Add test for using optimizers

tests/classifier/LinearSVC/LinearSVCJavaTest.py

@@ -2,8 +2,15 @@
 
 from unittest import TestCase
 
+from sklearn.datasets import load_digits
+from sklearn.decomposition import PCA, NMF
+from sklearn.feature_selection import SelectKBest
+from sklearn.feature_selection import chi2
+from sklearn.model_selection import GridSearchCV
+from sklearn.pipeline import Pipeline
 from sklearn.svm.classes import LinearSVC
 
+from sklearn_porter import Porter
 from ..Classifier import Classifier
 from ...language.Java import Java
 
@@ -16,3 +23,33 @@ def setUp(self):
 
     def tearDown(self):
         super(LinearSVCJavaTest, self).tearDown()
+
+    def test_model_within_optimizer(self):
+        pipe = Pipeline([
+            ('reduce_dim', PCA()),
+            ('classify', LinearSVC())
+        ])
+        n_features_options = [2, 4, 8]
+        c_options = [1, 10, 100, 1000]
+        param_grid = [
+            {
+                'reduce_dim': [PCA(iterated_power=7), NMF()],
+                'reduce_dim__n_components': n_features_options,
+                'classify__C': c_options
+            },
+            {
+                'reduce_dim': [SelectKBest(chi2)],
+                'reduce_dim__k': n_features_options,
+                'classify__C': c_options
+            },
+        ]
+        grid = GridSearchCV(pipe, cv=3, n_jobs=1, param_grid=param_grid)
+        digits = load_digits()
+        grid.fit(digits.data, digits.target)
+
+        try:
+            Porter(grid, language='java')
+        except ValueError:
+            self.assertTrue(False)
+        else:
+            self.assertTrue(True)