Merge pull request #230 from BiAPoL/add-more-tests

Add more tests

napari_clusters_plotter/_tests/test_plotter.py

@@ -1,4 +1,5 @@
 import numpy as np
+import pandas as pd
 from skimage import measure
 
 import napari_clusters_plotter as ncp
@@ -20,10 +21,7 @@
 from napari_clusters_plotter._utilities import get_layer_tabular_data, get_nice_colormap
 
 
-def test_plotting(make_napari_viewer):
-    viewer = make_napari_viewer()
-    widget_list = ncp.napari_experimental_provide_dock_widget()
-
+def get_labels_array():
     label = np.array(
         [
             [0, 0, 0, 0, 0, 0, 0],
@@ -35,30 +33,29 @@ def test_plotting(make_napari_viewer):
             [0, 7, 7, 0, 0, 0, 0],
         ]
     )
+    return label
+
+
+def test_plotting(make_napari_viewer):
+    viewer = make_napari_viewer()
+    widget_list = ncp.napari_experimental_provide_dock_widget()
 
-    # image = label * 1.5
+    label = get_labels_array()
 
     props = measure.regionprops_table(
         label, properties=(["label", "area", "perimeter"])
     )
 
     label_layer = viewer.add_labels(label, properties=props)
-    # image_layer = viewer.add_image(image)
 
     for widget in widget_list:
         _widget = widget(viewer)
-        # Doesn't work for now to use in tests because MeasureWidget uses cle function
-        # if isinstance(_widget, ncp._measure.MeasureWidget):
-        #     _widget.run(
-        #         image_layer, label_layer, "Measure now intensity shape", None, None
-        #     )
 
         if isinstance(_widget, ncp._plotter.PlotterWidget):
             plot_widget = _widget
 
     viewer.window.add_dock_widget(plot_widget)
     assert len(viewer.window._dock_widgets) == 1
-    # assert len(viewer.window._dock_widgets) == 2
 
     result = get_layer_tabular_data(label_layer)
 
@@ -145,3 +142,59 @@ def test_plotter_utilities():
 
     uc_plot_params = unclustered_plot_parameters(frame_ids, current_frame, n_datapoints)
     assert uc_plot_params == (result_au, result_su, result_cu)
+
+
+def test_plotting_histogram(make_napari_viewer):
+    from napari_clusters_plotter._plotter import PlotterWidget
+
+    viewer = make_napari_viewer()
+
+    label = get_labels_array()
+    measurements = measure.regionprops_table(
+        label, properties=(["label", "area", "perimeter"])
+    )
+    label_layer = viewer.add_labels(label, properties=measurements)
+    label_layer.features = measurements
+
+    viewer.window.add_dock_widget(PlotterWidget(viewer), area="right")
+    plotter_widget = PlotterWidget(viewer)
+    plotter_widget.plotting_type.setCurrentText("HISTOGRAM_2D")
+
+    plotter_widget.run(
+        features=pd.DataFrame(measurements),
+        plot_x_axis_name="area",
+        plot_y_axis_name="perimeter",
+        force_redraw=True,
+    )
+
+    assert plotter_widget.graphics_widget.axes.has_data()
+
+
+def test_cluster_image_generation_for_histogram(make_napari_viewer):
+    from napari_clusters_plotter._plotter import PlotterWidget
+
+    viewer = make_napari_viewer()
+
+    label = get_labels_array()
+    measurements = measure.regionprops_table(
+        label, properties=(["label", "area", "perimeter"])
+    )
+    measurements["MANUAL_CLUSTER_ID"] = np.array([1, 0, 2, -1, 0, 1, 2])
+    viewer.add_labels(label, properties=measurements)
+
+    viewer.window.add_dock_widget(PlotterWidget(viewer), area="right")
+    plotter_widget = PlotterWidget(viewer)
+    plotter_widget.plotting_type.setCurrentText("HISTOGRAM_2D")
+    plotter_widget.log_scale.value = True
+
+    plotter_widget.run(
+        features=pd.DataFrame(measurements),
+        plot_x_axis_name="area",
+        plot_y_axis_name="perimeter",
+        plot_cluster_name="MANUAL_CLUSTER_ID",
+        force_redraw=True,
+    )
+
+    assert plotter_widget.graphics_widget.axes.has_data()
+    assert "cluster_ids_in_space" in viewer.layers
+    assert int(viewer.layers["cluster_ids_in_space"].data.max()) == 3