def vars_from_data(bound_meta_lower=0, bound_meta_upper=1, low_prob=0, up_prob=1, dataset="states"): if (dataset == "states"): data = data_retrieval.get_states_expt1_consistent("expt3_mac") beliefs, metas = get_reports(data, bound_meta_lower, bound_meta_upper, low_prob, up_prob) actual_ans = np.array([int(d['actual']) for d in data]) nominal = [d['responses'] for d in data] elif dataset in ["lesions_mac", "lesions_cluster", "lesions_ubuntu"]: data = data_retrieval.get_lesion_data(dataset) beliefs = [np.array([pp['own_prob'] for pp in d['data']]).T for d in data] metas = [np.array([[1 - pp['meta']['percent'], pp['meta']['percent']] for pp in d['data']]).T for d in data] actual_ans = np.array([int(d['trueAnswerCorrect']) for d in data]) nominal = [np.array([pp['response'] for pp in d['data']]) for d in data] qnames = [d['data'][0]['qname'] for d in data] else: print("Unknown dataset") system.exit() return beliefs, metas, actual_ans, nominal, qnames
def lesions_25_wrong(): data = data_retrieval.get_lesion_data()