Add data_analysis/tests/test_core.py

data_analysis/tests/test_core.py

@@ -0,0 +1,61 @@
+import pytest
+import math
+from data_analysis import core
+
+@pytest.fixture
+def sample_raw_data():
+    return [
+        {"intensity": 100.0, "background_noise": 10.0},
+        {"intensity": 150.0, "background_noise": 15.0},
+        {"intensity": 200.0, "background_noise": 20.0}
+    ]
+
+@pytest.fixture
+def sample_reference_data():
+    return [
+        {"intensity": 5.0, "background_noise": 0.0},
+        {"intensity": 10.0, "background_noise": 0.0},
+        {"intensity": 15.0, "background_noise": 0.0}
+    ]
+
+def test_correct_flourescence_basic(sample_raw_data):
+    corrected = core.correct_flourescence(sample_raw_data)
+    assert isinstance(corrected, list)
+    assert all(isinstance(p, dict) for p in corrected)
+    assert len(corrected) == len(sample_raw_data)
+    
+    for p in corrected:
+        assert 'intensity' in p and 'background_noise' in p
+        assert p['intensity'] <= 200.0
+
+def test_correct_flourescence_input_validation():
+    with pytest.raises((TypeError, ValueError)):
+        core.correct_flourescence(None)
+    with pytest.raises((TypeError, ValueError)):
+        core.correct_flourescence([{"intensity": "bad", "background_noise": 1.0}])
+
+def test_substract_reference_valid(sample_raw_data, sample_reference_data):
+    corr = core.correct_flourescence(sample_raw_data)
+    result = core.substract_reference(corr, sample_reference_data)
+    assert isinstance(result, list)
+    assert len(result) == len(sample_reference_data)
+
+    for dp in result:
+        assert 'intensity' in dp
+        assert isinstance(dp['intensity'], float)
+        assert not math.isnan(dp['intensity'])
+
+
+def test_substract_reference_error_cases(sample_raw_data):
+    with pytest.raises((TypeError, ValueError)):
+        core.substract_reference(sample_raw_data, None)
+    with pytest.raises((TypeError, ValueError)):
+        core.substract_reference(None, sample_raw_data)
+
+
+def test_substract_reference_results_decrease(sample_raw_data, sample_reference_data):
+    corr = core.correct_flourescence(sample_raw_data)
+    result = core.substract_reference(corr, sample_reference_data)
+    for original, ref, res in zip(corr, sample_reference_data, result):
+        expected = original['intensity'] - ref['intensity']
+        assert pytest.approx(res['intensity'], rel=1e-6) == expected