add C# interface module, closes #4

src/dopt_sensor_anomalies/_csharp_interface.py

@@ -0,0 +1,14 @@
+from dopt_sensor_anomalies import detection
+
+
+def sensor_anomalies_detection(
+    user_img_path: str,
+    pixels_per_metric_X: float,
+    pixels_per_metric_Y: float,
+) -> None:
+    res = detection.pipeline(
+        user_img_path=user_img_path,
+        pixels_per_metric_X=pixels_per_metric_X,
+        pixels_per_metric_Y=pixels_per_metric_Y,
+    )
+    res.unwrap()

tests/_results/csharp_interface/window_19_fail_model.csv

@@ -0,0 +1 @@
+1177,318;804,803;947509,0;876,575;808,853;709020,9;952,191;804,781;766305,3;944,223;792,829;748607,2;838,797;804,902;675148,9;1203,187;792,829;953921,4;0;0

tests/test_csharp_interface.py

@@ -0,0 +1,64 @@
+import shutil
+from unittest.mock import patch
+
+import pytest
+
+from dopt_sensor_anomalies import _csharp_interface, constants, errors
+
+
+@patch("dopt_sensor_anomalies._find_paths.STOP_FOLDER_NAME", "lib")
+def test_sensor_anomalies_detection_FailImagePath(setup_temp_dir):
+    img_path = str(setup_temp_dir / "not-existing.bmp")
+    pixels_per_metric_X: float = 0.251
+    pixels_per_metric_Y: float = 0.251
+
+    MESSAGE = "The provided path seems not to exist"
+
+    with pytest.raises(FileNotFoundError, match=MESSAGE):
+        _csharp_interface.sensor_anomalies_detection(
+            img_path, pixels_per_metric_X, pixels_per_metric_Y
+        )
+
+
+@patch("dopt_sensor_anomalies._find_paths.STOP_FOLDER_NAME", "lib")
+def test_sensor_anomalies_detection_FailElectrodeCount(path_img_with_failure_ElectrodeCount):
+    img_path = str(path_img_with_failure_ElectrodeCount)
+    pixels_per_metric_X: float = 0.251
+    pixels_per_metric_Y: float = 0.251
+
+    MESSAGE = "Number of counted electrodes does not match the"
+
+    with pytest.raises(errors.InvalidElectrodeCount, match=MESSAGE):
+        _csharp_interface.sensor_anomalies_detection(
+            img_path, pixels_per_metric_X, pixels_per_metric_Y
+        )
+
+
+@patch("dopt_sensor_anomalies._find_paths.STOP_FOLDER_NAME", "lib")
+def test_sensor_anomalies_detection_Success(
+    results_folder, path_img_with_failure_TrainedModel
+):
+    # paths: check files for existence and delete because of other tests
+    root_img = path_img_with_failure_TrainedModel.parent
+    file_stem = path_img_with_failure_TrainedModel.stem
+    csv_file = root_img / f"{file_stem}.csv"
+    heatmap_file = root_img / f"{file_stem}{constants.HEATMAP_FILENAME_SUFFIX}.png"
+    if csv_file.exists():
+        csv_file.unlink()
+    if heatmap_file.exists():
+        heatmap_file.unlink()
+
+    img_path = str(path_img_with_failure_TrainedModel)
+    pixels_per_metric_X: float = 0.251
+    pixels_per_metric_Y: float = 0.251
+
+    _csharp_interface.sensor_anomalies_detection(
+        img_path, pixels_per_metric_X, pixels_per_metric_Y
+    )
+
+    assert csv_file.exists()
+    assert heatmap_file.exists()
+    target_folder = results_folder / "csharp_interface"
+    target_folder.mkdir(exist_ok=True)
+    shutil.copy(csv_file, (target_folder / csv_file.name))
+    shutil.copy(heatmap_file, (target_folder / heatmap_file.name))

tests/test_detection.py

@@ -150,6 +150,16 @@ def test_full_pipeline_wrapped_FailElectrodeCount(path_img_with_failure_Electrod
 
 @patch("dopt_sensor_anomalies._find_paths.STOP_FOLDER_NAME", "lib")
 def test_full_pipeline_wrapped_Success(results_folder, path_img_with_failure_TrainedModel):
+    # paths: check files for existence and delete because of other tests
+    root_img = path_img_with_failure_TrainedModel.parent
+    file_stem = path_img_with_failure_TrainedModel.stem
+    csv_file = root_img / f"{file_stem}.csv"
+    heatmap_file = root_img / f"{file_stem}{constants.HEATMAP_FILENAME_SUFFIX}.png"
+    if csv_file.exists():
+        csv_file.unlink()
+    if heatmap_file.exists():
+        heatmap_file.unlink()
+
     img_path = str(path_img_with_failure_TrainedModel)
     pixels_per_metric_X: float = 0.251
     pixels_per_metric_Y: float = 0.251
@@ -159,11 +169,6 @@ def test_full_pipeline_wrapped_Success(results_folder, path_img_with_failure_Tra
     assert ret.status.code == 0
     assert ret.status.ExceptionType is None
 
-    # check files for existence
-    root_img = path_img_with_failure_TrainedModel.parent
-    file_stem = path_img_with_failure_TrainedModel.stem
-    csv_file = root_img / f"{file_stem}.csv"
-    heatmap_file = root_img / f"{file_stem}{constants.HEATMAP_FILENAME_SUFFIX}.png"
     assert csv_file.exists()
     assert heatmap_file.exists()
     shutil.copy(csv_file, (results_folder / csv_file.name))