Hello, I wonder if it would be worth to enhance max, min, argmax and argmin (more?) with a tie breaking parameter: If multiple entries have the same value the first value is returned by now. It would be useful to have a parameter to alter this behavior to an arbitrary tie-breaking. I would propose, that the tie-breaking function gets a list with all indices of the max/mins.
Example: >>> a = np.array([ 1, 2, 5, 5, 2, 1]) >>> np.argmax(a, tie_breaking=random.choice) 3 >>> np.argmax(a, tie_breaking=random.choice) 2 >>> np.argmax(a, tie_breaking=random.choice) 2 >>> np.argmax(a, tie_breaking=random.choice) 2 >>> np.argmax(a, tie_breaking=random.choice) 3 Especially for some randomized experiments it is necessary that not always the first maximum is returned, but a random optimum. Thus I end up writing these things over and over again. I understand, that max and min are crucial functions, which shouldn't be slowed down by the proposed changes. Adding new functions instead of altering the existing ones would be a good option. Are there any concerns against me implementing these things and sending a pull request? Should such a function better be included in scipy for example? Best, Johannes _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
