├── imgs ├── static_bars_demo.png ├── static_scatter_demo.png ├── static_heatmap_default_demo.png ├── trend_nations_battles_demo.png ├── animation_trend_heatmap_demo.gif └── static_pie_default_battles_demo.png ├── .gitignore ├── utils.R ├── main.R ├── time_trend.R ├── time_animation.R ├── README.md ├── static_plot.R └── LICENSE /imgs/static_bars_demo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ControlNet/wt-data-project.visualization/HEAD/imgs/static_bars_demo.png -------------------------------------------------------------------------------- /imgs/static_scatter_demo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ControlNet/wt-data-project.visualization/HEAD/imgs/static_scatter_demo.png -------------------------------------------------------------------------------- /imgs/static_heatmap_default_demo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ControlNet/wt-data-project.visualization/HEAD/imgs/static_heatmap_default_demo.png -------------------------------------------------------------------------------- /imgs/trend_nations_battles_demo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ControlNet/wt-data-project.visualization/HEAD/imgs/trend_nations_battles_demo.png -------------------------------------------------------------------------------- /imgs/animation_trend_heatmap_demo.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ControlNet/wt-data-project.visualization/HEAD/imgs/animation_trend_heatmap_demo.gif -------------------------------------------------------------------------------- /imgs/static_pie_default_battles_demo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ControlNet/wt-data-project.visualization/HEAD/imgs/static_pie_default_battles_demo.png -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # History files 2 | .Rhistory 3 | .Rapp.history 4 | 5 | # Session Data files 6 | .RData 7 | 8 | # User-specific files 9 | .Ruserdata 10 | 11 | # Example code in package build process 12 | *-Ex.R 13 | 14 | # Output files from R CMD build 15 | /*.tar.gz 16 | 17 | # Output files from R CMD check 18 | /*.Rcheck/ 19 | 20 | # RStudio files 21 | .Rproj.user/ 22 | 23 | # produced vignettes 24 | vignettes/*.html 25 | vignettes/*.pdf 26 | 27 | # OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3 28 | .httr-oauth 29 | 30 | # knitr and R markdown default cache directories 31 | *_cache/ 32 | /cache/ 33 | 34 | # Temporary files created by R markdown 35 | *.utf8.md 36 | *.knit.md 37 | 38 | # R Environment Variables 39 | .Renviron 40 | -------------------------------------------------------------------------------- /utils.R: -------------------------------------------------------------------------------- 1 | library(ggsci) 2 | 3 | cache.all.file.path <- function(mode) { 4 | paste0("data/", mode, "_ranks_all.csv") 5 | } 6 | cache.1.file.path <- function(mode) { 7 | paste0("data/", mode, "_ranks_1.csv") 8 | } 9 | cache.0.file.path <- function(mode) { 10 | paste0("data/", mode, "_ranks_0.csv") 11 | } 12 | joined.dir.path <- "data/joined" 13 | ts.dir.path <- "data/ts" 14 | wk.dir.path <- "data/wk" 15 | 16 | # material colors 17 | get_material_color <- function(color, n = 6) pal_material(color)(10)[n] 18 | blue <- get_material_color("blue") 19 | purple <- get_material_color("purple") 20 | red <- get_material_color("red") 21 | indigo <- get_material_color("indigo") 22 | green <- get_material_color("green") 23 | yellow <- get_material_color("yellow") 24 | gray <- get_material_color("grey") 25 | orange <- get_material_color("orange") 26 | brown <- get_material_color("brown") 27 | white <- "white" 28 | black <- "black" 29 | 30 | # Nation order 31 | nation_order <- c("USA", "Germany", "USSR", "Britain", "Japan", 32 | "France", "Italy", "China", "Sweden") 33 | -------------------------------------------------------------------------------- /main.R: -------------------------------------------------------------------------------- 1 | source("visualization/utils.R") 2 | source("visualization/static_plot.R") 3 | source("visualization/time_animation.R") 4 | source("visualization/time_trend.R") 5 | 6 | static.heatmap.default.ground_vehicles.win_rate() 7 | ggsave("visualization/imgs/static_heatmap_default_demo.png", width = 7, height = 8, dpi = 100) 8 | 9 | static.pie.default.battles() 10 | ggsave("visualization/imgs/static_pie_default_battles_demo.png", width = 7, height = 6.5, dpi = 100) 11 | 12 | trend.nations.battles(class.sample = "Ground_vehicles", y = "rb_battles_sum") 13 | ggsave("visualization/imgs/trend_nations_battles_demo.png", width = 7, height = 8, dpi = 100) 14 | 15 | static.scatter(date.sample = read.csv(cache.all.file.path("rb")) %>% .$date %>% unique %>% .[1], 16 | class.sample = "Ground_vehicles", 17 | x = "rb_ground_frags_per_death", y = "rb_win_rate", size = "rb_battles", 18 | x.limits = NULL, y.limits = NULL, colors = NULL) 19 | ggsave("visualization/imgs/static_scatter_demo.png", width = 7, height = 8, dpi = 100) 20 | 21 | static.bars(nation.sample = "USA", 22 | date.sample = read.csv(cache.all.file.path("rb")) %>% .$date %>% unique %>% .[1], 23 | class.sample = c("Aviation", "Ground_vehicles"), 24 | y = "rb_win_rate", y.limits = NULL) 25 | ggsave("visualization/imgs/static_bars_demo.png", width = 7, height = 8, dpi = 100) 26 | 27 | animation.trend.heatmap(class.sample = "Ground_vehicles", fill = "rb_win_rate", 28 | fill.limits = c(0, 100), 29 | colors = c(white, black, red, yellow, green, black, black), 30 | colors.pos = c(0, 0.05, 0.4, 0.5, 0.6, 0.95, 1.0)) %>% 31 | animation.render(width = 7, height = 8, dpi = 100, fps = 10) 32 | anim_save(filename = "visualization/imgs/animation_trend_heatmap_demo.gif") 33 | 34 | -------------------------------------------------------------------------------- /time_trend.R: -------------------------------------------------------------------------------- 1 | library(dplyr) 2 | library(data.table) 3 | library(ggplot2) 4 | source("visualization/utils.R") 5 | 6 | trend.nations <- function(mode = "rb", class.sample = "Ground_vehicles", 7 | y = "rb_win_rate", rb_br.sample = "9.7 ~ 10.7") { 8 | # read the data generated by function cache_br_flat_df in integration/concator.py 9 | data <- read.csv(cache.1.file.path(mode)) %>% as.data.table 10 | 11 | data.sample <- data %>% 12 | filter(rb_br == rb_br.sample) %>% 13 | filter(cls == class.sample) %>% 14 | mutate(date = date %>% as.Date.factor) %>% 15 | mutate(nation = nation %>% factor( 16 | levels = c("USA", "Germany", "USSR", "Britain", "Japan", "China", "Italy", "France", "Sweden")) 17 | ) 18 | 19 | data.sample %>% ggplot + 20 | geom_line(aes_string(x = "date", y = y, color = "nation"), size = 1.2) + 21 | scale_x_date(date_labels = "%Y/%m") + 22 | labs(x = "Date", colors = "Nation", 23 | caption = "Repo: ControlNet/wt-data-project.visualization, Source: Thunderskill") + 24 | ggtitle(paste(y, "Trend for", class.sample, rb_br.sample, sep = " ")) 25 | } 26 | 27 | trend.nations.battles <- function(mode="rb", class.sample = "Ground_vehicles", y = "rb_battles_sum") { 28 | # read the data generated by function cache_br_flat_df in integration/concator.py 29 | data <- read.csv(cache.all.file.path(mode)) %>% as.data.table 30 | 31 | data.sample <- data %>% 32 | filter(rb_br == "1.0 ~ 10.7") %>% 33 | filter(cls == class.sample) %>% 34 | mutate(date = date %>% as.Date.factor) %>% 35 | mutate(nation = nation %>% factor( 36 | levels = c("Germany", "USSR", "USA", "Sweden", "Britain", "Italy", "France", "Japan", "China")) 37 | ) 38 | 39 | data.sample %>% ggplot + 40 | geom_area(aes_string(x = "date", y = y, fill = "nation"), color = "black") + 41 | scale_x_date(date_labels = "%Y/%m") + 42 | labs(x = "Date", fill = "Nation", 43 | caption = "Repo: ControlNet/wt-data-project.visualization, Source: Thunderskill") + 44 | scale_fill_manual(values = c(red, blue, green, gray, purple, indigo, yellow, orange, brown)) + 45 | ggtitle(paste("Battles Trend for", class.sample, sep = " ")) 46 | } 47 | 48 | trend.vehicles <- function(vehicles, y = "rb_win_rate", date.after = NULL) { 49 | files.filter <- list.files(ts.dir.path) %>% (function(file) { 50 | if (is.null(date.after)) TRUE 51 | else substr(file, 3, 12) > date.after 52 | }) 53 | 54 | file.paths <- paste0(ts.dir.path, "/", list.files(ts.dir.path)[files.filter]) 55 | data <- file.paths %>% lapply(FUN = function(file) { 56 | read.csv(file) %>% 57 | select(name, y) %>% 58 | filter(name %in% vehicles) %>% 59 | mutate(date = file %>% as.Date(format = paste0(ts.dir.path, "/ts%Y-%m-%d.csv"))) 60 | }) %>% Reduce(f = rbind) 61 | 62 | data %>% ggplot + 63 | geom_line(aes_string(x = "date", y = y, color = "name")) + 64 | ggtitle("Trend of Vehicles") + 65 | scale_x_date(date_labels = "%Y/%m") + 66 | labs(x = "Date", color = "Vehicle", 67 | caption = "Repo: ControlNet/wt-data-project.visualization, Source: Thunderskill") 68 | } 69 | -------------------------------------------------------------------------------- /time_animation.R: -------------------------------------------------------------------------------- 1 | library(dplyr) 2 | library(data.table) 3 | library(ggplot2) 4 | library(gganimate) 5 | require(gifski) 6 | source("visualization/utils.R") 7 | 8 | animation.render <- function(plot, width = 7, height = 8, dpi = 100, fps = 10) 9 | animate(plot, renderer = gifski_renderer(), width = width, height = height, fps = fps, res = dpi, units = "in") 10 | 11 | animation.trend.heatmap <- function(class.sample = "Ground_vehicles", fill = "rb_win_rate", 12 | fill.limits = c(0, 100), 13 | mode = "rb", 14 | colors = c(white, black, red, yellow, green, black, black), 15 | colors.pos = c(0, 0.05, 0.4, 0.5, 0.6, 0.95, 1.0)) { 16 | # read the data generated by function cache_br_flat_df in integration/concator.py 17 | data <- read.csv(cache.1.file.path(mode)) %>% 18 | as.data.table %>% 19 | mutate(date = date %>% as.Date.factor) 20 | # filter the data 21 | data.sample <- data %>% 22 | filter(cls == class.sample) %>% 23 | mutate(rb_lower_br = rb_lower_br %>% as.factor) 24 | # plot 25 | data.sample %>% ggplot + 26 | geom_tile(aes_string(x = "nation", y = "rb_lower_br", fill = fill), color = "black") + 27 | scale_y_discrete(labels = data.sample$rb_br) + 28 | scale_fill_gradientn(colors = colors, values = colors.pos, limits = fill.limits) + 29 | scale_x_discrete(limits = c("USA", "Germany", "USSR", "Britain", "Japan", 30 | "France", "Italy", "China", "Sweden")) + 31 | ggtitle(paste("Heatmap of", fill, "for", class.sample, "{frame_time}", sep = " ")) + 32 | labs(x = "Nation", y = "Battle Rating", 33 | caption = "Repo: ControlNet/wt-data-project.visualization, Source: Thunderskill") + 34 | transition_time(date) 35 | } 36 | 37 | animation.trend.scatter <- function(class.sample = "Ground_vehicles", 38 | x = "rb_ground_frags_per_death", y = "rb_win_rate", size = "rb_battles", 39 | x.limits = NULL, y.limits = NULL, colors = NULL, 40 | x.log = FALSE, y.log = FALSE, size.log = FALSE, size.threshold = 0) { 41 | # TODO: size threshold not implemented yet 42 | # read all ts data 43 | file.paths <- paste0(joined.dir.path, "/", list.files(joined.dir.path)) 44 | data <- file.paths %>% 45 | lapply(FUN = function(file) { 46 | data.sample <- read.csv(file) %>% 47 | filter(cls == class.sample) %>% 48 | select(x, y, nation, size) %>% 49 | mutate(date = file %>% 50 | as.Date(format = paste0(joined.dir.path, "/%Y-%m-%d.csv"))) 51 | # filter the vehicle with few battles 52 | data.sample <- data.sample[data.sample[size] > size.threshold,] 53 | data.sample[complete.cases(data.sample),] 54 | }) %>% 55 | Reduce(f = rbind) 56 | 57 | # plot 58 | if (size.log) size <- paste0("log10(", size, ")") 59 | p <- data %>% ggplot + 60 | geom_point(aes_string(x = x, y = y, color = "nation", size = size)) + 61 | ggtitle(paste("Scatter for", class.sample, "{frame_time}", sep = " ")) + 62 | labs(caption = "Repo: ControlNet/wt-data-project.visualization, Source: Thunderskill") 63 | # modify some attributes 64 | if (x.log) p <- p + scale_x_log10() 65 | if (y.log) p <- p + scale_y_log10() 66 | if (!is.null(x.limits)) p <- p + xlim(x.limits) 67 | if (!is.null(y.limits)) p <- p + ylim(y.limits) 68 | if (!is.null(colors)) p <- p + scale_color_manual(values = colors) 69 | # add time axis 70 | p + transition_time(date) 71 | } 72 | 73 | 74 | animation.trend.bars <- function(nation.sample, 75 | class.sample = c("Aviation", "Ground_vehicles"), 76 | mode = "rb", 77 | y = "rb_win_rate", y.limits = c(0, 100)) { 78 | # read data 79 | data <- read.csv(cache.1.file.path(mode)) %>% 80 | as.data.table %>% 81 | mutate(date = date %>% as.Date.factor) 82 | data <- data %>% 83 | filter(nation == nation.sample) %>% 84 | filter(cls %in% class.sample) 85 | 86 | # plot 87 | p <- ggplot(data) + 88 | geom_bar(aes_string(x = "rb_br", y = y, fill = "cls"), stat = "identity", position = position_dodge()) + 89 | coord_flip(ylim = y.limits) + 90 | ggtitle(paste("Bar Chart for", paste(class.sample, collapse = " and "), 91 | "of", nation.sample, "{frame_time}", sep = " ")) + 92 | labs(caption = "Repo: ControlNet/wt-data-project.visualization, Source: Thunderskill") 93 | 94 | p + transition_time(date) 95 | } 96 | 97 | 98 | animation.trend.histogram <- function(x = "rb_repair", x.limits = c(0, 30000), bins = 100, facet=TRUE) { 99 | # read data 100 | data <- paste0(wk.dir.path, "/", list.files(wk.dir.path)) %>% 101 | .[. > paste0(wk.dir.path, "/", "wk2020-03-23")] %>% 102 | lapply(FUN = function(file) { 103 | read.csv(file) %>% 104 | select(x, "cls") %>% 105 | mutate(date = file %>% 106 | as.Date(format = paste0(wk.dir.path, "/wk%Y-%m-%d.csv"))) 107 | }) %>% 108 | Reduce(f = rbind) %>% 109 | .[!is.na(.[y]),] 110 | 111 | # plot 112 | p <- ggplot(data) + 113 | geom_histogram(aes_string(x = x, fill = "cls"), bins = bins, color = black, size = 0.2) + 114 | xlim(x.limits) + 115 | labs(y = "Counts", caption = "Repo: ControlNet/wt-data-project.visualization, Source: Thunderskill", 116 | title = paste("Histogram for", x, "{frame_time}", sep = " ")) 117 | 118 | if (facet) p <- p + facet_wrap(~cls) 119 | 120 | p + transition_time(date) 121 | } 122 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # WT-DATA-PROJECT.VISUALIZATION 2 | This repo is the visualization part of wt-data-project. 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 16 | 17 | 18 | 19 | 25 | 26 | 27 | 28 | 33 | 34 |
RepositoryInfo
wt-data-project.data 12 | 13 | 14 | 15 |
wt-data-project.web 20 | 21 | 22 | 23 | 24 |
wt-data-project.visualization 29 | 30 | 31 | 32 |
35 | 36 | ## Data 37 | The data is in this [repo](https://github.com/ControlNet/wt-data-project.data). 38 | 39 | To use this visualization repo, you need create a directory like this. The `data` directory contains everything in 40 | the `wt-data-project.data` repo, and the `visualization` directory contains everything in this repo. 41 | 42 | ``` 43 | wt-data-project (as working directory) 44 | ├─data 45 | │ ├─joined 46 | │ ├─ts 47 | │ └─wk 48 | └─visualization 49 | ``` 50 | 51 | ## Web 52 | A web-based visualization [repo](https://github.com/ControlNet/wt-data-project.web) is in WIP. 53 | 54 | ### You can check this in **[https://wt.controlnet.space](https://wt.controlnet.space)**. 55 | 56 | ## Requirements 57 | This repo is written by R 4.0.2. 58 | Please [download](https://cran.r-project.org/bin/windows/base/old/4.0.2/) R interpreter to use. 59 | 60 | Please use code below to install 3rd-party packages. 61 | ```r 62 | install.packages("") 63 | ``` 64 | * dplyr 65 | * reshape2 66 | * ggplot2 67 | * data.table 68 | * gganimate 69 | * gifski 70 | * ggsci 71 | 72 | ## Example 73 | 74 | Please use `main.R` to run functions below. 75 | ```r 76 | source("visualization/utils.R") 77 | source("visualization/static_plot.R") 78 | source("visualization/time_animation.R") 79 | source("visualization/time_trend.R") 80 | 81 | # add everything you want 82 | # for example 83 | static.heatmap.default.ground_vehicles.win_rate() 84 | ``` 85 | 86 | There are some default functions for easy use. 87 | 88 | **Display the win rates/battles of ground vehicles/aviation for each BR range and nation.** 89 | ```r 90 | static.heatmap.default.ground_vehicles.win_rate() 91 | static.heatmap.default.ground_vehicles.battles() 92 | static.heatmap.default.aviation.win_rate() 93 | static.heatmap.default.aviation.battles() 94 | ``` 95 | ![static_heatmap_default_demo](https://github.com/ControlNet/wt-data-project.visualization/blob/master/imgs/static_heatmap_default_demo.png) 96 | 97 | **Display a pie chart of the battle counts for each nation** 98 | ```r 99 | static.pie.default.battles() 100 | ``` 101 | ![static_pie_default_battles_demo](https://github.com/ControlNet/wt-data-project.visualization/blob/master/imgs/static_pie_default_battles_demo.png) 102 | 103 | Except the default functions, there are more functions you can use for visualizations with specified arguments. 104 | 105 | For example, you can visualize the trend of battles counts with the code below. 106 | ```r 107 | trend.nations.battles(class.sample = "Ground_vehicles", y = "rb_battles_sum") 108 | ``` 109 | ![trend_nations_battles_demo](https://github.com/ControlNet/wt-data-project.visualization/blob/master/imgs/trend_nations_battles_demo.png) 110 | 111 | Also, you can plot each vehicle as a scatter. 112 | ```r 113 | static.scatter(date.sample = "2020-08-13", class.sample = "Ground_vehicles", 114 | x = "rb_ground_frags_per_death", y = "rb_win_rate", size = "rb_battles", 115 | x.limits = NULL, y.limits = NULL, colors = NULL) 116 | ``` 117 | ![static_scatter_demo](https://github.com/ControlNet/wt-data-project.visualization/blob/master/imgs/static_scatter_demo.png) 118 | 119 | With the code below, it is a bar chart for a nation in one specific date. 120 | ```r 121 | static.bars(nation.sample = "USA", 122 | date.sample = "2020-08-13", 123 | class.sample = c("Aviation", "Ground_vehicles"), 124 | y = "rb_win_rate", y.limits = NULL) 125 | ``` 126 | ![static_bars_demo](https://github.com/ControlNet/wt-data-project.visualization/blob/master/imgs/static_bars_demo.png) 127 | 128 | Also, you can make gif animation with these codes below. 129 | ```r 130 | animation.trend.heatmap(class.sample = "Ground_vehicles", fill = "rb_win_rate", 131 | fill.limits = c(0, 100), 132 | colors = c(white, black, red, yellow, green, black, black), 133 | colors.pos = c(0, 0.05, 0.4, 0.5, 0.6, 0.95, 1.0)) %>% animation.render 134 | 135 | # if you need save as a file 136 | anim_save(filename = "out.gif") 137 | ``` 138 | ![animation_trend_heatmap_demo](https://github.com/ControlNet/wt-data-project.visualization/blob/master/imgs/animation_trend_heatmap_demo.gif) 139 | 140 | -------------------------------------------------------------------------------- /static_plot.R: -------------------------------------------------------------------------------- 1 | library(dplyr) 2 | library(ggplot2) 3 | library(reshape2) 4 | source("visualization/utils.R") 5 | 6 | static.heatmap <- function(date.sample = data$date %>% unique %>% .[1], 7 | date.compare = data$date %>% unique %>% .[3], 8 | class.sample = "Ground_vehicles", 9 | mode = "rb", 10 | fill = "rb_win_rate", 11 | fill.limits = c(0, 100), 12 | fill.log = FALSE, 13 | colors = c(white, black, red, yellow, green, black, black), 14 | colors.pos = c(0, 0.05, 0.4, 0.5, 0.6, 0.95, 1.0)) { 15 | # read the data generated by function cache_br_flat_df in stat_utils/concator.py 16 | data <- read.csv(cache.1.file.path(mode)) 17 | # filter the data 18 | data.sample <- eval(parse(text = paste0("data %>% 19 | filter(cls == class.sample) %>% 20 | mutate(", mode, "_lower_br = ", mode, "_lower_br %>% as.factor)"))) 21 | # select two date for compare 22 | data.now <- data.sample %>% filter(date == date.sample) 23 | 24 | # calculate trend 25 | if (!is.null(date.compare)) { 26 | data.before <- data.sample %>% filter(date == date.compare) 27 | # calculate trend 28 | data.trend <- eval(parse(text = paste0("data.now %>% 29 | select(nation, paste0(mode, \"_lower_br\"), fill) %>% 30 | merge(data.before %>% select(nation, paste0(mode, \"_lower_br\"), fill), 31 | by = c(\"nation\", paste0(mode, \"_lower_br\")), all.x = TRUE) %>% 32 | mutate(trend.up = .[, 3] > .[, 4]) %>% 33 | mutate(trend.down = .[, 3] < .[, 4]) %>% 34 | mutate(x = match(nation, nation_order), 35 | y = match(", mode, "_lower_br, data.now$", mode, "_lower_br %>% unique))"))) 36 | 37 | data.trend.up <- data.trend %>% filter(trend.up) %>% select(x, y) 38 | data.trend.down <- data.trend %>% 39 | filter(trend.down) %>% 40 | select(x, y) 41 | } 42 | 43 | if (fill.log) 44 | fill <- paste0("log10(", fill, ")") 45 | 46 | # plot 47 | p <- data.now %>% ggplot + 48 | geom_tile(aes_string(x = "nation", y = paste0(mode, "_lower_br"), fill = fill), color = "black") + 49 | scale_fill_gradientn(colors = colors, values = colors.pos, limits = fill.limits) + 50 | scale_y_discrete(labels = data.now[paste0(mode, "_br")] %>% 51 | unique %>% 52 | unlist %>% 53 | as.character) + 54 | scale_x_discrete(limits = nation_order) + 55 | ggtitle(paste("Heatmap of", fill, "for", class.sample, date.sample, sep = " ")) + 56 | labs(x = "Nation", y = "Battle Rating", 57 | caption = "Repo: ControlNet/wt-data-project.visualization, Source: Thunderskill") 58 | 59 | if (!is.null(date.compare)) { 60 | p + 61 | annotate("point", x = data.trend.up$x, y = data.trend.up$y, shape = 24, fill = green, size = 1.5) + 62 | annotate("point", x = data.trend.down$x, y = data.trend.down$y, shape = 25, fill = red, size = 1.5) 63 | } else p 64 | } 65 | 66 | static.heatmap.default.ground_vehicles.win_rate <- function() static.heatmap() 67 | 68 | static.heatmap.default.ground_vehicles.battles <- function() 69 | static.heatmap(fill = "rb_battles_sum", fill.limits = c(2.5, 5.5), fill.log = TRUE, 70 | class.sample = "Ground_vehicles", colors.pos = c(0, 0.01, 0.4, 0.5, 0.6, 0.99, 1.0)) 71 | 72 | static.heatmap.default.aviation.win_rate <- function() 73 | static.heatmap(class.sample = "Aviation", colors.pos = c(0, 0.01, 0.5, 0.6, 0.7, 0.99, 1.0)) 74 | 75 | static.heatmap.default.aviation.battles <- function() 76 | static.heatmap(fill = "rb_battles_sum", fill.limits = c(2.5, 5.5), fill.log = TRUE, 77 | class.sample = "Aviation", colors.pos = c(0, 0.01, 0.4, 0.5, 0.6, 0.99, 1.0)) 78 | 79 | static.scatter <- function(date.sample, class.sample = "Ground_vehicles", 80 | x = "rb_ground_frags_per_death", y = "rb_win_rate", size = "rb_battles", 81 | x.limits = NULL, y.limits = NULL, colors = NULL, threshold = 0) { 82 | # read the ts data with specified date 83 | data <- paste0(joined.dir.path, "/", date.sample, ".csv") %>% read.csv 84 | # filter the class 85 | data.sample <- data %>% filter(cls == class.sample) 86 | # filter the vehicle with few battles 87 | data.sample <- data.sample[data.sample[size] > threshold,] 88 | 89 | # plot 90 | p <- data.sample %>% ggplot + 91 | geom_point(aes_string(x = x, y = y, color = "nation", size = size)) + 92 | scale_x_log10() + 93 | ggtitle(paste("The scatter of vehicles in", date.sample, sep = " ")) + 94 | labs(caption = "Repo: ControlNet/wt-data-project.visualization, Source: Thunderskill") 95 | if (!is.null(x.limits)) p <- p + xlim(x.limits) 96 | if (!is.null(y.limits)) p <- p + ylim(y.limits) 97 | if (!is.null(colors)) p <- p + scale_color_manual(values = colors) 98 | p 99 | } 100 | 101 | static.bars <- function(nation.sample, 102 | date.sample = data$date %>% unique %>% .[1], 103 | class.sample = c("Aviation", "Ground_vehicles"), 104 | y = "rb_win_rate", y.limits = NULL, mode = "rb") { 105 | # read data 106 | data <- read.csv(cache.1.file.path(mode)) 107 | data <- data %>% 108 | mutate(rb_lower_br = rb_lower_br %>% as.factor) %>% 109 | filter(date == date.sample) %>% 110 | filter(nation == nation.sample) %>% 111 | filter(cls %in% class.sample) 112 | 113 | # plot 114 | p <- data %>% ggplot + 115 | geom_bar(aes_string(x = "rb_lower_br", y = y, fill = "cls"), stat = "identity", position = position_dodge()) + 116 | coord_flip(ylim = y.limits) + 117 | scale_x_discrete(labels = data$rb_br) + 118 | ggtitle(paste("Bar Chart for", paste(class.sample, collapse = " and "), 119 | "of", nation.sample, date.sample, sep = " ")) + 120 | labs(caption = "Repo: ControlNet/wt-data-project.visualization, Source: Thunderskill", x = "Battle Rating") 121 | p 122 | } 123 | 124 | static.bars.modes.battles <- function(date.sample = NULL, 125 | class.sample = c("Aviation", "Ground_vehicles"), 126 | y.limits = NULL) { 127 | # read joined data 128 | if (is.null(date.sample)) { 129 | date.sample <- cache.1.file.path(mode) %>% 130 | read.csv %>% 131 | .$date %>% 132 | unique %>% 133 | .[1] 134 | } 135 | 136 | data <- paste0(joined.dir.path, "/", date.sample, ".csv") %>% read.csv 137 | data <- data %>% 138 | filter(cls %in% class.sample) 139 | 140 | # remove NA values 141 | for (col in c("ab_battles", "rb_battles", "sb_battles")) { 142 | data[is.na(data[col]),][col] <- 0 143 | } 144 | 145 | data.group <- data %>% 146 | select(nation, ab_battles, rb_battles, sb_battles) %>% 147 | group_by(nation) %>% 148 | summarise(ab = sum(ab_battles), 149 | rb = sum(rb_battles), 150 | sb = sum(sb_battles)) %>% 151 | mutate(nation = nation %>% factor( 152 | levels = nation_order) 153 | ) 154 | 155 | data.group %>% 156 | melt(id.vars = "nation") %>% 157 | ggplot + 158 | geom_bar(aes(fill = nation, y = value, x = variable), position = "stack", stat = "identity") + 159 | labs(title = paste("Stacked Bar Chart for Battles of", paste(class.sample, collapse = " and "), sep = " "), 160 | caption = "Repo: ControlNet/wt-data-project.visualization, Source: Thunderskill", 161 | x = "Mode", 162 | y = "Battles", 163 | fill = "Nation" 164 | ) + 165 | scale_fill_manual(values = c(red, blue, green, gray, purple, indigo, yellow, orange, brown)) + 166 | scale_x_discrete(labels = c("AB", "RB", "SB")) 167 | 168 | } 169 | 170 | static.pie.battles <- function(date.sample, 171 | class.sample = c("Aviation", "Ground_vehicles"), 172 | mode = "rb", 173 | colors = NULL) { 174 | # read joined data 175 | data <- paste0(joined.dir.path, "/", date.sample, ".csv") %>% read.csv 176 | data <- data %>% 177 | filter(cls %in% class.sample) 178 | 179 | battle.colname <- paste0(mode, "_battles") 180 | battle.sum.colname <- paste0(battle.colname, "_sum") 181 | # remove NA values 182 | data[is.na(data[battle.colname]),][battle.colname] <- 0 183 | # group and calculate the battles sum for each nation 184 | data.nation <- eval(parse(text = paste0("data %>% 185 | group_by(nation) %>% 186 | summarise(!!battle.sum.colname := sum(", battle.colname, "))"))) 187 | 188 | # plot 189 | p <- data.nation %>% ggplot + 190 | geom_bar(aes_string(x = "\"\"", y = battle.sum.colname, fill = "nation"), stat = "identity") + 191 | coord_polar("y", start = 0) + 192 | labs(title = paste("Pie Chart for", toupper(mode), "Battles of", paste(class.sample, collapse = " and "), 193 | "in", date.sample, sep = " "), 194 | caption = "Repo: ControlNet/wt-data-project.visualization, Source: Thunderskill", 195 | x = NULL, 196 | y = "Battles", 197 | fill = "Nation" 198 | ) + 199 | theme(axis.text.y = element_blank(), axis.line.y = element_blank(), axis.ticks.y = element_blank()) 200 | 201 | if (!is.null(colors)) p <- p + scale_fill_manual(values = colors) 202 | p 203 | } 204 | 205 | static.pie.default.battles <- function(mode = "rb") { 206 | # read the nearest date 207 | data <- read.csv(cache.1.file.path(mode)) 208 | date.sample <- data$date %>% unique %>% .[1] 209 | # plot pie chart 210 | static.pie.battles(date.sample, mode = mode, 211 | colors = c(blue, orange, indigo, black, green, purple, yellow, brown, red)) 212 | } -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU AFFERO GENERAL PUBLIC LICENSE 2 | Version 3, 19 November 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU Affero General Public License is a free, copyleft license for 11 | software and other kinds of works, specifically designed to ensure 12 | cooperation with the community in the case of network server software. 13 | 14 | The licenses for most software and other practical works are designed 15 | to take away your freedom to share and change the works. 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To "grant" such a patent license to a 484 | party means to make such an agreement or commitment not to enforce a 485 | patent against the party. 486 | 487 | If you convey a covered work, knowingly relying on a patent license, 488 | and the Corresponding Source of the work is not available for anyone 489 | to copy, free of charge and under the terms of this License, through a 490 | publicly available network server or other readily accessible means, 491 | then you must either (1) cause the Corresponding Source to be so 492 | available, or (2) arrange to deprive yourself of the benefit of the 493 | patent license for this particular work, or (3) arrange, in a manner 494 | consistent with the requirements of this License, to extend the patent 495 | license to downstream recipients. "Knowingly relying" means you have 496 | actual knowledge that, but for the patent license, your conveying the 497 | covered work in a country, or your recipient's use of the covered work 498 | in a country, would infringe one or more identifiable patents in that 499 | country that you have reason to believe are valid. 500 | 501 | If, pursuant to or in connection with a single transaction or 502 | arrangement, you convey, or propagate by procuring conveyance of, a 503 | covered work, and grant a patent license to some of the parties 504 | receiving the covered work authorizing them to use, propagate, modify 505 | or convey a specific copy of the covered work, then the patent license 506 | you grant is automatically extended to all recipients of the covered 507 | work and works based on it. 508 | 509 | A patent license is "discriminatory" if it does not include within 510 | the scope of its coverage, prohibits the exercise of, or is 511 | conditioned on the non-exercise of one or more of the rights that are 512 | specifically granted under this License. You may not convey a covered 513 | work if you are a party to an arrangement with a third party that is 514 | in the business of distributing software, under which you make payment 515 | to the third party based on the extent of your activity of conveying 516 | the work, and under which the third party grants, to any of the 517 | parties who would receive the covered work from you, a discriminatory 518 | patent license (a) in connection with copies of the covered work 519 | conveyed by you (or copies made from those copies), or (b) primarily 520 | for and in connection with specific products or compilations that 521 | contain the covered work, unless you entered into that arrangement, 522 | or that patent license was granted, prior to 28 March 2007. 523 | 524 | Nothing in this License shall be construed as excluding or limiting 525 | any implied license or other defenses to infringement that may 526 | otherwise be available to you under applicable patent law. 527 | 528 | 12. No Surrender of Others' Freedom. 529 | 530 | If conditions are imposed on you (whether by court order, agreement or 531 | otherwise) that contradict the conditions of this License, they do not 532 | excuse you from the conditions of this License. If you cannot convey a 533 | covered work so as to satisfy simultaneously your obligations under this 534 | License and any other pertinent obligations, then as a consequence you may 535 | not convey it at all. For example, if you agree to terms that obligate you 536 | to collect a royalty for further conveying from those to whom you convey 537 | the Program, the only way you could satisfy both those terms and this 538 | License would be to refrain entirely from conveying the Program. 539 | 540 | 13. Remote Network Interaction; Use with the GNU General Public License. 541 | 542 | Notwithstanding any other provision of this License, if you modify the 543 | Program, your modified version must prominently offer all users 544 | interacting with it remotely through a computer network (if your version 545 | supports such interaction) an opportunity to receive the Corresponding 546 | Source of your version by providing access to the Corresponding Source 547 | from a network server at no charge, through some standard or customary 548 | means of facilitating copying of software. This Corresponding Source 549 | shall include the Corresponding Source for any work covered by version 3 550 | of the GNU General Public License that is incorporated pursuant to the 551 | following paragraph. 552 | 553 | Notwithstanding any other provision of this License, you have 554 | permission to link or combine any covered work with a work licensed 555 | under version 3 of the GNU General Public License into a single 556 | combined work, and to convey the resulting work. The terms of this 557 | License will continue to apply to the part which is the covered work, 558 | but the work with which it is combined will remain governed by version 559 | 3 of the GNU General Public License. 560 | 561 | 14. Revised Versions of this License. 562 | 563 | The Free Software Foundation may publish revised and/or new versions of 564 | the GNU Affero General Public License from time to time. Such new versions 565 | will be similar in spirit to the present version, but may differ in detail to 566 | address new problems or concerns. 567 | 568 | Each version is given a distinguishing version number. If the 569 | Program specifies that a certain numbered version of the GNU Affero General 570 | Public License "or any later version" applies to it, you have the 571 | option of following the terms and conditions either of that numbered 572 | version or of any later version published by the Free Software 573 | Foundation. If the Program does not specify a version number of the 574 | GNU Affero General Public License, you may choose any version ever published 575 | by the Free Software Foundation. 576 | 577 | If the Program specifies that a proxy can decide which future 578 | versions of the GNU Affero General Public License can be used, that proxy's 579 | public statement of acceptance of a version permanently authorizes you 580 | to choose that version for the Program. 581 | 582 | Later license versions may give you additional or different 583 | permissions. However, no additional obligations are imposed on any 584 | author or copyright holder as a result of your choosing to follow a 585 | later version. 586 | 587 | 15. Disclaimer of Warranty. 588 | 589 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY 590 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT 591 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY 592 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, 593 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 594 | PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM 595 | IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF 596 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION. 597 | 598 | 16. Limitation of Liability. 599 | 600 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING 601 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS 602 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY 603 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE 604 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF 605 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD 606 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), 607 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF 608 | SUCH DAMAGES. 609 | 610 | 17. Interpretation of Sections 15 and 16. 611 | 612 | If the disclaimer of warranty and limitation of liability provided 613 | above cannot be given local legal effect according to their terms, 614 | reviewing courts shall apply local law that most closely approximates 615 | an absolute waiver of all civil liability in connection with the 616 | Program, unless a warranty or assumption of liability accompanies a 617 | copy of the Program in return for a fee. 618 | 619 | END OF TERMS AND CONDITIONS 620 | 621 | How to Apply These Terms to Your New Programs 622 | 623 | If you develop a new program, and you want it to be of the greatest 624 | possible use to the public, the best way to achieve this is to make it 625 | free software which everyone can redistribute and change under these terms. 626 | 627 | To do so, attach the following notices to the program. It is safest 628 | to attach them to the start of each source file to most effectively 629 | state the exclusion of warranty; and each file should have at least 630 | the "copyright" line and a pointer to where the full notice is found. 631 | 632 | 633 | Copyright (C) 634 | 635 | This program is free software: you can redistribute it and/or modify 636 | it under the terms of the GNU Affero General Public License as published by 637 | the Free Software Foundation, either version 3 of the License, or 638 | (at your option) any later version. 639 | 640 | This program is distributed in the hope that it will be useful, 641 | but WITHOUT ANY WARRANTY; without even the implied warranty of 642 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 643 | GNU Affero General Public License for more details. 644 | 645 | You should have received a copy of the GNU Affero General Public License 646 | along with this program. If not, see . 647 | 648 | Also add information on how to contact you by electronic and paper mail. 649 | 650 | If your software can interact with users remotely through a computer 651 | network, you should also make sure that it provides a way for users to 652 | get its source. For example, if your program is a web application, its 653 | interface could display a "Source" link that leads users to an archive 654 | of the code. There are many ways you could offer source, and different 655 | solutions will be better for different programs; see section 13 for the 656 | specific requirements. 657 | 658 | You should also get your employer (if you work as a programmer) or school, 659 | if any, to sign a "copyright disclaimer" for the program, if necessary. 660 | For more information on this, and how to apply and follow the GNU AGPL, see 661 | . 662 | --------------------------------------------------------------------------------