This vignette accompanies the paper "Zigzag expanded navigation plots in R: The R package zenplots". Note that sections are numbered accordingly (or omitted). Furthermore, it is recommended to read the paper to follow this vignette.
# attaching required packages library(PairViz) library(MASS) library(zenplots)
As example data, we use the olive
data set:
data(olive, package = "zenplots")
Reproducing the plots of Figure 1:
zenplot(olive)
zenplot(olive, plot1d = "layout", plot2d = "layout")
Considering the str()
ucture of zenplot()
(here formatted for nicer output):
str(zenplot)
function (x, turns = NULL, first1d = TRUE, last1d = TRUE, n2dcols = c("letter", "square", "A4", "golden", "legal"), n2dplots = NULL, plot1d = c("label", "points", "jitter", "density", "boxplot", "hist", "rug", "arrow", "rect", "lines", "layout"), plot2d = c("points", "density", "axes", "label", "arrow", "rect", "layout"), zargs = c(x = TRUE, turns = TRUE, orientations = TRUE, vars = TRUE, num = TRUE, lim = TRUE, labs = TRUE, width1d = TRUE, width2d = TRUE, ispace = match.arg(pkg) != "graphics"), lim = c("individual", "groupwise", "global"), labs = list(group = "G", var = "V", sep = ", ", group2d = FALSE), pkg = c("graphics", "grid", "loon"), method = c("tidy", "double.zigzag", "single.zigzag"), width1d = if (is.null(plot1d)) 0.5 else 1, width2d = 10, ospace = if (pkg == "loon") 0 else 0.02, ispace = if (pkg == "graphics") 0 else 0.037, draw = TRUE, ...)
To investigate the layout options of zenplots a bit more, we need a larger data set. To this end we simply double the olive data here (obviously only for illustration purposes):
olive2 <- cbind(olive, olive) # just for this illustration
Reproducing the plots of Figure 2:
zenplot(olive2, n2dcols = 6, plot1d = "layout", plot2d = "layout", method = "single.zigzag")
zenplot(olive2, n2dcols = 6, plot1d = "layout", plot2d = "layout", method = "double.zigzag")
zenplot(olive2, n2dcols = 6, plot1d = "layout", plot2d = "layout", method = "tidy")
Note that there is also method = "rectangular"
(leaving the zigzagging zenplot paradigm but
being useful for laying out 2d plots which are not necessarily connected through a variable; note
that in this case, we omit the 1d plots as the default (labels) is rather confusing in this
example):
zenplot(olive2, n2dcols = 6, plot1d = "arrow", plot2d = "layout", method = "rectangular")
Reproducing the plots of Figure 3:
zenplot(olive, plot1d = "layout", plot2d = "layout", method = "double.zigzag", last1d = FALSE, ispace = 0.1)
zenplot(olive, plot1d = "layout", plot2d = "layout", n2dcol = 4, n2dplots = 8, width1d = 2, width2d = 4)
A very basic path (standing for the sequence of pairs (1,2), (2,3), (3,4), (4,5)):
(path <- 1:5)
A zenpath through all pairs of variables (Eulerian):
(path <- zenpath(5))
If dataMat
is a five-column matrix, the zenplot of all pairs would then be constructed as follows:
zenplot(x = dataMat[,path])
The str()
ucture of zenpath()
(again formatted for nicer output):
str(zenpath)
function (x, pairs = NULL, method = c("front.loaded", "back.loaded", "balanced", "eulerian.cross", "greedy.weighted", "strictly.weighted"), decreasing = TRUE)
Here are some methods for five variables:
zenpath(5, method = "front.loaded") zenpath(5, method = "back.loaded") zenpath(5, method = "balanced")
The following method considers two groups: One of size three, the other of size five. The sequence of pairs is constructed such that the first variable comes from the first group, the second from the second.
zenpath(c(3,5), method = "eulerian.cross")
Reproducing Figure 4:
oliveAcids <- olive[, !names(olive) %in% c("Area", "Region")] # acids only zpath <- zenpath(ncol(oliveAcids)) # all pairs zenplot(oliveAcids[, zpath], plot1d = "hist", plot2d = "density")
Figure 5 can be reproduced as follows (note that we do not show the plot here due to a CRAN issue when running this vignette):
path <- c(1,2,3,1,4,2,5,1,6,2,7,1,8,2,3,4,5,3,6,4,7,3,8,4,5,6,7,5,8,6,7,8) turns <- c("l", "d","d","r","r","d","d","r","r","u","u","r","r","u","u","r","r", "u","u","l","l","u","u","l","l","u","u","l","l","d","d","l","l", "u","u","l","l","d","d","l","l","d","d","l","l","d","d","r","r", "d","d","r","r","d","d","r","r","d","d","r","r","d","d") library(ggplot2) # for ggplot2-based 2d plots stopifnot(packageVersion("ggplot2") >= "2.2.1") # need 2.2.1 or higher ggplot2d <- function(zargs) { r <- extract_2d(zargs) num2d <- zargs$num/2 df <- data.frame(x = unlist(r$x), y = unlist(r$y)) p <- ggplot() + geom_point(data = df, aes(x = x, y = y), cex = 0.1) + theme(axis.line = element_blank(), axis.ticks = element_blank(), axis.text.x = element_blank(), axis.text.y = element_blank(), axis.title.x = element_blank(), axis.title.y = element_blank()) if(num2d == 1) p <- p + theme(panel.background = element_rect(fill = 'royalblue3')) if(num2d == (length(zargs$turns)-1)/2) p <- p + theme(panel.background = element_rect(fill = 'maroon3')) ggplot_gtable(ggplot_build(p)) } zenplot(as.matrix(oliveAcids)[,path], turns = turns, pkg = "grid", plot2d = function(zargs) ggplot2d(zargs))
Split the olive data set into three groups (according to their variable Area
):
oliveAcids.by.area <- split(oliveAcids, f = olive$Area) # Replace the "." by " " in third group's name names(oliveAcids.by.area)[3] <- gsub("\\.", " ", names(oliveAcids.by.area)[3]) names(oliveAcids.by.area)
Reproducing the plots of Figure 6 (note that lim = "groupwise"
does not
make much sense here as a plot):
zenplot(oliveAcids.by.area, labs = list(group = NULL))
zenplot(oliveAcids.by.area, lim = "groupwise", labs = list(sep = " - "), plot1d = function(zargs) label_1d_graphics(zargs, cex = 0.8), plot2d = function(zargs) points_2d_graphics(zargs, group... = list(sep = "\n - \n")))
Find the "convexity" scagnostic for each pair of olive acids.
library(scagnostics) Y <- scagnostics(oliveAcids) # compute scagnostics (scatter-plot diagonstics) X <- Y["Convex",] # pick out component 'convex' d <- ncol(oliveAcids) M <- matrix(NA, nrow = d, ncol = d) # matrix with all 'convex' scagnostics M[upper.tri(M)] <- X # (i,j)th entry = scagnostic of column pair (i,j) of oliveAcids M[lower.tri(M)] <- t(M)[lower.tri(M)] # symmetrize round(M, 5)
Show the six pairs with largest "convexity" scagnostic:
zpath <- zenpath(M, method = "strictly.weighted") # list of ordered pairs head(M[do.call(rbind, zpath)]) # show the largest six 'convexity' measures
Extract the corresponding pairs:
(ezpath <- extract_pairs(zpath, n = c(6, 0))) # extract the first six pairs
Reproducing Figure 7 (visualizing the pairs):
library(graph) library(Rgraphviz) plot(graph_pairs(ezpath)) # depict the six most convex pairs (edge = pair)
Connect them:
(cezpath <- connect_pairs(ezpath)) # keep the same order but connect the pairs
Build the corresponding list of matrices:
oliveAcids.grouped <- groupData(oliveAcids, indices = cezpath) # group data for (zen)plotting
Reproducing Figure 8 (zenplot of the six pairs of acids with largest "convexity" scagnostic):
zenplot(oliveAcids.grouped)
Here is the structure of a return object of zenplot()
:
res <- zenplot(olive, plot1d = "layout", plot2d = "layout", draw = FALSE) str(res)
Let's have a look at the components. The occupancy matrix encodes the occupied cells in the rectangular layout:
res[["path"]][["occupancy"]]
The two-column matrix positions
contains in the ith row the row and column
index (in the occupancy matrix) of the ith plot:
head(res[["path"]][["positions"]])
Example structure of 2d plot based on graphics
:
points_2d_graphics
For setting up the plot region of plots based on graphics
:
plot_region
Determining the indices of the two variables to be plotted in the current 1d or 2d plot (the same for 1d plots):
plot_indices
Basic check that the return value of zenplot()
is actually the return value of the
underlying unfold()
(note that, the output of unfold
and res
is not identical since res
has specific class attributes):
n2dcols <- ncol(olive) - 1 # number of faces of the hypercube uf <- unfold(nfaces = n2dcols) identical(res, uf) #return FALSE for(name in names(uf)) { stopifnot(identical(res[[name]], uf[[name]])) }
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.