### Install and Use viridis Color Palette in Base R Plots

Source: https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html

Demonstrates how to install the viridis package and use its default color palette for creating visualizations in base R. It generates a contour plot using the viridis color scale.

```r
install.packages("viridis")
library(viridis)

x <- y <- seq(-8*pi, 8*pi, len = 40)
r <- sqrt(outer(x^2, y^2, "+"))
filled.contour(cos(r^2)*exp(-r/(2*pi)), 
               axes=FALSE,
               color.palette=viridis,
               asp=1)
```

--------------------------------

### Apply viridis Color Scales in ggplot2

Source: https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html

Shows how to integrate viridis color scales into ggplot2 visualizations using `scale_color_viridis()` and `scale_fill_viridis()`. This example creates a hexbin plot with a viridis fill scale.

```r
library(ggplot2)
ggplot(data.frame(x = rnorm(10000), y = rnorm(10000)), aes(x = x, y = y)) +
  geom_hex() + coord_fixed() +
  scale_fill_viridis() + theme_bw()
```

--------------------------------

### Apply Discrete Viridis Color Scale to Scatter Plot (R)

Source: https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html

This example shows how to apply a discrete viridis color scale to a scatter plot using ggplot2. It maps the number of cylinders to color. Requires ggplot2 and viridis.

```r
p <- ggplot(mtcars, aes(wt, mpg))
p + geom_point(size=4, aes(colour = factor(cyl))) +
    scale_color_viridis(discrete=TRUE) +
    theme_bw()
```

--------------------------------

### Generate Inferno Color Scale for Raster Image (R)

Source: https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html

This snippet demonstrates how to load a raster image, project it, and display it using the 'inferno' color scale from the viridis package. It requires the 'terra' and 'httr' libraries.

```r
library(terra)
library(httr)
par(mfrow=c(1,1), mar=rep(0.5, 4))
temp_raster <- "http://ftp.cpc.ncep.noaa.gov/GIS/GRADS_GIS/GeoTIFF/TEMP/us_tmax/us.tmax_nohads_ll_20150219_float.tif"
try(GET(temp_raster,
        write_disk("us.tmax_nohads_ll_20150219_float.tif")),
    silent=TRUE)
us <- rast("us.tmax_nohads_ll_20150219_float.tif")
us <- project(us, y="+proj=aea +lat_1=29.5 +lat_2=45.5 +lat_0=37.5 +lon_0=-96 +x_0=0 +y_0=0 +ellps=GRS80 +datum=NAD83 +units=m +no_defs")
image(us, col=inferno(256), asp=1, axes=FALSE, xaxs="i", xaxt='n', yaxt='n', ann=FALSE)
```

--------------------------------

### Create Choropleth Map with Magma Scale using ggplot2 (R)

Source: https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html

This code generates a choropleth map of US unemployment rates by county using ggplot2 and the 'magma' color scale from viridis. It requires the 'maps', 'mapproj', and 'viridis' packages.

```r
library(maps)
library(mapproj)

data(unemp, package = "viridis")

county_df <- map_data("county", projection = "albers", parameters = c(39, 45))
names(county_df) <- c("long", "lat", "group", "order", "state_name", "county")
county_df$state <- state.abb[match(county_df$state_name, tolower(state.name))]
county_df$state_name <- NULL

state_df <- map_data("state", projection = "albers", parameters = c(39, 45))

choropleth <- merge(county_df, unemp, by = c("state", "county"))
choropleth <- choropleth[order(choropleth$order), ]

ggplot(choropleth, aes(long, lat, group = group)) +
  geom_polygon(aes(fill = rate), colour = alpha("white", 1 / 2), linewidth = 0.2) +
  geom_polygon(data = state_df, colour = "white", fill = NA) +
  coord_fixed() +
  theme_minimal() +
  ggtitle("US unemployment rate by county") +
  theme(axis.line = element_blank(), axis.text = element_blank(),
        axis.ticks = element_blank(), axis.title = element_blank()) +
  scale_fill_viridis(option="magma")
```

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