basics.py 文件源码

def get_normals(hull, number_fitnodes=12):
    """
    Calculate normals from given hull points using local convex hull fitting.
    Orientation of normals is found using local center of mass.
    :param hull: 3D coordinates of points representing cell hull
    :type hull: np.array
    :return: normals for each hull point
    """
    normals = np.zeros_like(hull, dtype=np.float)
    hull_tree = spatial.cKDTree(hull)
    dists, nearest_nodes_ixs = hull_tree.query(hull, k=number_fitnodes,
                                                distance_upper_bound=1000)
    for ii, nearest_ixs in enumerate(nearest_nodes_ixs):
        nearest_nodes = hull[nearest_ixs[dists[ii] != np.inf]]
        ch = ConvexHull(nearest_nodes, qhull_options='QJ Pp')
        triangles = ch.points[ch.simplices]
        normal = np.zeros((3), dtype=np.float)
        # average normal
        for triangle in triangles:
            cnt = 0
            n_help = unit_normal(triangle[0], triangle[1], triangle[2])
            if not np.any(np.isnan(n_help)):
                normal += np.abs(n_help)
        normal /= np.linalg.norm(normal)
        normal_sign = (hull[ii] - np.mean(nearest_nodes, axis=0))/\
                      np.abs(hull[ii] - np.mean(nearest_nodes, axis=0))
        normals[ii] = normal * normal_sign
    return normals