scale = 100
nb = int(sys.argv[1])
points = [(scale * random.random(), scale * random.random())
for i in range(nb)]
else:
points = [
(0, 40),
(100, 60),
(40, 0),
(50, 100),
(90, 10),
# (50,50),
]
fig = plot.figure()
triangles = triangulation.delaunay_bowyer_watson(points)
delaunay_edges = triangulation.edges_of(triangles)
voronoi_graph = dual(triangles)
voronoi_edges = graph.edges_of(voronoi_graph)
print voronoi_edges
ax = fig.add_subplot(111)
ax.set_aspect('equal')
uberplot.scatter_segments(ax, delaunay_edges, facecolor="blue")
uberplot.plot_segments(ax, delaunay_edges, edgecolor="blue")
uberplot.scatter_segments(ax, voronoi_edges, facecolor="red")
uberplot.plot_segments(ax, voronoi_edges, edgecolor="red")
plot.show()
line_inter = []
for s0 in segments:
for s1 in segments:
if s0 != s1:
s = segment_intersection( s0, s1 )
if s is not None:
seg_inter.append(s)
l = line_intersection( s0, s1 )
if l is not None:
line_inter.append(l)
fig = plot.figure()
ax = fig.add_subplot(121)
uberplot.plot_segments( ax, segments, linewidth=0.5, edgecolor = "blue" )
uberplot.scatter_points( ax, points, edgecolor="blue", facecolor="blue", s=120, alpha=1, linewidth=1 )
uberplot.scatter_points( ax, line_inter, edgecolor="none", facecolor="green", s=60, alpha=0.5 )
uberplot.scatter_points( ax, seg_inter, edgecolor="none", facecolor="red", s=60, alpha=0.5 )
ax.set_aspect('equal')
# collinear test demo
if len(sys.argv) > 1:
scale = 100
nb = int(sys.argv[1])
triangles = []
for t in range(nb):
triangles.append( [ [scale*random.random(),scale*random.random()] for i in range(3)] )
# forced collinear
t = [ [scale*random.random(),scale*random.random()] for i in range(2)]
maxph = 0
for i in phero:
maxph = max(maxph, max(phero[i].values()))
# ant colony
# pheromones
for i in phero:
for j in phero[i]:
if i == j:
continue
nph = phero[i][j] / maxph
seg = [(i, j)]
# LOGN( nph,seg )
uberplot.plot_segments(ax,
seg,
alpha=0.01 * nph,
linewidth=1 * nph,
**theme["pheromones"])
# uberplot.scatter_segments( ax, seg, color="red", alpha=0.5, linewidth=nph )
if not ask_for.noplot_tour:
for traj in trajs:
LOGN("\ttraj", len(traj), "points")
# best tour
uberplot.plot_segments(ax, utils.tour(traj), **theme["tour"])
if not ask_for.noplot_penrose:
LOGN("\ttiling", len(penrose_segments), "segments")
uberplot.plot_segments(ax, penrose_segments, **theme["penrose"])
if not ask_for.noplot_triangulation:
import utils
import uberplot
import matplotlib.pyplot as plot
if len(sys.argv) > 1:
scale = 100
nb = int(sys.argv[1])
points = [ (scale*random.random(),scale*random.random()) for i in range(nb)]
else:
points = [
(0,40),
(100,60),
(40,0),
(50,100),
(90,10),
# (50,50),
]
fig = plot.figure()
triangles = delaunay_bowyer_watson( points, do_plot = fig )
edges = edges_of( triangles )
ax = fig.add_subplot(111)
ax.set_aspect('equal')
uberplot.scatter_segments( ax, edges, facecolor = "red" )
uberplot.plot_segments( ax, edges, edgecolor = "blue" )
plot.show()
seg_inter = []
line_inter = []
for s0 in segments:
for s1 in segments:
if s0 != s1:
s = segment_intersection(s0, s1)
if s is not None:
seg_inter.append(s)
l = line_intersection(s0, s1)
if l is not None:
line_inter.append(l)
fig = plot.figure()
ax = fig.add_subplot(121)
uberplot.plot_segments(ax, segments, linewidth=0.5, edgecolor="blue")
uberplot.scatter_points(ax,
points,
edgecolor="blue",
facecolor="blue",
s=120,
alpha=1,
linewidth=1)
uberplot.scatter_points(ax,
line_inter,
edgecolor="none",
facecolor="green",
s=60,
alpha=0.5)
uberplot.scatter_points(ax,
seg_inter,
scale = 100
nb = int(sys.argv[1])
points = [ (scale*random.random(),scale*random.random()) for i in range(nb)]
else:
points = [
(0,40),
(100,60),
(40,0),
(50,100),
(90,10),
# (50,50),
]
fig = plot.figure()
triangles = triangulation.delaunay_bowyer_watson( points )
delaunay_edges = triangulation.edges_of( triangles )
voronoi_graph = dual( triangles )
voronoi_edges = graph.edges_of( voronoi_graph )
print voronoi_edges
ax = fig.add_subplot(111)
ax.set_aspect('equal')
uberplot.scatter_segments( ax, delaunay_edges, facecolor = "blue" )
uberplot.plot_segments( ax, delaunay_edges, edgecolor = "blue" )
uberplot.scatter_segments( ax, voronoi_edges, facecolor = "red" )
uberplot.plot_segments( ax, voronoi_edges, edgecolor = "red" )
plot.show()
# print(quad)
# sys.stderr.write( "%i points in the quadtree / %i points\n" % (len(quad), len(points)) )
fig = plot.figure()
ax = fig.add_subplot(111)
ax.set_aspect('equal')
# Plot the whole quad tree and its points.
# Iterating over the quadtree will generate points, thus list(quad) is equivalent to quad.points()
uberplot.scatter_points( ax, list(quad), facecolor="green", edgecolor="None")
for q in quad.quadrants:
edges = list( utils.tour(as_rect(q)) )
uberplot.plot_segments( ax, edges, edgecolor = "blue", alpha = 0.1, linewidth = 2 )
# Plot a random query on the quad tree.
# Remember a quadrant is ( (orig_y,orig_y), width )
minp = ( round(random.uniform(-n,n),2), round(random.uniform(-n,n),2) )
rand_quad = ( minp, round(random.uniform(0,n),2) )
# Asking for a quadrant will query the quad tree and return the corresponding points.
uberplot.scatter_points( ax, quad[rand_quad], facecolor="None", edgecolor="red", alpha=0.5, linewidth = 2 )
edges = list( utils.tour(as_rect(rand_quad)) )
uberplot.plot_segments( ax, edges, edgecolor = "red", alpha = 0.5, linewidth = 2 )
plot.show()
assert(len(points) == len(quad))
if not ask_for.noplot_pheromones:
LOGN( "\tpheromones",len(phero),"nodes" )#,"x",len(phero[traj[0]]) )
maxph=0
for i in phero:
maxph = max( maxph, max(phero[i].values()))
# ant colony
# pheromones
for i in phero:
for j in phero[i]:
if i == j:
continue
nph = phero[i][j]/maxph
seg = [(i,j)]
# LOGN( nph,seg )
uberplot.plot_segments( ax, seg, alpha=0.01*nph, linewidth=1*nph, **theme["pheromones"] )
# uberplot.scatter_segments( ax, seg, color="red", alpha=0.5, linewidth=nph )
if not ask_for.noplot_tour:
for traj in trajs:
LOGN( "\ttraj",len(traj),"points" )
# best tour
uberplot.plot_segments( ax, utils.tour(traj), **theme["tour"])
if not ask_for.noplot_penrose:
LOGN( "\ttiling",len(penrose_segments),"segments" )
uberplot.plot_segments( ax, penrose_segments, **theme["penrose"])
if not ask_for.noplot_triangulation:
LOGN( "\ttriangulation",len(triangulation_edges),"edges" )
uberplot.plot_segments( ax, triangulation_edges, **theme["triangulation"])
import utils
import uberplot
import matplotlib.pyplot as plot
if len(sys.argv) > 1:
scale = 100
nb = int(sys.argv[1])
points = [(scale * random.random(), scale * random.random())
for i in range(nb)]
else:
points = [
(0, 40),
(100, 60),
(40, 0),
(50, 100),
(90, 10),
# (50,50),
]
fig = plot.figure()
triangles = delaunay_bowyer_watson(points, do_plot=fig)
edges = edges_of(triangles)
ax = fig.add_subplot(111)
ax.set_aspect('equal')
uberplot.scatter_segments(ax, edges, facecolor="red")
uberplot.plot_segments(ax, edges, edgecolor="blue")
plot.show()
ax = fig.add_subplot(111)
ax.set_aspect('equal')
# Plot the whole quad tree and its points.
# Iterating over the quadtree will generate points, thus list(quad) is equivalent to quad.points()
uberplot.scatter_points(ax,
list(quad),
facecolor="green",
edgecolor="None")
for q in quad.quadrants:
edges = list(utils.tour(as_rect(q)))
uberplot.plot_segments(ax,
edges,
edgecolor="blue",
alpha=0.1,
linewidth=2)
# Plot a random query on the quad tree.
# Remember a quadrant is ( (orig_y,orig_y), width )
minp = (round(random.uniform(-n, n), 2), round(random.uniform(-n, n), 2))
rand_quad = (minp, round(random.uniform(0, n), 2))
# Asking for a quadrant will query the quad tree and return the corresponding points.
uberplot.scatter_points(ax,
quad[rand_quad],
facecolor="None",
edgecolor="red",
alpha=0.5,
linewidth=2)
edges = list(utils.tour(as_rect(rand_quad)))
