Say I have a multi dimensional array like the following:
[
[.1, .2, .9],
[.3, .4, .5],
[.2, .4, .8]
]
What would be the best* way to return a single dimension array that contains the highest value from each sub-array ([.9,.5,.8]
)? I assume I could do it manually doing something like below:
newArray = []
for subarray in array:
maxItem = 0
for item in subarray:
if item > maxItem:
maxItem = item
newArray.append(maxItem)
But I'm curious if there is a cleaner way to do this?
*In this case best = fewest lines of code
Try this:
max(array.flatten())
Since you mentioned in a comment that you are using numpy ...
>>> import numpy as np
>>> a = np.random.rand(3,3)
>>> a
array([[ 0.43852835, 0.07928864, 0.33829191],
[ 0.60776121, 0.02688291, 0.67274362],
[ 0.2188034 , 0.58202254, 0.44704166]])
>>> a.max(axis=1)
array([ 0.43852835, 0.67274362, 0.58202254])
edit: the documentation is here
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