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 it
import numpy as np
import sys
try :
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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