snd_zones.R

library(jsonlite)
library(dplyr)
library(ggplot2)
library(scales)
library(png)
library(gganimate)

#set wd
setwd('C:/Users/JP/Documents/codstats/wwii_structured')
img <- readPNG('cwl-data/maps/ww2/ardennes_forest.png')
#make df to put output in
output <- data.frame()

location <- list.files(path = 'data', pattern = "structured")
for(j in 1:length(location)) {
  
  filenames <- list.files(path = paste('data/',location[j], sep = ""),pattern="*.json", full.names=TRUE)
  print(location[j]) # show when you start each new event
  
  
  for (i in 1:length(filenames)) {
    
    #read each json file in as list of lists
    data_json <- fromJSON(filenames[i], simplifyVector = T)
    # I filter out by mode,
    # but you can change this to whatever
    if(data_json$mode == "Search & Destroy" & data_json$map == "Ardennes Forest" & !is.null(nrow(data_json$events))){
      
      # get just spawns and deaths
      events <- (data_json$events)
      data <- subset(events, events$type == 'death')
      
      # make df of players and teams to match 
      team_rounds <- data.frame(player.team = rep(data_json$teams$name,each = data_json$rounds),
                                round = rep(seq(1,data_json$rounds),2),
                                homeaway = c(rep(c("home",'away'),length.out = data_json$rounds),rep(c("away",'home'),length.out = data_json$rounds)))
      #  win = c(data_json$teams$round_scores[[1]],data_json$teams$round_scores[[2]]))
      team_players <- data.frame(name = data_json$players$name, player.team = data_json$players$team, gun = data_json$players$fave_weapon,map=data_json$map) 
      
      data = do.call(cbind.data.frame, data)
      data = do.call(cbind.data.frame, data)
      data = do.call(cbind.data.frame, data)
      
      
      data<-merge(data, team_players, by.x ='data.attacker.id', by.y = 'name')
      data<-merge(data,team_players,by.x='data.id',by.y='name')
      data <- merge(data, team_rounds, by.x = c('player.team.x', 'round'),
                    by.y = c('player.team', 'round')) 
      
      if(data_json$map == "Ardennes Forest") {
        #docks
        zone1 = c(435,585)

      }
      if(data_json$map == "Ardennes Forest"){
        data$aAkill <- (data$homeaway=="home" & data$data.attacker.pos.y<=zone1[1])*1
        data$bAkill <- (data$homeaway=="home" & data$data.attacker.pos.y>=zone1[2])*1
        data$nAkill <- (data$homeaway=="home" & data$data.attacker.pos.y>zone1[1] & data$data.attacker.pos.y<zone1[2])*1
        
        data$aDkill <- (data$homeaway=="away" & data$data.attacker.pos.y<=zone1[1])*1
        data$bDkill <- (data$homeaway=="away" & data$data.attacker.pos.y>=zone1[2])*1
        data$nDkill <- (data$homeaway=="away" & data$data.attacker.pos.y>zone1[1] & data$data.attacker.pos.y<zone1[2])*1
        
        data$aAdeath <- (data$homeaway=="away" & data$data.pos.y<=zone1[1])*1
        data$bAdeath <- (data$homeaway=="away" & data$data.pos.y>=zone1[2])*1
        data$nAdeath <- (data$homeaway=="away" & data$data.pos.y>zone1[1] & data$data.attacker.pos.y<zone1[2])*1
        
        data$aDdeath <- (data$homeaway=="home" & data$data.pos.y<=zone1[1])*1
        data$bDdeath <- (data$homeaway=="home" & data$data.pos.y>=zone1[2])*1
        data$nDdeath <- (data$homeaway=="home" & data$data.pos.y>zone1[1] & data$data.attacker.pos.y<zone1[2])*1
      }
      
      if(('data.is_overtime' %in% colnames(data))==F) {
        data$data.is_overtime = 0}
      output<-rbind(output,data)
      
    }}}

h=dim(img)[1]
w=dim(img)[2]

gib1 <- subset(output,output$map.x == "Flak Tower" & (output$dzoneh==1 | output$dzonea==1))
ggplot(data=gib1) +
  annotation_custom(grid::rasterGrob(img, width=unit(1,"npc"), height=unit(1,"npc")), 0, w, 0,-h) +
  theme_bw() + theme(legend.position = 'none',axis.title = element_blank()) +
  coord_equal() + # To keep the aspect ratio of the image.
  scale_x_continuous(expand=c(0,0),limits=c(0,w)) +
  scale_y_reverse(expand=c(0,0),limits=c(h,0)) +
  geom_hline(yintercept=435,color="orange")+
  geom_hline(yintercept=585,color="orange")
  # geom_point(aes(data.attacker.pos.x,data.attacker.pos.y,color="red"))
  
  #geom_point(aes(data.attacker.pos.x,data.attacker.pos.y,color = as.factor(closerto))) +
  #geom_point(aes(data.pos.x,data.pos.y,color = as.factor(closerto)))
  #scale_color_manual(values=c("#CC6666", "#9999CC")) +
  #geom_point(aes(x = hill3[1], y = hill3[2]), shape = 17, size = 5, color = 'yellow') +
  #geom_point(aes(x = hill2[1], y = hill2[2]), shape = 17, size = 5, color = 'yellow') +
  # stat_bin2d(binwidth=3,aes(x,y,alpha=(..count..)^(1/2))) +
  # stat_binhex(aes(x=x, y=y, alpha=(..density..)^1), bins = 40) +
  # scale_fill_gradientn(colours=c( ('green'), ('yellow'),("red")),name = "Frequency") +
  # guides(alpha="none") +
# ggtitle(label = paste(team1, " setup on HP #", hpt, sep = ""))

stat_density2d(aes(x=data.attacker.pos.x,y=data.attacker.pos.y, fill=..level..,alpha=(..level..)),geom='polygon') +
  scale_fill_gradientn(colours=c('green','yellow',"red"),name = "Frequency") +
  guides(alpha="none")+
  ggtitle(label = "Flak Tower - Defensive Zone Kill Heat Map")

#dzone
kills<-output %>%
  filter(bDkill==1) %>%
  group_by(data.attacker.id) %>%
  summarise(kills=n())
deaths<-output %>%
  filter(bDdeath==1) %>%
  group_by(data.id) %>%
  summarise(deaths=n())
KD<-merge(kills,deaths, by.x=c("data.attacker.id"),by.y=c('data.id'))
KD$KD <- KD$kills/KD$deaths
KD$n<-KD$kills+KD$deaths
KD %>%
  filter(n>30)%>%
  arrange(desc(KD))%>%
  head()


kills<-output %>%
  filter(round != 11)%>%
  filter(bDkill==1) %>%
  group_by(player.team.x) %>%
  summarise(kills=n())
deaths<-output %>%
  filter(round != 11)%>%
  filter(bDdeath==1) %>%
  group_by(player.team.y) %>%
  summarise(deaths=n())
KD<-merge(kills,deaths, by.x=c("player.team.x"),by.y=c('player.team.y'))
KD$KD <- KD$kills/KD$deaths
KD$n<-KD$kills+KD$deaths
KD %>%
  filter(n>100)%>%
  arrange(desc(KD))%>%
  head()