Transforms coordinates in two dimensions in a linear manner for layers that
have an x
and y
parametrisation.
Arguments
- scale
A
numeric
of length two describing relative units with which to multiply thex
andy
coordinates respectively.- shear
A
numeric
of length two giving relative units by which to shear the output. The first number is for vertical shearing whereas the second is for horizontal shearing.- angle
A
numeric
noting an angle in degrees by which to rotate the input clockwise.- M
A
2
x2
realmatrix
: the transformation matrix for linear mapping. Overrides other arguments if provided.
Details
Linear transformation matrices are 2
x 2
real
matrices. The 'scale
', 'shear
' and 'rotation
'
arguments are convenience arguments to construct a transformation matrix.
These operations occur in the order: scaling - shearing - rotating. To
apply the transformations in another order, build a custom 'M
'
argument.
For some common transformations, you can find appropriate matrices for the
'M
' argument below.
Common transformations
Identity transformations
An
identity transformation, or returning the original coordinates, can be
performed by using the following transformation matrix: | 1 0 |
| 0 1 |
or M <- matrix(c(1, 0, 0, 1), 2)
Scaling
A scaling transformation multiplies the dimension of
an object by some amount. An example transformation matrix for scaling
everything by a factor 2: | 2 0 |
| 0 2 |
or
M <- matrix(c(2, 0, 0, 2), 2)
Squeezing
Similar
to scaling, squeezing multiplies the dimensions by some amount that is
unequal for the x
and y
coordinates. For example, squeezing
y
by half and expanding x
by two:
| | 2 | 0 | | | |||
| | 0 | 0.5 | | |
or M <- matrix(c(2, 0, 0, 0.5), 2)
Reflection
Mirroring the coordinates around one of the axes. Reflecting around the x-axis:
| | 1 | 0 | | | |||
| | 0 | -1 | | |
or M <- matrix(c(1, 0, 0, -1), 2)
Reflecting around the y-axis:
| | -1 | 0 | | | |||
| | 0 | 1 | | |
or M <- matrix(c(-1, 0, 0, 1), 2)
Projection
For projecting the coordinates on one of the axes,
while collapsing everything from the other axis. Projecting onto the
y
-axis:
| | 0 | 0 | | | |||
| | 0 | 1 | | |
or
M <- matrix(c(0, 0, 0, 1), 2)
Projecting onto the
x
-axis:
| | 1 | 0 | | | |||
| | 0 | 0 | | |
or
M <- matrix(c(1, 0, 0, 0), 2)
Shearing
Tilting the coordinates horizontally or vertically. Shearing vertically by 10\
| | 1 | 0 | | | |||
| | 0.1 | 1 | | |
or M <- matrix(c(1, 0.1, 0, 1), 2)
Shearing horizontally by 200\
| | 1 | 2 | | | |||
| | 0 | 1 | | |
or M <- matrix(c(1, 0, 2, 1), 2)
Rotation
A rotation performs a motion around a fixed point, typically the origin the coordinate system. To rotate the coordinates by 90 degrees counter-clockwise:
| | 0 | -1 | | | |||
| | 1 | 0 | | |
or M <- matrix(c(0, 1, -1, 0), 2)
For a rotation around any angle \(\theta\) :
| | \(cos\theta\) | \(-sin\theta\) | | | |||
| | \(sin\theta\) | \(cos\theta\) | | |
or M <- matrix(c(cos(theta), sin(theta), -sin(theta), cos(theta)), 2)
with 'theta
' defined in radians.
Examples
df <- data.frame(x = c(0, 1, 1, 0),
y = c(0, 0, 1, 1))
ggplot(df, aes(x, y)) +
geom_polygon(position = position_lineartrans(angle = 30))
# Custom transformation matrices
# Rotation
theta <- -30 * pi / 180
rot <- matrix(c(cos(theta), sin(theta), -sin(theta), cos(theta)), 2)
# Shear
shear <- matrix(c(1, 0, 1, 1), 2)
# Shear and then rotate
M <- rot %*% shear
ggplot(df, aes(x, y)) +
geom_polygon(position = position_lineartrans(M = M))
# Alternative shear and then rotate
ggplot(df, aes(x, y)) +
geom_polygon(position = position_lineartrans(shear = c(0, 1), angle = 30))
# Rotate and then shear
M <- shear %*% rot
ggplot(df, aes(x, y)) +
geom_polygon(position = position_lineartrans(M = M))