Add tests for invalid ref_index for MaxSum and MaxMin

selector/methods/tests/test_distance.py

@@ -126,6 +126,21 @@ def test_maxmin():
  assert_equal(selected_mocked, [0, 1, 2, 3, 4, 5, 6, 7, 8, 16, 15, 10, 13, 9, 18])
 
 
+def test_maxmin_invalid_input():
+ """Testing MaxMin class with invalid input."""
+ # case when the distance matrix is not square
+ x_dist = np.array([[0, 1], [1, 0], [4, 9]])
+ with pytest.raises(ValueError):
+ collector = MaxMin(ref_index=0)
+ _ = collector.select(x_dist, size=2)
+
+ # case when the distance matrix is not symmetric
+ x_dist = np.array([[0, 1, 2], [1, 0, 3], [4, 9, 0], [5, 6, 7]])
+ with pytest.raises(ValueError):
+ collector = MaxMin(ref_index=0)
+ _ = collector.select(x_dist, size=2)
+
+
 def test_maxsum_clustered_data():
  """Testing MaxSum class."""
  # generate random data points belonging to multiple clusters - coordinates and class labels
@@ -206,6 +221,21 @@ def test_maxsum_non_clustered_data():
  selected_ids = collector.select(coords, size=12)
 
 
+def test_maxsum_invalid_input():
+ """Testing MaxSum class with invalid input."""
+ # case when the distance matrix is not square
+ x_dist = np.array([[0, 1], [1, 0], [4, 9]])
+ with pytest.raises(ValueError):
+ collector = MaxSum(ref_index=0)
+ _ = collector.select(x_dist, size=2)
+
+ # case when the distance matrix is not symmetric
+ x_dist = np.array([[0, 1, 2], [1, 0, 3], [4, 9, 0], [5, 6, 7]])
+ with pytest.raises(ValueError):
+ collector = MaxSum(ref_index=0)
+ _ = collector.select(x_dist, size=2)
+
+
 def test_optisim():
  """Testing OptiSim class."""
  # generate random data points belonging to one cluster - coordinates and pairwise distance matrix