functions.py 文件源码

def pad_mirror(ar, padding):
    """Pad 3d array using mirroring.

    Parameters:
    ar - (numpy.array) array to be padded
    padding - (tuple) per-dimension padding values
    """
    shape = tuple((ar.shape[i] + 2*padding[i]) for i in range(3))
    result = np.zeros(shape, dtype=ar.dtype)
    slices_center = tuple(slice(padding[i], padding[i] + ar.shape[i]) for i in range(3))
    result[slices_center] = ar
    # z-axis, centers
    if padding[0] > 0:
        result[0:padding[0], slices_center[1] , slices_center[2]] = np.flip(ar[0:padding[0], :, :], axis=0)
        result[ar.shape[0] + padding[0]:, slices_center[1] , slices_center[2]] = np.flip(ar[-padding[0]:, :, :], axis=0)
    # y-axis
    result[:, 0:padding[1], :] = np.flip(result[:, padding[1]:2*padding[1], :], axis=1)
    result[:, padding[1] + ar.shape[1]:, :] = np.flip(result[:, ar.shape[1]:ar.shape[1] + padding[1], :], axis=1)
    # x-axis
    result[:, :, 0:padding[2]] = np.flip(result[:, :, padding[2]:2*padding[2]], axis=2)
    result[:, :, padding[2] + ar.shape[2]:] = np.flip(result[:, :, ar.shape[2]:ar.shape[2] + padding[2]], axis=2)
    return result