A transformation matrix maps a point, written as a column vector, to its image. Reflections, stretches, and rotations use , but translation requires , because an ordinary matrix always leaves the origin fixed.
This is HL-only content from AHL 3.9, Matrix transformations, and may be tested on any GDC-active HL paper.
For , multiply the matrix by the vector:
| Transformation | Matrix or rule |
|---|---|
| Reflection in the -axis |
Matrix multiplication works because each row determines one new coordinate. For example, reflecting in the -axis keeps the -coordinate unchanged and multiplies the -coordinate by . A rotation matrix combines both original coordinates using sine and cosine.
For example, rotate anticlockwise through , then translate by :
The rotation sends to ; the translation then adds horizontally and vertically.
For successive linear transformations, order matters. If acts first and acts second, then . Matrix multiplication is , so generally .
To transform an entire shape, apply the same rule to every vertex and join the image points in the corresponding order. The determinant provides a useful check: a negative determinant reverses orientation, while its absolute value gives the area scale factor. For example, a horizontal stretch by followed by a vertical stretch by has determinant , so every area is multiplied by . A rotation has determinant , so it preserves area. A reflection has determinant , preserving area but reversing orientation. These checks can reveal sign errors.
A common misconception is that translation can be represented by an ordinary matrix. It cannot; the translation vector must be added separately after the matrix multiplication.
Exam technique: preserve the stated order, show the matrix-vector setup, and give the final transformed coordinates. If asked about area, remember that the area scale factor is .
