best_dendro_corrs.append(max(dendro_corrs))
"""
Plotting best & final validation losses
"""
if len(validation_losses) > 0:
dendro_best_loss.append(min(validation_losses[1:]))
simple_best_loss.append(min(simple_validation_losses[1:]))
dendro_final_loss.append(validation_losses[-1])
simple_final_loss.append(simple_validation_losses[-1])
if len(dendro_best_loss) > 0:
names = ['dendro_best', 'dendro_final', 'simple_best', 'simple_final']
loss_outputs = [
dendro_best_loss, dendro_final_loss, simple_best_loss,
simple_final_loss
]
log_aucs(os.path.join(base_output_dir, 'loss_log.txt'), loss_outputs,
names)
print('Done disentanglement analysis')
disentanglement_metrics = {
'simple_errors': best_simple_errors,
'dendro_errors': best_dendro_errors,
'simple_correlations': best_simple_corrs,
'dendro_correlations': best_dendro_corrs,
# 'simple_final_weights': simple_final_weights,
# 'dendro_final_weights': dendro_final_weights
}
dump_dict(disentanglement_metrics,
base_output_dir,
name='disentanglement_metrics.csv')
roc_metrics[ls]['targets'].extend(targets)
roc_metrics[ls]['dendro_preds'].extend(dendro_predictions.numpy()[:, 1])
roc_metrics[ls]['simple_preds'].extend(simple_predictions.numpy()[:, 1])
if args.baselines:
_, parsimony_predictions, one_hot_predictions = baseline_experiment.retrieve_predictions()
roc_metrics[ls]['parsimony_preds'].extend(np.squeeze(parsimony_predictions.numpy())[:, 1])
roc_metrics[ls]['one_hot_preds'].extend(one_hot_predictions.numpy()[:, 1])
auc_list = list()
log_auc_names = list()
for ls in DIVERSE_TROPHIC_LEVELS:
for name in basenames:
auc_list.append(aucs[ls][name])
log_auc_names.append(str(ls + '_' + name))
if len(auc_list[0]) > 0:
log_aucs(os.path.join(base_output_dir, 'auc_log.txt'), auc_list, log_auc_names)
print('done')
if PLOT_ROC:
for ls in DIVERSE_TROPHIC_LEVELS:
pd_name = ls +'_roc_metrics.csv'
pd.DataFrame.from_dict(roc_metrics[ls]).to_csv(pd_name)
targets = roc_metrics[ls]['targets']
dendro_predictions = roc_metrics[ls]['dendro_preds']
simple_predictions = roc_metrics[ls]['simple_preds']
bin_targets = [t[1] for t in targets]
dendro_fpr, dendro_tpr, _ = roc_curve(bin_targets, dendro_predictions)
simple_fpr, simple_tpr, _ = roc_curve(bin_targets, simple_predictions)
dendro_auc = auc(dendro_fpr, dendro_tpr)
