Merge pull request #32 from eclarke/fixGroupOnX

Fix #31 with groupOnX defaults

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: ggbeeswarm
 Type: Package
 Title: Categorical Scatter (Violin Point) Plots
-Version: 0.5.4
-Date: 2017-07-31
+Version: 0.6.0
+Date: 2017-08-03
 Authors@R: c(
     person(given="Erik", family="Clarke", role=c("aut", "cre"), email="[email protected]"),
     person(given="Scott", family="Sherrill-Mix", role=c("aut"), email="[email protected]"))

R/position-beeswarm.R

@@ -3,7 +3,7 @@
 #' @family position adjustments
 #' @param priority Method used to perform point layout (see \code{\link{swarmx}})
 #' @param cex Scaling for adjusting point spacing (see \code{\link{swarmx}})
-#' @param groupOnX should jitter be added to the x axis if TRUE or y axis if FALSE (the default NULL causes the function to guess which axis is the categorical one based on the number of unique entries in each)
+#' @param groupOnX if TRUE then jitter is added to the x axis and if FALSE jitter is added to the y axis. Prior to v0.6.0, the default NULL causes the function to guess which axis is the categorical one based on the number of unique entries in each. This could result in unexpected results when the x variable has few unique values and so in v0.6.0 the default was changed to always jitter on the x axis unless groupOnX=FALSE. Also consider \code{\link[ggplot2]{coord_flip}}.
 #' @param dodge.width Amount by which points from different aesthetic groups will be dodged. This requires that one of the aesthetics is a factor.
 #' @export
 #' @importFrom beeswarm swarmx
@@ -28,8 +28,10 @@ PositionBeeswarm <- ggplot2::ggproto("PositionBeeswarm",ggplot2:::Position, requ
     data <- remove_missing(data, vars = c("x","y"), name = "position_beeswarm")
     if (nrow(data)==0) return(data.frame())
 
-    # more unique entries in x than y suggests y (not x) is categorical
-    if(is.null(params$groupOnX)) params$groupOnX <- length(unique(data$y)) > length(unique(data$x))
+    if(is.null(params$groupOnX)){
+      params$groupOnX<-TRUE
+      if(length(unique(data$y)) <= length(unique(data$x))) warning('The default behavior of beeswarm has changed in version 0.6.0. In versions <0.6.0, this plot would have been dodged on the y-axis.  In versions >=0.6.0, grouponX=FALSE must be explicitly set to group on y-axis. Please set grouponX=TRUE/FALSE to avoid this warning and ensure proper axis choice.')
+    }
 
     # dodge
     if(!params$groupOnX){

R/position-quasirandom.R

@@ -7,7 +7,7 @@
 #' Smaller numbers (< 1) produce a tighter "fit". (default: 0.5)
 #' @param nbins the number of bins used when calculating density (has little effect with quasirandom/random distribution)
 #' @param method the method used for distributing points (quasirandom, pseudorandom, smiley or frowney)
-#' @param groupOnX should jitter be added to the x axis if TRUE or y axis if FALSE (the default NULL causes the function to guess which axis is the categorical one based on the number of unique entries in each)
+#' @param groupOnX if TRUE then jitter is added to the x axis and if FALSE jitter is added to the y axis. Prior to v0.6.0, the default NULL causes the function to guess which axis is the categorical one based on the number of unique entries in each. This could result in unexpected results when the x variable has few unique values and so in v0.6.0 the default was changed to always jitter on the x axis unless groupOnX=FALSE. Also consider \code{\link[ggplot2]{coord_flip}}.
 #' @param dodge.width Amount by which points from different aesthetic groups will be dodged. This requires that one of the aesthetics is a factor.
 #' @export
 #' @importFrom vipor offsetX
@@ -28,7 +28,10 @@ PositionQuasirandom <- ggplot2::ggproto("PositionQuasirandom",ggplot2:::Position
     data <- remove_missing(data, vars = c("x","y"), name = "position_quasirandom")
     if (nrow(data)==0) return(data.frame())
 
-    if(is.null(params$groupOnX)) params$groupOnX <- length(unique(data$y)) > length(unique(data$x))
+    if(is.null(params$groupOnX)){
+      params$groupOnX<-TRUE
+      if(length(unique(data$y)) <= length(unique(data$x))) warning('The default behavior of beeswarm has changed in version 0.6.0. In versions <0.6.0, this plot would have been dodged on the y-axis.  In versions >=0.6.0, grouponX=FALSE must be explicitly set to group on y-axis. Please set grouponX=TRUE/FALSE to avoid this warning and ensure proper axis choice.')
+    }
 
     # dodge
     if(!params$groupOnX){

README.Rmd

@@ -25,7 +25,7 @@ Beeswarm plots (aka column scatter plots or violin scatter plots) are a way of p
 
 Features: 
 
-- Can handle categorical variables on the y-axis (thanks @smsaladi)
+- Can handle categorical variables on the y-axis (thanks @smsaladi, @koncina)
 - Automatically dodges if a grouping variable is categorical and `dodge.width` is specified (thanks @josesho)
 
 See the examples below.
@@ -64,7 +64,7 @@ Using `geom_quasirandom`:
 ggplot(mpg,aes(class, hwy)) + geom_quasirandom()
 
 # With categorical y-axis
-ggplot(mpg,aes(hwy, class)) + geom_quasirandom()
+ggplot(mpg,aes(hwy, class)) + geom_quasirandom(groupOnX=FALSE)
 
 # Some groups may have only a few points. Use `varwidth=TRUE` to adjust width dynamically.
 ggplot(mpg,aes(class, hwy)) + geom_quasirandom(varwidth = TRUE)
@@ -92,7 +92,7 @@ Using `geom_beeswarm`:
 ggplot(iris,aes(Species, Sepal.Length)) + geom_beeswarm()
 ggplot(mpg,aes(class, hwy)) + geom_beeswarm()
 # With categorical y-axis
-ggplot(mpg,aes(hwy, class)) + geom_beeswarm(cex=1.2)
+ggplot(mpg,aes(hwy, class)) + geom_beeswarm(cex=1.2,groupOnX=FALSE)
 
 # ggplot doesn't pass any information about the actual device size of the points
 # to the underlying layout code, so it's important to manually adjust the `cex` 

README.md

@@ -13,7 +13,7 @@ Beeswarm plots (aka column scatter plots or violin scatter plots) are a way of p
 
 Features: 
 
-- Can handle categorical variables on the y-axis (thanks @smsaladi)
+- Can handle categorical variables on the y-axis (thanks @smsaladi, @koncina)
 - Automatically dodges if a grouping variable is categorical and `dodge.width` is specified (thanks @josesho)
 
 See the examples below.
@@ -66,7 +66,7 @@ ggplot(mpg,aes(class, hwy)) + geom_quasirandom()
 
 ```r
 # With categorical y-axis
-ggplot(mpg,aes(hwy, class)) + geom_quasirandom()
+ggplot(mpg,aes(hwy, class)) + geom_quasirandom(groupOnX=FALSE)
 ```
 
 <img src="README_files/figure-html/ggplot2-examples-2.png" title="plot of chunk ggplot2-examples" alt="plot of chunk ggplot2-examples" width="432" />
@@ -142,7 +142,7 @@ ggplot(mpg,aes(class, hwy)) + geom_beeswarm()
 
 ```r
 # With categorical y-axis
-ggplot(mpg,aes(hwy, class)) + geom_beeswarm(cex=1.2)
+ggplot(mpg,aes(hwy, class)) + geom_beeswarm(cex=1.2,groupOnX=FALSE)
 ```
 
 <img src="README_files/figure-html/ggplot2-beeswarm-3.png" title="plot of chunk ggplot2-beeswarm" alt="plot of chunk ggplot2-beeswarm" width="432" />

inst/doc/usageExamples.R

@@ -60,13 +60,13 @@ packageKeywords<-"visualization, display, one dimensional, grouped, groups, viol
 ###################################################
 ### code chunk number 8: yaxis (eval = FALSE)
 ###################################################
-##   ggplot(mapping=aes(dat,labs)) + geom_quasirandom(aes(color=labs))
+##   ggplot(mapping=aes(dat,labs)) + geom_quasirandom(aes(color=labs),groupOnX=FALSE)
 
 
 ###################################################
 ### code chunk number 9: showYaxis
 ###################################################
-  ggplot(mapping=aes(dat,labs)) + geom_quasirandom(aes(color=labs))
+  ggplot(mapping=aes(dat,labs)) + geom_quasirandom(aes(color=labs),groupOnX=FALSE)
 
 
 ###################################################
@@ -87,14 +87,14 @@ packageKeywords<-"visualization, display, one dimensional, grouped, groups, viol
 ### code chunk number 12: dodgey (eval = FALSE)
 ###################################################
 ##   labs2<-factor(rep(1:2,each=n))
-##   ggplot(mapping=aes(dat,labs,color=labs2)) + geom_quasirandom(dodge.width=.8)
+##   ggplot(mapping=aes(dat,labs,color=labs2)) + geom_quasirandom(dodge.width=.8,groupOnX=FALSE)
 
 
 ###################################################
 ### code chunk number 13: showDodgey
 ###################################################
   labs2<-factor(rep(1:2,each=n))
-  ggplot(mapping=aes(dat,labs,color=labs2)) + geom_quasirandom(dodge.width=.8)
+  ggplot(mapping=aes(dat,labs,color=labs2)) + geom_quasirandom(dodge.width=.8,groupOnX=FALSE)
 
 
 ###################################################
@@ -115,14 +115,14 @@ packageKeywords<-"visualization, display, one dimensional, grouped, groups, viol
 ### code chunk number 16: dodgeYBee (eval = FALSE)
 ###################################################
 ##   ggplot(mapping=aes(dat,labs,color=labs2)) +
-##     geom_beeswarm(dodge.width=.8,cex=2)
+##     geom_beeswarm(dodge.width=.8,cex=2,groupOnX=FALSE)
 
 
 ###################################################
 ### code chunk number 17: showDodgeYBee
 ###################################################
   ggplot(mapping=aes(dat,labs,color=labs2)) +
-    geom_beeswarm(dodge.width=.8,cex=2)
+    geom_beeswarm(dodge.width=.8,cex=2,groupOnX=FALSE)
 
 
 ###################################################

inst/doc/usageExamples.Rnw

@@ -69,9 +69,9 @@ Factors can be used to generate custom group orderings:
 @
 \end{center}
 
-The axes can also be switched with a categorical y-axis:
+The axes can also be switched with a categorical y-axis using the argument \code{groupOnX=FALSE}:
 <<yaxis, echo=TRUE, eval=FALSE>>=
-  ggplot(mapping=aes(dat,labs)) + geom_quasirandom(aes(color=labs))
+  ggplot(mapping=aes(dat,labs)) + geom_quasirandom(aes(color=labs),groupOnX=FALSE)
 @
 \begin{center}
 <<showYaxis, fig=TRUE, height=3.5, width=5, echo=FALSE>>=
@@ -92,7 +92,7 @@ And dodging can be used to compare within groups:
 Or on the y-axis:
 <<dodgey, echo=TRUE, eval=FALSE>>=
   labs2<-factor(rep(1:2,each=n))
-  ggplot(mapping=aes(dat,labs,color=labs2)) + geom_quasirandom(dodge.width=.8)
+  ggplot(mapping=aes(dat,labs,color=labs2)) + geom_quasirandom(dodge.width=.8,groupOnX=FALSE)
 @
 \begin{center}
 <<showDodgey, fig=TRUE, height=3.5, width=5, echo=FALSE>>=
@@ -112,7 +112,7 @@ And with \code{geom_beeswarm}:
 \end{center}
 <<dodgeYBee, echo=TRUE, eval=FALSE>>=
   ggplot(mapping=aes(dat,labs,color=labs2)) +
-    geom_beeswarm(dodge.width=.8,cex=2)
+    geom_beeswarm(dodge.width=.8,cex=2,groupOnX=FALSE)
 @
 \begin{center}
 <<showDodgeYBee, fig=TRUE, height=3.5, width=5, echo=FALSE>>=

vignettes/usageExamples.Rnw

@@ -69,9 +69,9 @@ Factors can be used to generate custom group orderings:
 @
 \end{center}
 
-The axes can also be switched with a categorical y-axis:
+The axes can also be switched with a categorical y-axis using the argument \code{groupOnX=FALSE}:
 <<yaxis, echo=TRUE, eval=FALSE>>=
-  ggplot(mapping=aes(dat,labs)) + geom_quasirandom(aes(color=labs))
+  ggplot(mapping=aes(dat,labs)) + geom_quasirandom(aes(color=labs),groupOnX=FALSE)
 @
 \begin{center}
 <<showYaxis, fig=TRUE, height=3.5, width=5, echo=FALSE>>=
@@ -92,7 +92,7 @@ And dodging can be used to compare within groups:
 Or on the y-axis:
 <<dodgey, echo=TRUE, eval=FALSE>>=
   labs2<-factor(rep(1:2,each=n))
-  ggplot(mapping=aes(dat,labs,color=labs2)) + geom_quasirandom(dodge.width=.8)
+  ggplot(mapping=aes(dat,labs,color=labs2)) + geom_quasirandom(dodge.width=.8,groupOnX=FALSE)
 @
 \begin{center}
 <<showDodgey, fig=TRUE, height=3.5, width=5, echo=FALSE>>=
@@ -112,7 +112,7 @@ And with \code{geom_beeswarm}:
 \end{center}
 <<dodgeYBee, echo=TRUE, eval=FALSE>>=
   ggplot(mapping=aes(dat,labs,color=labs2)) +
-    geom_beeswarm(dodge.width=.8,cex=2)
+    geom_beeswarm(dodge.width=.8,cex=2,groupOnX=FALSE)
 @
 \begin{center}
 <<showDodgeYBee, fig=TRUE, height=3.5, width=5, echo=FALSE>>=