On Sun, Nov 1, 2015 at 9:04 PM, gers antifx <schweiger.ger...@gmail.com> wrote: > I have to write a LU-decomposition. My Code worked so far but (I want to > become better:) ) I want to ask you, if I could write this LU-decomposition > in a better way? > > def LU(x): > L = np.eye((x.shape[0])) > n = x.shape[0] > for ii in range(n-1): > for ll in range(1+ii,n): > factor = float(x[ll,ii])/x[ii,ii] > L[ll,ii] = factor > for kk in range(0+ii,n): > x[ll,kk] = x[ll,kk] - faktor*x[ii,kk] > LU = np.dot(L,x)
For a start, I would recommend being careful with your variable names. You have 'factor' all except one, where you have 'faktor' - transcription error, or nearly-identical global and local names? And all your other names are fairly opaque; can they be better named? I'm particularly looking at this line: x[ll,kk] = x[ll,kk] - faktor*x[ii,kk] It is *extremely not obvious* that the first two are using 'll' and the last one is using 'ii'. (Though I would write this as "x[ll,kk] -= faktor*x[ii,kk]", which at least cuts down the duplication, so it's less glitchy to have one out of three that's different.) I was going to ask if you had some reason for not inverting the factor and simply using "x[ll,kk] *= factor", till I read it again and saw the difference. I'm seeing here a lot of iteration over ranges, then subscripting with that. Is it possible to iterate over the numpy array itself instead? That's generally a more Pythonic way to do things. Assigning to the local name LU at the end of the function seems odd. Did you intend to return the dot-product? Beyond that, I'd need a better comprehension of the mathematics behind this, to evaluate what it's doing. So I'll let the actual experts dive in :) ChrisA -- https://mail.python.org/mailman/listinfo/python-list
