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prog_funs.R
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spr_heat_prog_get_events <- function(con,date){
evs <- dplyr::tbl(src = con,"v_sprint_heats") %>%
filter(date == local(date)) %>%
select(eventid,primary_tag,location,site,gender,length,tech) %>%
collect() %>%
distinct()
evs
}
spr_heat_prog_data <- function(con,ev_info){
if (is.null(ev_info) || length(ev_info) == 0){
return(NULL)
}
race_info <- tbl(src = con,"v_event") %>%
filter(eventid == local(ev_info$eventid)) %>%
select(eventid,date,season,location,tech,length,gender) %>%
collect()
spr_qual <- tbl(src = con,"v_sprint") %>%
filter(eventid == local(ev_info$eventid)) %>%
collect() %>%
select(eventid,name,nation,time,rank = rankqual) %>%
mutate(heat = "qual",
heat = factor(heat,
levels = c("qual","quarter","semi","final"),
labels = c("Qual","QF","SF","Final")),
qf = NA_integer_,
sf = NA_integer_,
fn = NA_integer_)
spr_heats_all <- tbl(src = con,"v_sprint_heats") %>%
filter(eventid == local(ev_info$eventid)) %>%
collect()
spr_heats <- spr_heats_all %>%
select(eventid,name,nation,
time = heat_time,
rank = heat_rank,qf,sf,fn,heat,ll) %>%
mutate(heat = case_when(substr(heat,1,1) == "1" ~ "quarter",
substr(heat,1,1) == "2" ~ "semi",
substr(heat,1,1) == "3" ~ "final"),
heat = factor(heat,
levels = c("qual","quarter","semi","final"),
labels = c("Qual","QF","SF","Final")))
lls <- spr_heats_all %>%
filter(ll == "Y") %>%
select(name,qf,sf) %>%
tidyr::pivot_longer(cols = c("qf","sf"),names_to = "heat") %>%
filter(!is.na(value)) %>%
mutate(heat = toupper(heat)) %>%
group_by(name) %>%
summarise(ll_heat = paste(heat,collapse = ",")) %>%
mutate(ll_name = paste(name,paste0("(LL: ",ll_heat,")"))) %>%
select(name,ll_name)
return(list(race_info = race_info,
spr_qual = spr_qual,
spr_heats = spr_heats,
lls = lls))
}
spr_heat_prog_plot <- function(race_data,time_scale,clip = NULL){
if (is.null(race_data) || length(race_data) == 0){
return(NULL)
}
race_info <- race_data$race_info
spr_qual <- race_data$spr_qual
spr_heats <- race_data$spr_heats
lls <- race_data$lls
data_clean <- bind_rows(spr_qual,spr_heats) %>%
mutate(heat_lab = as.character(coalesce(qf,sf)),
heat_lab = if_else(heat == "Qual",NA_character_,heat_lab))
data_clean <- left_join(data_clean,
lls,by = "name") %>%
mutate(name = coalesce(ll_name,name))
title <- paste(race_info$date,
race_info$location,
race_info$gender,
paste0(race_info$length,"km"),
race_info$tech)
subtitle <- "QF & SF heats indicated by numbers on the plot."
data_clean <- data_clean %>%
group_by(name) %>%
mutate(qual_only = all(heat == "Qual")) %>%
ungroup() %>%
filter(!qual_only) %>%
mutate(adv_thresh = case_when(heat == "Qual" ~ max(time[heat == "Qual"],na.rm = TRUE),
heat == "QF" ~ max(time[ll == "Y" & heat == "QF"],na.rm = TRUE),
heat == "SF" ~ max(time[ll == "Y" & heat == "SF"],na.rm = TRUE),
heat == "Final" ~ max(time[heat == "Final" & rank == 3],na.rm = TRUE)))
if (time_scale == "median"){
data_clean <- data_clean %>%
group_by(heat) %>%
mutate(time_y = time - median(time,na.rm = TRUE))
y_lab <- "Difference from median time (sec) within round"
}
if (time_scale == "raw") {
data_clean <- data_clean %>%
group_by(heat) %>%
mutate(time_y = time)
y_lab <- "Time (seconds)"
}
if (time_scale == "thresh"){
data_clean <- data_clean %>%
group_by(heat) %>%
mutate(time_y = time - adv_thresh)
y_lab <- "Difference from advancement time (sec) threshold"
}
spr_final <- data_clean %>%
filter(name %in% data_clean$name[data_clean$fn == 1])
name_lev_ord <- spr_final %>%
filter(heat == "Final") %>%
arrange(rank) %>%
pull(name)
spr_final$name <- factor(spr_final$name,levels = name_lev_ord)
p <- ggplot(data = data_clean,aes(x = heat,y = time_y,group = name)) +
geom_line(alpha = 0.5) +
geom_line(data = spr_final,
aes(color = name,group = name),
size = 1.1) +
geom_text(aes(label = heat_lab),
hjust = rep(c(1,0),length.out = nrow(data_clean))) +
scale_color_brewer(palette = "Set2") +
labs(x = "Round",
y = y_lab,
color = NULL) +
ggtitle(label = title,subtitle = subtitle) +
theme_bw()
if (!is.null(clip)){
p <- p + coord_cartesian(ylim = clip)
}
p
}