To get the Inner product of two multi-dimensional arrays, use the numpy.inner() method in Python. Ordinary inner product of vectors for 1-D arrays, in higher dimensions a sum product over the last axes. The parameters are 1 and b, two vectors. If a and b are nonscalar, their last dimensions must match.
Steps
At first, import the required libraries -
import numpy as np
Creating two numpy Two-Dimensional array using the array() method −
arr1 = np.array([[5, 10], [15, 20]]) arr2 = np.array([[6, 12], [18, 24]])
Display the arrays −
print("Array1...\n",arr1)
print("\nArray2...\n",arr2)Check the Dimensions of both the arrays −
print("\nDimensions of Array1...\n",arr1.ndim)
print("\nDimensions of Array2...\n",arr2.ndim)Check the Shape of both the arrays −
print("\nShape of Array1...\n",arr1.shape)
print("\nShape of Array2...\n",arr2.shape)To get the Inner product of two multi-dimensional arrays, use the numpy.inner() method in Python. Ordinary inner product of vectors for 1-D arrays, in higher dimensions a sum product over the last axes −
print("\nResult (Inner Product)...\n",np.inner(arr1, arr2))Example
import numpy as np
# Creating two numpy Two-Dimensional array using the array() method
arr1 = np.array([[5, 10], [15, 20]])
arr2 = np.array([[6, 12], [18, 24]])
# Display the arrays
print("Array1...\n",arr1)
print("\nArray2...\n",arr2)
# Check the Dimensions of both the arrays
print("\nDimensions of Array1...\n",arr1.ndim)
print("\nDimensions of Array2...\n",arr2.ndim)
# Check the Shape of both the arrays
print("\nShape of Array1...\n",arr1.shape)
print("\nShape of Array2...\n",arr2.shape)
# To get the Inner product of two multi-dimensional arrays, use the numpy.inner() method in Python
print("\nResult (Inner Product)...\n",np.inner(arr1, arr2))Output
Array1... [[ 5 10] [15 20]] Array2... [[ 6 12] [18 24]] Dimensions of Array1... 2 Dimensions of Array2... 2 Shape of Array1... (2, 2) Shape of Array2... (2, 2) Result (Inner Product)... [[150 330] [330 750]]