add radius and translations tests, refactor code

multi_imbalance/resampling/ccr.py

@@ -88,9 +88,9 @@ def _calculate_radius_and_translations(self, minority_examples, majority_example
  current_example = 0
  number_of_points_in_radius = 1
 
- while current_example != majority_count and energy > 0:
- example_distance_index = sorted_distances_index[current_example]
- distance = distances[example_distance_index]
+ while current_example < majority_count and energy > 0:
+ majority_distance_index = sorted_distances_index[current_example]
+ distance = distances[majority_distance_index]
  if distance <= r[i]:
  number_of_points_in_radius += 1
  dr = energy / number_of_points_in_radius

tests/resampling/test_ccr.py

@@ -33,14 +33,14 @@
 ])
 
 multiclass_X = np.vstack(
-  [
-  np.random.normal(0, 1, (100, 2)),
-  np.random.normal(3, 5, (30, 2)),
-  np.random.normal(-2, 2, (20, 2)),
-  np.random.normal(-4, 1, (10, 2)),
-  np.random.normal(10, 1, (5, 2)),
-  ]
- )
+ [
+ np.random.normal(0, 1, (100, 2)),
+ np.random.normal(3, 5, (30, 2)),
+ np.random.normal(-2, 2, (20, 2)),
+ np.random.normal(-4, 1, (10, 2)),
+ np.random.normal(10, 1, (5, 2)),
+ ]
+)
 
 multiclass_y = np.array([1] * 100 + [2] * 30 + [3] * 20 + [4] * 10 + [5] * 5)
 
@@ -51,6 +51,44 @@ def test_compare_cleaning_results_to_original_article_implementation():
  assert_array_equal(np.sort(resampled_X[:X.shape[0]], axis=0), np.sort(original_cleaning_results, axis=0))
 
 
+def test_radius_equal_to_energy_and_translations_equal_zero_when_majority_not_in_range():
+ clf = CCR(energy=0.5)
+ minority_examples = np.array([[0, 0]])
+ majority_examples = np.array([[1, 1], [-1, -1]])
+ r, t = clf._calculate_radius_and_translations(minority_examples, majority_examples)
+
+ assert_array_equal(r, np.array([0.5]))
+ assert_array_equal(t, np.array([[0, 0], [0, 0]]))
+
+def test_radius_decreases_and_translation_nonequal_zero_when_majority_in_range():
+ clf = CCR(energy=1)
+ minority_examples = np.array([[0, 0]])
+ majority_examples = np.array([[0.5, 0], [1, 0]])
+ r, t = clf._calculate_radius_and_translations(minority_examples, majority_examples)
+
+ assert_array_equal(r, np.array([0.75]))
+ assert_array_equal(t, np.array([[0.25, 0], [0, 0]]))
+
+
+def test_energy_cost_should_be_inversely_proportional_to_number_of_examples_in_radius():
+ clf = CCR(energy=10)
+ minority_examples = np.array([[0, 0]])
+ majority_examples = np.array([[0.5, 0], [1, 0], [1.5, 0], [2, 0], [2.5, 0]])
+ r, t = clf._calculate_radius_and_translations(minority_examples, majority_examples)
+
+ print(np.array([[2.5+2.5/6, 0]]) - majority_examples)
+ assert_array_equal(r, np.array([3]))
+ assert_array_equal(t, np.array([[2.5, 0], [2, 0], [1.5, 0], [1, 0], [0.5, 0]]))
+
+
+def test_translations_should_accumulate():
+ clf = CCR(energy=1)
+ minority_examples = np.array([[0, 0], [2, 0]])
+ majority_examples = np.array([[1, 0]])
+ _, t = clf._calculate_radius_and_translations(minority_examples, majority_examples)
+ assert_array_equal(t, np.array([[0, 0]]))
+
+
 def test_multiclass_ccr_call_count():
  clf = MultiClassCCR(energy=0.5)