def check_dpm(impl, data_count, beta0): check_cm(impl) data = histogram(np.random.randint(50, size=data_count)) data = dict([(str(i), obs) for i, obs in enumerate(data)]) betas = dict([(str(i), (1 - beta0) / len(data)) for i, obs in enumerate(data)]) hp = { 'gamma': 1., 'alpha': 1., 'beta0': beta0, 'betas': betas } ss = {'counts': data} cm = ComponentModel( impl, ss=ss, hp=hp) samples = cm.sample_data(SAMPS) counts = list(histogram([y for y in samples if y != -1])) probs = list(np.exp([cm.pred_prob(x) for x in range(max(samples) + 1)])) counts.append(len([y for y in samples if y == -1])) probs.append(np.exp(cm.pred_prob(-1))) assert_less(1 - sum(probs), THRESH) probs, counts = zip(*sorted(zip(probs, counts), reverse=True)[:TOPN]) p = mgof(probs, counts, SAMPS, truncated=True) assert_greater(p, THRESH)
def _check_discrete(cm): samples = cm.sample_data(SAMPS) counts = histogram(samples) probs = np.exp([cm.pred_prob(x) for x in range(max(samples) + 1)]) assert_less(1 - sum(probs), THRESH) probs, counts = zip(*sorted(zip(probs, counts), reverse=True)[:TOPN]) p = mgof(probs, counts, SAMPS, truncated=True) assert_greater(p, THRESH)
def check_dd(impl, data_count, D): check_cm(impl) data = histogram(np.random.randint(D, size=data_count), bin_count=D) cm = ComponentModel( impl, ss={'counts': data}, p={'D': D}) cm.realize_hp() _check_discrete(cm)
def check_dpm(impl, data_count, beta0): check_cm(impl) data = histogram(np.random.randint(50, size=data_count)) data = dict([(str(i), obs) for i, obs in enumerate(data)]) betas = dict([(str(i), (1 - beta0) / len(data)) for i, obs in enumerate(data)]) hp = {'gamma': 1., 'alpha': 1., 'beta0': beta0, 'betas': betas} ss = {'counts': data} cm = ComponentModel(impl, ss=ss, hp=hp) samples = cm.sample_data(SAMPS) counts = list(histogram([y for y in samples if y != -1])) probs = list(np.exp([cm.pred_prob(x) for x in range(max(samples) + 1)])) counts.append(len([y for y in samples if y == -1])) probs.append(np.exp(cm.pred_prob(-1))) assert_less(1 - sum(probs), THRESH) probs, counts = zip(*sorted(zip(probs, counts), reverse=True)[:TOPN]) p = mgof(probs, counts, SAMPS, truncated=True) assert_greater(p, THRESH)
def check_dd(impl, data_count, D): check_cm(impl) data = histogram(np.random.randint(D, size=data_count), bin_count=D) cm = ComponentModel(impl, ss={'counts': data}, p={'D': D}) cm.realize_hp() _check_discrete(cm)