Matrices as Transformations
Matrices as Transformations
In linear algebra, matrices are not just grids of numbersâthey are actions. A 2Ã2 matrix can represent a linear transformation of the 2D plane, mapping any point (x,y) to a new point (xâ²,yâ²).
How It Works
To apply a transformation, we multiply the transformation matrix by a column vector representing our point:
[xâ²yâ²â]=[acâbdâ][xyâ]=[ax+bycx+dyâ]
Common Transformations
Scaling
A scaling matrix stretches or compresses the plane along the x and y axes.
[kxâ0â0kyââ]
If kxâ=2, the x-coordinates are doubled. If kyâ=0.5, the y-coordinates are halved.
Reflections
Matrices can reflect points across specific lines.
- Over the x-axis: [10â0â1â]
- Over the y-axis: [â10â01â]
Rotations
To rotate a point counterclockwise around the origin by an angle Ξ, use the rotation matrix:
[cosΞsinΞââsinΞcosΞâ]
Composing Transformations
If you want to apply transformation A and then transformation B, you can simply multiply their matrices. The combined transformation matrix is BA. Note that matrix multiplication is not commutative, so the order matters: BA means transformation A happens first, followed by B.
Example Problems
Example 1: Find the matrix that rotates the plane by 90â counterclockwise.
Using the rotation matrix formula with Ξ=90â:
cos(90â)=0,sin(90â)=1
Substituting these into the rotation matrix gives:
[01ââ10â]
Example 2: Apply the matrix [20â03â] to the triangle with vertices (1,1), (2,0), (0,2).
We multiply the matrix by each vertex (written as column vectors):
[20â03â][11â]=[23â]
[20â03â][20â]=[40â]
[20â03â][02â]=[06â]
The new vertices of the transformed triangle are (2,3), (4,0), and (0,6).