# plotCorrmatrix: Calculates and plots correlation matrices for a set of... In growthPheno: Functional Analysis of Phenotypic Growth Data to Smooth and Extract Traits

 plotCorrmatrix R Documentation

## Calculates and plots correlation matrices for a set of responses

### Description

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. A matrix plot of all pairwise combinations of the variables can be produced. The matrix plot contains a scatter diagram for each pair, as well as the value of the correlation coefficient. The argument `pairs.sets` can be used to restrict the pairs in the matrix plot to those combinations within each set.

### Usage

``````plotCorrmatrix(data, responses, which.plots = c("heatmap","matrixplot"),
title = NULL, labels = NULL, labelSize = 4, pairs.sets = NULL,
show.sig = FALSE, axis.text.size = 20, ggplotFuncs = NULL,
printPlot = TRUE, ...)
``````

### Arguments

 `data` A `data.frame` containing the columns of variables to be correlated. `responses` A `character` giving the names of the columns in `data` containing the variables to be correlated. `which.plots` A `character` specifying the plots of the correlations to be produced. The possibilities are one or both of `heatmap` and `matrixplot`. `title` Title for the plots. `labels` A `character` specifying the labels to be used in the plots. If `labels` is `NULL`, `responses` is used for the `labels`. `labelSize` A `numeric` giving the size of the `labels` in the `matrixplot`. `pairs.sets` A `list` each of whose components is a `numeric` giving the position of the variable names in `responses` that are to be included in the set. All pairs of variables in this pairs.set will be included in a `matrixplot`. `show.sig` A `logical` indicating whether or not to give asterisks on the `heatmap` indicating the correlations are significantly different from zero. `axis.text.size` A `numeric` giving the size of the `labels` on the axes of the `heatmap`. `ggplotFuncs` A `list`, each element of which contains the results of evaluating a `ggplot` function. It is created by calling the `list` function with a `ggplot` function call for each element. These functions are applied in creating the `ggplot` object. `printPlot` A `logical` indicating whether or not to print the plot. `...` allows passing of arguments to other functions; not used at present.

### Details

The correlations and their p-values are producced using `rcorr` from the `Hmisc` package. The `heatmap` is produced using `ggplot` and the matrixplot is produced using `GGally`.

### Value

The `heatmap` plot, if produced, as an object of class "`ggplot`", which can be plotted using `print`; otherwise `NULL` is returned.

### Author(s)

Chris Brien

`rcorr`, `GGally`, `ggplot`.

### Examples

``````
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)))

``````

growthPheno documentation built on May 29, 2024, 6:03 a.m.