> |6> y[np.argmin(y, axis=0), np.arange(y.shape[1])] > array([0, 0, 0, 0, 0])
Can xrange in this case save me from creating a temporary array here or doesn't it matter? |6> y[np.argmin(y, axis=0), xrange(y.shape[1])] array([0, 0, 0, 0, 0]) //Torgil On Tue, Dec 13, 2011 at 11:27 PM, Robert Kern <robert.k...@gmail.com> wrote: > On Tue, Dec 13, 2011 at 22:11, Ken Basye <kbas...@jhu.edu> wrote: >> Hi folks, >> I need an efficient way to get both the min and argmin of a 2-d >> array along one axis. It seemed to me that the way to do this was to >> get the argmin and then use it to index into the array to get the min, >> but I can't figure out how to do it. Here's my toy example: > > [~] > |1> x = np.arange(25).reshape((5,5)) > > [~] > |2> y = np.abs(x - x.T) > > [~] > |3> y > array([[ 0, 4, 8, 12, 16], > [ 4, 0, 4, 8, 12], > [ 8, 4, 0, 4, 8], > [12, 8, 4, 0, 4], > [16, 12, 8, 4, 0]]) > > [~] > |4> i = np.argmin(y, axis=0) > > [~] > |5> y[i, np.arange(y.shape[1])] > array([0, 0, 0, 0, 0]) > > [~] > |6> y[np.argmin(y, axis=0), np.arange(y.shape[1])] > array([0, 0, 0, 0, 0]) > > -- > Robert Kern > > "I have come to believe that the whole world is an enigma, a harmless > enigma that is made terrible by our own mad attempt to interpret it as > though it had an underlying truth." > -- Umberto Eco > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
