About
Scaling is a transformation that is generally applied by the transformation matrix
See also: Linear Algebra - Scalar (Multiplication|Product) - Scaling
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Matrix multiplication
The functional form <MATH> x' = a.x \\ y' = d.y </MATH> becomes the following matrix. <MATH> \begin{bmatrix} x' \\ y' \\ \end{bmatrix} = \begin{bmatrix} a & 0 \\ 0 & d \\ \end{bmatrix} \begin{bmatrix} x \\ y \\ \end{bmatrix} </MATH>
Using the standard transformation matrix notation, it would become: <MATH> \begin{bmatrix} x' \\ y' \\ 1 \end{bmatrix} = \begin{bmatrix} a & 0 & 0 \\ 0 & d & 0 \\ 0 & 0 & 0 \end{bmatrix} \begin{bmatrix} x \\ y \\ 1 \end{bmatrix} </MATH>
Example
One point
- Scale Matrix Definition: To scale the point by two in the vertical direction, the corresponding matrix will be in two dimensions:
<MATH> \begin{bmatrix} 1 & 0 \\ 0 & 2 \end{bmatrix} </MATH>
- The scaling transformation of the point x,y applied with the matrix-vector multiplication would become:
<MATH> \begin{bmatrix}x' \\ y'\end{bmatrix} = \begin{bmatrix}1x \\ 2y\end{bmatrix} = \begin{bmatrix} 1 & 0 \\ 0 & 2 \end{bmatrix} \begin{bmatrix}x \\ y\end{bmatrix} </MATH>
Many points
To apply such a transformation to many points at the same time, the matrix-vector definition of matrix-matrix multiplication is used. The points are putted together to form a position matrix that is left-multiplied by the matrix representing the transformation: <MATH> \begin{bmatrix} 1 & 0 \\ 0 & 2 \end{bmatrix} \begin{bmatrix} \begin{array}{r|r|r} x_1 & x_2 & x_3 \\ y_1 & y_2 & y_3 \end{array} \end{bmatrix} \begin{bmatrix} \begin{array}{r|r|r} 1x_1 & 1x_2 & 1x_3 \\ 2y_1 & 2y_2 & 2y_3 \end{array} \end{bmatrix} </MATH>