| plotCorrmatrix | R Documentation |
Having calculated the correlations a heat map indicating the magnitude of the
correlations is produced using ggplot. In this heat map, the darker the red in
a cell then the closer the correlation is to -1, while the deeper the blue in the cell,
then the closer the correlation is to 1. Matrix plots of all pairwise
combinations of the variables can be produced that includes the values of the
the correlation coefficients. If pairs.sets is set, a matrix
plot, along with the values of the correlation coefficients, is produced for
each of the pair.sets. That is, the argument pairs.sets can be used to
restrict the pairs in a matrix plot to those combinations within each set.
plotCorrmatrix(data, responses, which.plots = c("heatmap","matrixplots"),
title = NULL, labels = NULL, labelSize = 4, pairs.sets = NULL,
show.sig = TRUE, axis.text.size = 20, ggplotFuncs = NULL,
printPlot = TRUE, ...)
data |
A |
responses |
A |
which.plots |
A |
title |
Title for the plots. |
labels |
A |
labelSize |
A |
pairs.sets |
A |
show.sig |
A |
axis.text.size |
A |
ggplotFuncs |
A |
printPlot |
A |
... |
allows passing of arguments to other functions; not used at present. |
The correlations and their p-values are producced using rcorr
from the Hmisc package. The heatmap is produced using
ggplot and the matrixplots are produced using GGally.
A list object that has components heatmap and matrixplots. The component heatmap will contain the heatmap plot, if produced, as an object of class "ggplot", which can be plotted using print; otherwise NULL is returned.
Similarly, if not NULL, the component matrixplots will contain a list with one or more components, depending on the setting of pair.sets, each of which is a scatterplot matrix stored as an object of class "ggmatrix".
Chris Brien
rcorr, GGally, ggplot.
data(exampleData)
longi.dat <- prepImageData(data=raw.dat, smarthouse.lev=1)
longi.dat <- within(longi.dat,
{
Max.Height <- pmax(Max.Dist.Above.Horizon.Line.SV1,
Max.Dist.Above.Horizon.Line.SV2)
Density <- PSA/Max.Height
PSA.SV = (PSA.SV1 + PSA.SV2) / 2
Image.Biomass = PSA.SV * (PSA.TV^0.5)
Centre.Mass <- (Center.Of.Mass.Y.SV1 + Center.Of.Mass.Y.SV2) / 2
Compactness.SV = (Compactness.SV1 + Compactness.SV2) / 2
})
responses <- c("PSA","PSA.SV","PSA.TV", "Image.Biomass", "Max.Height","Centre.Mass",
"Density", "Compactness.TV", "Compactness.SV")
plotCorrmatrix(longi.dat, responses, pairs.sets=list(c(1:4),c(5:7)))
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.