Approach #1. Here's a vectorized approach - m,n,r = volume.shape x,y,z = np.mgrid[0:m,0:n,0:r] X = x - roi[0] Y = y - roi[1] Z = z - roi[2] ... ... <看更多>

Vectorisation in Python is a programming style where operations on a single piece of data, typically in a loop, are replaced by operations on entire arrays. ... <看更多>

... time.time() for i in range(num): c += a[i]*b[i] end = time.time() print(c) print(" Loop version : " + str((end -start)*1000) + 'ms'). ... <看更多>

When programming in NumPy, you get best results if you can vectorize your computation — that is, replace explicit loops in Python with whole- ... ... <看更多>