---
title: "Introduction to ggchord2"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Introduction to ggchord2}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.align = "center"
)
```

```{r, warning=FALSE, message=FALSE}
library(ggchord2)
library(ggplot2)
```

## Simple chord diagram

```{r}
trade <- data.frame(
  source = c("USA", "USA", "China", "China", "Germany", "Germany"),
  target = c("China", "Germany", "USA", "Germany", "USA", "China"),
  freq   = c(50, 30, 60, 25, 35, 20)
)

ggplot(
  data = trade,
  mapping = aes(
    source = source,
    target = target,
    freq = freq
  )
) +
  geom_chord_diagram()
```

Colour by source node:

```{r}
ggplot(
  data = trade,
  mapping = aes(
    source = source,
    target = target,
    freq = freq,
    fill = source
  )
) +
  geom_chord_diagram()
```

You'll notice that some of the longer category labels may become cropped. This is a result of the way that the underlying `geom_text()` functions in `ggplot2` work. See the [vignette on positioning text](https://nrennie.gitlab.io/ggchord2/articles/Positioning-labels.html) for several different solutions.

## Asymmetric flows

```{r}
flows <- data.frame(
  source = c("Europe", "Europe", "Asia", "Asia", "Americas", "Americas"),
  target = c("Asia", "Americas", "Europe", "Americas", "Europe", "Asia"),
  freq   = c(12, 8, 15, 6, 9, 5)
)

ggplot(
  data = flows,
  mapping = aes(
    source = source,
    target = target,
    freq = freq,
    fill = source
  )
) +
  geom_chord_diagram(
    gap_degree   = 3,
    inner_radius = 0.55,
    outer_radius = 0.72
  )
```

Including flows from a source into itself:

```{r}
flows <- data.frame(
  source = c("Europe", "Europe", "Asia", "Asia"),
  target = c("Europe", "Americas", "Europe", "Americas"),
  freq   = c(12, 8, 15, 17)
)

ggplot(
  data = flows,
  mapping = aes(
    source = source,
    target = target,
    freq = freq,
    fill = source
  )
) +
  geom_chord_diagram(
    gap_degree   = 3,
    inner_radius = 0.55,
    outer_radius = 0.72
  )
```


## Faceting 

Faceting works as you would expect. For example, to facet by year:

```{r}
trade_ts <- rbind(
  cbind(trade, year = 2022),
  data.frame(
    source = c("USA", "China", "Germany"),
    target = c("China", "USA", "USA"),
    freq   = c(65, 70, 40),
    year   = 2023
  )
)

ggplot(
  data = trade_ts,
  mapping = aes(
    source = source,
    target = target,
    freq = freq,
    fill = source
  )
) +
  geom_chord_diagram() +
  facet_wrap(~year)
```

## Individual layers for more control

```{r}
g <- ggplot(
  data = trade,
  mapping = aes(
    source = source,
    target = target,
    freq = freq
  )
) +
  geom_chord_arcs(
    mapping = aes(fill = source),
    alpha = 0.5
  ) +
  geom_chord_sectors(
    mapping = aes(fill = source),
    colour = "white",
    linewidth = 0.8
  ) +
  geom_chord_labels(
    mapping = aes(colour = source),
    size = 4
  )
g
```

Add `ggplot2` styling:

```{r}
g +
  scale_x_continuous(limits = c(-1.5, 1.5)) +
  scale_colour_brewer(palette = "Dark2") +
  scale_fill_brewer(palette = "Dark2") +
  coord_fixed() +
  theme_void() +
  theme(legend.position = "none")
```