[TEST] restructure tests

test for functions from a specific python file are grouped together in the same structure under unit tests, larger workflow tests are add in e2e testing

tests/unit_tests/pipeline/test_base.py

@@ -0,0 +1,54 @@
+#######################################################
+# Unit tests for ../pipeline/base.py
+#######################################################
+
+import os
+import tempfile
+
+from scportrait.pipeline._base import Logable, ProcessingStep
+
+
+def test_logable_init():
+    with tempfile.TemporaryDirectory() as temp_dir:
+        logable = Logable(directory=temp_dir, debug=False)
+        assert not logable.debug
+
+
+def test_logable_log():
+    with tempfile.TemporaryDirectory() as temp_dir:
+        logable = Logable(directory=temp_dir, debug=True)
+        logable.log("Testing")
+
+        log_path = os.path.join(temp_dir, logable.DEFAULT_LOG_NAME)
+        assert os.path.isfile(log_path)
+
+        with open(log_path) as f:
+            log_content = f.read()
+            assert "Testing" in log_content
+
+
+def test_processing_step_init():
+    config = {"setting1": "value1"}
+    with tempfile.TemporaryDirectory() as temp_dir:
+        processing_step = ProcessingStep(config, f"{temp_dir}/test_step", temp_dir, debug=True)
+
+        assert processing_step.debug
+        assert config == processing_step.config
+
+
+def test_processing_step_register_parameter():
+    config = {"setting1": "value1"}
+    with tempfile.TemporaryDirectory() as temp_dir:
+        processing_step = ProcessingStep(config, f"{temp_dir}/test_step", temp_dir)
+
+        # Test registering a new parameter
+        processing_step.register_parameter("setting2", "value2")
+        assert "setting2" in processing_step.config
+        assert "value2" == processing_step.config["setting2"]
+
+
+def test_processing_step_get_directory():
+    config = {"setting1": "value1"}
+    with tempfile.TemporaryDirectory() as temp_dir:
+        processing_step = ProcessingStep(config, f"{temp_dir}/test_step", temp_dir)
+        assert f"{temp_dir}/test_step" == processing_step.get_directory()

tests/processing_test.py → tests/unit_tests/pipeline/test_pipeline_utils_segmentation.py

@@ -6,7 +6,7 @@
 from skimage import data  # test datasets for segmentation testing
 
 #######################################################
-# Unit tests for ../proccessing/segmentation.py
+# Unit tests for scportrait.pipeline._utils.segmentation
 #######################################################
 from scportrait.pipeline._utils.segmentation import (
     _segment_threshold,
@@ -213,159 +213,3 @@ def test_numba_mask_centroid():
     assert np.allclose(centers, expected_centers, atol=1e-6)
     assert np.all(points_class == expected_points_class)
     assert np.all(ids == expected_ids)
-
-
-#######################################################
-# Unit tests for ../proccessing/preprocessing.py
-#######################################################
-
-from scportrait.processing.images._image_processing import (
-    MinMax,
-    _percentile_norm,
-    percentile_normalization,
-    rolling_window_mean,
-)
-
-
-def test_percentile_norm():
-    rng = np.random.default_rng()
-    img = rng.random((4, 4))
-    norm_img = _percentile_norm(img, 0.1, 0.9)
-    assert np.min(norm_img) == pytest.approx(0)
-    assert np.max(norm_img) == pytest.approx(1)
-
-
-def test_percentile_normalization_C_H_W():
-    rng = np.random.default_rng()
-    test_array = rng.integers(2, size=(3, 100, 100))
-    test_array[:, 10:11, 10:11] = -1
-    test_array[:, 12:13, 12:13] = 3
-
-    normalized = percentile_normalization(test_array, 0.05, 0.95)
-    assert np.max(normalized) == pytest.approx(1)
-    assert np.min(normalized) == pytest.approx(0)
-
-
-def test_percentile_normalization_H_W():
-    rng = np.random.default_rng()
-    test_array = rng.integers(2, size=(100, 100))
-    test_array[10:11, 10:11] = -1
-    test_array[12:13, 12:13] = 3
-
-    normalized = percentile_normalization(test_array, 0.05, 0.95)
-    assert np.max(normalized) == pytest.approx(1)
-    assert np.min(normalized) == pytest.approx(0)
-
-
-def test_rolling_window_mean():
-    rng = np.random.default_rng()
-    array = rng.random((10, 10))
-    rolling_array = rolling_window_mean(array, size=5, scaling=False)
-    assert np.all(array.shape == rolling_array.shape)
-
-
-def test_MinMax():
-    rng = np.random.default_rng()
-    array = rng.random((10, 10))
-    normalized_array = MinMax(array)
-    assert np.min(normalized_array) == 0
-    assert np.max(normalized_array) == 1
-
-
-#######################################################
-# Unit tests for ../proccessing/utils.py
-#######################################################
-
-from scportrait.pipeline._utils.helper import flatten
-from scportrait.plotting.vis import plot_image, visualize_class
-
-
-def test_flatten():
-    nested_list = [[1, 2, 3], [4, 5], [6, 7, 8, 9]]
-    expected_output = [1, 2, 3, 4, 5, 6, 7, 8, 9]
-    assert flatten(nested_list) == expected_output
-
-
-def test_visualize_class():
-    class_ids = [1, 2]
-    seg_map = np.array([[0, 1, 0], [1, 2, 1], [2, 0, 1]])
-    rng = np.random.default_rng()
-    background = rng.random((3, 3)) * 255
-    # Since this function does not return anything, we just check if it produces any exceptions
-    try:
-        visualize_class(class_ids, seg_map, background)
-    except (ValueError, TypeError) as e:
-        pytest.fail(f"visualize_class raised exception: {str(e)}")
-
-
-def test_plot_image(tmpdir):
-    rng = np.random.default_rng()
-    array = rng.random((10, 10))
-    save_name = tmpdir.join("test_plot_image")
-
-    # Since this function does not return anything, we just check if it produces any exceptions
-    try:
-        plot_image(array, size=(5, 5), save_name=save_name)
-    except (OSError, ValueError, TypeError) as e:
-        pytest.fail(f"plot_image raised exception: {str(e)}")
-    assert os.path.isfile(str(save_name) + ".png")
-
-
-#######################################################
-# Unit tests for ../pipeline/base.py
-#######################################################
-
-import tempfile
-
-from scportrait.pipeline._base import Logable, ProcessingStep
-
-
-def test_logable_init():
-    with tempfile.TemporaryDirectory() as temp_dir:
-        logable = Logable(directory=temp_dir, debug=False)
-        assert not logable.debug
-
-
-def test_logable_log():
-    with tempfile.TemporaryDirectory() as temp_dir:
-        logable = Logable(directory=temp_dir, debug=True)
-        logable.log("Testing")
-
-        log_path = os.path.join(temp_dir, logable.DEFAULT_LOG_NAME)
-        assert os.path.isfile(log_path)
-
-        with open(log_path) as f:
-            log_content = f.read()
-            assert "Testing" in log_content
-
-
-def test_processing_step_init():
-    config = {"setting1": "value1"}
-    with tempfile.TemporaryDirectory() as temp_dir:
-        processing_step = ProcessingStep(config, f"{temp_dir}/test_step", temp_dir, debug=True)
-
-        assert processing_step.debug
-        assert config == processing_step.config
-
-
-def test_processing_step_register_parameter():
-    config = {"setting1": "value1"}
-    with tempfile.TemporaryDirectory() as temp_dir:
-        processing_step = ProcessingStep(config, f"{temp_dir}/test_step", temp_dir)
-
-        # Test registering a new parameter
-        processing_step.register_parameter("setting2", "value2")
-        assert "setting2" in processing_step.config
-        assert "value2" == processing_step.config["setting2"]
-
-
-def test_processing_step_get_directory():
-    config = {"setting1": "value1"}
-    with tempfile.TemporaryDirectory() as temp_dir:
-        processing_step = ProcessingStep(config, f"{temp_dir}/test_step", temp_dir)
-        assert f"{temp_dir}/test_step" == processing_step.get_directory()
-
-
-# general test to check that testing is working
-def test_test():
-    assert 1 == 1

tests/unit_tests/pipeline/test_utils_helper.py

@@ -0,0 +1,11 @@
+#######################################################
+# Unit tests for ../pipeline/_utils/helper.py
+#######################################################
+
+from scportrait.pipeline._utils.helper import flatten
+
+
+def test_flatten():
+    nested_list = [[1, 2, 3], [4, 5], [6, 7, 8, 9]]
+    expected_output = [1, 2, 3, 4, 5, 6, 7, 8, 9]
+    assert flatten(nested_list) == expected_output

tests/unit_tests/plotting/test_plotting_vis.py

@@ -0,0 +1,34 @@
+#######################################################
+# Unit tests for ../plotting/vis.py
+#######################################################
+import os
+
+import numpy as np
+import pytest
+
+from scportrait.plotting.vis import plot_image, visualize_class
+
+
+def test_visualize_class():
+    class_ids = [1, 2]
+    seg_map = np.array([[0, 1, 0], [1, 2, 1], [2, 0, 1]])
+    rng = np.random.default_rng()
+    background = rng.random((3, 3)) * 255
+    # Since this function does not return anything, we just check if it produces any exceptions
+    try:
+        visualize_class(class_ids, seg_map, background)
+    except (ValueError, TypeError) as e:
+        pytest.fail(f"visualize_class raised exception: {str(e)}")
+
+
+def test_plot_image(tmpdir):
+    rng = np.random.default_rng()
+    array = rng.random((10, 10))
+    save_name = tmpdir.join("test_plot_image")
+
+    # Since this function does not return anything, we just check if it produces any exceptions
+    try:
+        plot_image(array, size=(5, 5), save_name=save_name)
+    except (OSError, ValueError, TypeError) as e:
+        pytest.fail(f"plot_image raised exception: {str(e)}")
+    assert os.path.isfile(str(save_name) + ".png")