From 96ff6093361a5e5df0db0b8d185deef19748e425 Mon Sep 17 00:00:00 2001
From: Charly Lamothe <charly.lamothe@univ-amu.fr>
Date: Tue, 10 Mar 2020 15:32:53 +0100
Subject: [PATCH] Fix normalize_D missing transpose and fix stage4 result path
---
code/bolsonaro/models/omp_forest.py | 4 ++++
code/bolsonaro/models/omp_forest_classifier.py | 4 ++++
code/compute_results.py | 2 +-
3 files changed, 9 insertions(+), 1 deletion(-)
diff --git a/code/bolsonaro/models/omp_forest.py b/code/bolsonaro/models/omp_forest.py
index e4a5667..6c9a3f9 100644
--- a/code/bolsonaro/models/omp_forest.py
+++ b/code/bolsonaro/models/omp_forest.py
@@ -123,7 +123,9 @@ class SingleOmpForest(OmpForest):
forest_predictions = self._base_estimator_predictions(X)
if self._models_parameters.normalize_D:
+ forest_predictions = forest_predictions.T
forest_predictions /= self._forest_norms
+ forest_predictions = forest_predictions.T
return self._make_omp_weighted_prediction(forest_predictions, self._omp, self._models_parameters.normalize_weights)
@@ -139,7 +141,9 @@ class SingleOmpForest(OmpForest):
forest_predictions = self._base_estimator_predictions(X).T
if self._models_parameters.normalize_D:
+ forest_predictions = forest_predictions.T
forest_predictions /= self._forest_norms
+ forest_predictions = forest_predictions.T
weights = self._omp.coef_
omp_trees_indices = np.nonzero(weights)[0]
diff --git a/code/bolsonaro/models/omp_forest_classifier.py b/code/bolsonaro/models/omp_forest_classifier.py
index a51405a..3cb250d 100644
--- a/code/bolsonaro/models/omp_forest_classifier.py
+++ b/code/bolsonaro/models/omp_forest_classifier.py
@@ -37,7 +37,9 @@ class OmpForestBinaryClassifier(SingleOmpForest):
forest_predictions = np.array([tree.predict_proba(X) for tree in self._base_forest_estimator.estimators_])
if self._models_parameters.normalize_D:
+ forest_predictions = forest_predictions.T
forest_predictions /= self._forest_norms
+ forest_predictions = forest_predictions.T
weights = self._omp.coef_
omp_trees_indices = np.nonzero(weights)
@@ -119,7 +121,9 @@ class OmpForestMulticlassClassifier(OmpForest):
forest_predictions = np.array([tree.predict_proba(X) for tree in self._base_forest_estimator.estimators_]).T
if self._models_parameters.normalize_D:
+ forest_predictions = forest_predictions.T
forest_predictions /= self._forest_norms
+ forest_predictions = forest_predictions.T
label_names = []
preds = []
diff --git a/code/compute_results.py b/code/compute_results.py
index 406f0e0..a6eb2f5 100644
--- a/code/compute_results.py
+++ b/code/compute_results.py
@@ -389,7 +389,7 @@ if __name__ == "__main__":
raise ValueError('Score metrics of all experiments must be the same.')
experiments_score_metric = base_with_params_experiment_score_metric
- output_path = os.path.join(args.results_dir, args.dataset_name, 'stage4_fix')
+ output_path = os.path.join(args.results_dir, args.dataset_name, 'stage4')
pathlib.Path(output_path).mkdir(parents=True, exist_ok=True)
Plotter.plot_stage2_losses(
--
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