NumPy: Compute the inner product of vectors for 1-D arrays and in higher dimension
NumPy: Linear Algebra Exercise-6 with Solution
Write a NumPy program to compute the inner product of vectors for 1-D arrays (without complex conjugation) and in higher dimension.
Sample Solution :
Python Code :
import numpy as np a = np.array([1,2,5]) b = np.array([2,1,0]) print("Original 1-d arrays:") print(a) print(b) print result = np.inner(a, b) print("Inner product of the said vectors:") x = np.arange(9).reshape(3, 3) y = np.arange(3, 12).reshape(3, 3) print("Higher dimension arrays:") print(x) print(y) result = np.inner(x, y) print("Inner product of the said vectors:") print(result)
Original 1-d arrays: [1 2 5] [2 1 0] Inner product of the said vectors: Higher dimension arrays: [[0 1 2] [3 4 5] [6 7 8]] [[ 3 4 5] [ 6 7 8] [ 9 10 11]] Inner product of the said vectors: [[ 14 23 32] [ 50 86 122] [ 86 149 212]]
Python Code Editor:
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