building_a_tennis_match_simulator_in_python2

building_a_tennis_match_simulator_in_python2 · GitHub

games = 100 sims = 1000 probabs = np.linspace(0.5, 0.8, 4) results = {}

# for each server probability for p in probabs: # we now need to generate 1000 sims means = [] game_lengths = [] for i in range(0, sims): g_results = [sim_game(p) for x in range(games)] # get mean result mean_res = np.mean([x[0] for x in g_results]) # get mean game length mean_length = np.mean([len(x[1]) for x in g_results]) # join to results holders means.append(mean_res) game_lengths.append(mean_length) # add data to probab dict results[p] = (means, game_lengths)

# plot the mean server win percentage fig, axes = plt.subplots(ncols=2, nrows=2, figsize=(30,20)) axes = axes.reshape(-1)

xlims = (min([min(x[0]) for x in results.values()]), 1)

for data, ax in zip(results.items(), axes): # grab the means means = data[1][0] # plot them sns.distplot(means, ax=ax) ax.set_xlim(xlims) ax.set_title('Server Game Win Distribution, p: {:,.2%}'.format(data[0])) ax.set_xlabel('Server Game Win Probability') ax.set_xticklabels(['{:,.1%}'.format(x) for x in ax.get_xticks()]);