def average_idle_power(samples, file_prefix):
'''Compute average idle power to subtract from entries in log file'''
hardware = filestring_to_hardware(file_prefix)
hardware_samples = [s for s in samples if s['hardware'] == hardware]
average_power = mean([s['total_power'] for s in hardware_samples])
return average_power
2 * np.ones(con_2),
1 * np.ones(con_1)))
true_data = np.concatenate((5 * np.ones(true_5),
4 * np.ones(true_4),
3 * np.ones(true_3),
2 * np.ones(true_2),
1 * np.ones(true_1)))
mod_data = np.concatenate((5 * np.ones(mod_5),
4 * np.ones(mod_4),
3 * np.ones(mod_3),
2 * np.ones(mod_2),
1 * np.ones(mod_1)))
true_mean = mean(true_data)
true_ci = bootstrapci(true_data, mean)
print('')
print('Entailment')
print('Mean Rating: ', true_mean)
print('95% CIs: ', (true_ci[1] - true_ci[0]) / 2)
print(true_ci)
con_mean = mean(con_data)
con_ci = bootstrapci(con_data, mean)
print('')
print('Contradiction')
print('Mean Rating: ', con_mean)
print('95% CIs: ', (con_ci[1] - con_ci[0]) / 2)
print(con_ci)
2 * np.ones(neut_2),
1 * np.ones(neut_1)))
true_data = np.concatenate((5 * np.ones(true_5),
4 * np.ones(true_4),
3 * np.ones(true_3),
2 * np.ones(true_2),
1 * np.ones(true_1)))
mod_data = np.concatenate((5 * np.ones(mod_5),
4 * np.ones(mod_4),
3 * np.ones(mod_3),
2 * np.ones(mod_2),
1 * np.ones(mod_1)))
true_mean = mean(true_data)
true_ci = bootstrapci(true_data, mean)
print('')
print('Entailment')
print('Mean Rating: ', true_mean)
print('95% CIs: ', (true_ci[1] - true_ci[0]) / 2)
print(true_ci)
neut_mean = mean(neut_data)
neut_ci = bootstrapci(neut_data, mean)
print('')
print('Neutral')
print('Mean Rating: ', neut_mean)
print('95% CIs: ', (neut_ci[1] - neut_ci[0]) / 2)
print(neut_ci)
human_true_data = np.concatenate(
(5 * np.ones(human_true_5), 4 * np.ones(human_true_4),
3 * np.ones(human_true_3), 2 * np.ones(human_true_2),
1 * np.ones(human_true_1)))
model_true_data = np.concatenate(
(5 * np.ones(model_true_5), 4 * np.ones(model_true_4),
3 * np.ones(model_true_3), 2 * np.ones(model_true_2),
1 * np.ones(model_true_1)))
human_false_data = np.concatenate(
(5 * np.ones(human_false_5), 4 * np.ones(human_false_4),
3 * np.ones(human_false_3), 2 * np.ones(human_false_2),
1 * np.ones(human_false_1)))
human_true_mean = mean(human_true_data)
human_true_ci = bootstrapci(human_true_data, mean)
print('Human Data - True')
print('Mean Rating: ', human_true_mean)
print('95% CIs: ', human_true_ci[1], human_true_ci[0])
human_false_mean = mean(human_false_data)
human_false_ci = bootstrapci(human_false_data, mean)
print('Human Data - False')
print('Mean Rating: ', human_false_mean)
print('95% CIs: ', human_false_ci[1], human_false_ci[0])
model_true_mean = mean(model_true_data)
model_true_ci = bootstrapci(model_true_data, mean)