added tests to Fisher method

Author: Tomasz Latkowski

methods/__init__.py

@@ -1,4 +1,8 @@
 import tensorflow as tf
+import pandas as pd
+
+data_file = '../data/autism.tsv'
+df = pd.read_csv(data_file, sep='\t', header=None, index_col=0).T
 
 
 def fisher(data, num_instances: list, top_k=10):
@@ -15,7 +19,7 @@ def fisher(data, num_instances: list, top_k=10):
     class1, class2 = tf.split(data, num_instances)
     mean1, std1 = tf.nn.moments(class1, axes=0)
     mean2, std2 = tf.nn.moments(class2, axes=0)
-    fisher_coeffs = (mean1 - mean2) / (std1 + std2)
+    fisher_coeffs = tf.abs((mean1 - mean2)) / (std1 + std2)
     return tf.nn.top_k(fisher_coeffs, k=top_k)
 
 
@@ -46,3 +50,12 @@ def t_test(data, num_instances: list, top_k=10):
     t_test_coeffs = (mean1 - mean2) / tf.sqrt(tf.square(std1)/num_instances[0] + tf.square(std2) / num_instances[1])
     return tf.nn.top_k(t_test_coeffs, k=top_k)
 
+with tf.Session() as session:
+    input_data = df.as_matrix()
+    instances_per_class = [82, 64]
+    fisher_coeffs = session.run(fisher(data=input_data, num_instances=instances_per_class))
+    corr_coeffs = session.run(feature_correlation_with_class(data=input_data, num_instances=instances_per_class))
+    t_test_coeff = session.run(t_test(data=input_data, num_instances=instances_per_class))
+    print(fisher_coeffs)
+    print(corr_coeffs)
+    print(t_test_coeff)

selection.py renamed to methods/selection.py

@@ -0,0 +1,11 @@
+import tensorflow as tf
+
+
+class CorrelationWithClassSelectionTest(tf.test.TestCase):
+
+    def testCorrelationWithClassCorrectScore(self):
+        raise NotImplementedError
+
+
+if __name__ == '__main__':
+    tf.test.main()

tests/__init__.py

@@ -0,0 +1,28 @@
+import tensorflow as tf
+from methods.selection import fisher
+import numpy as np
+
+
+class FisherSelectionTest(tf.test.TestCase):
+
+    def testFisherCorrectScore(self):
+        with self.test_session() as test_session:
+            data = np.array([[2, 2],
+                             [4, 4],
+                             [3, 6],
+                             [5, 6]])
+            num_instances = [2, 2]
+            top_k = 2
+            actual_most_significant_features = test_session.run(fisher(data, num_instances, top_k))
+
+            correct_most_significant_features = tf.constant([3., .5])
+            self.assertAllEqual(actual_most_significant_features.values, correct_most_significant_features.eval())
+
+    def testFisherCorrectOrderOfFeatures(self):
+        raise NotImplementedError
+
+    def testMoreThan2ClassesIsNotAllowed(self):
+        raise NotImplementedError
+
+if __name__ == '__main__':
+    tf.test.main()

tests/corr.py

@@ -0,0 +1,11 @@
+import tensorflow as tf
+
+
+class TtestSelectionTest(tf.test.TestCase):
+
+    def testTtestCorrectScore(self):
+        raise NotImplementedError
+
+
+if __name__ == '__main__':
+    tf.test.main()