inzpar: iNZight Plotting Parameters

Description Usage Arguments Details Value Author(s)

View source: R/inzpar.R


Plotting parameters for iNZight Plots


inzpar(..., .viridis = requireNamespace("viridis", quietly = TRUE))



If arguments are supplied, then these values are set. If left empty, then


checks if the viridis package is installed; or can be turend off the default list is returned.


A whole suite of parameters that can be used to fine-tune plots obtained from the iNZightPlot function. The parameters include both plot type, style, and appearance. They are described below.


the plotting symbol to be used; default is '1' (empty circle)


the colour of points. this can either be a single value, or a vector of colours if colby is specified


the colour for missing values; default is a light grey


the overal scaling for the entire plot; values less than 1 will make the text and points smaller, while values larger than 1 will magnify everything


the scaling value for points


the scaling value for points in a dotplot. Note, this is not multiplicative with ''


the scaling value for the plot labels


the scaling value for the axis labels


the scaling value for the main plot title


the scaling value for text on the plot


transparency setting for points; default is 1, 0 is fully transparent


the background color for the plot


the fill colour for points; default is "transparent"


the line width of lines (for joining points)


the line type of lines (for joining points)


the line width used for points; default is 2


the colour of lines used to join points


vector of up to two colours for the background of subplot labels. If only one specified, it is used for both.


the default colour for locating points


the axes to add jitter to. Takes values "x", "y", or "xy" (default is en empty string, "")


the axes to add rugs to. Takes same values as jitter


a vector containing the trend lines to add to the plot. Possible values are c("linear", "quadratic", "cubic")


the smoothing (lowess) for the points. Takes a value between 0 and 1 (the default, 0, draws no smoother)


the line type used for smoothers if = TRUE


if quantile smoothers are desired, they can be specified here as either the quantiles to smooth over (e.g., c(0.25, 0.5, 0.75)), or "default", which uses the sample size to decide on an approprite set of quantile smoothers


logical, if TRUE, then a 1-1 line of equality is drawn


logical, if TRUE, then points are joined by lines


logical, if join = TRUE and colby is specified, points are joined by the specified variable


a named list of colors to be used for drawing the lines. The default is list(linear = "blue", quadratic = "red", cubic = "green4")


a named list of line types for various types of trend lines. The default is list(linear = 1, quadratic = 2, cubic = 3)


logical, if TRUE, then trend lines are drawn separately for each group specified by colby


logical, if TRUE, the trend lines by group are given the same slope; otherwise they are fit independently


the colour of the smoother


the colour of the line of equality


the line type of the line of equality


logical, if TRUE, a boxplot is drawn with dotplots and histgrams

'box.lwd', 'box.col', 'box.fill'

the line width, colour, and fill colour for the box plot drawn

'bar.lwd', 'bar.col', 'bar.fill'

the line width, colour, and fill colour of bars in a bar plot


logical, if TRUE bar graphs will display counts instead of percentages (the default)


may no longer be necessary ...

'inf.lwd.comp', 'inf.lwd.conf'

the line width of comparison and confidence intervals, respectively

'inf.col.comp', 'inf.col.conf'

the colour of comparison and confidence intervals, respectively. These take a length 2 vector, where the first element is used for normal inference, while the second is used for bootstrap intervals


the type of inference added to the plot. Possible values are c("comp", "conf")


the parameter which we obtain intervals for. For a dotplot or histogram, this can be either "mean" or "median"; for bar plots it can be "proportion"


logical, if TRUE, then nonparametric bootstrap simulation is used to obtain the intervals


the min count for barplots inference; counts less than this are ignored


the number of bootstrap simulations to perform


sample sizes over this value will use a large-sample plot variant (i.e., scatter plots will become hex plots, dot plots become histograms)


logical, if TRUE, then the large-sample plot variance is used


the number, N, of bins to use for the scatter-grid plot, producing an N x N matrix


the number of bins to use for hexagonal binning


the style of the hexagons, one of "size" or "alpha"


if quant.smooth = "default", these sample size values are used to determine which quantiles are drawn


used to override the default plot type. Possible values, depending on data type, include c("scatter"|"grid"|"hex"|"dot"|"hist")


logical, if TRUE, then the type of plot is kept consistent between different subsets


a vector of two values used to decide whether to use all small-sample or all large-sample plots


a vector defining the x axis limits (default NULL will use the data)


a vector defining the y axis limits (default NULL will use the data)


a list of variable transformations (e.g., list(x = 'log'))


a list containing any additional features for new plots (e.g., maptype)


an object of class inzpar.list



iNZightVIT/iNZightPlots documentation built on May 17, 2019, 10:10 p.m.