Addins bayesian optimization functionnality with skopt

.gitignore

@@ -1,3 +1,4 @@
 
 **/*.ipynb_checkpoints
 __pycache__
+/.vscode/

brainDecode/towardMoabbIntegration/utils/bayesian.py

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+
+from skopt import BayesSearchCV
+from skopt.space import Categorical, Real, Integer
+from brainDecode.towardMoabbIntegration.brainDecodeSKLearnWrapper.ShallowFBCSPNet_GeneralTrainer import ShallowFBCSPNet_GeneralTrainer
+
+
+def bayes_optimize(classifier=None, X_train=None, Y_train=None):
+    classifier = ShallowFBCSPNet_GeneralTrainer(nb_epoch=25)
+
+    searches = {            # This should containt Dimension instances (Reals, Integer, or Categorical)
+        "n_filters_time":Integer(5, 15),
+        "filter_time_length":Integer(50,75),
+        "n_filters_spat":Integer(3,10),
+        "pool_time_length":Integer(50,80),
+        "pool_time_stride":Integer(20,40)
+    }
+
+    bayes_optmizer = BayesSearchCV(classifier, searches)
+
+    # now fit and profit
+    bayes_optmizer.fit(X_train, Y_train)

requirements.txt

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+mne>=0.16.1
+seaborn
+pandas
+scikit-learn
+torch==0.4.0
+braindecode==0.4.5
+scikit-optimize==0.5.2