Numpy inner - Python NumPy inner() Function

NumPy inner() Function:

Numpy inner: The inner product of two arrays is returned by the inner() function of the NumPy module. It returns the ordinary inner product for 1-D arrays (without complex conjugation). A sum product over the last axes is returned for higher dimensions.

Syntax:

numpy.inner(a, b)

Parameters

a: This is required. It is the first array_like parameter given as input. If a and b are nonscalar, they must have the same last dimension.

b: This is required. It is the second array_like parameter given as input.

Return Value:

The inner product of a and b is returned.

Note: If the last dimension of a and b are different sizes, a ValueError exception is thrown.

NumPy inner() Function in Python

Example1

np.inner: Here the two scalars passed as arguments for the inner() function.

Approach:

Import numpy module using the import keyword.
Pass two random numbers as the arguments to the inner () function of numpy module to calculate the inner product of the given two numbers.
Store it in a variable.
Print the inner product of the given two numbers.
The Exit of the Program.

Below is the implementation:

# Import numpy module using the import keyword
import numpy as np
# Pass two random numbers as the arguments to the inner() function
# of numpy module to calculate the inner product of given two numbers
# Store it in a variable.
rslt = np.inner(4, 6)
# Print the inner product of the given two numbers 
print("The inner product of given two numbers = ", rslt)

Output:

The inner product of given two numbers = 24

Example2

Approach:

Import numpy module using the import keyword.
Give the first array as static input and store it in a variable.
Give the second array as static input and store it in another variable.
Pass the given two array’s as an argument to the inner() function of numpy module to get the inner product of the given two arrays.
Store it in another variable.
Print the inner product of the given two arrays.
The Exit of the Program.

Below is the implementation:

# Import numpy module using the import keyword
import numpy as np
# Give the first array as static input and store it in a variable.
fst_arry = [3, 9, 2]
# Give the second array as static input and store it in another variable.
scnd_arry = [4, 3, 5]
# Pass the given two array's as an argument to the inner() function of numpy module 
# to get the inner product of the given two arrays.
# Store it in another variable.
rslt = np.inner(fst_arry, scnd_arry)
# Print the inner product of the given two arrays.
print("The inner product of the given two arrays = ", rslt)

Output:

The inner product of the given two arrays = 49

Example3

Below is the implementation:

# Import numpy module using the import keyword
import numpy as np
# Pass the random list of complex numbers as an argument to the array() function 
# to create an array. 
# Store it in a variable.
fst_arry = np.array([1+4j, 1+3j])
# Pass the random list of complex numbers as an argument to the array() function 
# to create another array. 
# Store it in another variable.
scnd_arry = np.array([2+1j, 3+2j])
# Pass the given two array's as the argument to the inner() function of numpy module 
# to get the inner product of the given two arrays of complex numbers.
# Store it in another variable.
rslt = np.inner(fst_arry, scnd_arry)
# Print the inner product of the given two arrays of complex numbers.
print("The inner product of the given two arrays of complex numbers = ")
print(rslt)

Output:

The inner product of the given two arrays of complex numbers =
(-5+20j)

Example4

The function does inner product on the matrix’s last axes when two matrices are used.

Below is the implementation:

# Import numpy module using the import keyword
import numpy as np
# Pass the random list(2D) as an argument to the array() function 
# to create an array. 
# Store it in a variable.
fst_arry = np.array([[5, 6], 
                     [1, 7]])
# Pass the random list(2D) as an argument to the array() function 
# to create another array. 
# Store it in another variable.
scnd_arry = np.array([[2, 4], 
                      [8, 7]])
# Pass the given two array's as the argument to the inner() function of numpy module 
# to get the inner product of the given two 2D arrays 
# Here it does the inner product on last axes of the matrix.
# Store it in another variable.
rslt = np.inner(fst_arry, scnd_arry)
# Print the inner product of given two arrays(matrices)
print("The inner product of given two arrays(matrices) = ")
print(rslt)

Output:

The inner product of given two arrays(matrices) = 
[[34 82]
 [30 57]]

Numpy inner – Python NumPy inner() Function

NumPy inner() Function in Python

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