Numpy ndarray.dot() function

Exploring NumPy's ndarray.dot() Function

What is the ndarray.dot() Function?

• 1D arrays: Computes the inner product, resulting in a scalar.
• 2D arrays: Performs matrix multiplication.
• Higher-dimensional arrays: Applies matrix multiplication over the last two axes.

Syntax

numpy.ndarray.dot(arr, out=None)

• arr: The input array for the dot product.
• out (optional): A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to.

Example 1: Dot Product of 1D Arrays

import numpy as np
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
result = a.dot(b)
print(result)

Example 2: Matrix Multiplication

import numpy as np
A = np.array([[1, 2], [3, 4]])
B = np.array([[5, 6], [7, 8]])
result = A.dot(B)
print(result)

Example 3: Dot Product with Higher-Dimensional Arrays

import numpy as np
A = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
B = np.array([[[9, 10], [11, 12]], [[13, 14], [15, 16]]])
result = A.dot(B)
print(result)

Performance Considerations

Conclusion