Rename Project and first working version

mfs/tests/MFS_test.py

@@ -0,0 +1,49 @@
+import unittest
+from mdlp import MDLP
+from sklearn.datasets import load_wine
+
+from ..Selection import MFS
+
+
+class MFS_test(unittest.TestCase):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        mdlp = MDLP(random_state=1)
+        X, self.y = load_wine(return_X_y=True)
+        self.X = mdlp.fit_transform(X, self.y).astype("int64")
+        self.m, self.n = self.X.shape
+
+    # @classmethod
+    # def setup(cls):
+    #     pass
+
+    def test_initialize(self):
+        mfs = MFS()
+        mfs.fcbs(self.X, self.y, 0.05)
+        mfs._initialize()
+        self.assertIsNone(mfs.get_results())
+        self.assertListEqual([], mfs.get_scores())
+        self.assertDictEqual({}, mfs._su_features)
+        self.assertIsNone(mfs._su_labels)
+
+    def test_csf(self):
+        mfs = MFS()
+        expected = [6, 4]
+        self.assertListEqual(expected, mfs.cfs(self.X, self.y).get_results())
+        expected = [0.5218299405215557, 2.4168234005280964]
+        self.assertListEqual(expected, mfs.get_scores())
+
+    def test_fcbs(self):
+        mfs = MFS()
+        computed = mfs.fcbs(self.X, self.y, threshold=0.05).get_results()
+        expected = [6, 9, 12, 0, 11, 4]
+        self.assertListEqual(expected, computed)
+        expected = [
+            0.5218299405215557,
+            0.46224298637417455,
+            0.44518278979085646,
+            0.38942355544213786,
+            0.3790082191220976,
+            0.24972405134844652,
+        ]
+        self.assertListEqual(expected, mfs.get_scores())