geometry.py 文件源码

def medial_axis(samples, contains):
    '''
    Given a set of samples on a boundary, find the approximate medial axis based
    on a voronoi diagram and a containment function which can assess whether
    a point is inside or outside of the closed geometry. 

    Arguments
    ----------
    samples:    (n,d) set of points on the boundary of the geometry
    contains:   function which takes (m,d) points and returns an (m) bool array

    Returns
    ----------
    lines:     (n,2,2) set of line segments
    '''

    from scipy.spatial import Voronoi
    from .path.io.load import load_path

    # create the voronoi diagram, after vertically stacking the points
    # deque from a sequnce into a clean (m,2) array
    voronoi = Voronoi(samples)
    # which voronoi vertices are contained inside the original polygon
    contained = contains(voronoi.vertices)
    # ridge vertices of -1 are outside, make sure they are False
    contained = np.append(contained, False)
    inside = [i for i in voronoi.ridge_vertices if contained[i].all()]
    line_indices = np.vstack([stack_lines(i) for i in inside if len(i) >=2])
    lines = voronoi.vertices[line_indices]    
    return load_path(lines)