tests package
Submodules
tests.test_CLiMB module
- class tests.test_CLiMB.TestCLiMB(methodName='runTest')
Bases:
TestCase- setUp()
Create synthetic datasets for testing
- test_builder_setters()
Test builder pattern setters
- test_fit_blobs()
Test fitting on blob dataset
- test_fit_mixed()
Test fitting on mixed dataset with known and unknown clusters
- test_initialization()
Test proper initialization of CLiMB
- test_inverse_transform()
Test inverse transform of scaled data
- test_visualization()
Test visualization methods
- test_with_known_labels()
Test with known labels for matching
tests.test_KBound module
- class tests.test_KBound.TestKBound(methodName='runTest')
Bases:
TestCase- setUp()
Hook method for setting up the test fixture before exercising it.
- test_fit_custom_metric()
Test fit method with custom distance metric.
- test_fit_dict_seeds()
Test fit method with dictionary of seed points.
- test_fit_mahalanobis_metric_auto_vi()
Test fit method with Mahalanobis distance metric and automatic VI calculation.
- test_fit_mahalanobis_metric_precomputed_vi()
Test fit method with Mahalanobis distance metric and pre-computed VI.
- test_fit_no_seeds()
Test fit method with no seeds.
- test_fit_with_known_labels()
Test fit method with known labels.
- test_fit_with_seed_dict_does_not_raise_attribute_error()
Tests that KBound.fit() does not raise an AttributeError when initialized with a dictionary of seed points. This replicates a bug where a list was not converted to a NumPy array internally.
- test_initialization_custom_params()
Test initialization with custom parameters.
- test_initialization_default()
Test initialization with default parameters.
- test_invalid_custom_metric_params()
Test ValueError when metric_params is missing for custom metric.
- test_invalid_mahalanobis_params()
Test ValueError when metric_params is missing for Mahalanobis.
- test_post_process_seeds_dict()
Test _post_process_seeds with dictionary seeds.
- test_unsupported_metric()
Test ValueError for unsupported distance metric.
tests.test_exploratory module
- class tests.test_exploratory.TestExploratoryAlgorithms(methodName='runTest')
Bases:
TestCaseTests for specific exploratory clustering algorithms
- setUp()
Create synthetic datasets for testing
- test_algorithm_comparison()
Compare different exploratory algorithms on complex shapes
- test_dbscan_exploratory()
Test DBSCANExploratory algorithm
- test_exploratory_integration()
Test integration with CLiMB main class
- test_hdbscan_exploratory()
Test HDBSCANExploratory algorithm
- test_optics_exploratory()
Test OPTICSExploratory algorithm