numpy.dot - Python

Introduction

numpy.dot is a function in the NumPy library of Python that is used to compute the dot product of two arrays. It is a fundamental operation in linear algebra and is commonly used in various scientific and mathematical computations.

The dot product is calculated as the sum of the element-wise multiplication of corresponding elements from two arrays. The arrays must have the same shape or be broadcastable to the same shape.

Syntax

The syntax for numpy.dot is as follows:

numpy.dot(a, b, out=None)

Where,

• a and b are the input arrays. Both should be 1-D or 2-D arrays.
• out (optional) is the output array where the result is stored.

Example Usage

Here is an example that demonstrates the usage of numpy.dot:

import numpy as np

a = np.array([1, 2, 3])
b = np.array([4, 5, 6])

result = np.dot(a, b)
print(result)

Output:

32

In this example, we compute the dot product of arrays a and b using numpy.dot. The dot product is calculated as 1*4 + 2*5 + 3*6, which results in 32. The result is then printed.

Broadcasting Rules

It is important to note that when the input arrays have different shapes, NumPy's broadcasting rules are applied. The broadcasting rules allow arrays with different shapes to be used in arithmetic operations.

For example, if we have a 2-D array a of shape (2, 3) and a 1-D array b of shape (3,), the dot product will still be calculated correctly. The 1-D array will be broadcasted (replicated) to match the shape of the 2-D array for the calculation.

Conclusion

In summary, numpy.dot is a useful function in Python that allows us to compute the dot product of two arrays. It is extensively used in linear algebra, signal processing, and other scientific computations. Understanding how to use numpy.dot effectively can greatly enhance your coding abilities in various domains.