Description Usage Arguments Details Value See Also Examples
Take a series of points lying in a horizontal or vertical line, and jitter them in the other dimension such that no points are overlapping.
1 2 3 4 5 6 7 8 9 10 11 12 | swarmx(x, y,
xsize = xinch(0.08, warn.log = FALSE),
ysize = yinch(0.08, warn.log = FALSE),
log = NULL, cex = par("cex"), side = 0L,
priority = c("ascending", "descending", "density", "random", "none"),
fast = TRUE, compact = FALSE)
swarmy(x, y,
xsize = xinch(0.08, warn.log = FALSE),
ysize = yinch(0.08, warn.log = FALSE),
log = NULL, cex = par("cex"), side = 0L,
priority = c("ascending", "descending", "density", "random", "none"),
fast = TRUE, compact = FALSE)
|
x, y |
Coordinate vectors in any format supported by |
xsize, ysize |
Width and height of the plotting character in user coordinates. |
log |
Character string indicating which axes are logarithmic, as in |
cex |
Relative plotting character size. |
side |
Direction to perform jittering: 0: both directions; 1: to the right or upwards; -1: to the left or downwards. |
priority |
Method used to perform point layout (see below). |
fast |
Use compiled version of algorithm? This option is ignored for all methods except |
compact |
Use compact layout? (see below) |
For swarmx
, the input coordinates must lie in a vertical line. For swarmy
, the input coordinates must lie in a horizontal line.
swarmx
adjusts coordinates to the left or right; swarmy
adjusts coordinates up or down.
priority
controls the order in which the points are placed; this has generally has a noticeable effect on the resulting appearance. "ascending"
gives the "traditional" beeswarm plot in which the points are placed in an ascending order. "descending"
is the opposite. "density"
prioritizes points with higher local density. "random"
places points in a random order. "none"
places points in the order provided.
When compact
is FALSE, points are placed in a predetermined order. When compact
is TRUE, a greedy strategy is used to determine which point will be placed next. This often leads to a more tightly-packed layout. The strategy is very simple: on each iteration, a point that can be placed as close as possible to the non-data axis is chosen and placed. If there are two or more equally good points, priority
is used to break ties.
Usually it makes sense to call this function after a plotting device has already been set up (e.g. when adding points to an existing plot), so that the default values for xsize
, ysize
, and log
will be appropriate.
A data frame with columns x
and y
with the new coordinates.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 |
## Plot points in one dimension
index <- rep(0, 100)
values <- rnorm(100)
plot(index, values, xlim = c(-0.5, 2.5))
points(swarmx(index + 1, values), col = 2)
points(swarmx(index + 2, values, cex = 1.5), col = 3, cex = 1.5)
## Try the horizontal direction, with a log scale
plot(values, index, log = "x", ylim = c(-1, 2))
points(swarmy(values, index + 1), col = 2)
## Newer examples using "side", "priority", and "compact"
plot(c(-0.5, 3.5), range(values), type = 'n')
points(swarmx(index + 0, values), col = 1)
points(swarmx(index + 0.9, values, side = -1), col = 2)
points(swarmx(index + 1.1, values, side = 1, priority = "descending"), col = 3)
points(swarmx(index + 2 , values, priority = 'density'), col = 4)
points(swarmx(index + 3 , values, priority = 'random'), col = 5)
points(swarmx(index + 3 , values, priority = 'random', compact = TRUE), col = 5)
|
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