library(ggplot2)
library(dplyr)
library(betfaiR)
arslei <- readRDS("vignette_two/arslei.RDS")
markets <- readRDS("vignette_two/marketIds.RDS")
winner <- readRDS("vignette_two/winner.RDS")
winner <- plyr::ldply(winner, .fun = function(i) {
    x <- plyr::ldply(i$runners, .fun = function(j) {
        j$basic
    })
    x$collectedAt <- i$collectedAt
    return(x)
})
winner <- winner %>%
    left_join(markets$winner[[1]]$runners)

arslei <- plyr::ldply(arslei, .fun = function(i) {
    x <- plyr::ldply(i$runners, .fun = function(j) {
        j$basic
    })
    x$collectedAt <- i$collectedAt
    return(x)
})
arslei <- arslei %>%
    left_join(markets$arslei[[1]]$runners)

winner %>%
    filter(collectedAt == min(collectedAt),
           runnerName %in% c("Arsenal", "Leicester", "Man City", "Tottenham")) %>%
    mutate(runnerName = factor(runnerName, levels = c("Arsenal", "Leicester", "Man City", "Tottenham")),
           prob = 1 / lastPriceTraded) %>%
    ggplot(aes(x = runnerName,
               y = prob)) +
        geom_bar(stat = "identity",
                 aes(fill = runnerName)) +
        scale_fill_manual(values = c("Leicester" = "#0053A0",
                                     "Arsenal" = "#EF0107",
                                     "Man City" = "#5DBFEB",
                                     "Tottenham" = "#001C58")) +
        labs(title = "Outright Market") +
        betfair_theme() +
        theme(
            legend.position = "none",
            axis.title.x = element_blank()
        )

arslei %>%
    ggplot(aes(x = collectedAt,
               y = 1 / lastPriceTraded)) +
        geom_line(aes(colour = factor(runnerName))) +
        labs(x = "time",
             y = "prob") +
        title_with_subtitle(title = "Arsenal vs Leicester",
                            subtitle = "minute by minute implied probability") +
        scale_colour_manual(values = betfair_palette) +
        betfair_theme() +
        theme(
            legend.title = element_blank()
        )