Python，如何优化此代码

Question

我试图优化下面的代码，但我不知道如何提高计算速度。我试过python，但是性能和python一样。

是否有可能在不重写C/c++中的一切的情况下提高性能?

谢谢你的帮助

import numpy as np
heightSequence = 400
widthSequence = 400
nHeights = 80
DOF = np.zeros((heightSequence, widthSequence), dtype = np.float64)
contrast = np.float64(np.random.rand(heightSequence, widthSequence, nHeights))
initDOF = np.zeros([heightSequence, widthSequence], dtype = np.float64)
initContrast = np.zeros([heightSequence, widthSequence, nHeights], dtype = np.float64)
initHeight = np.float64(np.r_[0:nHeights:1.0])
initPixelContrast = np.array(([0 for ii in range(nHeights)]), dtype = np.float64)

# for each row
for row in range(heightSequence):
    # for each col
    for col in range(widthSequence):
        # initialize variables            
        height = initHeight # array ndim = 1
        c = initPixelContrast # array ndim = 1
        # for each height            
        for indexHeight in range(0, nHeights):
            # get contrast profile for current pixel
            tempC = contrast[:, :, indexHeight]
            c[indexHeight] = tempC[row, col]
        # save original contrast            
        # originalC = c
        # originalHeight = height                
        # remove profile before maximum and after minumum contrast
        idxMaxContrast = np.argmax(c)
        c = c[idxMaxContrast:]
        height = height[idxMaxContrast:]
        idxMinContrast = np.argmin(c) + 1
        c = c[0:idxMinContrast]
        height = height[0:idxMinContrast]              
        # remove some refraction
        if (len(c) <= 1) | (np.max(c) <= 0):
            DOF[row, col] = 0                  
        else:
            # linear fitting of profile contrast                                             
            P = np.polyfit(height, c, 1)
            m = P[0]
            q = P[1]
            # remove some refraction               
            if m >= 0:
                DOF[row, col] = 0
            else:
                DOF[row, col] = -q / m
    print 'row=%i/%i' %(row, heightSequence)
# set range of DOF
DOF[DOF < 0] = 0
DOF[DOF > nHeights] = 0

Answer 1

通过查看代码，似乎可以完全摆脱两个外部循环，将代码转换为向量化形式。然而，np.polyfit调用必须用其他表达式代替，但是线性拟合的系数很容易找到，也是矢量化的形式。最后一个if-else可以变成np.where呼叫