tests

Author: timtreis

tests/pl/test_render_shapes.py

@@ -689,47 +689,35 @@ def test_plot_can_handle_nan_values_in_color_data(self, sdata_blobs: SpatialData
         """Test that NaN values in color data are handled gracefully."""
         sdata_blobs["table"].obs["region"] = pd.Categorical(["blobs_circles"] * sdata_blobs["table"].n_obs)
         sdata_blobs["table"].uns["spatialdata_attrs"]["region"] = "blobs_circles"
-        
+
         # Add color column with NaN values
         sdata_blobs.shapes["blobs_circles"]["color_with_nan"] = [1.0, 2.0, np.nan, 4.0, 5.0]
-        
+
         # Test that rendering works with NaN values and issues warning
         with pytest.warns(UserWarning, match="Found 1 NaN values in color data"):
-            sdata_blobs.pl.render_shapes(
-                element="blobs_circles", 
-                color="color_with_nan", 
-                na_color="red"
-            ).pl.show()
+            sdata_blobs.pl.render_shapes(element="blobs_circles", color="color_with_nan", na_color="red").pl.show()
 
     def test_plot_colorbar_normalization_with_nan_values(self, sdata_blobs: SpatialData):
         """Test that colorbar normalization works correctly with NaN values."""
         sdata_blobs["table"].obs["region"] = pd.Categorical(["blobs_polygons"] * sdata_blobs["table"].n_obs)
         sdata_blobs["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
-        
+
         sdata_blobs.shapes["blobs_polygons"]["color_with_nan"] = [1.0, 2.0, np.nan, 4.0, 5.0]
-        
+
         # Test colorbar with NaN values - should use nanmin/nanmax
-        sdata_blobs.pl.render_shapes(
-            element="blobs_polygons", 
-            color="color_with_nan",
-            na_color="gray"
-        ).pl.show()
+        sdata_blobs.pl.render_shapes(element="blobs_polygons", color="color_with_nan", na_color="gray").pl.show()
 
     def test_plot_can_handle_non_numeric_radius_values(self, sdata_blobs: SpatialData):
         """Test that non-numeric radius values are handled gracefully."""
         sdata_blobs.shapes["blobs_circles"]["radius_mixed"] = [1.0, "invalid", 3.0, np.nan, 5.0]
-        
+
         sdata_blobs.pl.render_shapes(element="blobs_circles", color="red").pl.show()
 
     def test_plot_can_handle_mixed_numeric_and_color_data(self, sdata_blobs: SpatialData):
         """Test handling of mixed numeric and color-like data."""
         sdata_blobs["table"].obs["region"] = pd.Categorical(["blobs_circles"] * sdata_blobs["table"].n_obs)
         sdata_blobs["table"].uns["spatialdata_attrs"]["region"] = "blobs_circles"
-        
+
         sdata_blobs.shapes["blobs_circles"]["mixed_data"] = [1.0, 2.0, np.nan, "red", 5.0]
-        
-        sdata_blobs.pl.render_shapes(
-            element="blobs_circles", 
-            color="mixed_data",
-            na_color="gray"
-        ).pl.show()
+
+        sdata_blobs.pl.render_shapes(element="blobs_circles", color="mixed_data", na_color="gray").pl.show()

tests/pl/test_utils.py

@@ -1,5 +1,6 @@
 import matplotlib
 import matplotlib.pyplot as plt
+import numpy as np
 import pandas as pd
 import pytest
 import scanpy as sc
@@ -91,16 +92,17 @@ def test_is_color_like(color_result: tuple[ColorLike, bool]):
 
 def test_extract_scalar_value():
     """Test the new _extract_scalar_value function for robust numeric conversion."""
+
     from spatialdata_plot.pl.utils import _extract_scalar_value
-    
+
     # Test basic functionality
     assert _extract_scalar_value(3.14) == 3.14
     assert _extract_scalar_value(42) == 42.0
-    
+
     # Test with collections
     assert _extract_scalar_value(pd.Series([1.0, 2.0, 3.0])) == 1.0
     assert _extract_scalar_value([1.0, 2.0, 3.0]) == 1.0
-    
+
     # Test edge cases
     assert _extract_scalar_value(np.nan) == 0.0
     assert _extract_scalar_value("invalid") == 0.0
@@ -109,15 +111,18 @@ def test_extract_scalar_value():
 
 def test_plot_can_handle_per_row_rgba_colors(sdata_blobs: SpatialData):
     """Test handling of per-row RGBA color arrays."""
-    rgba_colors = np.array([
-        [1.0, 0.0, 0.0, 1.0],  # red
-        [0.0, 1.0, 0.0, 1.0],  # green
-        [0.0, 0.0, 1.0, 1.0],  # blue
-        [1.0, 1.0, 0.0, 1.0],  # yellow
-        [1.0, 0.0, 1.0, 1.0],  # magenta
-    ])
+
+    rgba_colors = np.array(
+        [
+            [1.0, 0.0, 0.0, 1.0],  # red
+            [0.0, 1.0, 0.0, 1.0],  # green
+            [0.0, 0.0, 1.0, 1.0],  # blue
+            [1.0, 1.0, 0.0, 1.0],  # yellow
+            [1.0, 0.0, 1.0, 1.0],  # magenta
+        ]
+    )
     sdata_blobs.shapes["blobs_circles"]["rgba_colors"] = rgba_colors.tolist()
-    
+
     sdata_blobs.pl.render_shapes(element="blobs_circles", color="rgba_colors").pl.show()