如何在 Shapely 中的一条线上获得等间距的点
How to get equally spaced points on a line in Shapely
我正在尝试(大致)均等地 space 一条直线的点到预定义的距离。
距离之间有一些公差是可以的,但尽可能接近是可取的。
我知道我可以手动遍历我的行中的每个点并检查 p1 与 p2 的距离,并在需要时添加更多点。
但我想知道是否有人知道是否有办法实现这一点,因为我已经在 LineString 中有了坐标。
可以使用shapely
substring
操作:
from shapely.geometry import LineString
from shapely.ops import substring
line = LineString(([0, 0], [2, 1], [3,2], [3.5, 1], [5, 2]))
mp = shapely.geometry.MultiPoint()
for i in np.arange(0, line.length, 0.2):
s = substring(line, i, i+0.2)
mp = mp.union(s.boundary)
此数据的结果如下。每个圆圈是一个点。
一种方法是使用 interpolate
method that returns points at specified distances along the line. You just have to generate a list of the distances somehow first. Taking the input line example from :
import numpy as np
from shapely.geometry import LineString
from shapely.ops import unary_union
line = LineString(([0, 0], [2, 1], [3, 2], [3.5, 1], [5, 2]))
指定距离分割:
distance_delta = 0.9
distances = np.arange(0, line.length, distance_delta)
# or alternatively without NumPy:
# points_count = int(line.length // distance_delta) + 1
# distances = (distance_delta * i for i in range(points_count))
points = [line.interpolate(distance) for distance in distances] + [line.boundary[1]]
multipoint = unary_union(points) # or new_line = LineString(points)
请注意,由于距离是固定的,您可能会在该行的末尾遇到问题,如图所示。根据您的需要,您可以 include/exclude 添加直线端点的 [line.boundary[1]]
部分或使用 distances = np.arange(0, line.length, distance_delta)[:-1]
排除倒数第二个点。
此外,请注意循环内的 unary_union
I'm using should be more efficient than calling object.union(other)
,如另一个答案所示。
拆分为固定点数:
n = 7
# or to get the distances closest to the desired one:
# n = round(line.length / desired_distance_delta)
distances = np.linspace(0, line.length, n)
# or alternatively without NumPy:
# distances = (line.length * i / (n - 1) for i in range(n))
points = [line.interpolate(distance) for distance in distances]
multipoint = unary_union(points) # or new_line = LineString(points)
我正在尝试(大致)均等地 space 一条直线的点到预定义的距离。
距离之间有一些公差是可以的,但尽可能接近是可取的。
我知道我可以手动遍历我的行中的每个点并检查 p1 与 p2 的距离,并在需要时添加更多点。
但我想知道是否有人知道是否有办法实现这一点,因为我已经在 LineString 中有了坐标。
可以使用shapely
substring
操作:
from shapely.geometry import LineString
from shapely.ops import substring
line = LineString(([0, 0], [2, 1], [3,2], [3.5, 1], [5, 2]))
mp = shapely.geometry.MultiPoint()
for i in np.arange(0, line.length, 0.2):
s = substring(line, i, i+0.2)
mp = mp.union(s.boundary)
此数据的结果如下。每个圆圈是一个点。
一种方法是使用 interpolate
method that returns points at specified distances along the line. You just have to generate a list of the distances somehow first. Taking the input line example from
import numpy as np
from shapely.geometry import LineString
from shapely.ops import unary_union
line = LineString(([0, 0], [2, 1], [3, 2], [3.5, 1], [5, 2]))
指定距离分割:
distance_delta = 0.9
distances = np.arange(0, line.length, distance_delta)
# or alternatively without NumPy:
# points_count = int(line.length // distance_delta) + 1
# distances = (distance_delta * i for i in range(points_count))
points = [line.interpolate(distance) for distance in distances] + [line.boundary[1]]
multipoint = unary_union(points) # or new_line = LineString(points)
请注意,由于距离是固定的,您可能会在该行的末尾遇到问题,如图所示。根据您的需要,您可以 include/exclude 添加直线端点的 [line.boundary[1]]
部分或使用 distances = np.arange(0, line.length, distance_delta)[:-1]
排除倒数第二个点。
此外,请注意循环内的 unary_union
I'm using should be more efficient than calling object.union(other)
,如另一个答案所示。
拆分为固定点数:
n = 7
# or to get the distances closest to the desired one:
# n = round(line.length / desired_distance_delta)
distances = np.linspace(0, line.length, n)
# or alternatively without NumPy:
# distances = (line.length * i / (n - 1) for i in range(n))
points = [line.interpolate(distance) for distance in distances]
multipoint = unary_union(points) # or new_line = LineString(points)