in ucr form np array
    ucr_x = np.zeros((n, max_length, n_var), dtype=np.float64)

    # loop through each time series
    for i in range(n):
        mts = x[i]
        curr_length = mts.shape[1]
        idx = np.array(range(curr_length))
        idx_new = np.linspace(0, idx.max(), max_length)
        for j in range(n_var):
            ts = mts[j]
            # linear interpolation
            f = interp1d(idx, ts, kind='cubic')
            new_ts = f(idx_new)
            ucr_x[i, :, j] = new_ts

    return ucr_x