---
title: "scale_* functions (ggplot2)"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{scale_* functions (ggplot2)}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 5
)
library(paletteNMR)
suppressPackageStartupMessages({
  library(dplyr)
  library(lubridate)
  library(ggplot2)
  library(scales)
  library(patchwork)
  library(datasets)
})

theme_set(theme_nmr() +
            theme(panel.grid.major.y = element_line(colour = "grey50")))
```

In addition to the NMR palettes themselves, `paletteNMR` contains `scale_*` functions for use in ggplot2 graphics

Below, two figures with discrete color scales are created using `scale_nmr_color_*` variants and `scale_nmr_fill` variants respectively:

```{r iris}
iris |> 
  ggplot(aes(Sepal.Length, Petal.Length)) +
  geom_point(aes(colour = Species),
             size = rel(4), alpha = 1/1.2) +
  scale_nmr_color_categorical(pal = "quad",
                              set = "C",
                              reverse = TRUE)

iris |> 
  ggplot(aes(Sepal.Length, Petal.Length)) +
  geom_point(aes(fill = Species),
             shape = 21, size = rel(4), alpha = 1/1.2) +
  scale_nmr_fill_categorical(pal = "quad",
                              set = "C",
                              reverse = TRUE)
```

Testing cases with more discrete colors (using the `airmiles` dataset from the `datasets` pkg)

```{r miles}
airmiles |> 
  as.data.frame() |> 
  setNames("miles") |> 
  mutate(yr = time(airmiles) |> 
           parse_date_time("Y")) |> 
  mutate(yr_grp = floor_date(yr, "10 years") |> 
           year() |> factor()) |> 
  ggplot(aes(yr, miles)) +
  geom_point(aes(color = yr_grp),
             size = rel(4), alpha = 1/1.2) +
  labs(x = NULL, y = "Miles traveled",
       color = NULL) +
  scale_x_datetime(date_breaks = "10 years",
                   date_labels = "%Y") +
  scale_y_continuous(labels = unit_format(unit = "k", scale = 1e-3)) +
  scale_nmr_color_categorical(pal = "quad",
                              set = "C",
                              reverse = TRUE)
```

Continuous values work too!

```{r iris_cont}
iris |> 
  ggplot(aes(Sepal.Length, Petal.Length)) +
  geom_point(aes(colour = Petal.Length),
             size = rel(4), alpha = 1/1.2) +
  scale_nmr_color_sequential(set = "GT6",
                             discrete = FALSE,
                             reverse = TRUE) +
  guides(color = "none")

iris |> 
  ggplot(aes(Sepal.Length, Petal.Length)) +
  geom_point(aes(fill = Petal.Length),
             shape = 21, 
             size = rel(4), alpha = 1/1.2) +
  scale_nmr_fill_sequential(set = "GT6",
                            discrete = FALSE,
                            reverse = TRUE) +
  guides(fill = "none")
```

Take care to specify the right arguments. For example, using `scale_nmr_color_sequential` assumes a divergent palette (i.e. `pal = "diverg"`), so it only requires specifying the `set` argument (e.g. `set = "GT6"`)


```{r iris_error, error=TRUE}
iris |> 
  ggplot(aes(Sepal.Length, Petal.Length)) +
  geom_point(aes(colour = Petal.Length),
             size = rel(4), alpha = 1/1.2) +
  scale_nmr_color_sequential(pal = "GT6",
                             discrete = FALSE,
                             reverse = TRUE) +
  guides(color = "none")
```