Vectorized matrix operations are operations that occur in parallel on the elements of two matrices. This allows you to write code that is efficient, concise, and easier to read than in non-vectorized languages.
For example, the following code multiplies two matrices together:
x <- matrix(1:4, 2, 2)
y <- matrix(rep(10, 4), 2, 2)
x %*% y
This code is vectorized, so the multiplication operation is performed on each element of the matrices x and y, and the result is a new matrix.
Another example of a vectorized matrix operation is element-wise multiplication. The following code multiplies each element of the matrix x by each element of the matrix y:
x * y
This code returns a new matrix, where each element is the product of the corresponding elements of x and y.
Vectorized matrix operations can be used with a wide variety of matrix operations, including addition, subtraction, multiplication, division, and element-wise comparisons. They are a powerful tool that can help you write efficient and concise code for working with matrices.
Examples of vectorized matrix operations
- `x + y` adds each element of x to each element of y.
- `x - y` subtracts each element of x from each element of y.
- `x / y` divides each element of x by each element of y.
- `x == y` compares each element of x to each element of y and returns a logical matrix indicating which elements are equal.
- `x != y` compares each element of x to each element of y and returns a logical matrix indicating which elements are not equal.
