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I can find quite a few permutations of this question, but not this (rather simple) one: how do I find the maximum value of a specific column of a numpy array (in the most pythonic way)?
a = array([[10, 2], [3, 4], [5, 6]]) What I want is the max value in the first column and second column (these are x,y coordinates and I eventually need the height and width of each shape), so max x coordinate is 10 and max y coordinate is 6.
I've tried:
xmax = numpy.amax(a,axis=0) ymax = numpy.amax(a,axis=1) but these yield
array([10, 6]) array([10, 4, 6]) ...not what I expected.
My solution is to use slices:
xmax = numpy.max(a[:,0]) ymax = numpy.max(a[:,1]) Which works but doesn't seem to the best approach.
Suggestions?
967
maximum() function is used to find the element-wise maximum of array elements. It compares two arrays and returns a new array containing the element-wise maxima. If one of the elements being compared is a NaN, then that element is returned.
amax() will find the max value in an array, and numpy. amin() does the same for the min value.
To get the indizes of the maxima in the columns, you can use the ndarray. argmax() function. You can also pass the axis argument ot this function, but there is no keepdims option. In both commands axis=0 describes the columns, axis=1 describes the rows.
Just unpack the list:
In [273]: xmax, ymax = a.max(axis=0) In [274]: print xmax, ymax #10 6 If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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