# y = 2*(np.random.random()-0.5)
# pc.add_point(x, y, 0)
for pt in pc.points:
pt.normal = -pt.position / np.sqrt(np.dot(pt.position, pt.position))
return pc
def get_dist_func(pc):
def dist(x, y):
pt = Point(x, y, 0)
neighbors = pc.nearest_neighbors(pt, 50)
d = 0
for pt2 in neighbors:
diff = pt.position - pt2.position
d += np.dot(diff, pt2.normal)
return d
return dist
if __name__ == '__main__':
pc = get_circle()
dist = get_dist_func(pc)
quadtree = Quadtree(pc.points, 4)
contour = quadtree.compute_contour(dist)
print 'Found %d edges' % len(contour)
# quadtree.display()
for (pt1, pt2) in contour:
x1, y1, _ = pt1.position
x2, y2, _ = pt2.position
plt.plot([x1, x2], [y1, y2])
# plt.show()
quadtree.display()
pt.normal = -pt.position / np.sqrt(np.dot(pt.position, pt.position))
return pc
def get_dist_func(pc):
def dist(x, y):
pt = Point(x, y, 0)
neighbors = pc.nearest_neighbors(pt, 50)
d = 0
for pt2 in neighbors:
diff = pt.position - pt2.position
d += np.dot(diff, pt2.normal)
return d
return dist
if __name__ == '__main__':
pc = get_circle()
dist = get_dist_func(pc)
quadtree = Quadtree(pc.points, 4)
contour = quadtree.compute_contour(dist)
print 'Found %d edges' % len(contour)
# quadtree.display()
for (pt1, pt2) in contour:
x1, y1, _ = pt1.position
x2, y2, _ = pt2.position
plt.plot([x1, x2], [y1, y2])
# plt.show()
quadtree.display()
