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Preserve Categorical dtype for color_vector with non-unique colors #542

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Merged
timtreis merged 2 commits into from
Mar 5, 2026
+7 −6
Merged

Preserve Categorical dtype for color_vector with non-unique colors #542

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5f9bb16
Preserve Categorical dtype for color_vector with non-unique colors
timtreis Mar 5, 2026
75d3dfa
Unify categorical type checks to isinstance(dtype, CategoricalDtype)
timtreis Mar 5, 2026
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6 changes: 2 additions & 4 deletions src/spatialdata_plot/pl/render.py
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Original file line number Diff line number Diff line change
Expand Up @@ -358,8 +358,7 @@ def _render_shapes(

color_key = (
[_hex_no_alpha(x) for x in color_vector.categories.values]
if (type(color_vector) is pd.core.arrays.categorical.Categorical)
and (len(color_vector.categories.values) > 1)
if isinstance(color_vector.dtype, pd.CategoricalDtype) and (len(color_vector.categories.values) > 1)
else None
)

Expand Down Expand Up @@ -854,8 +853,7 @@ def _render_points(

color_key: list[str] | None = (
list(color_vector.categories.values)
if (type(color_vector) is pd.core.arrays.categorical.Categorical)
and (len(color_vector.categories.values) > 1)
if isinstance(color_vector.dtype, pd.CategoricalDtype) and (len(color_vector.categories.values) > 1)
else None
)

Expand Down
7 changes: 5 additions & 2 deletions src/spatialdata_plot/pl/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1120,7 +1120,10 @@ def _set_color_source_vec(
raise ValueError("Unable to create color palette.")

# do not rename categories, as colors need not be unique
color_vector = color_source_vector.map(color_mapping)
# pd.Categorical.map() demotes to object dtype when mapped values aren't unique
# (e.g. two categories share a color). Wrapping back in pd.Categorical ensures
# downstream consumers always receive a Categorical for categorical data.
color_vector = pd.Categorical(color_source_vector.map(color_mapping, na_action="ignore"))

return color_source_vector, color_vector, True

Expand All @@ -1146,7 +1149,7 @@ def _map_color_seg(
) -> ArrayLike:
cell_id = np.array(cell_id)

if pd.api.types.is_categorical_dtype(color_vector.dtype):
if isinstance(color_vector.dtype, pd.CategoricalDtype):
# Case A: users wants to plot a categorical column
if np.any(color_source_vector.isna()):
cell_id[color_source_vector.isna()] = 0
Expand Down