On 4/21/09, [email protected] <[email protected]> wrote: > On Tue, Apr 21, 2009 at 6:23 PM, Keith Goodman <[email protected]> wrote: > >> On 4/21/09, Mathew Yeates <[email protected]> wrote: >> > Hi >> > I posted something about this earlier >> > >> > Say I have 2 arrays X and Y with shapes (N,3) where N is large >> > I am doing the following >> > >> > for row in range(N): >> > result=polyfit(X[row,:],Y[row,:],1,full=True) # fit 3 points with a >> line >> > >> > This takes forever and I was hoping to find a way to speed things up. >> > But now I'm starting to wonder if this pointless. If the routine "poly >> > fit takes a long time, when compared with the time for a Python >> > function call, then things can't be sped up. >> > >> > Any comments? >> >> If you remove the mean from x and y (along axis = 1) then can't you >> just do something like >> >> (x*y).sum(1) / (x*x).sum(axis=1) >> > > I think that's what I said 8 days ago.
Nice. You even calculated the intercepts. _______________________________________________ Numpy-discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
