In kraaijenbrink/pkrf: Philip Kraaijenbrink's R functions

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Sectioning

First subsection

Second subsection

Subsubsection

Color scheme

The color scheme used in this template reflects those used for mountain hydrology powerpoint presentations and posters. This color scheme is, next to many others, available via the custom palette function of the pkrf package.

library(pkrf)
mhcolors <- pkPal('mnthydro')       # load the  palette using pkrf::pkPal()

To show all palettes and their colors available in pkrf in a plot use the following syntax:
pkPal(show=TRUE)


The mountain hydrology palette consists of the following colors:

par(mar=c(1.5,0,0,0)); image(matrix(seq(mhcolors)),col=mhcolors,axes=F)
mtext(1:length(mhcolors), at=seq(0,1,length.out=length(mhcolors)), side=1, line=0.5)

Figures

Figures can be added by running R code directly. For instance a curve of $f(x)=sin(x)$:

par(mar=c(4,4,1,0.5), mgp=c(2.5,0.75,0), cex.axis=0.75, tck=-0.02, las=1)
curve(sin(x), xlim=c(-2*pi,2*pi), xaxs='i', col=mhcolors[1], lwd=3); abline(v=0,h=0,lty=3)

Local and external figures

Local or external figures can also be added easily:

{width=500px}

Interactive figures

Interactive figures can be made using various html widgets.
For example, one could covert a ggplot2 plot to a plotly one using ggplotly:

library(ggplot2); library(plotly); library(pkrf)
p <- ggplot(warming) +
     geom_point(aes(x=dt_glob,y=dv_hma, label=gcm, color=rcp)) + scale_color_manual(values=mhcolors[1:4]) + 
     geom_smooth(aes(x=dt_glob,y=dv_hma), method='lm') + 
     labs(x='Global temperature rise (K)', y='Glacier mass loss in HMA (%)') + 
     theme_light()
ggplotly()

Maps

Static map

This is an example section with an R-generated study area map, using data from the rworldmap package.

par(mar=c(0.5,0.25,0.5,0.2))
library(rworldmap); library(raster); library(rgdal)
roi <- extent(c(range(glaciers$longitude),range(glaciers$latitude)))
plot(rworldmap::countriesLow, col=mhcolors[3], xlim=(roi*2)[1:2], ylim=(roi*2)[3:4], border='white', asp=1)
lines(as(roi,'SpatialPolygons'), lwd=3, col=mhcolors[2],0.75)
labelCountries(col=mhcolors[1])
box(lwd=2, col=mhcolors[1])

Dynamic maps with Leaflet

You can also easily make interactive multilayer maps using leaflet.

library(leaflet); library(magrittr); library(rgdal);
library(raster); library(pkrf); library(base64enc);

# calculate data derivatives
glac              <- glaciers
coordinates(glac) <- c(1,2)
glac$percentage   <- glac$mass_debris_ela / glac$mass_total * 100
glacrast          <- rasterFromXYZ(glaciers)
crs(glac) <- crs(glacrast) <- crs("+init=EPSG:4326")
precip <- projectRaster(glacrast$precip, res=10000, crs=crs("+init=EPSG:3857"))

# construct colors palettes
rastpal <- colorBin(palette='Blues', bins=c(seq(0,2000,250),5000), na.color='#00000000')
fillpal <- colorBin(palette = 'Greys', bins=c(seq(0,30,5),100))
linepal <- colorFactor(palette=pkPal('uumain',rand=T), domain=glac$region)

# make some simple base64 encoded figures to embed in popup labels
b64img <- lapply(1:nrow(glaciers), function(i){
  tmpfn <- tempfile('subplot_',fileext='.png')
  png(tmpfn, width=200, height=100, res=100)
  par(mar=c(1.25,6,0.2,0.5), mgp=c(2,0.25,0), las=1, cex.axis=0.7, tck=-0.03)
  barplot(unlist(glaciers[i,11:14]), ylab='', col=mhcolors, horiz=T,
           names.arg=c('Total mass','Mass blw. ELA','Debris-covered','DC blw. ELA'))
  dev.off()
  b64 <- paste0('data:image/png;base64, ',base64encode(tmpfn))
  return(b64)
})

# construct html labels, incl the base64 images
labels <- sprintf('<strong>%s</strong></br>Glaciers: %.0f</br>ELA: %.0f m',
                   glac$region, glac$count, glac$ela) 
labels <- sprintf('%s<br><div style="width:200px"><img src="%s"></div>',labels,b64img)
labels <- lapply(labels, htmltools::HTML)

# call leaflet and add multiple layers of data
leaflet(glac) %>% 
  addProviderTiles(providers$Esri.WorldImagery, option=list(opacity=1.0)) %>%
  addProviderTiles(providers$Esri.WorldPhysical, option=list(opacity=0.6)) %>%
  addRasterImage(precip, color=rastpal, opacity=0.85) %>%
  addCircleMarkers(radius=~sqrt(count)/3, stroke=T, opacity=0.8, fillOpacity=1,
                   weight=2, color=~linepal(region), fillColor=~fillpal(percentage),
                   label=labels, labelOptions=list(textsize='13px')) %>%
  addLegend('topright',pal=rastpal, values=c(0,cellStats(glacrast$precip,max)), opacity=0.85, title = "Precip (mm)") %>%
  addLegend("topright", pal=fillpal, values=~percentage, opacity=0.85, title = "Debris-cover (%)") %>%
  addLegend("topright", colors=mhcolors[2], labels='Region', opacity=1, title = NA)

Tables

Tables can be added in multiple ways.
For instance a raw HTML table using knitr::kable, or a nicely formatted table using DT::datatable

library(DT)
glacsum <- aggregate(glaciers[,c(7,11)], by=list(glaciers$region), FUN=sum)
datatable(glacsum, rownames=F, options=list(pageLength=5),
          colnames=c('Region','Area (km2)','Mass (Gt)'))

References

A bib file can be used and references can be used inline, like this reference to @Kraaijenbrink2016a.
They can also be between parentheses by using square brackets [@Kraaijenbrink2017].

kraaijenbrink/pkrf documentation built on July 4, 2023, 10:16 p.m.