• Themes
  • Interactive Data Analysis
  • Exploratory Spatial Data Analysis
  • Time Series
  • Maps with Backdrops

rain %>%  group_by(Year,Month) %>% filter(Station=="Cork Airport") %>%
    summarise(Rainfall=sum(Rainfall)) %>% ungroup %>% transmute(Rainfall) %>%
    ts(start=c(1850,1),freq=12) ->  cork_ts
bdc_ts <- cbind(bel_ts,dub_ts,cork_ts)
bdc_ts %>% dygraph(width=800,height=450) %>% dyRangeSelector %>% dyRoller

• More on interaction
• Interactive maps for temporal exploration

local_monthplot('Derry',rain2)

png('test.png',width=400,height=300)
local_monthplot('Derry',rain2)
dev.off()

• No graph appears - but it is stored in test.png
• Try clicking on it after running the above code
• Depending on your operating system, an application should open it

• tmap is built on another package called leaflet
• leaflet is more powerful and fklexible
• leaflet is generally harder to use
• You can start off a map object in tmap but switch to leaflet
  1. create a tmap object in 'view' mode
  2. Convert with tmap_leaflet
  3. take it from there…

library(sf)
library(tmap)
counties <- st_read('counties.geojson') %>% st_transform(4326) # leaflet objects must be long/lat (epsg 4326)
tmap_mode('view')
tm_start <- tm_shape(counties) + tm_borders()
tm_start

tmap_leaflet(tm_start) %>% 
  addPolygons(data=counties,
              color = NA,  
              popup = popupImage('test.png',embed = TRUE)) 

for (i in 1:nrow(files))
  with(files, {
    png(Filename[i],width=400,height=300)
    local_monthplot(Station[i],rain2)
    dev.off()} )

• Check your directory again
  • Should be a png for each Station

rain %>% group_by(Station) %>%  summarise(mrain=mean(Rainfall))  %>% left_join(files)  %>% 
  select(Station,Long,Lat,mrain,Filename) %>% 
  st_as_sf(coords=c('Long','Lat'),crs=4326) -> station_means
station_means %>% head

## Simple feature collection with 6 features and 3 fields
## geometry type:  POINT
## dimension:      XY
## bbox:           xmin: -8.29 ymin: 52.19 xmax: -5.99 ymax: 54.79
## geographic CRS: WGS 84
## # A tibble: 6 x 4
##   Station   mrain Filename                                              geometry
##   <chr>     <dbl> <chr>                                              <POINT [°]>
## 1 Ardara    140.  /Users/chrisbrunsdon/Dropbox/climate_chan…       (-8.29 54.79)
## 2 Armagh     68.3 /Users/chrisbrunsdon/Dropbox/climate_chan…       (-6.64 54.35)
## 3 Athboy     74.7 /Users/chrisbrunsdon/Dropbox/climate_chan…        (-6.93 53.6)
## 4 Belfast    87.1 /Users/chrisbrunsdon/Dropbox/climate_chan…        (-5.99 54.5)
## 5 Birr       70.8 /Users/chrisbrunsdon/Dropbox/climate_chan…       (-7.88 53.08)
## 6 Cappoqui… 121.  /Users/chrisbrunsdon/Dropbox/climate_chan…        (-7.8 52.19)

tmap_leaflet(tm_start) %>% 
  addCircleMarkers(data=station_means,
                   popup=popupImage(station_means$Filename,embed=TRUE)) 

tm_start2 <- tm_shape(station_means) + tm_dots(col='mrain',popup.vars=FALSE,scale=1.5)
tmap_leaflet(tm_start2) %>% 
  addCircleMarkers(data=station_means,stroke = NA,
                   popup=popupImage(station_means$Filename,embed=TRUE)) 

• tm_start2 is a new tmap kick-off map based on shading the dots by mean rainfall.
• popup_vars = FALSE stops pop-up on tmap map
  • gets confusing if both leaflet and tmap have pop-ups
• stroke=NA stops leaflet drawing an outer ring on the pop-up markers

tmap_leaflet(tm_start2) %>% 
  addCircleMarkers(data=station_means,stroke = NA,
                   popup=popupImage(station_means$Filename,embed=TRUE)) %>%
  addScaleBar()

tmap_leaflet(tm_start2) %>% 
  addCircleMarkers(data=station_means,stroke = NA,
                   popup=popupImage(station_means$Filename,embed=TRUE)) %>%
  addMiniMap(zoomLevelOffset = -3)

bnds <- st_bbox(counties) # lng1, lat1, lng2, lat2
tmap_leaflet(tm_start2) %>% 
  addCircleMarkers(data=station_means,stroke = NA,
                   popup=popupImage(station_means$Filename,embed=TRUE)) %>%
  addMeasure()

local_trendplot <- function(station,raindata) {
  raindata %>% filter(Station == station) -> local_rd
  local_rd$Rainfall %>% ts(freq=12,start=1850) %>% 
  stl(s.window='periodic',t.window=721)  -> rain_stl
  rain_ts <- rain_stl$time.series[,1] + rain_stl$time.series[,2] 
  rain_ts %>% monthplot(col='dodgerblue',col.base='indianred',lwd.base=3)
}

local_trendplot('Derry',rain2)

• New R ideas
  • Pop-up information on leaflet maps
  • Interplay between tmap and leaflet
• Next lecture - ggvis