Add invalid tests for distance based methods

selector/methods/tests/test_distance.py

@@ -135,7 +135,7 @@ def test_maxmin_invalid_input():
  _ = 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]])
+ x_dist = np.array([[0, 1, 2, 1], [1, 1, 0, 3], [4, 9, 4, 0], [6, 5, 6, 7]])
  with pytest.raises(ValueError):
  collector = MaxMin(ref_index=0)
  _ = collector.select(x_dist, size=2)
@@ -229,12 +229,18 @@ def test_maxsum_invalid_input():
  collector = MaxSum(ref_index=0)
  _ = collector.select(x_dist, size=2)
 
- # case when the distance matrix is not symmetric
+ # case when the distance matrix is not square
  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)
 
+ # case when the distance matrix is not symmetric
+ x_dist = np.array([[0, 1, 2, 1], [1, 1, 0, 3], [4, 9, 4, 0], [6, 5, 6, 7]])
+ with pytest.raises(ValueError):
+ collector = MaxSum(ref_index=0)
+ _ = collector.select(x_dist, size=2)
+
 
 def test_optisim():
  """Testing OptiSim class."""
@@ -270,13 +276,18 @@ def test_optisim():
  # make sure all the selected indices are the same with expectation
  assert_equal(selected_ids, [0, 8, 55, 37, 41, 13, 12, 42, 6, 30, 57, 76])
 
- # tester to check if OptiSim gives same results as MaxMin for k=>infinity
+ # check if OptiSim gives same results as MaxMin for k=>infinity
  collector = OptiSim(ref_index=85, k=999999)
  selected_ids_optisim = collector.select(coords, size=12)
  collector = MaxMin()
  selected_ids_maxmin = collector.select(arr_dist, size=12)
  assert_equal(selected_ids_optisim, selected_ids_maxmin)
 
+ # test with invalid ref_index
+ with pytest.raises(ValueError):
+ collector = OptiSim(ref_index=10000)
+ _ = collector.select(coords, size=12)
+
 
 def test_directed_sphere_size_error():
  """Test DirectedSphereExclusion error when too many points requested."""