ggprroc: Plotting PRROC objects using ggplot2
In PRROC: Precision-Recall and ROC Curves for Weighted and Unweighted Data

View source: R/PRROC.R

ggprroc

R Documentation

Plotting PRROC objects using ggplot2

Description

Plots the PR or ROC curves of a PRROC object using ggplot2. To obtain such curves, pr.curve or roc.curve must be called with argument curve=TRUE.

Usage

ggprroc(x, auc.main=TRUE, auc.type=c("integral","davis.goadrich"),
    xlab=NULL,ylab=NULL,
    main=NULL,
    max.plot = FALSE, min.plot = FALSE, rand.plot = FALSE,
    fill.area = (max.plot & min.plot))

Arguments

`x`	a PRROC object obtained from `pr.curve` or `roc.curve`
`auc.main`	`TRUE` to show the area under curve in the title
`auc.type`	the area under the curve shown in the title (see also `pr.curve`). Ignored if `auc.main=FALSE` or `x$type=="ROC"`.
`xlab`	the label of the x-axis. If `NULL`, label is chosen according the kind of the curve.
`ylab`	the label of the y-axis. If `NULL`, label is chosen according the kind of the curve.
`main`	the title of the plot. If `NULL`, title is chosen according the kind of the curve.
`max.plot`	if `TRUE` and `x` has been computed including the maximum curve, plot this maximum curve
`min.plot`	if `TRUE` and `x` has been computed including the minimum curve, plot this maximum curve
`rand.plot`	if `TRUE` and `x` has been computed including the curve of a random classifier, plot this curve
`fill.area`	fill the area between maximum and minimum curve (given both have been computed for `x`) (ignored if `add=TRUE`)

Details

This function plots PRROC objects as a curve using ggplot2, specifically geom_line. If minimum, maximum or random curves have been computed, these can be added to the plot.

The function returns a ggplot2 object that may be further modified using themes, scales on the colours, etc.

Author(s)

Jan Grau and Jens Keilwagen

Examples

# create artificial scores as random numbers
x <- rnorm( 1000 );
y <- rnorm( 1000, -1 );

# compute PR curve
pr <- pr.curve( x, y, curve = TRUE );

# standard plot of PR curve
ggprroc( pr );

# compute ROC curve
roc <- roc.curve( x, y, curve = TRUE );

# standard plot of ROC curve
ggprroc( roc );


# include maximum, minimum and random curves
pr <- pr.curve( x, y, curve = TRUE, max.compute = TRUE, 
    min.compute = TRUE, rand.compute = TRUE );
    
ggprroc( pr, max.plot = TRUE, min.plot = TRUE, rand.plot = TRUE )


# modify theme and colour scale

pl <- ggprroc( pr, max.plot = TRUE, min.plot = TRUE, rand.plot = TRUE )


if(require(ggplot2)){
  pl + scale_color_viridis_c(option="D",name="Some score") +
      xlab("Sensitivity")+
      theme_gray()
}

PRROC documentation built on April 12, 2025, 1:46 a.m.