波比较函数

使用了局部贪心算法加横向损失. 目前我认为是最好的时序比较函数.

#=====对于波的比较函数的优化
muban999=[0,1,1,0,-1,-1,-1,-1,-1,-1,-1,1]
beipipei999=[0,1,1,0,-1,0,1,1,1,1]
# beipipei999=[0,1,1,0,-1,-1,-1,-1,-1,-1,-1,1]

def jisuan_diff(b,m):
  print(1)
  changdu=0 # 横坐标的偏移 产生的diff
  gaodu=0  # 纵坐标的偏移 产生的diff
  kaishi=1
  saving=0
  jilu=0 # 记录上一个匹配成功的位置.
  for i in range(1,len(m)): # 模板第0个,跟被查数组0个假设已经对齐, 从索引1开始对齐.


      chagndu=3

      tmpjuli=float('inf')
      
      for j in range(kaishi,kaishi+chagndu+1):
       if j<len(b):
        gaodu=abs(m[i]-b[j])
        if i!=1:
          changdu=(abs(abs(j-kaishi)-1))*0.5
        diff=gaodu+changdu
        if diff<tmpjuli:
          tmpjuli=diff
          jilu=j

      # 加上横坐标偏移惩罚: 移动一个格作为0惩罚.
      # tmpjuli+=abs(jilu-kaishi-1)
      kaishi=jilu
      print(i,jilu,tmpjuli,kaishi)
      saving+=tmpjuli
  return (saving+abs(b[0]-m[0]))/len(m)
sadfasdfadsfasd=jisuan_diff(beipipei999,muban999)
print(sadfasdfadsfasd)

import matplotlib.pyplot as plt
plt.plot(muban999,c='r')
plt.plot(beipipei999,c='g')
plt.savefig('sdfaasd.png')