def mpi_make_predictions_and_evaluate(conf,shot_list,loader,custom_path=None):
y_prime,y_gold,disruptive = mpi_make_predictions(conf,shot_list,loader,custom_path)
analyzer = PerformanceAnalyzer(conf=conf)
roc_area = analyzer.get_roc_area(y_prime,y_gold,disruptive)
shot_list.set_weights(analyzer.get_shot_difficulty(y_prime,y_gold,disruptive))
loss = get_loss_from_list(y_prime,y_gold,conf['data']['target'])
return y_prime,y_gold,disruptive,roc_area,loss
def make_predictions_and_evaluate_multiple_times(conf,
shot_list,
loader,
times,
custom_path=None):
y_prime, y_gold, disruptive = make_predictions(conf, shot_list, loader,
custom_path)
areas = []
losses = []
for T_min_curr in times:
# if 'monitor_test' in conf['callbacks'].keys() and
# conf['callbacks']['monitor_test']:
conf_curr = deepcopy(conf)
T_min_warn_orig = conf['data']['T_min_warn']
conf_curr['data']['T_min_warn'] = T_min_curr
assert conf['data']['T_min_warn'] == T_min_warn_orig
analyzer = PerformanceAnalyzer(conf=conf_curr)
roc_area = analyzer.get_roc_area(y_prime, y_gold, disruptive)
# shot_list.set_weights(analyzer.get_shot_difficulty(y_prime, y_gold,
# disruptive))
loss = get_loss_from_list(y_prime, y_gold, conf['data']['target'])
areas.append(roc_area)
losses.append(loss)
return areas, losses
