Sebastian Rust
44 lines
1.7 KiB
R
44 lines
1.7 KiB
R
#!/usr/bin/env Rscript
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source("common.R")
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# Random sample size per solution. stat_ecdf emits one tikz path segment per
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# unique x value; the raw idts.csv has ~120 K unique values per solution,
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# producing a ~500 K-line tikz file that exceeds pdflatex main_memory.
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# 5000 samples per solution preserve the CDF shape (including the 92.5-100 %
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# zoom tail: ~375 points) and keep the tikz file manageable.
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SAMPLE_PER_SOLUTION <- 20000
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parser <- fig_parser(description = "Per-flow inter-departure-time CDF")
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parser$add_argument("--sample", type = "integer", default = SAMPLE_PER_SOLUTION,
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help = "downsample to N points per solution (0 = no downsampling)")
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parser$add_argument("--seed", type = "integer", default = 1,
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help = "RNG seed for downsampling")
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args <- parser$parse_args()
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set.seed(args$seed)
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idts <- read_csv(file.path(args$data, "idts.csv"), show_col_types = FALSE) %>%
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prepare_solution()
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if (args$sample > 0) {
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idts <- idts %>%
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group_by(solution) %>%
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slice_sample(n = args$sample) %>%
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ungroup()
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}
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p <- ggplot(idts, aes(x = idt_us, colour = solution, linetype = solution)) +
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stat_ecdf(linewidth = 0.9, pad = FALSE, key_glyph = "rect") +
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scale_x_log10(labels = label_comma()) +
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scale_y_continuous(labels = label_pct()) +
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scale_colour_manual(values = LABEL_COLORS) +
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scale_linetype_manual(values = LABEL_LINETYPES) +
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labs(x = paste0("Inter-departure time within flow (", label_us(), ")"), y = "CDF") +
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theme_paper() +
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theme(legend.text = element_text(size = rel(0.8)),
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legend.key.size = unit(6, "pt"))
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if (args$zoom) {
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p <- p + coord_cartesian(xlim = c(10, 1000), ylim = c(0.925, 1.0))
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}
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save_figure(p, args)
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