knitr::opts_chunk$set(
    echo = TRUE, 
    tidy.opts = list(width.cutoff = 65),
    tidy = TRUE)

set.seed(12314159)


imageDirectory <- "/Users/rwoldford/Documents/Research/talks/MontrealRtutorial2018/Slides/img"
dataDirectory <- "/Users/rwoldford/Documents/Research/talks/MontrealRtutorial2018/Slides/data"
path_concat <- function(path1, path2, sep="/") {paste(path1, path2, sep = sep)}
## devtools::install_github("rwoldford/loon", subdir="R")
## install.packages(c("maps", "sp", "rworldmap", "RColorBrewer", "scales",
##                    "ElemStatLearn", "zenplots", "RnavGraphImageData",
##                    "gridExtra", "dimRed", "vegan", "MASS" ) )
## 
## source("https://bioconductor.org/biocLite.R")
## biocLite(c('graph', 'RDRToolbox', 'Rgraphviz'),
##          suppressUpdates=TRUE, suppressAutoUpdate=TRUE)
knitr::include_graphics(path_concat(imageDirectory, "Rgraphics0.png"))
knitr::include_graphics(path_concat(imageDirectory, "Rgraphics1.png"))
knitr::include_graphics(path_concat(imageDirectory, "Rgraphics3.png"))
knitr::include_graphics(path_concat(imageDirectory, "Rgraphics4.png"))
knitr::include_graphics(path_concat(imageDirectory, "Rgraphics5.png"))
knitr::include_graphics(path_concat(imageDirectory, "Rgraphics6.png"))
knitr::include_graphics(path_concat(imageDirectory, "loon_fable.png"))
library(loon)
l_plot(x = quakes$long, y = quakes$lat, 
       xlabel = "longitude", ylabel = "latitude",
       title = "Tonga trench earthquakes")
knitr::include_graphics(path_concat(imageDirectory, "inspectorQuakesOriginal"))
knitr::include_graphics(path_concat(imageDirectory, "quakesOriginal"))
knitr::include_graphics(path_concat(imageDirectory, "panning.png"))
knitr::include_graphics(path_concat(imageDirectory, "zooming.png"))
knitr::include_graphics(path_concat(imageDirectory, "selecting.png"))
knitr::include_graphics(path_concat(imageDirectory, "selecting.png"))
knitr::include_graphics(path_concat(imageDirectory, "inspectorQuakesOriginal"))
knitr::include_graphics(path_concat(imageDirectory, "quakesGuides"))
knitr::include_graphics(path_concat(imageDirectory, "inspectorPlotAnalysis.png"))
knitr::include_graphics(path_concat(imageDirectory, "quakesWorldViewDefault.png"))
knitr::include_graphics(path_concat(imageDirectory, "analysisPlotOptions.png"))
knitr::include_graphics(path_concat(imageDirectory, "analysisPlotSelection.png"))
knitr::include_graphics(path_concat(imageDirectory, "analysisPlotModify.png"))
knitr::include_graphics(path_concat(imageDirectory, "inspectorSelectDefaults.png"))
knitr::include_graphics(path_concat(imageDirectory, "inspectorQuakesPlus10Cols.png"))
l_getColorList()
palette()
## l_setColorList_baseR()                             # base R palette
## l_setColorList_ColorBrewer("Set2")                 # colorblind friendly choice from ColorBrewer
## l_setColorList_hcl(luminance = 80)                 # set of hcl colours
## l_setColorList_ggplot2()                           # ggplot2's palette
## l_setColorList_loon()                              # default loon palette
## l_setColorList(l_colRemoveAlpha(rainbow(5)))       # any set of colours without alpha
knitr::include_graphics(path_concat(imageDirectory, "inspectorRbaseCols.png"))
knitr::include_graphics(path_concat(imageDirectory, "inspectorColorBrewerCols"))
knitr::include_graphics(path_concat(imageDirectory, "inspectorHclCols"))
knitr::include_graphics(path_concat(imageDirectory, "inspectorGgplot2Cols"))
## # loon graphics (note that the result is assigned to p)
## p <- l_plot(x = quakes$long, y = quakes$lat,
##             xlabel = "longitude", ylabel = "latitude",
##             title = "Tonga trench earthquakes")
# accessing the plot from its string representation
p <- l_create_handle(".l0.plot")
p 
## library(grid)
## grid.newpage()
## grid.loon(p)
library(grid)
gp <- grid.loon(p, draw = FALSE) # produces a grob
grid.ls(gp)  # lists the contents of the grob
names(p)
p["showGuides"]
getGroups <- function(loonplot){
    
    if (!"l_plot" %in% class(loonplot)) stop("loonplot must be an l_plot")
    
    lapply(unique(loonplot['color']),
           FUN = function(group){
               loonplot['color'] == group
               }
           )
}

myGroups <- getGroups(p)  # returns groups identified by unique colour in p
nGroups <- length(myGroups) # number of groups
head(quakes[myGroups[[1]],]) # Data on first few quakes in group 1.
p["showGuides"] <- TRUE

p["size"] <- sample(1:30, size = length(p["x"]), replace = TRUE)

for (i in 1:length(myGroups))  {
    p["selected"] <- myGroups[[i]]
    Sys.sleep(1)
}
p["selected"] <- FALSE

# something a little more involved for up to 6 groups
myCols <- c("firebrick", "steelblue", "purple", 
            "orange", "grey10", "grey80")
for (i in 1:length(myGroups)) {
    p["color"][myGroups[[i]]] <- myCols[i]
}

# something crazy
for (j in 1:10) {
  p["xTemp"] <- p["x"] + runif(length(p["x"]), min = -0.5, max = 0.5)
  Sys.sleep(0.1)
}

# putting locations and size back
p["xTemp"] <- p["x"]
p["size"] <- 4

## library(gridExtra)
## gs  <- lapply(myGroups,
##               FUN = function(group) {
##                   p["selected"] <- group
##                   loonGrob(p)
##               })
## grid.arrange(grobs = gs, ncol = 2)
## p["selected"] <- FALSE
library(maps)
NZFijiMap <- map("world2", regions=c("New Zealand", "Fiji"), plot=FALSE)
l_layer(p, NZFijiMap, 
        label = "New Zealand and Fiji",
        color = "forestgreen",
        index = "end")
knitr::include_graphics(path_concat(imageDirectory, "quakesGuidesMapInspector"))
knitr::include_graphics(path_concat(imageDirectory, "quakesGuidesMap"))
knitr::include_graphics(path_concat(imageDirectory, "quakesWorldViewScaling.png"))
knitr::include_graphics(path_concat(imageDirectory, "quakesLayersInspector.png"))
## # Base graphics
## plot(x = quakes$long, y = quakes$lat,
##      xlab = "longitude", ylab = "latitude",
##      main = "Tonga trench earthquakes")
## 
## # loon graphics
## l_plot(x = quakes$long, y = quakes$lat,
##        xlabel = "longitude", ylabel = "latitude",
##        title = "Tonga trench earthquakes")
h <- l_hist(quakes$depth, 
            xlabel = "depth", 
            title = "Tonga trench earthquakes")
library(RColorBrewer)
cols <- brewer.pal(9, "Blues")[-c(1:4)] # get rid of lightest
l_setColorList(cols)
h["color"] <- cols[cut(quakes$depth, breaks=5)]
h_mag <- l_hist(quakes$mag, linkingGroup = "quakes", 
                showStackedColors = TRUE,
                yshows = "density",
                xlabel = "magnitude")
h_stations <- l_hist(quakes$stations, linkingGroup = "quakes", 
                     showStackedColors = TRUE,
                     yshows = "density",
                     xlabel = "Number of stations reporting")
p_mag_stations <- l_plot(quakes$mag, quakes$stations, 
                         linkingGroup = "quakes", 
                         xlabel = "Magnitude", 
                         ylabel = "Number of stations reporting")