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]]
