Python Numpy matrix.argmax() Function

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NumPy Library 

NumPy is a library in python that is created to work efficiently with arrays in python. It is fast, easy to learn, and provides efficient storage. It also provides a better way of handling data for the process. We can create an n-dimensional array in NumPy. To use NumPy simply have to import it into our program and then we can easily use the functionality of NumPy in our program.

NumPy is a Python library that is frequently used for scientific and statistical analysis. NumPy arrays are grids of the same datatype’s values.

Numpy matrix.argmax() Function:

Using the matrix.argmax() method of the Numpy module, we can obtain the index value of the largest/maximum element in a given matrix including one or more dimensions.

Syntax:

 matrix.argmax()

Return Value:

The index value of the largest/maximum element in a given matrix is returned by the argmax() Function.

Numpy matrix.argmax() Function in Python

For 2-Dimensional (2D) Matrix

Approach:

  • Import numpy module using the import keyword
  • Create a matrix(2-Dimensional) using the matrix() function of numpy module by passing some random 2D matrix as an argument to it and store it in a variable
  • Print the given matrix.
  • Apply the argmax() function on the given matrix to get the index value of the maximum (largest) element in a given matrix and store it in another variable
  • Print the index value of the largest element in a given matrix.
  • The Exit of the Program.

Below is the implementation:

# Import numpy module using the import keyword
import numpy as np
            
# Create a matrix(2-Dimensional) using the matrix() function of numpy module by passing 
# some random 2D matrix as an argument to it and store it in a variable
gvn_matrx = np.matrix('[10, 8; 3, 1]')

# Print the given matrix
print("The given matrix is:") 
print(gvn_matrx)   

# Apply the argmax() function on the given matrix to get the index value of the 
# maximum(largest) element in a given matrix and store it in another variable
rslt = gvn_matrx.argmax()

# Print the index value of the largest element in a given matrix 
print("The index of the largest element in a given matrix = ", rslt)

Output:

The given matrix is:
[[10 8]
 [ 3 1]]
The index of the largest element in a given matrix = 0

For 3-Dimensional (3D) Matrix

Approach:

  • Import numpy module using the import keyword
  • Create a matrix(3-Dimensional) using the matrix() function of numpy module by passing some random 3D matrix as an argument to it and store it in a variable
  • Print the given matrix.
  • Apply the argmax() function on the given matrix to get the index value of the maximum (largest) element in a given matrix and store it in another variable
  • Print the index value of the largest element in a given matrix.
  • The Exit of the Program.

Below is the implementation:

# Import numpy module using the import keyword
import numpy as np
            
# Create a matrix(3-Dimensional) using the matrix() function of numpy module by passing 
# some random 3D matrix as an argument to it and store it in a variable
gvn_matrx = np.matrix('[5, 6, 4; 2, 7, 8; 9, -1, 3]')

# Print the given matrix
print("The given matrix is:") 
print(gvn_matrx)   

# Apply the argmax() function on the given matrix to get the index value of the 
# maximum(largest) element in a given matrix and store it in another variable
rslt = gvn_matrx.argmax()

# Print the index value of the largest element in a given matrix 
print("The index of the largest element in a given matrix = ", rslt)

Output:

The given matrix is:
[[ 5 6 4]
 [ 2 7 8]
 [ 9 -1 3]]
The index of the largest element in a given matrix = 6