Hi, Thanks to everybody for all you valuable responses. This approach by Rick White seems to nail it all down:
>> b = np.array([ >> [0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 7, 8, 9, 10, >> 11], >> [5, 6, 1, 0, 2, 7, 3, 8, 1, 4, 9, 2, 10, 5, 3, 4, 11, 0, 0, 1, 2, 3, 4, 5] >> ]) >> >> a = [1,2,3,7,8] >> >> keepdata = np.ones(12, dtype=np.bool) >> keepdata[a] = False >> w = np.where(keepdata[b[0]] & keepdata[b[1]]) >> newindex = keepdata.cumsum()-1 >> c = newindex[b[:,w[0]]] Also, I'd like to mention that I did think about using the graph module from SciPy. But the index bookkeeping done by numpy is in fact index pointers to memory location in a C++ driver - and not just labels. An when atoms are deleted, there memory chunks are also cleared, and therefore all pointers to these must be decremented. So using numpy for the bookkeeping seems a natural choice. Best regards, Mads On 02/03/2014 02:36 PM, Rick White wrote: > b = np.array([ > [0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 7, 8, 9, 10, 11], > [5, 6, 1, 0, 2, 7, 3, 8, 1, 4, 9, 2, 10, 5, 3, 4, 11, 0, 0, 1, 2, 3, 4, 5] > ]) > > a = [1,2,3,7,8] > > keepdata = np.ones(12, dtype=np.bool) > keepdata[a] = False > w = np.where(keepdata[b[0]] & keepdata[b[1]]) > newindex = keepdata.cumsum()-1 > c = newindex[b[:,w[0]]] -- +---------------------------------------------------------+ | Mads Ipsen | +----------------------+----------------------------------+ | Gåsebæksvej 7, 4. tv | phone: +45-29716388 | | DK-2500 Valby | email: mads.ip...@gmail.com | | Denmark | map : www.tinyurl.com/ns52fpa | +----------------------+----------------------------------+ _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
