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| 1 | import numpy as np | |
| 2 | from numba import autojit, jit, void, double, int_ | |
| 3 | ||
| 4 | def doloop(X,Y,mm): | |
| 5 | for i in range(Y): | |
| 6 | xx = mm[:] | |
| 7 | x = 0 | |
| 8 | for j in range(X): | |
| 9 | xx[x] = x | |
| 10 | x += 1 | |
| 11 | return 1 | |
| 12 | ||
| 13 | looper = autojit(doloop) | |
| 14 | ||
| 15 | if __name__ == '__main__': | |
| 16 | X = 1000 | |
| 17 | Y = 10000000 | |
| 18 | zz = np.random.random(X) | |
| 19 | looper(X, Y, zz) | |
| 20 | # zz = np.random.randint(0,9,X) | |
| 21 | # zz = [0 for i in range(X)] # ... much slower than np array | |
| 22 | - | # doloop(X,Y/10,zz) |
| 22 | + | # doloop(X,1000000,zz) |
| 23 | # | |
| 24 | # 10,000,000 takes 7.6 seconds with numba | |
| 25 | # 1,000,000 takes 166 seconds with python | |
| 26 | # gain = 210 times |
