计算CV值

import numpy as np 
import matplotlib.pyplot as plt
import os 
# 读取文件夹
def file_name(file_dir):  
  L=[]  
  for root, dirs, files in os.walk(file_dir): 
    for file in files: 
      if os.path.splitext(file)[1] == '.npy': 
        L.append(os.path.join(root, file)) 
  return L
# 将不同的树和在一起,形成整个树
totalTree = []
GAN_type = 'Men_389_Bifurcation'
dirList = file_name('C:\\Users\\Administrator\\Desktop\\finalTrees\\%s' % GAN_type)
for i in range(len(dirList)):
  data = np.load(dirList[i])
  for j in range(len(data)):
    totalTree.append(data[j])
totalTree = np.array(totalTree)
print(GAN_type)
print(totalTree.shape)
######################################################################################
# data = np.load('C:\\Users\\Administrator\\Desktop\\NewDCGANTree\\Men_546_Convergence_DCGAN_gen_Trees\\Men_546_Convergence_DCGAN_gen4.npy')
# print(data.shape)
#######################################################################################
# 提取segment,data为一个树,返回一个数组,存储一段的坐标和管径[[x],[y],[diam]]
def extractSegment(data):
  # 将数组变为列表
  dataList = []
  for i in range(len(data)):
    fencha = []
    for j in range(len(data[i])):
      fencha.append(data[i][j].tolist())
    dataList.append(fencha)
  segments = []
  for i in range(len(dataList)):
    if [dataList[i][0],dataList[i][3],dataList[i][6]]  in segments:
      segments.append([dataList[i][0],dataList[i][3],dataList[i][6]])
    if [dataList[i][1],dataList[i][4],dataList[i][7]] not in segments:
      segments.append([dataList[i][1],dataList[i][4],dataList[i][7]])
    if [dataList[i][2],dataList[i][5],dataList[i][8]] not in segments:
      segments.append([dataList[i][2],dataList[i][5],dataList[i][8]])
  # 在将提取的segment变为数组
  segments_ = []
  for i in range(len(segments)):   
    segment = [np.array(segments[i][0]),np.array(segments[i][1]),np.array(segments[i][2])]
    segments_.append(segment)
  segments = np.array(segments_)
  print("总共血管段数: ", len(segments))
  return segments

# 得到分支x,y坐标,segment为单个分支
def get_axis_segment(segment):
  x = segment[0]
  y = segment[1]
  diam = segment[2]
  return x, y, diam
# 距离计算公式
def get_len(x1,x2,y1,y2):
    diff_x = (x1-x2)**2
    diff_y = (y1-y2)**2
    length = np.sqrt(diff_x+diff_y)
    return length
#计算分支总长度,segment为单个分支
def get_total_len_diam(segment):
    x, y, diam = get_axis_segment(segment)
    # 相邻两点距离列表
    lin_list = []
    for i in range(1,len(x)):
        lin_len = get_len(x[i-1],x[i],y[i-1],y[i])
        lin_list.append(lin_len)
    # 一段总长度
    total_len = 0
    for file in lin_list:
        total_len += file
    # 返回这一段的长度和管径大小
    return total_len,diam[0]
# data为一个树,返回异质性CV值,和平均值
def getAvgAndCV(data):
  segments = extractSegment(data)
  # 计算一个树中所有段的长度和管径,加入列表
  totalLenList = []
  diamList = []
  for i in range(len(segments)):
    total_len,diam = get_total_len_diam(segments[i])
    totalLenList.append(total_len)
    diamList.append(diam)
  # 平均值
  lenMean = np.mean(totalLenList)
  diamMean = np.mean(diamList)
  # 标准差
  lenSD = np.std(totalLenList,ddof=1)
  diamSD = np.std(diamList,ddof=1)
  # CV值
  lenCV = lenSD/lenMean
  diamCV = diamSD/diamMean
  return lenMean, diamMean, lenCV, diamCV
lenMean, diamMean, lenCV, diamCV = getAvgAndCV(totalTree)
print("Length Avg: %f, Length CV: %f  " % (lenMean, lenCV))
print("Diameter Avg: %f, Diameter CV: %f" % (diamMean, diamCV))