Hi,
a lot of people think that C (or C++) is faster than python, yes I agree,
but I think that's not the case with numpy, I believe numpy is faster than
C, at least in some cases.
*Is there another explanation ?Or where can find a doc speaking about the
subject?*Thanks a lot
Regards
Numpy implements vectorization for arrays, or I'm wrong. Anyway here is an
example Let's look at the following case:
Here is the result on my laptop i3:
Labs$ *python3 tempsExe.py 50000*
sum with Python: 1250025000 and NumPy 1250025000
time used Python Sum: * 37.28 sec *
time used Numpy Sum: *1.85 sec*
Labs$ *./tt 50000 *
* CPU time :7.521730*
* The value : 1250025000 *
*This is the Python3 program :import timeit as itimport numpy as npimport
systry : n=eval(sys.argv[1])except: print ("needs integer as argument") ;
exit() a=range(1,n+1)b=np.array(a)def func1(): return sum(a)def
func2(): return np.sum(b)print(f"sum with Python: {func1()} and NumPy
{func2()} ")tm1=it.timeit(stmt=func1, number=n)print(f"time used Python
Sum: {round(tm1,2)} sec")tm2=it.timeit(stmt=func2, number=n)print(f"time
used Numpy Sum: {round(tm2,2)} sec")*
*and Here the C program:#include <time.h>#include <stdio.h>#include
<stdlib.h>long func1(int n){ long r=0; for (int i=1; i<=
n;i++) r+= i; return r;}int main(int argc, char* argv[]){
clock_t c0, c1; long v,count; int n; if ( argc < 2)
{ printf("Please give an argument"); return
-1; } n=atoi(argv[1]); c0 = clock();*
* for (int j=0;j < n;j++) v=func1(n); c1 = clock(); printf
("\tCPU time :%.2f sec", (float)(c1 - c0)/CLOCKS_PER_SEC);
printf("\n\tThe value : %ld\n", v);}*
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