﻿ NumPy: Compute the inner product of vectors for 1-D arrays and in higher dimension - 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:

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## 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)
```