[python-uk] C is it faster than numpy

[BELAHCENE Abdelkader]

Thanks,
But the different is very significant!!!
so?

Le ven. 25 févr. 2022 à 10:58, Edward Hartley <ed.hartley at gmail.com> a
écrit :

>
> Hi,
> Simply check the original Numpy aka Numerical Python docs where it’s
> comprehensively explained that the library is implemented in C with a thin
> Python wrapper. The docs were written circa ‘98 by the original library
> author. The library was optimised over a long period before being released.
> I’ve seen similar results when replacing an optimised Fortran library with
> C/C++ the key is the effort given to optimisation, and care with avoiding
> unnecessary memory allocation.
> I’ll dig out the reference when I’ve tracked it down.
> Best of Luck
> Ed Hartley
>
> On 25 Feb 2022, at 09:42, Giorgio Zoppi <giorgio.zoppi at gmail.com> wrote:
>
> 
> Well,
> numpy is written in C :) Maybe your C is not the numpy equivalent?
> Best Regards,
> Giorgio
>
> Il giorno ven 25 feb 2022 alle ore 09:03 BELAHCENE Abdelkader <
> abdelkader.belahcene at enst.dz> ha scritto:
>
>> 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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>
>
> --
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