bubble.R

  ##################################################################
  ## Source code for the book: "Displaying time series, spatial and
  ## space-time data with R"
  
  ## Copyright (C) 2013-2012 Oscar Perpiñán Lamigueiro
  
  ## This program is free software you can redistribute it and/or modify
  ## it under the terms of the GNU General Public License as published
  ## by the Free Software Foundation; either version 2 of the License,
  ## or (at your option) any later version.
   
  ## This program is distributed in the hope that it will be useful, but
  ## WITHOUT ANY WARRANTY; without even the implied warranty of
  ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
  ## General Public License for more details.
   
  ## You should have received a copy of the GNU General Public License
  ## along with this program; if not, write to the Free Software
  ## Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
  ## 02111-1307, USA.
  ####################################################################

  ##################################################################
  ## Initial configuration
  ##################################################################
  ## Clone or download the repository and set the working directory
  ## with setwd to the folder where the repository is located.
  
  library(lattice)
  library(ggplot2)
  library(latticeExtra)
  
  myTheme <- custom.theme.2(pch=19, cex=0.7,
                            region=rev(brewer.pal(9, 'YlOrRd')),
                            symbol = brewer.pal(n=8, name = "Dark2"))
  myTheme$strip.background$col='transparent'
  myTheme$strip.shingle$col='transparent'
  myTheme$strip.border$col='transparent'
  
  xscale.components.custom <- function(...){
      ans <- xscale.components.default(...)
      ans$top=FALSE
      ans}
  yscale.components.custom <- function(...){
      ans <- yscale.components.default(...)
      ans$right=FALSE
      ans}
  myArgs <- list(as.table=TRUE,
                 between=list(x=0.5, y=0.2),
                 xscale.components = xscale.components.custom,
                 yscale.components = yscale.components.custom)
  defaultArgs <- lattice.options()$default.args
  
  lattice.options(default.theme = myTheme,
                  default.args = modifyList(defaultArgs, myArgs))
  

  ##################################################################
  ## Proportional symbol mapping
  ##################################################################

##################################################################
## Introduction
##################################################################

##################################################################
## Proportional symbol with spplot
##################################################################

  library(sp)
  
  load('data/NO2sp.RData')

pdf(file="figs/airMadrid_spplot.pdf")
  airPal <- colorRampPalette(c('springgreen1', 'sienna3', 'gray5'))(5)
  
  spplot(NO2sp["mean"], col.regions=airPal, cex=sqrt(1:5),
         edge.col='black', scales=list(draw=TRUE),
         key.space='right')
dev.off()

  NO2df <- data.frame(NO2sp)
  NO2df$Mean <- cut(NO2sp$mean, 5)
  
  ggplot(data=NO2df, aes(long, lat, size=Mean, fill=Mean)) +
      geom_point(pch=21, col='black') + theme_bw() +
      scale_fill_manual(values=airPal)

##################################################################
## Optimal classification and sizes to improve discrimination
##################################################################

  library(classInt)
  ## The number of classes is chosen between the Sturges and the
  ## Scott rules.
  nClasses <- 5
  intervals <- classIntervals(NO2sp$mean, n=nClasses, style='fisher')
  ## Number of classes is not always the same as the proposed number
  nClasses <- length(intervals$brks) - 1

  op <- options(digits=4)
  tab <- print(intervals)
  options(op)

  ## Complete Dent set of circle radii (mm)
  dent <- c(0.64, 1.14, 1.65, 2.79, 4.32, 6.22, 9.65, 12.95, 15.11)
  ## Subset for our dataset
  dentAQ <- dent[seq_len(nClasses)]
  ## Link Size and Class: findCols returns the class number of each
  ## point; cex is the vector of sizes for each data point
  idx <- findCols(intervals)
  cexNO2 <- dentAQ[idx]

  NO2sp$classNO2 <- factor(names(tab)[idx])

  ## ggplot2 version
  NO2df <- data.frame(NO2sp)
  
  ggplot(data=NO2df, aes(long, lat, size=classNO2, fill=classNO2)) +
      geom_point(pch=21, col='black') + theme_bw() +
      scale_fill_manual(values=airPal) +
      scale_size_manual(values=dentAQ*2)
  

pdf(file="figs/airMadrid_classes.pdf")
  ## spplot version
  
  ## Definition of an improved key with title and background
  NO2key <- list(x=0.98, y=0.02, corner=c(1, 0),
                title=expression(NO[2]~~(paste(mu, plain(g))/m^3)),
                cex.title=.75, cex=0.7,
                background='gray92')
  
  pNO2 <- spplot(NO2sp["classNO2"],
                 col.regions=airPal,  cex=dentAQ,
                 edge.col='black',
                 scales=list(draw=TRUE),
                 key.space=NO2key)
  pNO2
dev.off()

##################################################################
## Spatial context with underlying layers and labels
##################################################################

##################################################################
## Static image
##################################################################

  madridBox <- bbox(NO2sp)

  ## ggmap solution
  library(ggmap)
  madridGG <- get_map(c(madridBox), maptype='watercolor', source='stamen')

  ## OpenStreetMap solution
  library(OpenStreetMap)
  ul <- madridBox[c(4, 1)]
  lr <- madridBox[c(2, 3)]
  madridOM <- openmap(ul, lr, type='stamen-watercolor')
  madridOM <- openproj(madridOM)

  NO2df <- data.frame(NO2sp)
  
  ## ggmap
  ggmap(madridGG) +
      geom_point(data=NO2df,
                 aes(long, lat, size=classNO2, fill=classNO2),
                 pch=21, col='black') +
         scale_fill_manual(values=airPal) +
         scale_size_manual(values=dentAQ*2)
  
  ##OpenStreetMap
  autoplot(madridOM) + 
      geom_point(data=NO2df,
                 aes(long, lat, size=classNO2, fill=classNO2),
                 pch=21, col='black') +
      scale_fill_manual(values=airPal) +
      scale_size_manual(values=dentAQ*2)  
  

pdf(file="figs/airMadrid_stamen.pdf")
  ## the 'bb' attribute stores the bounding box of the get_map result
  bbMap <- attr(madridGG, 'bb')
  ## This information is needed to resize the image with grid.raster
  height <- with(bbMap, ur.lat - ll.lat)
  width <- with(bbMap, ur.lon - ll.lon)
  
  pNO2 + layer(grid.raster(madridGG,
                            width=width, height=height,
                            default.units='native'),
               under=TRUE)
dev.off()

  tile <- madridOM$tile[[1]]
  
  height <- with(tile$bbox, p1[2] - p2[2])
  width <- with(tile$bbox, p2[1] - p1[1])
  
  colors <- as.raster(matrix(tile$colorData,
                             ncol=tile$yres,
                             nrow=tile$xres,
                             byrow=TRUE))
  
  pNO2 + layer(grid.raster(colors,
                           width=width,
                           height=height,
                           default.units='native'),
               under=TRUE)
  

##################################################################
## Vector data
##################################################################

  library(maptools)
  library(rgdal)
    
  ## nomecalles http://www.madrid.org/nomecalles/Callejero_madrid.icm
  ## Form at http://www.madrid.org/nomecalles/DescargaBDTCorte.icm
  
  ## Madrid districts
  unzip('Distritos de Madrid.zip')
  distritosMadrid <- readShapePoly('Distritos de Madrid/200001331')
  proj4string(distritosMadrid) <- CRS("+proj=utm +zone=30")
  distritosMadrid <- spTransform(distritosMadrid, CRS=CRS("+proj=longlat +ellps=WGS84"))
  
  ## Madrid streets
  unzip('Callejero_ Ejes de viales.zip')
  streets <- readShapeLines('Callejero_ Ejes de viales/call2011.shp')
  streetsMadrid <- streets[streets$CMUN=='079',]
  proj4string(streetsMadrid) <- CRS("+proj=utm +zone=30")
  streetsMadrid <- spTransform(streetsMadrid, CRS=CRS("+proj=longlat +ellps=WGS84"))

  spDistricts <- list('sp.polygons', distritosMadrid, fill='gray97', lwd=0.3)
  spStreets <- list('sp.lines', streetsMadrid, lwd=0.05)
  spNames <- list(sp.pointLabel, NO2sp,
                  labels=substring(NO2sp$codEst, 7),
                  cex=0.6, fontfamily='Palatino')
  
  spplot(NO2sp["classNO2"], col.regions=airPal, cex=dentAQ,
         edge.col='black', alpha=0.8,
         sp.layout=list(spDistricts, spStreets, spNames),
         scales=list(draw=TRUE),
         key.space=NO2key)
  

png(filename="figs/airMadrid.png",res=600,height=4000,width=4000)
  pNO2 +
      layer(sp.pointLabel(NO2sp,
                          labels=substring(NO2sp$codEst, 7),
                          cex=0.8, fontfamily='Palatino')
            ) +
      layer_({
          sp.polygons(distritosMadrid, fill='gray97', lwd=0.3)
          sp.lines(streetsMadrid, lwd=0.05)
      })
dev.off()

##################################################################
## Spatial interpolation
##################################################################

  library(gstat)
  
  airGrid <- spsample(NO2sp, type='regular', n=1e5)
  gridded(airGrid) <- TRUE
  airKrige <- krige(mean ~ 1, NO2sp, airGrid)

png(filename="figs/airMadrid_krige.png",res=600,height=4000,width=4000)
spplot(airKrige["var1.pred"],
       col.regions=colorRampPalette(airPal)) +
  layer({
    sp.polygons(distritosMadrid, fill='transparent', lwd=0.3)
    sp.lines(streetsMadrid, lwd=0.07)
    sp.points(NO2sp, pch=21, alpha=0.8, fill='gray50', col='black')
    })
dev.off()

##################################################################
## GeoJSON and OpenStreepMap
##################################################################

library(rgdal)
writeOGR(NO2sp, 'data/NO2.geojson', 'NO2sp', driver='GeoJSON')

  library(rgdal)
  writeOGR(NO2sp, dsn='NO2_mean.kml', layer='mean', driver='KML')

  library(plotKML)
  plotKML(NO2sp["mean"], points_names=NO2sp$codEst)

##################################################################
## Additional information with tooltips and hyperlinks
##################################################################

  library(XML)

  old <- setwd('images')
  for (i in 1:nrow(NO2df)){
    codEst <- NO2df[i, "codEst"]
    ## Webpage of each station
    codURL <- as.numeric(substr(codEst, 7, 8))
    rootURL <- 'http://www.mambiente.munimadrid.es'
    stationURL <- paste(rootURL,
                        '/opencms/opencms/calaire/contenidos/estaciones/estacion',
                        codURL, '.html', sep='')
    content <- htmlParse(stationURL, encoding='utf8')
    ## Extracted with http://www.selectorgadget.com/
    xPath <- '//*[contains(concat( " ", @class, " " ), concat( " ", "imagen_1", " " ))]'
    imageStation <- getNodeSet(content, xPath)[[1]]
    imageURL <- xmlAttrs(imageStation)[1]
    imageURL <- paste(rootURL, imageURL, sep='')
    download.file(imageURL, destfile=paste(codEst, '.jpg', sep=''))
  }
  setwd(old)

  print(pNO2 + layer_(sp.polygons(distritosMadrid, fill='gray97', lwd=0.3)))

  library(gridSVG)
  
  NO2df <- as.data.frame(NO2sp)
  
  tooltips <- sapply(seq_len(nrow(NO2df)), function(i){
    codEst <- NO2df[i, "codEst"]
    ## Information to be attached to each line
    stats <- paste(c('Mean', 'Median', 'SD'),
                   signif(NO2df[i, c('mean', 'median', 'sd')], 4),
                   sep=' = ', collapse='<br />')
    ## Station photograph 
    imageURL <- paste('images/', codEst, '.jpg', sep='')
    imageInfo <- paste("<img src=", imageURL,
                       " width='100' height='100' />", sep='')
    ## Text to be included in the tooltip
    nameStation <- paste('<b>', 
                         as.character(NO2df[i, "Nombre"]),
                         '</b>', sep='')
    info <- paste(nameStation, stats, sep='<br />')
    ## Tooltip includes the image and the text
    paste(imageInfo, info, sep='<br />')
  })
  grid.garnish('points.panel', title=tooltips,  grep=TRUE, group=FALSE)

  ## Webpage of each station
  rootURL <- 'http://www.mambiente.munimadrid.es'
  urlList <- sapply(seq_len(nrow(NO2df)), function(i){
    codEst <- NO2df[i, "codEst"]
    codURL <- as.numeric(substr(codEst, 7, 8))
    stationURL <- paste(rootURL,
                        '/opencms/opencms/calaire/contenidos/estaciones/estacion',
                        codURL, '.html', sep='')
    })
  
  grid.hyperlink('points.panel', urlList, grep=TRUE, group=FALSE)

  ## Add jQuery and jQuery UI scripts
  grid.script(file='http://code.jquery.com/jquery-1.8.3.js')
  grid.script(file='http://code.jquery.com/ui/1.9.2/jquery-ui.js')
  ## Simple JavaScript code to initialize the tooltip
  grid.script(file='js/myTooltip.js')
  ## Produce the SVG graphic: the results of grid.garnish,
  ## grid.hyperlink and grid.script are converted to SVG code
  grid.export('figs/airMadrid.svg')

  htmlBegin <- '<!DOCTYPE html>
  <html>
  <head>
  <title>Tooltips with jQuery and gridSVG</title>
  <link rel="stylesheet" type="text/css" href="http://code.jquery.com/ui/1.9.2/themes/smoothness/jquery-ui.css" />
  <meta charset="utf-8">
  </head>
  <body>'
  
  htmlEnd <- '</body> </html>'
    
  svgText <- paste(readLines('figs/airMadrid.svg'), collapse='\n')
    
  writeLines(paste(htmlBegin, svgText, htmlEnd, sep='\n'),
             'airMadrid.html')