quickest_path.py 文件源码

def direction_map(dmap: DistanceMap):
    r"""Computes normalized gradient of distance map. Not defined when length of
    the gradient is zero.

    .. math::
       \hat{\mathbf{e}}_{S} = -\frac{\nabla S(\mathbf{x})}{\| \nabla S(\mathbf{x}) \|}

    Args:
        dmap (numpy.ndarray):
            Distance map.

    Returns:
        DirectionMap: Direction map.
    """
    u, v = np.gradient(dmap)
    l = np.hypot(u, v)
    # Avoids zero division
    l[l == 0] = np.nan
    # Flip order from (row, col) to (x, y)
    return v / l, u / l


# Potentials