Adds the voronoi.merge_enclosed function
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2 changed files with 84 additions and 5 deletions
13
run_all.py
13
run_all.py
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@ -150,7 +150,7 @@ if args.triangulation:
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else:
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LOGN( "Compute the triangulation of the penrose vertices" )
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points = utils.vertices_from_set(penrose_segments)
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points = utils.vertices_of(penrose_segments)
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triangles = triangulation.delaunay_bowyer_watson( points, do_plot = False )
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LOGN( "\tCompute the convex hull of",len(points),"points" )
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@ -197,10 +197,15 @@ if args.voronoi:
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else:
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# LOGN( "Compute the nodes of the Voronoï diagram" )
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voronoi_graph = voronoi.dual( triangulated )
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voronoi_tri_graph = voronoi.dual(triangulated)
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voronoi_tri_edges = voronoi.edges_of( voronoi.dual(triangulated) )
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voronoi_tri_centers = voronoi_tri_graph.keys()
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voronoi_graph = voronoi.merge_enclosed( voronoi_tri_graph, penrose_segments )
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voronoi_edges = voronoi.edges_of( voronoi_graph )
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voronoi_centers = voronoi_graph.keys()
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# with open("d%i_voronoi_centers.points" % depth, "w") as fd:
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# for p in voronoi_centers:
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# fd.write( "%f %f\n" % (p[0],p[1]) )
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@ -245,8 +250,8 @@ uberplot.scatter_segments( ax, penrose_segments, edgecolor=tcol, alpha=0.9, line
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uberplot.plot_segments( ax, triangulation_edges, edgecolor="green", alpha=0.2, linewidth=1 )
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# Voronoï
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uberplot.scatter_points( ax, voronoi_centers, edgecolor="magenta", facecolor="white", s=200, alpha=0.5 )
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uberplot.plot_segments( ax, voronoi_edges, edgecolor="magenta", alpha=0.2, linewidth=1 )
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uberplot.scatter_points( ax, voronoi_centers, edgecolor="magenta", facecolor="white", s=200, alpha=1 )
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uberplot.plot_segments( ax, voronoi_edges, edgecolor="magenta", alpha=1, linewidth=1 )
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ax.set_aspect('equal')
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76
voronoi.py
76
voronoi.py
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@ -1,7 +1,9 @@
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#/usr/bin/env python
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#encoding: utf-8
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from utils import tour,LOG,LOGN,x,y
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import triangulation
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import geometry
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def nodes( triangles ):
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"""Compute the locations of the centers of all the circumscribed circles of the given triangles"""
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@ -41,6 +43,7 @@ def neighbours( triangle, polygons ):
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def dual( triangles ):
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"""Compute the dual Voronoï graph of a triangulation."""
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graph = {}
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def add_edge( current, neighbor ):
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@ -73,10 +76,81 @@ def edges_of( graph ):
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if k != n and (k,n) not in edges and (n,k) not in edges:
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# edges.add( (k,n) )
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edges.append( (k,n) )
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return edges
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def merge_nodes( graph, n0, n1, n2 ):
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"""Merge n0 and n1 nodes as n2 within the given graph."""
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# Assert that the old nodes are in the graph
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# and that they are linked by an edge.
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assert( n0 in graph )
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assert( n1 in graph[n0] )
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assert( n1 in graph )
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assert( n0 in graph[n1] )
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assert( n0 != n1 )
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# Remove and save the neigbhours of the old nodes.
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n0_ngb = graph.pop(n0)
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n1_ngb = graph.pop(n1)
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# Insert the new node along with the old neighbours.
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# We use a set to ensure that there is no duplicated nodes.
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neighbours = list(set(n0_ngb + n1_ngb))
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# Filter out duplicate of the considered nodes.
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# Because the new node cannot be linked to the old nodes, nor to itself.
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graph[n2] = filter( lambda n: n not in (n0,n1,n2), neighbours )
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for node in graph:
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# Replace occurences of old nodes as neighbours by the new node.
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while n0 in graph[node]:
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graph[node].remove(n0)
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graph[node].append(n2)
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while n1 in graph[node]:
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graph[node].remove(n1)
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graph[node].append(n2)
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# assert that any neighbour is also a node of the graph.
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for node in graph:
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for neighbour in graph[node]:
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assert( neighbour in graph )
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assert( neighbour != node )
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return graph
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def merge_enclosed( graph, segments ):
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"""Merge nodes of the given graph that are on edges that do not intersects with the given segments."""
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i=0
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LOG("Merge",len(graph),"nodes")
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while i < len(graph.keys()):
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node = graph.keys()[i]
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j=0
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altered = False
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while j < len(graph[node]):
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neighbour = graph[node][j]
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assert( neighbour in graph )
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edge = (node,neighbour)
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if not any( geometry.segment_intersection(edge,seg) for seg in segments ):
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graph = merge_nodes( graph, edge[0], edge[1], geometry.middle(*edge) )
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altered = True
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LOG(".")
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break
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else:
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j+=1
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continue
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if altered:
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i = 0
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else:
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i+=1
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LOGN("as",len(graph),"enclosed nodes")
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return graph
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if __name__ == "__main__":
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import sys
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import random
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