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问题:
I'm trying to find an elegant way to find the max value in a two-dimensional array.
for example for this array:
[0, 0, 1, 0, 0, 1] [0, 1, 0, 2, 0, 0][0, 0, 2, 0, 0, 1][0, 1, 0, 3, 0, 0][0, 0, 0, 0, 4, 0]
I would like to extract the value '4'.
I thought of doing a max within max but I'm struggling in executing it.
回答1:
Max of max numbers (map(max, numbers)
yields 1, 2, 2, 3, 4):
>>> numbers = [0, 0, 1, 0, 0, 1], [0, 1, 0, 2, 0, 0], [0, 0, 2, 0, 0, 1], [0, 1, 0, 3, 0, 0], [0, 0, 0, 0, 4, 0]
>>> map(max, numbers)
<map object at 0x0000018E8FA237F0>
>>> list(map(max, numbers)) # max numbers from each sublist
[1, 2, 2, 3, 4]
>>> max(map(max, numbers)) # max of those max-numbers
4
回答2:
Another way to solve this problem is by using function numpy.amax()
>>> import numpy as np
>>> arr = [0, 0, 1, 0, 0, 1] , [0, 1, 0, 2, 0, 0] , [0, 0, 2, 0, 0, 1] , [0, 1, 0, 3, 0, 0] , [0, 0, 0, 0, 4, 0]
>>> np.amax(arr)
回答3:
Not quite as short as falsetru's answer but this is probably what you had in mind:
>>> numbers = [0, 0, 1, 0, 0, 1], [0, 1, 0, 2, 0, 0], [0, 0, 2, 0, 0, 1], [0, 1, 0, 3, 0, 0], [0, 0, 0, 0, 4, 0]
>>> max(max(x) for x in numbers)
4
回答4:
How about this?
import numpy as np
numbers = np.array([[0, 0, 1, 0, 0, 1], [0, 1, 0, 2, 0, 0], [0, 0, 2, 0, 0, 1], [0, 1, 0, 3, 0, 0], [0, 0, 0, 0, 4, 0]])
print(numbers.max())
4