ggMarginal_Hist2D: Add marginal histograms to ggplot2 2d histogram plots
In wStockhausen/wtsPlots: Functions for creating various types of plots

ggMarginal_Hist2D

R Documentation

Add marginal histograms to ggplot2 2d histogram plots

Description

Create a ggplot2 2d histogram plot with marginal histogram plots.

Usage

ggMarginal_Hist2D(
  data,
  x,
  y,
  size = 5,
  after_stat_var = c("ncount", "count", "density", "ndensity"),
  hist_scale = c("arithmetic", "log10", "4th-root"),
  bins = 30,
  binwidths = NULL,
  xlab = NULL,
  ylab = NULL,
  xparams = list(limits = NULL, breaks = waiver(), labels = waiver(), name = waiver(),
    oob = scales::squish),
  yparams = list(limits = NULL, breaks = waiver(), labels = waiver(), name = waiver(),
    oob = scales::squish),
  fill_scale = ggplot2::scale_fill_viridis_c(option = "magma", name = ""),
  legend.position = c(0.99, 0.99),
  legend.justification = c(1, 1),
  ...,
  groupColour = FALSE,
  groupFill = FALSE,
  showIntermediates = FALSE,
  testing = FALSE
)

Arguments

`data`	The data.frame to use for creating the plots.
`x`	The name of the variable along the x axis.
`y`	The name of the variable along the y axis.
`size`	Integer describing the relative size of the marginal plots compared to the main plot. A size of 5 means that the main plot is 5x wider and 5x taller than the marginal plots.
`hist_scale`	- scale for histograms; options = ("arithmetic","log10","4th-root")
`bins`	- number of bins to use (scalar or 2-element vector); default=30
`binwidths`	- bin widths to use (scalar or 2-element vector); default=NULL
`xlab`	- x-axis title; default=NULL (i.e., use ggplot2 default)
`ylab`	- y-axis title; default=NULL (i.e., use ggplot2 default)
`xparams`	- list of [ggplot2::scale_x_continuous()] parameters; default = list(limits=NULL,breaks=waiver(),labels=waiver(),oob=scales::squish)
`yparams`	- list of [ggplot2::scale_y_continuous()] parameters; default = list(limits=NULL,breaks=waiver(),labels=waiver(),oob=scales::squish)
`fill_scale`	- 2d histogram fill scale; default=ggplot2::scale_fill_viridis_c(option="magma",name="")
`legend.position`	- legend position; default=c(0.99,0.99)
`legend.justification`	- legend justification; default=c(1,1)
`...`	Extra parameters to pass to the marginal plots. Any parameter that [ggplot2::geom_histogram()] accepts can be used. For example, `colour = "red"` can be used for any marginal plot type,
`groupColour`	If `TRUE`, the colour (or outline) of the marginal plots will be grouped according to the variable mapped to `colour` in the scatter plot. The variable mapped to `colour` in the scatter plot must be a character or factor variable. See examples below.
`groupFill`	If `TRUE`, the fill of the marginal plots will be grouped according to the variable mapped to `colour` in the scatter plot. The variable mapped to `colour` in the scatter plot must be a character or factor variable.
`testing`	- flag (T/F) to include
`stat_var`	- name of statistical variable to plot; options=("count","ncount","density","ndensity")

Value

If testing is false, a ggGTbl object that can be printed using S3 dispatch with print. If testing is TRUE, a list with elements

ggGTbl - an object of class ggGTbl.
built - a list with elements p2d, px,py corresponding to ggplot2 objects "built" with [ggplot2::ggplot_build()]

Note

The grid, gtable, and rlang packages are required for this function.

This function and related code are based on the [ggExtra::ggMarginal()] code developed by Dean Attali ("daattali@gmail.com").

Examples

library(ggplot2)
ggGTbl = ggMarginal_Hist2D(data=mtcars,x=wt,y=mpg,
                          hist_scale="arithmetic",
                          binwidths=c(0.5,7),
                          xparams=list(limits=c(0, 3),breaks=seq(0, 7,0.5),oob=scales::squish),
                          yparams=list(limits=c(0,40),breaks=seq(0,40,2),oob=scales::squish),
                          legend.position=c(0.01,0.99),
                          legend.justification=c(0,1),
                          showIntermediates=FALSE);
print(ggGTbl,newpage=TRUE);
gglst = ggMarginal_Hist2D(data=mtcars,x=wt,y=mpg,
                          hist_scale="arithmetic",
                          binwidths=c(0.5,7),
                          xparams=list(limits=c(0, 3),breaks=seq(0, 7,0.5),oob=scales::squish),
                          yparams=list(limits=c(0,40),breaks=seq(0,40,2),oob=scales::squish),
                          legend.position=c(0.01,0.99),
                          legend.justification=c(0,1),
                          showIntermediates=FALSE,
                          testing=TRUE);
print(gglst$ggGTbl,newpage=TRUE);

wStockhausen/wtsPlots documentation built on July 19, 2023, 8:15 p.m.