w3resource

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)

Sample Output:

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:


Have another way to solve this solution? Contribute your code (and comments) through Disqus.

Previous: Write a NumPy program to evaluate Einstein’s summation convention of two given multidimensional arrays.
Next: Write a NumPy program to compute the eigenvalues and right eigenvectors of a given square array.

What is the difficulty level of this exercise?

Test your Python skills with w3resource's quiz



Python: Tips of the Day

Python: The Zip() Function

>>> students = ('John', 'Mary', 'Mike')
>>> ages = (15, 17, 16)
>>> scores = (90, 88, 82, 17, 14)
>>> for student, age, score in zip(students, ages, scores):
...     print(f'{student}, age: {age}, score: {score}')
... 
John, age: 15, score: 90
Mary, age: 17, score: 88
Mike, age: 16, score: 82
>>> zipped = zip(students, ages, scores)
>>> a, b, c = zip(*zipped)
>>> print(b)
(15, 17, 16)