Description
Context
When the multiply operation is performed on two-dimensional matrixes, np.matmul() and np.dot() give the same result, which is a matrix.
Problem
In mathematics, the result of the dot product is expected to be a scalar rather than a vector. The np.dot() returns a new matrix for two-dimensional matrixes multiplication, which does not match with its mathematics semantics. Developers sometimes use np.dot() in scenarios where it is not supposed to, e.g., two-dimensional multiplication.
Solution
When the multiply operation is performed on two-dimensional matrixes, np.matmul() is preferred over np.dot() for its clear semantic.
Type
API-Specific
Existing Stage
Data Cleaning
Effect
Readability
Example
### NumPy
import numpy as np
a = [[1, 0], [0, 1]]
b = [[4, 1], [2, 2]]
- np.dot(a, b)
+ np.matmul(a, b)