Python Numpy matrix.cumsum() 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 in 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.cumsum() Function: 

Using the matrix.cumsum() function of the NumPy module, we can find the cumulative sum of a given matrix and returns the output as a 1-Dimensional matrix.

Syntax:

 matrix.cumsum()

Return Value:

The cumulative sum of a given matrix is returned by the cumsum() function.

Cumulative sum:

The cumulative sum denotes “how much so far.” The cumulative sum is defined as the sum of a given sequence that grows or increases with more additions.

Numpy matrix.cumsum() Function in Python

For 1-Dimensional (1D) Matrix

Approach:

  • Import numpy module using the import keyword
  • Create a matrix(1-Dimensional) using the matrix() function of numpy module by passing some random 1D matrix as an argument to it and store it in a variable
  • Apply cumsum() function on the given matrix to get the cumulative sum of a given matrix.
  • Store it in another variable
  • Print the cumulative sum of 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(1-Dimensional) using the matrix() function of numpy module by passing 
# some random 1D matrix as an argument to it and store it in a variable
gvn_matrx = np.matrix('[1, 4, 2]')
            
# Apply cumsum() function on the given matrix to get the cumulative sum of a given matrix.
# Store it in another variable
rslt = gvn_matrx.cumsum()
# Print the cumulative sum of a given matrix.
print("The cumulative sum of a given matrix:")
print(rslt)

Output:

The cumulative sum of a given matrix:
[[1 5 7]]

Explanation:

Here it prints 1, adds 1+4 = 5, and adds that result to the next element i.e, 5+2=7

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
  • Apply cumsum() function on the given matrix to get the cumulative sum of a given matrix.
  • Store it in another variable
  • Print the cumulative sum of 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('[1, 2; 4, 5]')
            
# Apply cumsum() function on the given matrix to get the cumulative sum of a given matrix.
# Store it in another variable
rslt = gvn_matrx.cumsum()
# Print the cumulative sum of a given matrix.
print("The cumulative sum of a given matrix:")
print(rslt)

Output:

The cumulative sum of a given matrix:
[[ 1 3 7 12]]