inst/doc/vignette_examples.R

In jgcricolors: Manage 'JGCRI' Color Palettes

## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
options(rmarkdown.html_vignette.check_title = FALSE)

## ---- eval=TRUE, warning=FALSE, message=FALSE---------------------------------
library(jgcricolors)

# See all available color palettes
names(jgcricol())

# Load a color palette
mypal1 <- jgcricol()$pal_basic  # To load values only
mypal2 <- jgcricol("pal_basic") # To see an example piechart and values


## ---- eval=F, echo=T, warning=FALSE, message=FALSE----------------------------
#  library(jgcricolors)
#  library(ggplot2)
#  
#  # Set your palette
#  mypal = jgcricol()$pal_all
#  
#  # Example categories for data to plot
#  # Can replace these with any other GCAM technologies or classes as done in the subsequent figures.
#  techs = c("a oil","a oil CCS","b natural gas","b natural gas CCS","c coal","c coal CCS",
#      "d biomass","d biomass CCS","e nuclear","f hydro","g wind","h solar","i geothermal",
#      "j traditional biomass","energy reduction")
#  
#  # Create data
#  data <- data.frame(label=rep(techs,each=4), x=rep(c(1:4),length(techs)), value=runif(4*length(techs))) %>%
#    mutate(label=as.factor(label))
#  
#  # Plot
#    print(ggplot(data, aes(x=x,y=value, fill=label)) +
#        geom_bar(position="stack", stat="identity", col="black",lwd=0.5) +
#        scale_fill_manual(values=mypal[names(mypal) %in% techs]) +
#        theme_bw() +
#        xlab(NULL) +
#        ylab(NULL) +
#        ggtitle("Primary Energy"))
#  

## ---- eval=TRUE, echo=FALSE, warning=FALSE, message=FALSE, results = 'asis'----
library(jgcricolors)
library(ggplot2)

# Set your palette
mypal = jgcricol()$pal_all

# Example lists of different GCAM data
listx <- list(
  # Primary energy colors including CCS
  `Primary energy` = c(
    "a oil","a oil CCS","b natural gas","b natural gas CCS","c coal","c coal CCS",
    "d biomass","d biomass CCS","e nuclear","f hydro","g wind","h solar","i geothermal",
    "j traditional biomass","energy reduction"),
  
  `Elec gen by fuel` = c( "a Coal",
      "b Coal w/CCS",
      "c Gas",
      "d Gas w/CCS",
      "e Oil",
      "f Oil w/CCS",
      "g Biomass",
      "h Biomass w/CCS",
      "i Nuclear",
      "j Geothermal",
      "k Hydro",
      "l Wind",
      "m Solar",
      "n CHP",
      "o Battery",
      "energy reduction"),
  
  `Elec by Tech` = c('biomass',
      'coal',
      'gas',
      'geothermal',
      'grid_storage',
      'hydro',
      'hydrogen',
      'nuclear',
      'refined liquids',
      'rooftop_pv',
      'solar',
      'wind'),
  
  `Transport by fuel` = c( "liquids",
      "gas",
      "coal",
      "biomass",
      "electricity",
      "hydrogen"),
  
  `Transport by tech` = c( 
    "LDV",
    "Bus",
    "Rail",
    "Plane",
    "MotorBike",
    "Truck",
    "Ship",
    "2W", 
    "3W", 
    "LHDT", 
    "MHDT", 
    "HHDT"),
  
    `AgLu by crop` = c( 'Biomass',
      'Corn',
      'FiberCrop',
      'Fodder',
      'Forest',
      'Grass',
      'MiscCrop',
      'OilCrop',
      'Other',
      'PalmFruit',
      'Pasture',
      'Rice',
      'RootTuber',
      'Shrub',
      'SugarCrop',
      'Urban',
      'Wheat'),
  
    `Water by sec` = c( 'agriculture',
      'electricity',
      'industry',
      'livestock',
      'mining',
      'municipal'
      )
  
    )
              
for(i in 1:length(listx)){
  techs = listx[[i]]              
  data <- data.frame(label=rep(techs,each=4), x=rep(c(1:4),length(techs)), value=runif(4*length(techs)))
  cat("  \n##", names(listx[i]), "  \n")
  print(ggplot(data, aes(x=x,y=value, fill=label)) +
    geom_bar(position="stack", stat="identity",col="black",lwd=0.5) +
    scale_fill_manual(values=mypal[names(mypal) %in% techs]) +
    theme_bw() +
    xlab(NULL) + ylab(NULL))
  cat('<div class="clearer"></div>')
}


## ---- eval=T, warning=FALSE, message=FALSE------------------------------------
library(jgcricolors)
library(graphics)
mypal1 <- jgcricol()$pal_basic  # To load silently
names(mypal1) <- mypal1
mypal2 = c(mypal1,"animal energy"="#FFF700", "human energy"="lawngreen")
oldpar <- par()
par(mfrow=c(1,2))
par(mai = c(0.5, 0.5, 0.5, 0.5))
pie(rep(1,length(mypal2)),label=names(mypal1),col=mypal1, main="Pal 1 w/ Missing Colors") # Plot as pie chart
pie(rep(1,length(mypal2)),label=names(mypal2),col=mypal2, main="Pal 2 w/ Added Colors") # Plot as pie chart
par(oldpar)

## ---- echo=FALSE, eval=TRUE, warning=FALSE, message=FALSE,results = 'asis'----
library(jgcricolors)
library(ggplot2)

# See all available color palettes
my_pals <- names(jgcricol())[!names(jgcricol()) %in% c("pal_all","pal_sankey")]
 
for(i in my_pals){
  mypal <- jgcricol()[[i]]
  if(i != "pal_scarcityCat"){names(mypal) <- mypal}
  mypal1 <- mypal
  names(mypal1) <- NULL
  cat("  \n##",  i, "  \n")
  cat('<div class="column-left">')
  oldpar <- par()
  par(mai = c(0, 0, 0, 0))
  pie(rep(1,length(mypal)),label=names(mypal),col=mypal)
  cat('</div>')
  cat('<div class="column-right">')
  cat('<p></p>')
  cat('<p></p>')

  print(ggplot() +
  geom_polygon(data =  jgcricolors::mapUS49df,
               aes(x = long, y = lat, group = group, fill = subRegion),
               colour = "gray10", lwd=0.5) +
  scale_fill_manual(values=rep(mypal1,50)[1:length(unique(jgcricolors::mapUS49df$subRegion))]) +
  theme_void() +
  coord_fixed(ratio = 1.25) +
  theme(legend.position = "none"))

  cat('</div>')
  cat('<div class="clearer"></div>')
  par(oldpar)
}

## ---- eval=TRUE, warning=FALSE, message=FALSE---------------------------------
library(RColorBrewer)
library(graphics)
getcol = colorRampPalette(brewer.pal(9, 'Pastel1')); 
values=getcol(9);
pie(rep(1,length(values)),label=names(values),col=values)