plot_logscale: Add log transformations to graphs

In grafify: Easy Graphs for Data Visualisation and Linear Models for ANOVA

Add log transformations to graphs

Description

This function allows "log10" or "log2" transformation of X or Y axes. With "log10" transformation, log10 ticks are also added on the outside.

Usage

plot_logscale(
  Plot,
  LogYTrans = "log10",
  LogXTrans,
  LogYBreaks = waiver(),
  LogXBreaks = waiver(),
  LogYLimits = NULL,
  LogXLimits = NULL,
  LogYLabels = waiver(),
  LogXLabels = waiver(),
  fontsize = 22,
  ...
)

Arguments

Plot	a ggplot2 object.
LogYTrans	transform Y axis into "log10" (default) or "log2"
LogXTrans	transform X axis into "log10" or "log2"
LogYBreaks	argument for ggplot2[scale_y_continuous] for Y axis breaks on log scales, default is waiver(), or provide a vector of desired breaks.
LogXBreaks	argument for ggplot2[scale_x_continuous] for Y axis breaks on log scales, default is waiver(), or provide a vector of desired breaks.
LogYLimits	a vector of length two specifying the range (minimum and maximum) of the Y axis.
LogXLimits	a vector of length two specifying the range (minimum and maximum) of the X axis.
LogYLabels	argument for ggplot2[scale_y_continuous] for Y axis labels on log scales, default is waiver(), or provide a vector of desired labels.
LogXLabels	argument for ggplot2[scale_x_continuous] for Y axis labels on log scales, default is waiver(), or provide a vector of desired labels.
fontsize	this parameter sets the linewidth of the log10 tickmarks (8*fontsize/22 for long ticks and 4*fontsize/22 for middle ticks). It is set to 20 as default to be consistent with rest of grafify. It will need to be changed to 12, which is the default fontsize for graphs produced natively with ggplot2.
...	any other arguments to pass to scale_y_continuous[ggplot2] or scale_x_continuous[ggplot2]

Details

Arguments allow for axes limits, breaks and labels to passed on.

Value

This function returns a ggplot2 object of class "gg" and "ggplot".

Examples

#save a ggplot object
P <- ggplot(data_t_pratio, 
aes(Genotype,Cytokine))+
geom_jitter(shape = 21, 
size = 5, width = .2, 
aes(fill = Genotype), 
alpha = .7)
#transform Y axis
plot_logscale(Plot = P)

#or in one go 
plot_logscale(ggplot(data_t_pratio, 
aes(Genotype,Cytokine))+
geom_jitter(shape = 21, 
size = 5, width = .2, 
aes(fill = Genotype), 
alpha = .7))

grafify documentation built on May 29, 2024, 3:49 a.m.