Matrices as Transformations
Matrices as Transformations
In linear algebra, matrices are not just grids of numbersโthey are actions. A 2ร2 matrix can represent a linear transformation of the 2D plane, mapping any point (x,y) to a new point (xโฒ,yโฒ).
How It Works
To apply a transformation, we multiply the transformation matrix by a column vector representing our point:
[xโฒyโฒโ]=[acโbdโ][xyโ]=[ax+bycx+dyโ]
Common Transformations
Scaling
A scaling matrix stretches or compresses the plane along the x and y axes.
[kxโ0โ0kyโโ]
If kxโ=2, the x-coordinates are doubled. If kyโ=0.5, the y-coordinates are halved.
Reflections
Matrices can reflect points across specific lines.
- Over the x-axis: [10โ0โ1โ]
- Over the y-axis: [โ10โ01โ]
Rotations
To rotate a point counterclockwise around the origin by an angle ฮธ, use the rotation matrix:
[cosฮธsinฮธโโsinฮธcosฮธโ]
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 90โ counterclockwise.
Using the rotation matrix formula with ฮธ=90โ:
cos(90โ)=0,sin(90โ)=1
Substituting these into the rotation matrix gives:
[01โโ10โ]
Example 2: Apply the matrix [20โ03โ] to the triangle with vertices (1,1), (2,0), (0,2).
We multiply the matrix by each vertex (written as column vectors):
[20โ03โ][11โ]=[23โ]
[20โ03โ][20โ]=[40โ]
[20โ03โ][02โ]=[06โ]
The new vertices of the transformed triangle are (2,3), (4,0), and (0,6).