#' @include utilities.R ggplot2.customize.R
NULL
#' Easy scatterplot plot using ggplot2
#'
#' @description
#' Draw easily a scatter plot using ggplot2 package
#' @param data data.frame or a numeric vector. Columns are variables and rows
#' are observations.
#' @param xName The name of column containing x variable (i.e groups).
#' @param yName The name of column containing y variable.
#' @param groupName The name of column containing group variable. This variable
#' is used to color plot according to the group.
#' @param addRegLine If TRUE, regression line is added. Default value is FALSE.
#' @param regLineColor Color of regression line. Default value is blue.
#' @param regLineSize Weight of regression line. Default value is 0.5.
#' @param smoothingMethod Smoothing method (function) to use, eg. lm, glm, gam,
#' loess, rlm. For datasets with n < 1000 default is loess. For datasets with
#' 1000 or more observations defaults to gam. lm for linear smooths, glm for
#' generalised linear smooths, loess for local smooths, gam fits a generalized
#' additive model.
#' @param addConfidenceInterval Display confidence interval around smooth?
#' (FALSE by default).
#' @param confidenceLevel Level controling confidence region. Default is 95\%
#' @param confidenceIntervalFill Fill color of confidence intervall
#' @param setColorByGroupName If TRUE, points are colored according the groups.
#' Default value is TRUE.
#' @param setShapeByGroupName If TRUE, point shapes are different according to
#' the group. Default value is FALSE.
#' @param groupColors Color of groups. groupColors should have the same length
#' as groups.
#' @param brewerPalette This can be also used to indicate group colors. In this
#' case the parameter groupColors should be NULL. e.g: brewerPalette="Paired".
#' @param ... Other parameters passed on to ggplot2.customize custom function
#' or to geom_smooth and to geom_point functions from ggplot2 package.
#' @return a ggplot
#' @author Alboukadel Kassambara <alboukadel.kassambara@@gmail.com>
#' @seealso \code{\link{ggplot2.dotplot}, \link{ggplot2.violinplot},
#' \link{ggplot2.stripchart}, \link{ggplot2.boxplot}, \link{ggplot2.histogram},
#' \link{ggplot2.lineplot}, \link{ggplot2.barplot}}
#' @references http://www.sthda.com
#' @examples
#' df <- mtcars
#' ggplot2.scatterplot(data=df, xName='wt',yName='mpg', size=3,
#' mainTitle="Plot of miles per gallon \n according to the weight",
#' xtitle="Weight (lb/1000)", ytitle="Miles/(US) gallon")
#'
#' #Or use this
#' plot<-ggplot2.scatterplot(data=df, xName='wt',yName='mpg', size=3)
#' plot<-ggplot2.customize(plot, mainTitle="Plot of miles per gallon \n according to the weight",
#' xtitle="Weight (lb/1000)", ytitle="Miles/(US) gallon")
#' print(plot)
#'
#' @export ggplot2.scatterplot
ggplot2.scatterplot<-function(data, xName, yName, groupName=NULL,
addRegLine=FALSE,regLineColor="blue",regLineSize=0.5,
smoothingMethod=c("lm", "glm", "gam", "loess", "rlm"),
addConfidenceInterval=FALSE, confidenceLevel= 0.95,confidenceIntervalFill="#C7C7C7",
setColorByGroupName=TRUE, setShapeByGroupName=FALSE,
groupColors=NULL, brewerPalette=NULL,...)
{
spms <- .standard_params(...)
p<-ggplot(data=data, aes_string(x=xName, y=yName))
#Set color/shape by another variable
#++++++++++
if(!is.null(groupName)){
data[,groupName]=factor(data[,groupName])#transform groupName to factor
#set shape and color by groups
if(setColorByGroupName & setShapeByGroupName)
p<-ggplot(data=data, aes_string(x=xName, y=yName, color=groupName, shape=groupName))
#set only color by group
else if(setColorByGroupName==TRUE & setShapeByGroupName==FALSE)
p<-ggplot(data=data, aes_string(x=xName, y=yName, color=groupName))
#set only shape by group
else if(setColorByGroupName==FALSE & setShapeByGroupName==TRUE)
p<-ggplot(data=data, aes_string(x=xName, y=yName, shape=groupName))
}
#plot
if(is.null(groupName)) p<-p+geom_point(shape = spms$shape, color = spms$color, fill = spms$fill, size = spms$size)
else p <- p+geom_point()
#Add regression line
if(addRegLine){
if(is.null(groupName))
p<-p+geom_smooth(method=smoothingMethod[1], se=addConfidenceInterval, level=confidenceLevel,
color=regLineColor, size=regLineSize,fill=confidenceIntervalFill)
else p<-p+geom_smooth(method=smoothingMethod[1], se=addConfidenceInterval, level=confidenceLevel,
size=regLineSize,fill=confidenceIntervalFill)
}#end addRegressionLine
else if (addConfidenceInterval) p<-p+geom_smooth(se=addConfidenceInterval, level=confidenceLevel,
fill=confidenceIntervalFill)
#group colors
if(!is.null(groupColors)){
p<-p+scale_fill_manual(values=groupColors)
p<-p+scale_colour_manual(values=groupColors)
}
else if(!is.null(brewerPalette)){
p<-p+scale_fill_brewer(palette=brewerPalette)
p<-p+scale_colour_brewer(palette=brewerPalette, guide="none")
}
#ggplot2.customize : titles, colors, background, legend, ....
p<-ggplot2.customize(p,...)
p
}
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