Python:帮助优化代码

Question

我有一个程序，用来计算矩形网格中的单元中心。网格大小相当大(650列乘1150行)。代码运行得非常慢。我想知道是否可以使用任何技巧来减少下面的示例runtime.In，deltax是列间隔的一维数组，deltay是行间隔的一维数组。

center_x = np.empty((nrow,ncol),dtype ='double')
center_y = np.empty((nrow,ncol),dtype ='double')
for i in range(nrow-1,-1,-1):
    if(i == nrow-1):
        center_y[i,:] = 0.5*deltay[nrow-1]
    else:
        center_y[i,:] = center_y[i+1,:] + 0.5*deltay[i+1] + 0.5*deltay[i]

for j in range(0,ncol):
    if(j ==0):
        center_x[:,j] = 0.5*deltax[0]
    else:
        center_x[:,j]= center_x[0,j-1] + 0.5*deltax[j-1] + 0.5*deltax[j]

Answer 1

至少有两件事：

for i in range(nrow-1,-1,-1):
    if(i == nrow-1):
        center_y[i,:] = 0.5*deltay[nrow-1]
    else:
        center_y[i,:] = center_y[i+1,:] + 0.5*deltay[i+1] + 0.5*deltay[i]

可以更改以避免分支：

center_y[nrow-1,:] = 0.5*deltay[nrow-1]
for i in range(nrow-2,-1,-1):
    center_y[i,:] = center_y[i+1,:] + 0.5*deltay[i+1] + 0.5*deltay[i]

这更能利用numpy的优势：

center_y[nrow-1,:] = 0.5*deltay[nrow-1]
center_y[:nrow-1, :] = 0.5*deltay[1:] + 0.5*deltay[:nrow-1]
# expl: deltay[i+1] in the loop skips the first element, deltay[i] skips the last element
for i in range(nrow-2,-1,-1): # can't move this part since center_y[i,:] depends on center_y[i+1,:] 
    center_y[i,:] = center_y[i+1,:] 

Answer 2

center_x[:,j]= center_x[0,j-1] + 0.5*deltax[j-1] + 0.5*deltax[j]
...
center_y[i,:] = center_y[i+1,:] + 0.5*deltay[i+1] + 0.5*deltay[i]

你必须分配给[:,j]和[i,:]，而不仅仅是[i]和[j]吗？这类似于(但并不是因为有多个维度)，而是将其提高到O(n^2)。