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Merge pull request #109 from rwoldford/master
The version to go with the release 1.3.1 on github
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‎R/_pkgdown.yml

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- title: Loon display layers
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desc: Loon plots have multiple display layers
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contents:

‎R/demo/00Index

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loon an introductory example
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l_glyphs demonstrate glyph types
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l_glyph_sizes size mapping to various glyph types
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l_map layer a map from the map R package
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l_layers demonstrate layer types
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l_layout custom layout widgets
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l_linking linking examples
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l_linkPrimitiveGlyphs custom linking, link the primitive glyphs
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l_glyphs demonstrate glyph types
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l_glyph_sizes size mapping to various glyph types
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l_make_glyphs anything R can draw can be a glyph
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periodic_table explore the periodicity in the table using custom glyphs
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l_polygons_sp layer polygons with class sp as defined in the sp R package
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l_widgets custom layout
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l_power scatterplot and two scales that control the power transformation for each axis
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l_timeseries seasonal trend decomposition stl
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l_regression layer fit, confidence, and prediction intervals
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l_us_and_them gapminder data made famous by Hans Rosling; fertility, life expectancy, and income
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l_us_and_them_slider show the life expectancy vs. fertility data for the year selected on a slider
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l_us_and_them_choropleth life expectancy on a world map and linked with a scatterplot
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l_linkPrimitiveGlyphs custom linking, link the primitive glyphs
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l_add_regressions interactively add regression lines of a particular order to selected points
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l_knn interactively highlight k nearest points in some subspace
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l_ng_images_frey_LLE navigation graph for the frey image data using LLE for dimensionality reduction
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l_ng_images_frey_isomap navigation graph for the frey image data using isomap for dimensionality reduction
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l_ng_images_faces navigation graph with olivetti faces data
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l_ng_dimred compare results from various dimensionality reduction methods using navigation graphs
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l_layout custom layout widgets
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l_widgets custom layout

‎R/demo/l_make_glyphs.R

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# Produce any statistical glyph from any drawing function(on png)
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# Add these glyphs as the point symbols for the loon scatterplot.
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#
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# Here we look at Italian growing areas corresponding to the
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# olive oil data.
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# The location of each area is a point in the loon plot
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# We introduce a new glyph for each point/growing area based on a
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# scatterplot of the fatty acid pair (linoleic, arachidic)
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# for all olive oils in that growing area.
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# Then a map of Italy is layered on the scatterplot.
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if(requireNamespace("maps", quietly = TRUE)) {
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local({
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p <- with(oliveLocations,
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l_plot(x = long, y = lat,
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xlabel = "longitude", ylabel = "latitude",
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showGuides = TRUE, color = "darkolivegreen4",
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itemLabel = Area, showItemLabels = TRUE,
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title = "Olive oil growing areas")
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)
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readline("Hit <Return> to construct the statistical images (9 in total)")
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#
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# Now we construct statistical glyphs for each area.
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# First split the olive data into a list by Area
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# in the order of the Area from the scatterplot
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#
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oliveByArea <- lapply(oliveLocations$Area,
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FUN = function(area) {
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subset(olive,
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Area == area)})
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# Want the scatterplot glyphs to all be on the
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# same range and to have the Area superimposed
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# on top.
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# We'll use base graphics to construct the glyphs
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# Will be producing a scatterplot of two fatty acids
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# for each growing area
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xlim <- extendrange(olive[,"linoleic"], f = .25)
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ylim <- extendrange(olive[,"arachidic"], f = .25)
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xlim10 <- extendrange(olive[,"linoleic"], f = .10)
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ylim10 <- extendrange(olive[,"arachidic"], f = .10)
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pointcol <- adjustcolor("steelblue", 0.5)
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textcol <- "steelblue"
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#
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# Now construct the statistical images
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scatterplot_images <-
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l_make_glyphs(
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oliveByArea, # data
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width = 300, height = 300, # image size
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draw_fun = function(area) { # draw function for each Area
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# Following line included *only* for demo
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devAskNewPage(ask = FALSE)
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# get rid of borders for the png device
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par(mai = rep(0,4),
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mar = rep(0,4),
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oma = rep(0,4))
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# Draw the plot we want
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# Just a scatterplot of two of the fatty
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# acids
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plot(area$linoleic, area$arachidic,
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xlim = xlim, ylim = ylim,
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ann = FALSE, xaxt = "n", yaxt = "n", bty = "n",
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pch=19, cex = 2, col = pointcol)
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# Add text of Area name
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text(mean(xlim), min(ylim10), # Bottom of plot
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paste(area$Area[1]),
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cex = 3.5, col = textcol)
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}
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)
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readline("Hit <Return> to get images for viewer")
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# Look at the images
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l_imageviewer(scatterplot_images)
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readline("Hit <Return> to assign statistical images as point glyphs")
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# Create the glyphs from the images for the l_plot
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glyphs <- l_glyph_add_image(p,
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scatterplot_images,
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# A meaningful label for this glyph
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label = "plot(linoleic, arachidic)"
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)
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# Change the plot glyphs to these image glyphs
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p["glyph"] <- glyphs
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readline("Hit <Return> to finish plot by layering a map of Italy")
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# Now layer a map of Italy from the maps package
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l_layer(p,
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maps::map('italy', fill = FALSE, plot = FALSE),
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label = "Italy",
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color = "cornsilk",
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index = "end")
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# Scale the plot to the all layers
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l_scaleto_world(p)
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}) # End local
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}

‎R/demo/periodic_table.R

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# This uses l_make_glyphs to build standard periodic table labels
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# for glyphs of the elements data from loon.data package.
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#
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if(requireNamespace("loon.data", quietly = TRUE)) {
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local({
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data("elements", package = "loon.data")
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# A draw function for each element
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draw_element_box <- function(symbol,
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name, number,
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mass_number,
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mass, col) {
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if (missing(col)) col <- "white"
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oldPar <- par(bg = col, mar = rep(1, 4))
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#
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# Following line included *only* for demo
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devAskNewPage(ask = FALSE)
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plot(NA, xlim = c(0,1), ylim = c(0, 1), axes=FALSE, ann = FALSE)
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text(0.5, 0.6, labels = symbol, cex = 18)
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text(0.15, 1, labels = number, cex = 6, adj= c(0.5,1))
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text(0.5, 0.25, labels = name, cex = 6)
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text(0.5, 0.11, labels = mass_number, cex = 3)
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text(0.5, 0.01, labels = mass, cex = 3)
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box()
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par(oldPar)
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}
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# Get the categories
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colIDs <- paste(elements$Category, elements$Subcategory)
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# Get a loon palette function
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colFn <- color_loon()
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# Get colors identified with categories
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tableCols <- colFn(colIDs)
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#
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# A function to an element box image for each element.
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make_element_boxes <- function(elements,
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cols,
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width = 500,
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height = 500) {
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if (missing(cols)) cols <- rep("white", nrow(elements))
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listOfElements <- lapply(1:nrow(elements),
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FUN = function(i) {
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list(vals = elements[i,],
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col = cols[i])
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})
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# glyphs created here
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l_make_glyphs(listOfElements,
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draw_fun = function(element){
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x <- element$vals
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col <- element$col
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draw_element_box(symbol = x$Symbol,
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name = x$Name,
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number = x$Number,
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mass_number = x$Mass_number,
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mass = x$Mass,
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col = col)
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},
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width = width,
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height = height)
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}
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# Construct the glyphs
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boxGlyphs <- make_element_boxes(elements, cols = tableCols)
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readline("Hit <Return> to scroll through the elements")
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# Look at the images
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l_imageviewer(boxGlyphs)
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readline("Hit <Return> to lay them out in the periodic table.")
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# Get a couple of plots
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periodicTable <- l_plot(x = elements$x, y = elements$y,
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xlabel = "", ylabel = "",
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title = "Periodic Table of the Elements",
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linkingGroup = "elements",
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color = tableCols)
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# Add the images as possible glyphs
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bg <- l_glyph_add_image(periodicTable,
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images = boxGlyphs,
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label = "Symbol box")
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# Set this to be the glyph
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periodicTable['glyph'] <- bg
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message("Enlarge the window so that all elements can be seen. \n")
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readline(
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"Hit <Return> to construct a plot of each element's Density versus its Mass.")
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#
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# Get a second plot that shows the periodicity
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#
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# First some itemlabels
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elementLabels <- with(elements,
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paste(" ", Number, Symbol, "\n",
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" ", Name, "\n",
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" ", Mass
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)
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)
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periodicPlot <- l_plot(x = elements$Mass, y = elements$Density,
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xlabel = "Mass", ylabel = "Density",
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itemLabel = elementLabels,
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showItemLabels = TRUE,
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linkingGroup = "elements",
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color = tableCols)
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bg2 <- l_glyph_add_image(periodicPlot,
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images = boxGlyphs,
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label = "Symbol box")
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readline(
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"Hit <Return> to show the noble gases by their 'Symbol Box' glyph")
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nobleGases <- elements$Subcategory == "Noble gas"
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periodicPlot["glyph"][nobleGases] <- "glyph0"
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readline(
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"Hit <Return> to show the reactive nonmetals by their 'Symbol Box' glyph")
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reactiveNonMetals <- elements$Subcategory == "Reactive nonmetal"
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periodicPlot["glyph"][reactiveNonMetals] <- "glyph0"
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readline("Hit <Return> to focus on the noble gases and the reactive nonmetals")
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periodicPlot["active"] <- nobleGases | reactiveNonMetals
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l_scaleto_active(periodicPlot)
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periodicPlot["active"] <- TRUE
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readline("Hit <Return> to return plot to closed circles and scale.")
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periodicPlot["glyph"] <- "ccircle"
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l_scaleto_world(periodicPlot)
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message(paste0("Suggestions: \n",
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" - Brush/Select in either plot to explore the periodicity of the elements. \n",
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" - On the table brushing whole rows or whole columns is interesting. \n",
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" - Try selecting by colour and setting the glyph to the symbol boxes. \n",
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" - So activating only selected colours and panning and zooming in the Mass/Density plot. \n",
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" - Activate only selected colours and then try panning and zooming in the Mass/Density plot. \n"))
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message()
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}) # End local
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}

‎docs/articles/introduction.html

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‎docs/articles/teaching-example-smoothing.html

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‎docs/pkgdown.yml

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introduction: introduction.html
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savingLoonPlots: savingLoonPlots.html
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teaching-example-smoothing: teaching-example-smoothing.html
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last_built: 2020-06-13T14:30Z
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last_built: 2020-06-15T18:27Z
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