Min and Max Problem
The tool min returns the minimum value along a given axis.
import numpy my_array = numpy.array([[2, 5], [3, 7], [1, 3], [4, 0]]) print numpy.min(my_array, axis = 0) #Output : [1 0] print numpy.min(my_array, axis = 1) #Output : [2 3 1 0] print numpy.min(my_array, axis = None) #Output : 0 print numpy.min(my_array) #Output : 0
By default, the axis value is None
. Therefore, it finds the minimum over all the dimensions of the input array.
The tool max returns the maximum value along a given axis.
import numpy my_array = numpy.array([[2, 5], [3, 7], [1, 3], [4, 0]]) print numpy.max(my_array, axis = 0) #Output : [4 7] print numpy.max(my_array, axis = 1) #Output : [5 7 3 4] print numpy.max(my_array, axis = None) #Output : 7 print numpy.max(my_array) #Output : 7
By default, the axis value is None
. Therefore, it finds the maximum over all the dimensions of the input array.
Task
You are given a 2-D array with dimensions N X M.
Your task is to perform the min function over axis 1 and then find the max of that.
Input Format
The first line of input contains the space separated values of N and M.
The next N lines contains M space separated integers.
Output Format
Compute the min along axis 1 and then print the max of that result.
Sample Input
4 2 2 5 3 7 1 3 4 0
Sample Output
3
Explanation
The min along axis 1 = [2,3,1,0]
The max of [2,3,1,0]=3
Code:
import numpy N,M=map(int,input().split()) A = numpy.array([input().split() for _ in range(N)], int) print(numpy.max(numpy.min(A, axis=1)))
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