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Numpy has np.argmax, np.argmin, so as a alternative we need those functions
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>>> a = np.arange(6).reshape(2,3) + 10 >>> a array([[10, 11, 12], [13, 14, 15]]) >>> np.argmax(a) 5 >>> np.argmax(a, axis=0) # at y axis 13>10 and 14>11 and 15>12 array([1, 1, 1]) >>> np.argmax(a, axis=1) # x axis array([2, 2])
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Numpy has np.argmax, np.argmin, so as a alternative we need those functions
The text was updated successfully, but these errors were encountered: