Fix path_length silently ignored in CalculateImageStats

pyopia/__init__.py

@@ -1 +1 @@
-__version__ = "2.16.6"
+__version__ = "2.16.7"

pyopia/process.py

@@ -734,7 +734,7 @@ def __call__(self, data):
         d50 = pyopia.statistics.d50_from_stats(data['stats'], pixel_size)
         data['image_stats'].loc[data['timestamp'], 'd50'] = d50
 
-        path_length = getattr(data['settings']['general'], 'path_length', 40)
+        path_length = data['settings']['general'].get('path_length', 40)
         if path_length is not None:
             # Get image dimensions from the corrected image
             image = data.get('imraw')

pyopia/tests/test_pipeline.py

@@ -189,6 +189,54 @@ def test_silcam_pipeline():
                                                      ' Something has altered the number of particles detected')
 
 
+def test_calculate_image_stats_uses_configured_path_length():
+    '''Verifies CalculateImageStats uses the path_length configured in general settings,
+    rather than silently falling back to the default of 40mm.
+
+    Regression test: data['settings']['general'] is a plain dict, so a previous
+    implementation using getattr(general, 'path_length', 40) always returned the
+    default, silently ignoring any configured path_length.
+    '''
+    import pandas as pd
+    from pyopia.statistics import nc_vc_from_stats
+
+    pixel_size = 28.0
+    path_length = 123.0  # deliberately not the default of 40, to catch silent fallback
+    imy, imx = 100, 200
+
+    timestamp = pd.Timestamp('2026-01-01T00:00:00')
+    stats = pd.DataFrame({
+        'major_axis_length': [10.0],
+        'minor_axis_length': [8.0],
+        'equivalent_diameter': [9.0],
+        'saturation': [1.0],
+        'export_name': ['D20260101T000000.000000-PN0'],
+        'timestamp': [timestamp],
+    })
+
+    data = {
+        'settings': {'general': {'pixel_size': pixel_size, 'path_length': path_length}},
+        'imraw': np.zeros((imy, imx, 3), dtype=np.uint8),
+        'stats': stats,
+        'timestamp': timestamp,
+    }
+
+    step = pyopia.process.CalculateImageStats()
+    data = step(data)
+
+    expected_nc, expected_vc, expected_sample_volume, expected_junge = nc_vc_from_stats(
+        stats, pixel_size, path_length, imx=imx, imy=imy)
+
+    result = data['image_stats'].loc[data['timestamp']]
+    np.testing.assert_allclose(result['vc'], expected_vc)
+    np.testing.assert_allclose(result['sample_volume'], expected_sample_volume)
+
+    # Sanity check that this isn't coincidentally matching the old (broken) default of 40mm
+    wrong_nc, wrong_vc, wrong_sample_volume, wrong_junge = nc_vc_from_stats(
+        stats, pixel_size, 40, imx=imx, imy=imy)
+    assert not np.isclose(result['vc'], wrong_vc)
+
+
 def test_per_class_concentration():
     '''Verifies PerClassConcentration writes timestamp-indexed per-class
     number concentrations (numbers/L) to CSV across multiple images.