评估数据，包括长度，角度，卷曲度

角度测试

import numpy as np
import matplotlib.pyplot as plt
x = [0,3,0,0]
y = [0,0,4,0]
a = 3
b = 4
c = 5
cos_angle = (a**2 +b**2-c**2)/(2*b*c)
angle = np.arccos(cos_angle)
angle1 = angle*180/np.pi
print("弧度:%f,角度:%f" % (angle,angle1))
plt.plot(x,y,color='red',linewidth=10)
plt.axis('off')
plt.show()

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\\头不旋转.npy')  
arr = data[0:20,:,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
def getAngle(a,b,c):
    cos_angle = (a**2 +b**2-c**2)/(2*b*c)
    angle = np.arccos(cos_angle)
    angle1 = angle*180/np.pi
    return angle1
angle = []
for i in range(len(arr)):
    x11 = arr[i][0][28]
    y11 = arr[i][0][58]
    x22 = arr[i][0][29]
    y22 = arr[i][0][59]
    x33 = arr[i][1][1]
    y33 = arr[i][1][31]
    x44 = arr[i][2][1]
    y44 = arr[i][2][31]
    x12 = getLen(x11,y11,x22,y22)
    x23 = getLen(x22,y22,x33,y33)
    x24 = getLen(x22,y22,x44,y44)
    x13 = getLen(x11,y11,x33,y33)
    x14 = getLen(x11,y11,x44,y44)
    x34 = getLen(x33,y33,x44,y44)
    angle13 = getAngle(x12,x23,x13)
    angle14 = getAngle(x12,x24,x14)
    angle34 = getAngle(x23,x24,x34)
    anglehe = [angle13,angle14,angle34]
    angle.append(anglehe)
print(angle)
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()
    
    

计算长度，及卷曲读，并将数据存入txt或excel中

from datetime import datetime  
import os  
import matplotlib.pyplot as plt  
import numpy as np  
import tensorflow as tf  
import math
import xlwt
from six.moves import xrange  
data = np.load('data\头不旋转.npy')  
arr = data[0:10,:,0:60]
def getLen(x1,y1,x2,y2):
    diff_x = (x1-x2)**2
    diff_y = (y1-y2)**2
    length = np.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 = lenSum / duandian
        wanqu1.append(wanqu2)
        len1.append(lenSum)
    len_arr.append(len1)
    wanqu.append(wanqu1)
def getAngle(a,b,c):
    cos_angle = (a**2 +b**2-c**2)/(2*a*b)
    angle = np.arccos(cos_angle)
    angle1 = angle*180/np.pi
    return angle1
angle = []
for i in range(len(arr)):
    n = 29
    while(arr[i][0][n] == arr[i][0][n-1] and arr[i][0][n+30] == arr[i][0][n-1+30]):
        n = n-1
    n = n-1
    x11 = arr[i][0][n]
    y11 = arr[i][0][n+30]
    x22 = arr[i][0][29]#节点x
    y22 = arr[i][0][59]#节点y,x,y坐标相差30
    n1 = 0
    while(arr[i][1][n1] == arr[i][1][n1+1] and arr[i][1][n1+30] == arr[i][1][n1+1+30]):
        n1 = n1+1
    n1 = n1+1
    x33 = arr[i][1][n1]
    y33 = arr[i][1][n1+30]
    n2 = 0
    while(arr[i][2][n2] == arr[i][2][n2+1] and arr[i][2][n2+30] == arr[i][1][n2+1+30]):
        n2 = n2+1
    n2 = n2+1
    x44 = arr[i][2][n2]
    y44 = arr[i][2][n2+30]
    x12 = getLen(x11,y11,x22,y22)
    x23 = getLen(x22,y22,x33,y33)
    x24 = getLen(x22,y22,x44,y44)
    x13 = getLen(x11,y11,x33,y33)
    x14 = getLen(x11,y11,x44,y44)
    x34 = getLen(x33,y33,x44,y44)
    angle13 = getAngle(x12,x23,x13)
    angle14 = getAngle(x12,x24,x14)
    angle34 = getAngle(x23,x24,x34)
    anglehe = [angle13,angle14,angle34]
    angle.append(anglehe)
#打印数组中曲线长度
book = xlwt.Workbook(encoding='utf-8',style_compression=0)
sheet = book.add_sheet('mysheet',cell_overwrite_ok=True)
zhuti = ["主分叉长度","左分叉长度","右分叉长度","主左长度比","主右长度比","主分叉弯曲度","左分叉卷曲度","右分叉卷曲度","主左角度","主右角度","左右角度"]
for i in range(len(zhuti)):
    sheet.write(0,i,zhuti[i])
for i in range(1,len(len_arr)):
        bili1 = len_arr[i][0]/len_arr[i][1]
        bili2 = len_arr[i][0]/len_arr[i][2]
        suoyou = [len_arr[i][0],len_arr[i][1],len_arr[i][2],bili1,bili2,wanqu[i][0],wanqu[i][1],wanqu[i][2],angle[i][0],angle[i][1],angle[i][2]]
        for j in range(len(suoyou)):
            sheet.write(i,j,suoyou[j])
            book.save('C:\\Users\\Administrator\\Desktop\\重新整理血管网络\\原始数据1.xls')
print("结束")
        
#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()