grid_jitter2 | R Documentation |
Data jittering reduces overplotting by adding small variances to values. grid_jitter2 removes it entirely by first rounding points to a custom grid and then reallocating individual duplicate points to the nearest vacant cells within a maximum tolerance threshold. If no vacant cells are available the function will abort. This function applies Hungarian algorithm with small area constraints. (By contrast grid_jitter applies Hungarian to match the entire points set to the whole grid.) This function is much faster than grid_jitter with bigger point sets and grids.
grid_jitter2(x, y = NULL, nx = 50, ny = NULL, tol = 5, plotresults = TRUE, file = NULL, w = 20, h = 20)
x |
Numeric vector or 2 column matrix or data.frame of data points to plot |
y |
Numeric vector, y coordinates matching x (if a vector) |
nx |
Numeric, grid x/y dimensions |
ny |
Numeric |
tol |
Numeric, the maximum distance overplotted points are allowed to move to the nearest vacant grid cell |
plotresults |
Logical, output plots to illustrate point displacements and cell-reallocations |
file |
String, if not NULL the result of plotresults will save to filename instead of rendering in R |
w |
Numeric, width/height (inches) of plotresults if output to file (PDF) |
h |
Numeric |
A 2 column matrix of grid-jittered point coordinates
# 1. normal distribution d1 = data.frame(x = rnorm(500), y = rnorm(500)) d1g = grid_jitter2(d1, nx=75, ny=75, tol=5) # 2. faithful dataset d2 = faithful d2g = grid_jitter2(d2, nx=50, ny=50, tol=3) # 3. mpg example d3 = ggplot2::mpg[,c(3,8)] d3g = grid_jitter2(d3, nx=100, ny=100, tol=3) # 4. diamonds - carat vs price d4 = ggplot2::diamonds[sample(1:53940, 1000),c('carat','price')] d4g = grid_jitter2(d4, nx=500, ny=500, tol=2) # fails d4g = grid_jitter2(d4, nx=500, ny=500, tol=5, plotresults=FALSE) # 5. US States d5 = data.frame(x=state.center$x, y=state.center$y, id=state.abb) d5j = grid_jitter2(d5[,1:2], nx=10, ny=8, tol=3, plotresults=TRUE) cols = sample(colorRampPalette(c('darkblue','blue','lightblue'))(50)) par(mai=rep(.6,4), mfrow=c(1,2)) plot(d5[,1:2], pch=15, cex=2.5, col=cols, asp=2.5, xlab=NA, ylab=NA) text(d5[,1:2], labels=state.abb, col='white', cex=.7) plot(d5j, pch=15, cex=2.5, col=cols, asp=2.5, xlab=NA, ylab=NA) text(d5j, labels=d5$id, col='white', cex=.7) # 6. to illuste cell reallocation d5 = data.frame(x = c(1,rep(50, 398), 100), y = c(1,rep(50, 398), 100)) d5g = grid_jitter2(d5, nx=30, ny=30, tol=15)
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