From eadac78dd1019f11219e12d854d4a419824bdaec Mon Sep 17 00:00:00 2001
From: Charly Lamothe <charly.lamothe@univ-amu.fr>
Date: Wed, 26 Feb 2020 11:25:35 +0100
Subject: [PATCH] Start to add back density plot
---
code/bolsonaro/models/model_raw_results.py | 8 ++++----
code/bolsonaro/models/omp_forest.py | 2 ++
code/bolsonaro/trainer.py | 9 ++++++++-
code/compute_results.py | 6 ++++++
4 files changed, 20 insertions(+), 5 deletions(-)
diff --git a/code/bolsonaro/models/model_raw_results.py b/code/bolsonaro/models/model_raw_results.py
index e503742..26e86da 100644
--- a/code/bolsonaro/models/model_raw_results.py
+++ b/code/bolsonaro/models/model_raw_results.py
@@ -6,12 +6,12 @@ import datetime
class ModelRawResults(object):
- def __init__(self, model_object, training_time,
+ def __init__(self, model_weights, training_time,
datetime, train_score, dev_score, test_score,
train_score_base, dev_score_base,
test_score_base, score_metric, base_score_metric):
- self._model_object = model_object
+ self._model_weights = model_weights
self._training_time = training_time
self._datetime = datetime
self._train_score = train_score
@@ -24,8 +24,8 @@ class ModelRawResults(object):
self._base_score_metric = base_score_metric
@property
- def model_object(self):
- return self.model_object
+ def model_weights(self):
+ return self.model_weights
@property
def training_time(self):
diff --git a/code/bolsonaro/models/omp_forest.py b/code/bolsonaro/models/omp_forest.py
index 16c3e1c..f1b42e8 100644
--- a/code/bolsonaro/models/omp_forest.py
+++ b/code/bolsonaro/models/omp_forest.py
@@ -8,6 +8,7 @@ from sklearn.base import BaseEstimator
class OmpForest(BaseEstimator, metaclass=ABCMeta):
+
def __init__(self, models_parameters, base_forest_estimator):
self._base_forest_estimator = base_forest_estimator
self._models_parameters = models_parameters
@@ -95,6 +96,7 @@ class OmpForest(BaseEstimator, metaclass=ABCMeta):
pass
class SingleOmpForest(OmpForest):
+
def __init__(self, models_parameters, base_forest_estimator):
# fit_intercept shouldn't be set to False as the data isn't necessarily centered here
# normalization is handled outsite OMP
diff --git a/code/bolsonaro/trainer.py b/code/bolsonaro/trainer.py
index ce233d5..5920fa2 100644
--- a/code/bolsonaro/trainer.py
+++ b/code/bolsonaro/trainer.py
@@ -126,8 +126,15 @@ class Trainer(object):
:param model: Object with
:param models_dir: Where the results will be saved
"""
+
+ model_weights = ''
+ if type(model) == RandomForestRegressor:
+ model_weights = model.coef_
+ elif type(model) == OmpForestRegressor:
+ model_weights = model._omp.coef_
+
results = ModelRawResults(
- model_object='',
+ model_weights=model_weights,
training_time=self._end_time - self._begin_time,
datetime=datetime.datetime.now(),
train_score=self.__score_func(model, self._dataset.X_train, self._dataset.y_train),
diff --git a/code/compute_results.py b/code/compute_results.py
index 473044d..bad281c 100644
--- a/code/compute_results.py
+++ b/code/compute_results.py
@@ -33,6 +33,8 @@ def extract_scores_across_seeds_and_extracted_forest_sizes(models_dir, results_d
# Used to check if all losses were computed using the same metric (it should be the case)
experiment_score_metrics = list()
+ all_weights = list()
+
# For each seed results stored in models/{experiment_id}/seeds
seeds = os.listdir(experiment_seed_root_path)
seeds.sort(key=int)
@@ -120,6 +122,7 @@ if __name__ == "__main__":
DEFAULT_RESULTS_DIR = os.environ["project_dir"] + os.sep + 'results'
DEFAULT_MODELS_DIR = os.environ["project_dir"] + os.sep + 'models'
+ DEFAULT_PLOT_WEIGHT_DENSITY = False
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('--stage', nargs='?', type=int, required=True, help='Specify the stage number among [1, 5].')
@@ -130,6 +133,7 @@ if __name__ == "__main__":
parser.add_argument('--dataset_name', nargs='?', type=str, required=True, help='Specify the dataset name. TODO: read it from models dir directly.')
parser.add_argument('--results_dir', nargs='?', type=str, default=DEFAULT_RESULTS_DIR, help='The output directory of the results.')
parser.add_argument('--models_dir', nargs='?', type=str, default=DEFAULT_MODELS_DIR, help='The output directory of the trained models.')
+ parser.add_argument('--plot_weight_density', action='store_true', default=DEFAULT_PLOT_WEIGHT_DENSITY, help='Plot the weight density. Only working for regressor models for now.')
args = parser.parse_args()
if args.stage not in list(range(1, 6)):
@@ -224,6 +228,8 @@ if __name__ == "__main__":
ylabel=experiments_score_metric,
title='Loss values of {}\nusing best and default hyperparameters'.format(args.dataset_name)
)
+
+ Plotter.plot_weight_density()
elif args.stage == 2:
if len(args.experiment_ids) != 4:
raise ValueError('In the case of stage 2, the number of specified experiment ids must be 4.')
--
GitLab