https://github.com/cj-holmes/ggambit

Visualise FEN chess positions with ggplot2
https://github.com/cj-holmes/ggambit

Last synced: about 2 months ago
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Visualise FEN chess positions with ggplot2

• Host: GitHub
• URL: https://github.com/cj-holmes/ggambit
• Owner: cj-holmes
• Created: 2020-12-05T20:17:51.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2021-07-17T08:47:58.000Z (about 3 years ago)
• Last Synced: 2024-02-13T10:03:13.775Z (8 months ago)
• Language: R
• Size: 2.94 MB
• Stars: 20
• Watchers: 3
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.Rmd

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README

        
---

output: github_document

---

```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "60%",

  dpi = 300)

```

# ggambit 

[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)

**THIS IS A DEVELOPMENTAL WORK IN PROGRESS**

## Introduction

The aim of `ggambit` is to visualise Forsyth–Edwards Notation (FEN) chess positions in R using `ggplot2`. Simple annotations (such as arrows and circles) can also be added to the image by specifying standard chess square notation (e4, c5, etc...). 

As the plotting engine is `ggplot2`, any additional `ggplot2` layers may be added to the image, giving the user full creative control.

### Attribution

Chess piece SVG design file downloaded from https://commons.wikimedia.org/wiki/File:Chess_Pieces_Sprite.svg

  

  * jurgenwesterhof (adapted from work of Cburnett), CC BY-SA 3.0 , via Wikimedia Commons

## Installation

`ggambit` can be installed from github

```{r eval=FALSE}

remotes::install_github('cj-holmes/ggambit')

```

```{r}

library(ggambit)

```

## Plotting FEN positions

Visualise the FEN starting position using the default settings (from white's perspective)

```{r}

plot_fen()

```

Use `add_arrow()`, `highlight_squares()`, `add_piece()`, `add_box()` and `fade_board()` to include simple annotations specified by chess board squares. These annotations are added to the plot in layers.

```{r}

plot_fen() + add_arrow("e2", "e4") + highlight_squares(c("d5", "f5"))

plot_fen() + add_box("d4", "e5", fill="white", alpha=1/2) + add_arrow("c2", "c4")

```

### A more interesting example

```{r}

my_fen <- "2k4r/pp3pp1/2p1bn1p/4N3/1b2PQ2/4KB2/Pq1r1PPP/R6R b - - 1 18"

```

```{r}

plot_fen(my_fen) + add_arrow("b4", "c5") + highlight_squares("e3")

```

Change perspective with the `perspective` argument

```{r}

plot_fen(my_fen, perspective = "b") + add_arrow("b4", "c5") + highlight_squares("e3")

```

## Board customisation

Square fill colours can be specified with the `palette` argument. An attempt at a newspaper style can be set using `palette = "news"`. See `plot_fen()` documentation for more details and options.

```{r}

plot_fen(palette = "green")

plot_fen(palette = "news")

```

## Parsing PGN files

There is a new **experimental** (and slow!) function for the parsing of PGN files to a long-format dataframe `pgn_to_df()`. Currently this function only works with raw (un-annotated) PGN files and **should be used with extreme caution**.

Here I demonstrate using it to parse my own personal PGNs (from [Lichess](https://lichess.org/)) and combining it with `plot_fen()` to visualise where I move pieces to as a heat map.

Parse the PGN file

```{r message=FALSE}

pgn_df <- pgn_to_df('tests/lichess_holmestorm_2021-01-03.pgn')

```

Visualise 

```{r message=FALSE, warning=FALSE, out.width="100%", fig.width=10}

library(ggplot2)

library(dplyr)

plot_fen(palette = c("white", "white"), show_coords = FALSE, border_col = 1)+

  fade_board(fade = 0.3)+

  ggnewscale::new_scale_fill()+

  geom_tile(data =

              pgn_df %>%

              filter(player == "holmestorm") %>%

              mutate(piece_moved = factor(piece_moved, levels = c("P", "B", "N", "R", "Q", "K"))) %>%

              count(colour, piece_moved, x, y) %>%

              group_by(colour, piece_moved) %>%

              mutate(t = sum(n),

                     p = 100 * (n/t)),

            aes(x, y, fill = p), alpha = 0.9)+

  facet_grid(colour ~ piece_moved)+

  scale_fill_viridis_c(option="viridis")+

  theme(legend.position = "bottom")+

  labs(title = "Where do I move my pieces to?",

       subtitle = "Facetted by piece [columns] and side (White/Black) [rows]",

       fill = "%",

       caption = "Data source: Lichess, Username: holmestorm")

```