import argparse import matplotlib.pyplot as plt import matplotlib.dates as mdates from datetime import datetime, timedelta import collections class wdldata: def __init__(self, prefix): self.prefix = prefix self.data = [] # tuples: (date, draws, games, pairdraws, pairs, DD) self.rolling_window_size = 0 with open(prefix + ".csv") as f: for line in f: line = line.strip() if line.startswith("Start") or not line: continue parts = line.split(",") date = datetime.fromisoformat(parts[0]) wins = int(parts[1]) draws = int(parts[2]) losses = int(parts[3]) LL = int(parts[4]) LD = int(parts[5]) WLDD = int(parts[6]) WD = int(parts[7]) WW = int(parts[8]) games = wins + draws + losses WL = WLDD - (draws - WD - LD) // 2 DD = WLDD - WL pairs = LL + LD + WLDD + WD + WW self.data.append((date, draws, games, WLDD, pairs, DD)) self.data.sort(key=lambda x: x[0]) self.date = [item[0] for item in self.data] self.draws = [item[1] for item in self.data] self.games = [item[2] for item in self.data] self.pairdraws = [item[3] for item in self.data] self.pairs = [item[4] for item in self.data] self.DD = [item[5] for item in self.data] def calculate_rolling_averages(self, window_days=7): self.rolling_window_size = window_days self.rolling_dates = [] self.rolling_drawrate = [] self.rolling_pairdrawrate = [] self.rolling_DDrate = [] self.rolling_games_avg = [] window = collections.deque() sum_draws = sum_games = sum_pairdraws = sum_pairs = sum_DD = 0 started_rolling = False window_delta = timedelta(days=window_days) half_window = timedelta(days=window_days / 2) for item in self.data: current_date, draws, games, pairdraws, pairs, DD = item window.append(item) sum_draws += draws sum_games += games sum_pairdraws += pairdraws sum_pairs += pairs sum_DD += DD while window and current_date - window[0][0] >= window_delta: ( _, old_draws, old_games, old_pairdraws, old_pairs, old_DD, ) = window.popleft() sum_draws -= old_draws sum_games -= old_games sum_pairdraws -= old_pairdraws sum_pairs -= old_pairs sum_DD -= old_DD if not started_rolling: started_rolling = True self.rolling_dates = self.rolling_dates[-1:] self.rolling_drawrate = self.rolling_drawrate[-1:] self.rolling_pairdrawrate = self.rolling_pairdrawrate[-1:] self.rolling_DDrate = self.rolling_DDrate[-1:] self.rolling_games_avg = self.rolling_games_avg[-1:] drawrate = (sum_draws / sum_games * 100) if sum_games else 0 pairdrawrate = (sum_pairdraws / sum_pairs * 100) if sum_pairs else 0 DDrate = (sum_DD / sum_pairdraws * 100) if sum_pairdraws else 0 games_avg = sum_games / window_days self.rolling_dates.append(current_date - half_window) self.rolling_drawrate.append(drawrate) self.rolling_pairdrawrate.append(pairdrawrate) self.rolling_DDrate.append(DDrate) self.rolling_games_avg.append(games_avg) def create_graph(self, logplot=False, plot_scatter=True, plot_DDrate=False): dotSize, smallDotSize, lineWidth = 20, 4, 1.8 if len(self.date) >= 100: dotSize, smallDotSize = 10, 3 fig, ax1 = plt.subplots(figsize=(12, 7)) yColor, gamesColor = "black", "dimgray" gamesAvgColor = "darkgray" gamesDailyColor = "lightgray" drawColor, pairdrawColor = "limegreen", "blue" rollingDrawColor, rollingPairDrawColor = "darkgreen", "darkblue" rollingDDrateColor = "darkorange" plot_rolling = self.rolling_window_size >= 1 if plot_scatter: raw_drawrate = [ (self.draws[i] / self.games[i] * 100) if self.games[i] else 0 for i in range(len(self.draws)) ] raw_pairdrawrate = [ (self.pairdraws[i] / self.pairs[i] * 100) if self.pairs[i] else 0 for i in range(len(self.pairs)) ] point_size = smallDotSize * 1.5 if plot_rolling else dotSize scatter_alpha = 0.4 if plot_rolling else 1.0 draw_scatter_label = "Draw Rate" if not plot_rolling else None pair_scatter_label = "Pair Draw Rate" if not plot_rolling else None ax1.scatter( self.date, raw_drawrate, label=draw_scatter_label, color=drawColor, s=point_size, alpha=scatter_alpha, ) ax1.scatter( self.date, raw_pairdrawrate, label=pair_scatter_label, color=pairdrawColor, s=point_size, alpha=scatter_alpha, ) if plot_rolling: draw_label = f"Draw Rate ({self.rolling_window_size}-day avg)" pair_draw_label = f"Pair Draw Rate ({self.rolling_window_size}-day avg)" DDrate_label = f"DD/(DD+WL) ({self.rolling_window_size}-day avg)" ax1.plot( self.rolling_dates, self.rolling_drawrate, label=draw_label, color=rollingDrawColor, linewidth=lineWidth, ) ax1.plot( self.rolling_dates, self.rolling_pairdrawrate, label=pair_draw_label, color=rollingPairDrawColor, linewidth=lineWidth, ) if plot_DDrate: ax1.plot( self.rolling_dates, self.rolling_DDrate, label=DDrate_label, color=rollingDDrateColor, linewidth=lineWidth, ) ax1.set_ylabel("%", color=yColor) ax1.tick_params(axis="y", labelcolor=yColor) ax1.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m-%d")) ax1.grid( True, which="major", axis="both", alpha=0.3, linewidth=0.5, ) fig.autofmt_xdate(rotation=30, ha="right") plt.setp(ax1.get_xticklabels(), fontsize=8) ax2 = ax1.twinx() if plot_scatter: ax2.scatter( self.date, self.games, label="Daily Games", color=gamesDailyColor, s=smallDotSize, alpha=0.6, ) if plot_rolling: ax2.plot( self.rolling_dates, self.rolling_games_avg, color=gamesAvgColor, linewidth=lineWidth, alpha=0.9, ) ax2.set_ylabel("# Games per Day", color=gamesColor) ax2.tick_params(axis="y", labelcolor=gamesColor) if logplot: ax2.set_yscale("log") ax1.legend(fontsize="small") plt.title(f"WDL and Pentanomial Statistics for {self.prefix}.csv") plt.tight_layout(rect=[0, 0.03, 1, 0.98]) if self.rolling_window_size >= 1: save_path = self.prefix + f"_d{self.rolling_window_size}" + ".png" else: save_path = self.prefix + ".png" plt.savefig(save_path, dpi=300) print(f"Plot saved to {save_path}") plt.close(fig) if __name__ == "__main__": parser = argparse.ArgumentParser( description="Plot WDL data with optional rolling average.", formatter_class=argparse.ArgumentDefaultsHelpFormatter, ) parser.add_argument( "filename", nargs="?", help="CSV file with WDL statistics over time", default="results.csv", ) parser.add_argument( "--logplot", action="store_true", help="Use log scale for the games count axis.", ) parser.add_argument( "--rolling", type=int, default=30, help="Number of days for the rolling average window. Set to 0 to disable rolling average.", ) parser.add_argument( "--hide-scatter", action="store_true", help="Do not show the raw daily scatter points.", ) parser.add_argument( "--show-DDrate", action="store_true", help="Show rolling average of DD / (DD + WL).", ) args = parser.parse_args() prefix, _, _ = args.filename.partition(".") data = wdldata(prefix) if args.rolling >= 1: data.calculate_rolling_averages(args.rolling) data.create_graph(args.logplot, not args.hide_scatter, args.show_DDrate)