File size: 4,766 Bytes
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pattern_vector <- c("\\w+-\\w+", "-", stop = "\\d", "-", topm = "\\d")
df_side <- df |>
filter(grepl(attempt_prefix, attempt)) |>
mutate(atmpt = attempt) |>
separate_wider_regex(
atmpt,
pattern_vector
) |>
mutate(
setting = paste0(stop, topm)
) |>
select(!c("stop", "topm"))
return(df_side)
}
pick_attempt_data_milp <- function(df, attempt_prefix) {
df_side <- df |>
filter(grepl(attempt_prefix, attempt)) |>
mutate(atmpt = attempt) |>
separate_wider_regex(
atmpt,
c("(?:\\w+-)+", topm = "\\d")
) |>
mutate(
setting = topm
) |>
select(!c("topm"))
return(df_side)
}
# Mandatory columns df_side_x:
# model, algo, config, bpp, attempt, ppl_wikitext, ppl_c4, load_mem_allot
# Optional columns df_side_x: setting
calc_wtl_score_det <- function(
df_side_a,
df_side_b,
sidea_name,
sideb_name,
join_cond = c("model", "bpp"),
dump_det_data = FALSE) {
key_fields <- c(
"algo",
"config",
"attempt"
)
value_fields <- c(
"ppl_wikitext",
"ppl_c4"
)
key_fields <- c(key_fields, join_cond)
fields <- c(key_fields, value_fields)
df_det <- df_side_a |>
select(
all_of(fields)
) |>
left_join(
df_side_b,
suffix = c("_sidea", ""),
by = join_cond
) |>
mutate(
ppl_wikitext_sidea = round(ppl_wikitext_sidea, digits = 2),
ppl_c4_sidea = round(ppl_c4_sidea, digits = 2),
ppl_wikitext = round(ppl_wikitext, digits = 2),
ppl_c4 = round(ppl_c4, digits = 2)
) |>
mutate(
score_wk = round(ppl_wikitext_sidea - ppl_wikitext, digits = 4),
score_c4 = round(ppl_c4_sidea - ppl_c4, digits = 4)
) |>
mutate(
wins = ifelse(score_wk < 0, 1, 0) + ifelse(score_c4 < 0, 1, 0),
ties = ifelse(score_wk == 0, 1, 0) + ifelse(score_c4 == 0, 1, 0),
losses = ifelse(score_wk > 0, 1, 0) + ifelse(score_c4 > 0, 1, 0)
) |>
select(
c(
"model",
"algo",
"config",
"bpp",
"attempt_sidea",
"wins",
"losses",
"ties",
"ppl_wikitext_sidea",
"ppl_wikitext",
"ppl_c4_sidea",
"ppl_c4"
)
)
if (dump_det_data) {
write.xlsx(
df_det,
paste0("df_det-", sidea_name, "-", sideb_name, ".xlsx"),
asTable = TRUE
)
}
return(df_det)
}
# Mandatory columns df_side_x:
# model, algo, config, bpp, attempt, ppl_wikitext, ppl_c4, load_mem_allot
# Optional columns df_side_x: setting
calc_wtl_score <- function(
df_side_a,
df_side_b,
sidea_name,
sideb_name,
join_cond = c("model", "bpp"),
dump_det_data = FALSE) {
df_det <- calc_wtl_score_det(
df_side_a,
df_side_b,
sidea_name,
sideb_name,
join_cond = join_cond,
dump_det_data = dump_det_data
)
df_sum <- df_det |>
group_by(model) |>
summarise(
wins = sum(wins),
ties = sum(ties),
losses = sum(losses)
) |>
ungroup()
df_sum$Method1 <- sidea_name
df_sum$Method2 <- sideb_name
return(df_sum)
}
# Create the horizontal stacked bar chart
plot_win_tie_loss <- function(df_disp, output_file) {
plt <- ggplot(
# results_long, aes(x = Percentage, y = as.numeric(Method1), fill = Result)
df_disp, aes(x = Percentage, y = Method, fill = Result)
) +
geom_col(width = 5.8) +
# Nature/Science-inspired color palette
scale_fill_manual(values = c(
"wins" = "#66c2a5", # Steel blue
"losses" = "#fc8d62", # Muted red
"ties" = "#8da0cb" # Purple
)) +
# Add percentage labels
geom_text(
data = subset(df_disp, Percentage > 0),
aes(label = sprintf("%.0f", Percentage)),
position = position_stack(vjust = 0.5),
color = "white",
size = 6.0
) +
theme_minimal() +
guides(fill = guide_legend(reverse = TRUE)) +
labs(
title = "",
x = NULL,
y = NULL,
fill = "Result"
) +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.text.y = element_blank(),
axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
plot.title = element_text(
hjust = 0.5, size = 14, face = "bold", color = "black"
),
legend.position = "left",
legend.text = element_text(color = "black", size = 26),
legend.title = element_blank(),
strip.text.x = element_text(face = "bold", size = 26),
strip.text.y = element_text(size = 14, angle = 40, face = "bold", hjust = 0.01, vjust = -0.01)
) +
facet_grid(Method ~ model)
ggsave(
paste0("pdfs/", output_file),
plot = plt,
width = 13,
height = 7
)
}
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