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()
