Coverage for tests/test_integration.py: 0%

1import os 

2import unittest 

3 

4import pytest 

5import torch 

6from torch.utils.data import DataLoader 

7 

8from copick_torch import CopickDataset 

9 

10# This test requires actual data 

11# Skip it if the test config file is not available 

12TEST_CONFIG_PATH = os.environ.get("COPICK_TEST_CONFIG", "./examples/czii_object_detection_training.json") 

13 

14 

15@pytest.mark.skipif(not os.path.exists(TEST_CONFIG_PATH), reason="Test config file not available") 

16class TestIntegration(unittest.TestCase): 

17 """Integration tests that require actual data. 

18 

19 These tests will be skipped if the test data is not available. 

20 """ 

21 

22 def setUp(self): 

23 # Create a cache directory if it doesn't exist 

24 self.cache_dir = os.path.join(os.path.dirname(__file__), "test_cache") 

25 os.makedirs(self.cache_dir, exist_ok=True) 

26 

27 def test_dataset_with_real_data(self): 

28 """Test dataset with real data if available.""" 

29 # Skip if data not available 

30 if not os.path.exists(TEST_CONFIG_PATH): 

31 self.skipTest("Test config file not available") 

32 

33 # Initialize dataset with small boxsize and limited samples for faster testing 

34 dataset = CopickDataset( 

35 config_path=TEST_CONFIG_PATH, 

36 boxsize=(16, 16, 16), 

37 augment=False, 

38 cache_dir=self.cache_dir, 

39 max_samples=5, 

40 ) 

41 

42 # If no data was loaded (possibly because tomograms couldn't be accessed), 

43 # skip the test instead of failing 

44 if len(dataset) == 0: 

45 self.skipTest("No data could be loaded from the test configuration") 

46 

47 # Test accessing an item only if dataset is not empty 

48 if len(dataset) > 0: 

49 volume, label = dataset[0] 

50 self.assertIsInstance(volume, torch.Tensor) 

51 self.assertEqual(volume.shape[0], 1) # Check channel dimension 

52 

53 # Test dataloader 

54 dataloader = DataLoader(dataset, batch_size=2) 

55 batch = next(iter(dataloader)) 

56 self.assertEqual(len(batch), 2) # Input and label 

57 self.assertEqual(batch[0].shape[0], min(2, len(dataset))) # Batch dimension 

58 

59 def test_examples_method(self): 

60 """Test the examples method with real data if available.""" 

61 # Skip if data not available 

62 if not os.path.exists(TEST_CONFIG_PATH): 

63 self.skipTest("Test config file not available") 

64 

65 # Initialize dataset 

66 dataset = CopickDataset( 

67 config_path=TEST_CONFIG_PATH, 

68 boxsize=(16, 16, 16), 

69 augment=False, 

70 cache_dir=self.cache_dir, 

71 max_samples=5, 

72 ) 

73 

74 # If no data was loaded, skip the test 

75 if len(dataset) == 0: 

76 self.skipTest("No data could be loaded from the test configuration") 

77 

78 # Get examples 

79 examples, class_names = dataset.examples() 

80 

81 # Check that we got examples for each class 

82 if examples is not None: 

83 self.assertEqual(len(examples), len(class_names)) 

84 self.assertIsInstance(examples, torch.Tensor) 

85 self.assertEqual(examples.shape[1], 1) # Channel dimension 

86 self.assertEqual(examples.shape[2:], (16, 16, 16)) # Spatial dimensions 

87 

88 

89if __name__ == "__main__": 

90 unittest.main()