Thanks for the speedy response but where can I locate the find function as it isn't in numpy.
Andy mark wrote: > I think you can create an array with a true value in the right spot as > folows: > > row = all( equal(a,b), 1 ) > > Then you can either find the row (but you already knew that one, as it > is b) > > a[row] > > or the row index > > find(row==True) > > Mark > > On Aug 15, 11:53 am, Andy Cheesman <[EMAIL PROTECTED]> > wrote: >> Dear nice people >> >> I'm trying to match a row (b) within a large numpy array (a). My most >> successful attempt is below >> >> hit = equal(b, a) >> total_hits = add.reduce(hit, 1) >> max_hit = argmax(total_hits, 0) >> answer = a[max_hit] >> >> where ... >> a = array([[ 0, 1, 2, 3], >> [ 4, 5, 6, 7], >> [ 8, 9, 10, 11], >> [12, 13, 14, 15]]) >> >> b = array([8, 9, 10, 11]) >> >> I was wondering if people could suggest a possible more efficient route >> as there seems to be numerous steps. >> >> Thanks >> Andy >> _______________________________________________ >> Numpy-discussion mailing list >> [EMAIL PROTECTED]://projects.scipy.org/mailman/listinfo/numpy-discussion > > _______________________________________________ > Numpy-discussion mailing list > [email protected] > http://projects.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
