Finding the Max value in a two dimensional Array

Question

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.

Oliverolivera

Answer 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

Memorize

Answer 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)

Dodecanese

Better than the accepted answer in every way – Prem

except that it doesn't work on an input like [[0, 1, 2], [3, 4]] – Substitute

Answer 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

Excavation

Answer 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]

You may add key parameter to max as below to find Max value in a 2-D Array/List

>>> max(max(numbers, key=max))
4

Fredra

Answer 5

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

Loreeloreen

and how about to get the index of each sub-list which has max value? – Spermary

Answer 6

One very easy solution to get both the index of your maximum and your maximum could be :

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]])
ind = np.argwhere(numbers == numbers.max()) # In this case you can also get the index of your max
numbers[ind[0,0],ind[0,1]]

Supen

Answer 7

This approach is not as intuitive as others but here goes,

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]

maximum = -9999

for i in numbers:

    maximum = max(maximum,max(i))

return maximum"

Parnassus

Answer 8

chain.from_iterable is an elegant solution:

from itertools import chain
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]
res = max(chain.from_iterable(numbers)) # 4

Inferential