Created
August 29, 2017 07:33
-
-
Save benoitrosa/5087120222c38a6646dfc8e04cad5d1d to your computer and use it in GitHub Desktop.
Numpy linalg.norm(A) vs np.sqrt(np.inner(A,A)
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| import numpy as np | |
| import timeit | |
| def norm(A): | |
| if A.ndim == 1: | |
| return np.sqrt(np.inner(A,A)) | |
| return np.linalg.norm(A) | |
| def time_norms(A, n_eval): | |
| start_time = timeit.default_timer() | |
| for i in range(n_eval): | |
| norm(A) | |
| end_time = timeit.default_timer() | |
| time_norm_ms = (end_time-start_time)*1.0/n_eval*10**3 | |
| start_time = timeit.default_timer() | |
| for i in range(n_eval): | |
| np.linalg.norm(A) | |
| end_time = timeit.default_timer() | |
| time_linalg_ms = (end_time-start_time)*1.0/n_eval*10**3 | |
| print "time(Norm)/time(np.linalg.norm) = ", time_norm_ms/time_linalg_ms | |
| if __name__ == '__main__': | |
| n_eval = 100 | |
| m = 35 | |
| for n in range(10,50,5): | |
| print "n = ", n | |
| A = np.random.rand(n) | |
| print "1D array" | |
| time_norms(A,n_eval) | |
| A = np.random.rand(n,m) | |
| print "2D array" | |
| time_norms(A,n_eval) | |
| A = np.random.rand(n,m,n) | |
| print "3D array" | |
| time_norms(A,n_eval) | |
| print "" |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment