On Mon, Jan 21, 2013 at 2:41 PM, Neal Becker <[email protected]> wrote: > I have an array to be used for indexing. It is 2d, where the rows are all the > permutations of some numbers. So: > > array([[-2, -2, -2], > [-2, -2, -1], > [-2, -2, 0], > [-2, -2, 1], > [-2, -2, 2], > ... > [ 2, 1, 2], > [ 2, 2, -2], > [ 2, 2, -1], > [ 2, 2, 0], > [ 2, 2, 1], > [ 2, 2, 2]]) > > Here the array is 125x3 > > I want to select all the rows of the array in which all the 3 elements are > equal, so I can remove them. So for example, the 1st and last row.
all_equal_mask = np.logical_and.reduce(arr[:,1:] == arr[:,:-1], axis=1) some_unequal = arr[~all_equal_mask] -- Robert Kern _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
