Testing team awesome

hands_on/pyanno_voting/pyanno/tests/test_voting.py

@@ -5,6 +5,7 @@
 
 
 def test_labels_count():
+    #Given
     annotations = [
         [1,  2, MV, MV],
         [MV, MV,  3,  3],
@@ -13,7 +14,11 @@ def test_labels_count():
     ]
     nclasses = 5
     expected = [0, 3, 1, 3, 0]
+
+    #When
     result = voting.labels_count(annotations, nclasses)
+
+    #Then
     assert result == expected
 
 
@@ -41,3 +46,20 @@ def test_majority_vote_empty_item():
     expected = [1, MV, 2]
     result = voting.majority_vote(annotations)
     assert result == expected
+
+
+def test_label_frequency():
+    #Given
+    annotations = np.array(
+        [[1, 2, 3],
+         [-1, -1, -1],
+         [1, 2, 2]]
+    )
+    n_classes = 4
+    expected = np.array([2/6, 3/6, 1/6, 0/6])
+
+    #When
+    result = voting.labels_frequency(annotations, n_classes)
+
+    #Then
+    assert np.allclose(result, expected, rtol = 1e-6)

hands_on/pyanno_voting/pyanno/voting.py

@@ -100,3 +100,11 @@ def labels_frequency(annotations, nclasses):
         freq[k] is the frequency of elements of class k in `annotations`, i.e.
         their count over the number of total of observed (non-missing) elements
     """
+
+    result = np.array([0]*nclasses)
+    for val in np.array(annotations).flatten():
+        if val > 0:
+            result[val-1] += 1
+
+
+    return result/sum(result)