Partymaker

sampler.py

def one_run(max_size, max_iters, p, q, disable=False):
    max_idea = 0
    run_times = []
    for size in tqdm(range(max_size), disable=disable):
        ideas = [None for i in range(size)] + [None]

        condition = True
        run_time = 0
        while condition:
            run_time += 1
            new_ideas = [a for a in ideas]
            for i, idea in enumerate(ideas):
                action = np.random.choice(['accept', 'decline', 'new'], p=[p, q, (1 - p - q)])
                if action == 'accept':
                    new_ideas[i] = np.random.choice(ideas)
                if action == 'decline':
                    new_ideas[i] = ideas[i]
                if action == 'new':
                    max_idea += 1
                    new_ideas[i] = max_idea
            ideas = new_ideas

            condition = (not ((len(set(ideas)) == 1) and (not (ideas[0] is None)))) and (run_time < max_iters)

        run_times.append(run_time)
    return run_times

### Sample 
NRUNS = 10
results = []
for p in tqdm(np.linspace(0.05, 0.95, 20)):
    for q in np.linspace(0, 0.95, 20):
        if p + q < 1:
            for _ in range(NRUNS):
                results.append([p, q] + one_run(50, 800, p, q, disable=True))
# Make DataFrame
results_df = pd.DataFrame(results, columns=['p', 'q'] + ['size_{}'.format(i) for i in range(50)])
grouped = results_df.groupby(['p', 'q']).mean().reset_index()

# Draw Results
col = 'size_10'
plt.figure(figsize=(10, 10))
plt.scatter(grouped['p'].values, grouped['q'].values,
            grouped[col].values, marker='.',
            c=grouped[col].values,
           cmap='rainbow');
plt.title(col.replace('_', ': '))
plt.xlabel('Acceptance Rate')
plt.ylabel('Rejection Rate')