Python求数组中相邻两点间直线距离

欧氏距离 

欧式距离（L2范数）是最易于理解的一种距离计算方法，源自欧式空间中两点间的距离公式（如下图所示）。

 

#导入math包
import math
#定义点的函数
class Point:
    def __init__(self,x=0,y=0):
        self.x=x
        self.y=y
    def getx(self):
        return self.x
    def gety(self):
        return self.y 
#定义直线函数   
class Getlen:
    def __init__(self,p1,p2):
        self.x=p1.getx()-p2.getx()
        self.y=p1.gety()-p2.gety()
        #用math.sqrt（）求平方根
        self.len= math.sqrt((self.x**2)+(self.y**2))
    #定义得到直线长度的函数
    def getlen(self):
        return self.len

#设置点p1的坐标为（0,0）       
p1=Point(0,0)
#设置点p2的坐标为（3,4）
p2=Point(3,4)
l=Getlen(p1,p2)
#获取两点之间直线的长度
l.getlen()

import matplotlib.pyplot as plt
import numpy as np
import math
data = np.load('final37.npy')
arr = data[0:10,:,0:60]
# arr = [[[1,2,3,3,3,3],[4,5,6,4,4,4],[7,8,9,7,7,7]]]
# arr = np.array(arr)
def getLen(x1,y1,x2,y2):
    diff_x = (x1-x2)**2
    diff_y = (y1-y2)**2
    length = math.sqrt(diff_x+diff_y)
    return length
len_arr = []
for i in range(len(arr)):
    len1 = []
    for j in range(len(arr[i])):
        halfLen = len(arr[i][j])//2
        arrLen = [] #数组中相邻坐标点的长度
        for k in range(halfLen-1):
            x1 = arr[i][j][k]
            x2 = arr[i][j][k+1]
            y1 = arr[i][j][k+halfLen]
            y2 = arr[i][j][k+halfLen+1]
            lineLen = getLen(x1,y1,x2,y2) #两点之间的长度
            arrLen.append(lineLen)
        lenSum = 0.
        for n in range(len(arrLen)):
            lenSum = arrLen[n] + lenSum
        len1.append(lenSum)
    len_arr.append(len1)
#打印数组中曲线长度
print(len_arr)
for i in range(len(len_arr)):
    print("第%d个图" % i)
    for j in range(len(len_arr[i])):
        print("第%d个图,第%d个分支长度1: %f" % (i,j,len_arr[i][j]))
        
#可视化图像
data_images = arr
for i in range(10):
    plt.figure(figsize=(100,100),dpi=1)
    plt.plot(data_images[i][0][0:30],data_images[i][0][30:60],color='blue',linewidth=150)
    plt.plot(data_images[i][1][0:30],data_images[i][1][30:60],color='red',linewidth=150)
    plt.plot(data_images[i][2][0:30],data_images[i][2][30:60],color='green',linewidth=150)
    plt.axis('off')
    plt.show()
#     plt.savefig('C:\\Users\\Administrator\\Desktop\\调整分辨率\\原始图\\resouce%d.jpg' %(i),dpi=1)
    plt.close()

from datetime import datetime  
import os  
import matplotlib.pyplot as plt  
import numpy as np  
import tensorflow as tf  
import math
from six.moves import xrange  
data = np.load('C:\\Users\\Administrator\\Desktop\\重新整理血管网络\\txt\\头尾不旋转.npy')  
arr = data[0:10,:,0:60]
# arr = [[[1,2,3,3,3,3],[4,5,6,4,4,4],[7,8,9,7,7,7]]]
# arr = np.array(arr)
def getLen(x1,y1,x2,y2):
    diff_x = (x1-x2)**2
    diff_y = (y1-y2)**2
    length = math.sqrt(diff_x+diff_y)
    return length
len_arr = []
wanqu = []
for i in range(len(arr)):
    len1 = []
    wanqu1 = []
    for j in range(len(arr[i])):
        halfLen = len(arr[i][j])//2
        arrLen = [] #数组中相邻坐标点的长度
        #两端点的长度
        duandian = getLen(arr[i][j][0],arr[i][j][30],arr[i][j][29],arr[i][j][59])
        for k in range(halfLen-1):
            x1 = arr[i][j][k]
            x2 = arr[i][j][k+1]
            y1 = arr[i][j][k+halfLen]
            y2 = arr[i][j][k+halfLen+1]
            lineLen = getLen(x1,y1,x2,y2) #两点之间的长度
            arrLen.append(lineLen)
        #曲线的长度
        lenSum = 0.
        for n in range(len(arrLen)):
            lenSum = arrLen[n] + lenSum
        wanqu2 = duandian / lenSum
        wanqu1.append(wanqu2)
        len1.append(lenSum)
#         print("a:%f,b:%f"% (duandian,lenSum))
    len_arr.append(len1)
    wanqu.append(wanqu1)
print(wanqu)
print(len_arr)
#打印数组中曲线长度
# print(len_arr)
# for i in range(len(len_arr)):
#     print("第%d个图" % i)
#     for j in range(len(len_arr[i])):
#         print("第%d个图,第%d个分支长度1: %f" % (i,j,len_arr[i][j]))


#可视化图像
# data_images = arr
# for i in range(10):
#     plt.figure(figsize=(100,100),dpi=1)
#     plt.plot(data_images[i][0][0:30],data_images[i][0][30:60],color='blue',linewidth=150)
#     plt.plot(data_images[i][1][0:30],data_images[i][1][30:60],color='red',linewidth=150)
#     plt.plot(data_images[i][2][0:30],data_images[i][2][30:60],color='green',linewidth=150)
#     plt.axis('off')
#     plt.show()
# #     plt.savefig('C:\\Users\\Administrator\\Desktop\\调整分辨率\\原始图\\resouce%d.jpg' %(i),dpi=1)
#     plt.close()