How to create a new matrix using MIN and MAX from original array

I have a matrix named A, and I want to create a new matrix named B, where each element value is generated by this formula:

B[i][j] = (A[i][j] - MIN) / (MAX - MIN), where

• i is the line index
• j is the column index.
• MIN is the minimum from A
• MAX is the value with highest value from A.

I tried a for loop but I want to increase efficiency, I want to use numpy function but I don’t know which function I have to use and how to use this function, with my problem.

Answer

I’m not sure whether the MIN&MAX are standing for

1. the MIN&MAX value of the column/row from A, or
2. the MIN&MAX value of the entire matrix(A).

Plz leave a comment if I’m misunderstanding and here’s the solution for second meaning of MIN&MAX.

import numpy as np

A = np.matrix(np.arange(12).reshape((3,4)))
MAX, MIN = A.max(), A.min()
B = np.matrix((A - MIN)/(MAX - MIN))
print(A)
print(B)

Output:

[[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]]
[[0.         0.09090909 0.18181818 0.27272727]
 [0.36363636 0.45454545 0.54545455 0.63636364]
 [0.72727273 0.81818182 0.90909091 1.        ]]