sturlamolden wrote: > as well as looping over the data only once. This is one of the main > reasons why Fortran is better than C++ for scientific computing. I.e. > instead of > > for (i=0; i<n; i++) > array1[i] = (array1[i] + array2[i]) * (array3[i] + array4[i]); > > one actually gets something like three intermediates and four loops: > > tmp1 = malloc(n*sizeof(whatever)); > for (i=0; i<n; i++) > tmp1[i] = array1[i] + array2[i]; > tmp2 = malloc(n*sizeof(whatever)); > for (i=0; i<n; i++) > tmp2[i] = array3[i] + array4[i]; > tmp3 = malloc(n*sizeof(whatever)); > for (i=0; i<n; i++) > tmp3[i] = tmp1[i] + tmp2[i]; > free(tmp1); > free(tmp2); > for (i=0; i<n; i++) > array1[i] = tmp3[i]; > free(tmp3);
C/C++ do not allocate extra arrays. What you posted _might_ bear a small resemblance to what numpy might produce (if using vectorized code, not explicit loop code). This is entirely unrelated to the reasons why fortran can be faster than c. -Mike -- http://mail.python.org/mailman/listinfo/python-list
