uniform color handling between labels and points/shapes

Author: Sonja Stockhaus

src/spatialdata_plot/pl/basic.py

@@ -598,7 +598,7 @@ def render_labels(
         norm: Normalize | None = None,
         na_color: ColorLike | None = "default",
         outline_alpha: float | int = 0.0,
-        fill_alpha: float | int = 0.4,
+        fill_alpha: float | int | None = None,
         scale: str | None = None,
         table_name: str | None = None,
         table_layer: str | None = None,
@@ -643,8 +643,9 @@ def render_labels(
             won't be shown.
         outline_alpha : float | int, default 0.0
             Alpha value for the outline of the labels. Invisible by default.
-        fill_alpha : float | int, default 0.4
-            Alpha value for the fill of the labels.
+        fill_alpha : float | int, optional.
+            Alpha value for the fill of the labels. When no alpha is implied by the passed color, a default value of 0.4
+            is used.
         scale :  str | None
             Influences the resolution of the rendering. Possibilities for setting this parameter:
                 1) None (default). The image is rasterized to fit the canvas size. For multiscale images, the best scale
@@ -702,6 +703,7 @@ def render_labels(
             sdata.plotting_tree[f"{n_steps + 1}_render_labels"] = LabelsRenderParams(
                 element=element,
                 color=param_values["color"],
+                col_for_color=param_values["col_for_color"],
                 groups=param_values["groups"],
                 contour_px=param_values["contour_px"],
                 cmap_params=cmap_params,
@@ -984,13 +986,13 @@ def show(
 
                     if wanted_labels_on_this_cs:
                         if (table := params_copy.table_name) is not None:
-                            assert isinstance(params_copy.color, str)
-                            colors = sc.get.obs_df(sdata[table], [params_copy.color])
-                            if isinstance(colors[params_copy.color].dtype, pd.CategoricalDtype):
+                            assert isinstance(params_copy.col_for_color, str)
+                            colors = sc.get.obs_df(sdata[table], [params_copy.col_for_color])
+                            if isinstance(colors[params_copy.col_for_color].dtype, pd.CategoricalDtype):
                                 _maybe_set_colors(
                                     source=sdata[table],
                                     target=sdata[table],
-                                    key=params_copy.color,
+                                    key=params_copy.col_for_color,
                                     palette=params_copy.palette,
                                 )
 

src/spatialdata_plot/pl/render.py

@@ -1084,7 +1084,8 @@ def _render_labels(
     table_name = render_params.table_name
     table_layer = render_params.table_layer
     palette = render_params.palette
-    color = render_params.color
+    color = render_params.color.get_hex() if render_params.color else None
+    col_for_color = render_params.col_for_color
     groups = render_params.groups
     scale = render_params.scale
 
@@ -1137,18 +1138,21 @@ def _render_labels(
         sdata=sdata_filt,
         element=label,
         element_name=element,
-        value_to_plot=color,
+        # value_to_plot=color, # TODO
+        value_to_plot=col_for_color,
         groups=groups,
         palette=palette,
-        na_color=render_params.cmap_params.na_color,
+        # na_color=render_params.cmap_params.na_color, # TODO
+        na_color=render_params.color if render_params.color is not None else render_params.cmap_params.na_color,
         cmap_params=render_params.cmap_params,
         table_name=table_name,
         table_layer=table_layer,
+        render_type="labels",
     )
 
     # rasterize could have removed labels from label
     # only problematic if color is specified
-    if rasterize and color is not None:
+    if rasterize and (color is not None or col_for_color is not None):
         labels_in_rasterized_image = np.unique(label.values)
         mask = np.isin(instance_id, labels_in_rasterized_image)
         instance_id = instance_id[mask]
@@ -1157,8 +1161,8 @@ def _render_labels(
             color_vector = color_vector.remove_unused_categories()
             assert color_source_vector is not None
             color_source_vector = color_source_vector[mask]
-        else:
-            assert color_source_vector is None
+        # else:
+        #     assert color_source_vector is None # TODO: delete?
 
     def _draw_labels(seg_erosionpx: int | None, seg_boundaries: bool, alpha: float) -> matplotlib.image.AxesImage:
         labels = _map_color_seg(
@@ -1228,7 +1232,8 @@ def _draw_labels(seg_erosionpx: int | None, seg_boundaries: bool, alpha: float)
         cax=cax,
         fig_params=fig_params,
         adata=table,
-        value_to_plot=color,
+        # value_to_plot=color, # TODO
+        value_to_plot=col_for_color,
         color_source_vector=color_source_vector,
         color_vector=color_vector,
         palette=palette,

src/spatialdata_plot/pl/render_params.py

@@ -254,7 +254,8 @@ class LabelsRenderParams:
 
     cmap_params: CmapParams
     element: str
-    color: str | None = None
+    color: Color | None = None
+    col_for_color: str | None = None
     groups: str | list[str] | None = None
     contour_px: int | None = None
     outline: bool = False

src/spatialdata_plot/pl/utils.py

@@ -777,10 +777,11 @@ def _set_color_source_vec(
     alpha: float = 1.0,
     table_name: str | None = None,
     table_layer: str | None = None,
-    render_type: Literal["points"] | None = None,
+    render_type: Literal["points", "labels"] | None = None,
 ) -> tuple[ArrayLike | pd.Series | None, ArrayLike, bool]:
     if value_to_plot is None and element is not None:
-        color = np.full(len(element), na_color.get_hex_with_alpha())
+        n_elements = len(element) if render_type != "labels" else len(dask.array.unique(element.data).compute())
+        color = np.full(n_elements, na_color.get_hex_with_alpha())
         return color, color, False
 
     # Figure out where to get the color from
@@ -1000,7 +1001,7 @@ def _get_categorical_color_mapping(
     alpha: float = 1,
     groups: list[str] | str | None = None,
     palette: list[str] | str | None = None,
-    render_type: Literal["points"] | None = None,
+    render_type: Literal["points", "labels"] | None = None,
 ) -> Mapping[str, str]:
     if not isinstance(color_source_vector, Categorical):
         raise TypeError(f"Expected `categories` to be a `Categorical`, but got {type(color_source_vector).__name__}")
@@ -1648,15 +1649,15 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
     }:
         if not isinstance(color, str | tuple | list):
             raise TypeError("Parameter 'color' must be a string or a tuple/list of floats.")
-        if element_type in {"shapes", "points"}:
+        if element_type in {"shapes", "points", "labels"}:
             if _is_color_like(color):
                 logger.info("Value for parameter 'color' appears to be a color, using it as such.")
                 param_dict["col_for_color"] = None
                 param_dict["color"] = Color(color)
                 if param_dict["color"].alpha_is_user_defined():
                     if element_type == "points" and param_dict.get("alpha") is None:
                         param_dict["alpha"] = param_dict["color"].get_alpha_as_float()
-                    elif element_type == "shapes" and param_dict.get("fill_alpha") is None:
+                    elif element_type in ["shapes", "labels"] and param_dict.get("fill_alpha") is None:
                         param_dict["fill_alpha"] = param_dict["color"].get_alpha_as_float()
                     else:
                         logger.info(
@@ -1668,7 +1669,7 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
                 param_dict["color"] = None
             else:
                 raise ValueError(f"{color} is not a valid RGB(A) array and therefore can't be used as 'color' value.")
-    elif "color" in param_dict and element_type != "labels":
+    elif "color" in param_dict and element_type != "images":
         param_dict["col_for_color"] = None
 
     if outline_width := param_dict.get("outline_width"):
@@ -1754,6 +1755,8 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
     elif element_type == "shapes":
         # set default fill_alpha for shapes if not given by user explicitly or implicitly (as part of color)
         param_dict["fill_alpha"] = 1.0
+    elif element_type == "lables":
+        param_dict["fill_alpha"] = 0.4
 
     if (cmap := param_dict.get("cmap")) is not None and (palette := param_dict.get("palette")) is not None:
         raise ValueError("Both `palette` and `cmap` are specified. Please specify only one of them.")
@@ -1894,7 +1897,7 @@ def _validate_label_render_params(
     element: str | None,
     cmap: list[Colormap | str] | Colormap | str | None,
     color: str | None,
-    fill_alpha: float | int,
+    fill_alpha: float | int | None,
     contour_px: int | None,
     groups: list[str] | str | None,
     palette: list[str] | str | None,
@@ -1939,12 +1942,23 @@ def _validate_label_render_params(
         element_params[el]["table_layer"] = param_dict["table_layer"]
 
         element_params[el]["table_name"] = None
-        element_params[el]["color"] = None
-        color = param_dict["color"]
-        if color is not None:
-            color, table_name = _validate_col_for_column_table(sdata, el, color, param_dict["table_name"], labels=True)
+
+        # element_params[el]["color"] = None # TODO: delete
+        # color = param_dict["color"]
+        # if color is not None:
+        #     color, table_name = _validate_col_for_column_table(sdata, el, color, param_dict["table_name"],
+        #           labels=True)
+        #     element_params[el]["table_name"] = table_name
+        #     element_params[el]["color"] = color
+        element_params[el]["color"] = param_dict["color"]
+
+        element_params[el]["col_for_color"] = None
+        if (col_for_color := param_dict["col_for_color"]) is not None:
+            col_for_color, table_name = _validate_col_for_column_table(
+                sdata, el, col_for_color, param_dict["table_name"], labels=True
+            )
             element_params[el]["table_name"] = table_name
-            element_params[el]["color"] = color
+            element_params[el]["col_for_color"] = col_for_color
 
         element_params[el]["palette"] = param_dict["palette"] if element_params[el]["table_name"] is not None else None
         element_params[el]["groups"] = param_dict["groups"] if element_params[el]["table_name"] is not None else None