# Quick look: the natural course of each world against the calibration targets (plan 5.4).
pkgload::load_all("pvisim", quiet = TRUE)
library(data.table)
args <- commandArgs(TRUE); worlds <- if (length(args)) args else c("W0", "WR")
for (w in worlds) {
  par <- load_params(w, "harm")
  t0 <- Sys.time()
  pop <- make_population(par, seed = 1L)
  ev <- simulate_course(pop, par, policy("natural"), seed = 2L, record = FALSE)$events
  ev <- merge(ev, pop$pat[, .(id, phys_id)], by = "id")
  early <- !is.na(ev$t_pvi) & ev$t_pvi < 6 & ev$pvi_elective %in% TRUE
  h <- 53  # Sorber median follow-up about 4.4 years
  late <- !is.na(ev$t_pvi) & ev$t_pvi >= 6 | !is.na(ev$t_rr) & ev$t_rr >= 6
  late <- late & pmin(ev$t_pvi * NA^(ev$t_pvi < 6), ifelse(!is.na(ev$t_rr) & ev$t_rr >= 6, ev$t_rr, NA), na.rm = TRUE) < h
  clti <- !is.na(ev$t_clti_code) & ev$t_clti_code < h
  phys <- ev[, .(n = .N, rate = mean(!is.na(t_pvi) & t_pvi < 6 & pvi_elective %in% TRUE)), by = phys_id]
  sdr <- sd(phys$rate); out <- mean(phys$rate >= mean(phys$rate) + 2 * sdr)
  cat(sprintf("\n%s (%.0fs)\n  early PVI %.1f%% (target 3.2)\n  physician rate: median %.1f%%, max %.0f%%, >=2SD outliers %.1f%% (0, 58, 5.6)\n",
              w, as.numeric(Sys.time() - t0, units = "secs"), 100 * mean(early),
              100 * median(phys$rate), 100 * max(phys$rate), 100 * out))
  cat(sprintf("  late PVI by 4.4y: early %.1f%% vs not %.1f%% (22.5 vs 3.6)\n", 100 * mean(late[early]), 100 * mean(late[!early])))
  cat(sprintf("  coded CLTI by 4.4y: early %.1f%% vs not %.1f%% (16.4 vs 7.8)\n", 100 * mean(clti[early]), 100 * mean(clti[!early])))
  cat(sprintf("  death by 5y %.1f%% (about 35)   MALE by 5y %.1f%%   amputation %.2f%%   disease composite %.1f%%\n",
              100 * cum_inc(ev$t_death), 100 * cum_inc(ev$t_male), 100 * cum_inc(ev$t_amp), 100 * cum_inc(ev$t_disease)))
  cat(sprintf("  NCO1 %.1f%%  NCO2 %.1f%%  NCE %.1f%%\n", 100 * cum_inc(ev$t_nco1), 100 * cum_inc(ev$t_nco2), 100 * cum_inc(ev$t_nce)))
}