我在寻找一个处理2D动态rectilinear convex hulls的有效算法。在
我已经编写了一个静态算法,但虽然它在大多数情况下都能工作,但根本不起作用,所以我也在寻找关于静态直线凸壳的资源。维基百科有一些关于算法的研究论文,但我无法访问它们。因此,寻找其他来源或帮助编写代码。在
任何帮助都将不胜感激,一个Python算法,非常感谢。在
当前静态代码:
def stepped_hull(points, is_sorted=False, return_sections=False):
# May be equivalent to the orthogonal convex hull
if not is_sorted:
points = sorted(set(points))
if len(points) <= 1:
return points
# Get extreme y points
min_y = min(points, lambda p:p[1])
max_y = max(points, lambda p:p[1])
points_reversed = list(reversed(points))
# Create upper section
upper_left = build_stepped_upper(points, max_y)
upper_right = build_stepped_upper(points_reversed, max_y)
# Create lower section
lower_left = build_stepped_lower(points, min_y)
lower_right = build_stepped_lower(points_reversed, min_y)
# Correct the ordering
lower_right.reverse()
upper_left.reverse()
if return_sections:
return lower_left, lower_right, upper_right, upper_left
# Remove duplicate points
hull = OrderedSet(lower_left + lower_right + upper_right + upper_left)
return list(hull)
def build_stepped_upper(points, max_y):
# Steps towards the highest y point
section = [points[0]]
if max_y != points[0]:
for point in points:
if point[1] >= section[-1][1]:
section.append(point)
if max_y == point:
break
return section
def build_stepped_lower(points, min_y):
# Steps towards the lowest y point
section = [points[0]]
if min_y != points[0]:
for point in points:
if point[1] <= section[-1][1]:
section.append(point)
if min_y == point:
break
return section
为了实现正确的算法,您可能需要看看this。对于直线凸壳的动态维护,最好寻找动态数据结构来保持集合的最大值,这是一个研究较多的课题。点集的最大元素集是直线凸壳的顶点集,因此这两个问题是等价的。在
您可以在this paper中找到一种算法,该算法每次操作花费$O(\logn)$时间。在
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