Python 如何访问嵌套索引？

我想用欧几里得公式。我需要x2和y2分别作为嵌套在蓝色_点中的所有列表的内部[1]和[2]索引，但它不这样做。我试图用point1列表计算蓝_点的欧几里德距离，然后确定它是否小于或大于/等于，这样程序可以分别返回True或False

import math

# [ID, X coordinate, Y coordinate]
blue_points = [[30, 536254.99137, 3659453.06343],
[33, 536721.584912, 3659162.97207],
[50, 535807.099324, 3659576.92825],
[112, 536827.131371, 3657913.01245],
[117, 536473.254082, 3659433.57702],
[120, 536196.9844, 3658713.72722],
[127, 536387.547701, 3658527.70015],
[133, 537397.838429, 3659554.48657],
[144, 537715.931243, 3658625.59997],
[164, 538367.648437, 3658867.34288],
[172, 537112.662366, 3657921.28957],
[173, 536418.315024, 3658715.47946],
[209, 538096.28422, 3658514.93514],
[211, 538077.87716, 3658138.39337],
[223, 536220.396985, 3659243.54161],
[242, 536102.087002, 3658703.61054],
[244, 536968.755886, 3659409.42857],
[246, 535996.903591, 3658705.08691],
[275, 538078.165429, 3659022.35547],
[303, 535999.885405, 3658521.91524]]

# [ID, X coordinate,Y coordinate]
point1 = [1, 1073706.744,3658967.925]

neighbor_points = [] # Empty list to store values.
for point2 in blue_points:
    if (math.sqrt(((point2[1] - point1[1]) ** 2) + ((point2[2] - point1[2]) ** 2))): # Euclidean distance formula.
        neighbor_points.append(point2) # Add points to empty list.
        print(point2[1:3]) # Print to check if indeces are correct.

x1 = point1[1]
y1 = point1[2]
x2 = blue_points[1]
y2 = blue_points[2]
                
distance = math.sqrt((neighbor_points[1] - point1[1]) ** 2) + ((neighbor_points[2] - point1[2]) ** 2)

def identify_neighbor(point1, point2):
    
    if (distance < 536000):
        print(distance)
        print("True.")
        return True
    else:
        print(distance)
        print("False")
        return False

neighbors = []
for point in blue_points:
    if (math.sqrt(((neighbor_points[1] - point1[1]) ** 2) + ((neighbor_points[2] - point1[2]) ** 2))):
        neighbors.append(point)
        print(point[0])
        identify_neighbor(point1, point2)

导入数学
#[ID，X坐标，Y坐标]
蓝点=[[30,536254.99137,3659453.06343]，
[33, 536721.584912, 3659162.97207],
[50, 535807.099324, 3659576.92825],
[112, 536827.131371, 3657913.01245],
[117, 536473.254082, 3659433.57702],
[120, 536196.9844, 3658713.72722],
[127, 536387.547701, 3658527.70015],
[133, 537397.838429, 3659554.48657],
[144, 537715.931243, 3658625.59997],
[164, 538367.648437, 3658867.34288],
[172, 537112.662366, 3657921.28957],
[173, 536418.315024, 3658715.47946],
[209, 538096.28422, 3658514.93514],
[211, 538077.87716, 3658138.39337],
[223, 536220.396985, 3659243.54161],
[242, 536102.087002, 3658703.61054],
[244, 536968.755886, 3659409.42857],
[246, 535996.903591, 3658705.08691],
[275, 538078.165429, 3659022.35547],
[303, 535999.885405, 3658521.91524]]
#[ID，X坐标，Y坐标]
点1=[11073706.7443658967.925]
邻居点=[]#存储值的空列表。
对于蓝色点中的点2：
如果（math.sqrt（（（point2[1]-point1[1]）**2）+（（point2[2]-point1[2]）**2））：#欧氏距离公式。
相邻点。追加（点2）#将点添加到空列表。
打印（第2点[1:3]）#打印以检查索引是否正确。
x1=点1[1]
y1=点1[2]
x2=蓝色_点[1]
y2=蓝色_点[2]
距离=数学sqrt（（相邻_点[1]-点1[1]）**2+（（相邻_点[2]-点1[2]）**2）
def标识_邻居（点1、点2）：
如果（距离<536000）：
打印（距离）
打印（“真”）
返回真值
其他：
打印（距离）
打印（“假”）
返回错误
邻居=[]
对于蓝色点中的点：
如果（math.sqrt（（（相邻_点[1]-点1[1]）**2）+（相邻_点[2]-点1[2]）**2））：
邻居。追加（点）
打印（点[0]）
识别邻居（点1、点2）

好吧，你的密码很奇怪。但只有一个问题

要使用

python数组

访问嵌套数组（矩阵），您需要

mat[i][j]

访问de元素

i，j

因此，对于代码运行，您只需要更改距离函数

distance=math.sqrt（（相邻_点[1]-点1[1]）**2+（（相邻_点[2]-点1[2]）**2）

到

distance=math.sqrt（（相邻_点[0][1]-点1[1]）**2+（（相邻_点[0][2]-点1[2]）**2）

对于进一步的实现，我建议您创建一个这样做的函数

def欧几里得距离（p1，p2）：
返回math.sqrt（（p2[1]-p1[1]）**2+（（p2[2]-p1[2]）**2）

你可以这样称呼它

距离=欧几里德距离（相邻点[0]，点1）

---

有关更多信息，请参见或

如果我正确理解了目标，您希望在

蓝色\u点

中找到与

点1

相邻的所有点。为此，您可以循环通过

蓝色_点

，找到每个点的距离，然后在列表中收集相邻点

请尝试以下代码：

import math

# [ID, X coordinate, Y coordinate]
blue_points = [
[30, 536254.99137, 3659453.06343],
[33, 536721.584912, 3659162.97207],
[50, 535807.099324, 3659576.92825],
[112, 536827.131371, 3657913.01245],
[117, 536473.254082, 3659433.57702],
[120, 536196.9844, 3658713.72722],
[127, 536387.547701, 3658527.70015],
[133, 537397.838429, 3659554.48657],
[144, 537715.931243, 3658625.59997],
[164, 538367.648437, 3658867.34288],
[172, 537112.662366, 3657921.28957],
[173, 536418.315024, 3658715.47946],
[209, 538096.28422, 3658514.93514],
[211, 538077.87716, 3658138.39337],
[223, 536220.396985, 3659243.54161],
[242, 536102.087002, 3658703.61054],
[244, 536968.755886, 3659409.42857],
[246, 535996.903591, 3658705.08691],
[275, 538078.165429, 3659022.35547],
[303, 535999.885405, 3658521.91524]]

# [ID, X coordinate,Y coordinate]
point1 = [1, 1073706.744,3658967.925]

neighbor_points = []
outer_points = []  # not neighbor

for pt in blue_points:
   distance = math.sqrt(((pt[1] - point1[1]) ** 2) + ((pt[2] - point1[2]) ** 2))
   if (distance < 536000):
        neighbor_points.append(pt)
   else:
        outer_points.append(pt)

print('neighbor_points')
for pt in neighbor_points:
   print(pt)
print()
print('outer_points')
for pt in outer_points:
   print(pt)

---

这回答了你的问题吗？

neighbor_points
[144, 537715.931243, 3658625.59997]
[164, 538367.648437, 3658867.34288]
[209, 538096.28422, 3658514.93514]
[211, 538077.87716, 3658138.39337]
[275, 538078.165429, 3659022.35547]

outer_points
[30, 536254.99137, 3659453.06343]
[33, 536721.584912, 3659162.97207]
[50, 535807.099324, 3659576.92825]
[112, 536827.131371, 3657913.01245]
[117, 536473.254082, 3659433.57702]
[120, 536196.9844, 3658713.72722]
[127, 536387.547701, 3658527.70015]
[133, 537397.838429, 3659554.48657]
[172, 537112.662366, 3657921.28957]
[173, 536418.315024, 3658715.47946]
[223, 536220.396985, 3659243.54161]
[242, 536102.087002, 3658703.61054]
[244, 536968.755886, 3659409.42857]
[246, 535996.903591, 3658705.08691]
[303, 535999.885405, 3658521.91524]