This is part of the course “Linear Algebra with JavaScript”.
A matrix is a rectangular array of real numbers with m rows and n columns. For example, a 3×2 matrix looks like this:
Let’s go right to the code. The constructor of the Matrix class will receive rows as a parameter. We will access a particular element in the matrix by first taking row by row index and then element by column index.
Matrix-vector product
The matrix-vector product Ax⃗ produces a linear combination of the columns of the matrix A with coefficients x⃗. For example, the product of a 3×2 matrix A and a 2D vector x⃗ results in a 3D vector, which we’ll denote y⃗: y⃗=Ax⃗
Consider some set of vectors {e⃗₁, e⃗₂}, and a third vector y⃗ that is a linear combination of the vectors e⃗₁ and e⃗₂: y⃗=αe⃗₁ + βe⃗₂. The numbers α, β ∈ R are the coefficients in this linear combination.
The matrix-vector product is defined expressly for the purpose of studying linear combinations. We can describe the above linear combination as the following matrix vector product: y⃗=Ex⃗. The matrix E has e⃗₁ and e⃗₂ as columns. The dimensions of the matrix will be n×2, where n is the dimension of the vectors e⃗₁, e⃗₂ and y⃗.
In the picture below we can see vector v⃗ represented as a linear combination of vectors î and ĵ.
Linear Transformation
The matrix-vector product corresponds to the abstract notion of a linear transformation, which is one of the key notions in the study of linear algebra. Multiplication by a matrix can be thought of as computing a linear transformation that takes n-dimensional vector as an input and produces m-dimensional vector as an output. We can say matrix is a certain transformation of vector in space.
It will become more clear on examples, but first, let’s add a method to Matrix class that will return columns of the matrix.
In the code sample below you can examples of different vector-matrix products. The dimension of the resulting vector will always be equal to the number of matrix rows. If we multiply a 2D vector to a 3×2 matrix, we will receive a 3D vector, and when we multiply a 3D vector to a 2×3 matrix, we will receive a 2D vector. If a number of columns in the matrix not equal to vector dimension, we throw an error.
Examples
Now let’s try to move and change the two-dimensional object by using linear transformations. First, we will create a new class — Contour that will receive a list of vectors in the constructor and for now, will have only one method — transform, that will transform all coordinates of the contour and will return a new one.
Now, let’s go to the linear-algebra-demo project and try out different transformation matrices. Red square is an initial contour, and the blue one is a result of applying the transformation.
This way we can make a matrix that will rotate a given vector on a certain angle.
Transformation works the same way for objects in 3D space, below you can see the animated transformation from the red cube, to blue parallelepiped.
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