Implement colorbar logic

src/spatialdata_plot/pl/render.py

@@ -26,6 +26,7 @@
 from spatialdata_plot._logging import logger
 from spatialdata_plot.pl.render_params import (
     Color,
+    ColorbarSpec,
     FigParams,
     ImageRenderParams,
     LabelsRenderParams,
@@ -61,6 +62,55 @@
 _Normalize = Normalize | abc.Sequence[Normalize]
 
 
+def _split_colorbar_params(params: dict[str, object] | None) -> tuple[dict[str, object], dict[str, object], str | None]:
+    """Split colorbar params into layout hints, Matplotlib kwargs, and label override."""
+    layout: dict[str, object] = {}
+    cbar_kwargs: dict[str, object] = {}
+    label_override: str | None = None
+    for key, value in (params or {}).items():
+        key_lower = key.lower()
+        if key_lower in {"loc", "location"}:
+            layout["location"] = value
+        elif key_lower == "width" or key_lower == "fraction":
+            layout["fraction"] = value
+        elif key_lower == "pad":
+            layout["pad"] = value
+        elif key_lower == "label":
+            label_override = None if value is None else str(value)
+        else:
+            cbar_kwargs[key] = value
+    return layout, cbar_kwargs, label_override
+
+
+def _resolve_colorbar_label(
+    colorbar_params: dict[str, object] | None, fallback: str | None, *, is_default_channel_name: bool = False
+) -> str | None:
+    """Pick a colorbar label from params or fall back to provided value."""
+    _, _, label = _split_colorbar_params(colorbar_params)
+    if label is not None:
+        return label
+    if is_default_channel_name:
+        return None
+    return fallback
+
+
+def _should_request_colorbar(
+    colorbar: bool | str | None,
+    *,
+    has_mappable: bool,
+    is_continuous: bool,
+    auto_condition: bool = True,
+) -> bool:
+    """Resolve colorbar setting to a final boolean request."""
+    if not has_mappable or not is_continuous:
+        return False
+    if colorbar is True:
+        return True
+    if colorbar in {False, None}:
+        return False
+    return bool(auto_condition)
+
+
 def _render_shapes(
     sdata: sd.SpatialData,
     render_params: ShapesRenderParams,
@@ -69,6 +119,7 @@ def _render_shapes(
     fig_params: FigParams,
     scalebar_params: ScalebarParams,
     legend_params: LegendParams,
+    colorbar_requests: list[ColorbarSpec] | None = None,
 ) -> None:
     element = render_params.element
     col_for_color = render_params.col_for_color
@@ -80,7 +131,8 @@ def _render_shapes(
         filter_tables=bool(render_params.table_name),
     )
 
-    if (table_name := render_params.table_name) is None:
+    table_name = render_params.table_name
+    if table_name is None:
         table = None
         shapes = sdata_filt[element]
     else:
@@ -159,16 +211,13 @@ def _render_shapes(
     else:
         palette = ListedColormap(dict.fromkeys(color_vector[~pd.Categorical(color_source_vector).isnull()]))
 
-    if (
+    has_valid_color = (
         len(set(color_vector)) != 1
         or list(set(color_vector))[0] != render_params.cmap_params.na_color.get_hex_with_alpha()
-    ):
+    )
+    if has_valid_color and color_source_vector is not None and col_for_color is not None:
         # necessary in case different shapes elements are annotated with one table
-        if color_source_vector is not None and col_for_color is not None:
-            color_source_vector = color_source_vector.remove_unused_categories()
-
-        # False if user specified color-like with 'color' parameter
-        colorbar = False if col_for_color is None else legend_params.colorbar
+        color_source_vector = color_source_vector.remove_unused_categories()
 
     # Apply the transformation to the PatchCollection's paths
     trans, trans_data = _prepare_transformation(sdata_filt.shapes[element], coordinate_system)
@@ -515,8 +564,11 @@ def _render_shapes(
         if color_source_vector is not None and render_params.col_for_color is not None:
             color_source_vector = color_source_vector.remove_unused_categories()
 
-        # False if user specified color-like with 'color' parameter
-        colorbar = False if render_params.col_for_color is None else legend_params.colorbar
+        wants_colorbar = _should_request_colorbar(
+            render_params.colorbar,
+            has_mappable=cax is not None,
+            is_continuous=render_params.col_for_color is not None and color_source_vector is None,
+        )
 
         _ = _decorate_axs(
             ax=ax,
@@ -534,7 +586,13 @@ def _render_shapes(
             legend_loc=legend_params.legend_loc,
             legend_fontoutline=legend_params.legend_fontoutline,
             na_in_legend=legend_params.na_in_legend,
-            colorbar=colorbar,
+            colorbar=wants_colorbar and legend_params.colorbar,
+            colorbar_params=render_params.colorbar_params,
+            colorbar_requests=colorbar_requests,
+            colorbar_label=_resolve_colorbar_label(
+                render_params.colorbar_params,
+                col_for_color if isinstance(col_for_color, str) else None,
+            ),
             scalebar_dx=scalebar_params.scalebar_dx,
             scalebar_units=scalebar_params.scalebar_units,
         )
@@ -548,6 +606,7 @@ def _render_points(
     fig_params: FigParams,
     scalebar_params: ScalebarParams,
     legend_params: LegendParams,
+    colorbar_requests: list[ColorbarSpec] | None = None,
 ) -> None:
     element = render_params.element
     col_for_color = render_params.col_for_color
@@ -894,6 +953,12 @@ def _render_points(
         else:
             palette = ListedColormap(dict.fromkeys(color_vector[~pd.Categorical(color_source_vector).isnull()]))
 
+        wants_colorbar = _should_request_colorbar(
+            render_params.colorbar,
+            has_mappable=cax is not None,
+            is_continuous=col_for_color is not None and color_source_vector is None,
+        )
+
         _ = _decorate_axs(
             ax=ax,
             cax=cax,
@@ -910,7 +975,13 @@ def _render_points(
             legend_loc=legend_params.legend_loc,
             legend_fontoutline=legend_params.legend_fontoutline,
             na_in_legend=legend_params.na_in_legend,
-            colorbar=legend_params.colorbar,
+            colorbar=wants_colorbar and legend_params.colorbar,
+            colorbar_params=render_params.colorbar_params,
+            colorbar_requests=colorbar_requests,
+            colorbar_label=_resolve_colorbar_label(
+                render_params.colorbar_params,
+                col_for_color if isinstance(col_for_color, str) else None,
+            ),
             scalebar_dx=scalebar_params.scalebar_dx,
             scalebar_units=scalebar_params.scalebar_units,
         )
@@ -925,6 +996,7 @@ def _render_images(
     scalebar_params: ScalebarParams,
     legend_params: LegendParams,
     rasterize: bool,
+    colorbar_requests: list[ColorbarSpec] | None = None,
 ) -> None:
     sdata_filt = sdata.filter_by_coordinate_system(
         coordinate_system=coordinate_system,
@@ -1003,9 +1075,26 @@ def _render_images(
             norm=render_params.cmap_params.norm,
         )
 
-        if legend_params.colorbar:
+        wants_colorbar = _should_request_colorbar(
+            render_params.colorbar,
+            has_mappable=n_channels == 1,
+            is_continuous=True,
+            auto_condition=n_channels == 1,
+        )
+        if wants_colorbar and legend_params.colorbar and colorbar_requests is not None:
             sm = plt.cm.ScalarMappable(cmap=cmap, norm=render_params.cmap_params.norm)
-            fig_params.fig.colorbar(sm, ax=ax)
+            colorbar_requests.append(
+                ColorbarSpec(
+                    ax=ax,
+                    mappable=sm,
+                    params=render_params.colorbar_params,
+                    label=_resolve_colorbar_label(
+                        render_params.colorbar_params,
+                        str(channels[0]),
+                        is_default_channel_name=isinstance(channels[0], (int, np.integer)),
+                    ),
+                )
+            )
 
     # 2) Image has any number of channels but 1
     else:
@@ -1165,6 +1254,7 @@ def _render_labels(
     scalebar_params: ScalebarParams,
     legend_params: LegendParams,
     rasterize: bool,
+    colorbar_requests: list[ColorbarSpec] | None = None,
 ) -> None:
     element = render_params.element
     table_name = render_params.table_name
@@ -1310,6 +1400,12 @@ def _draw_labels(seg_erosionpx: int | None, seg_boundaries: bool, alpha: float)
     else:
         raise ValueError("Parameters 'fill_alpha' and 'outline_alpha' cannot both be 0.")
 
+    colorbar_requested = _should_request_colorbar(
+        render_params.colorbar,
+        has_mappable=cax is not None,
+        is_continuous=color is not None and color_source_vector is None and not categorical,
+    )
+
     _ = _decorate_axs(
         ax=ax,
         cax=cax,
@@ -1326,7 +1422,13 @@ def _draw_labels(seg_erosionpx: int | None, seg_boundaries: bool, alpha: float)
         legend_loc=legend_params.legend_loc,
         legend_fontoutline=legend_params.legend_fontoutline,
         na_in_legend=(legend_params.na_in_legend if groups is None else len(groups) == len(set(color_vector))),
-        colorbar=legend_params.colorbar,
+        colorbar=colorbar_requested and legend_params.colorbar,
+        colorbar_params=render_params.colorbar_params,
+        colorbar_requests=colorbar_requests,
+        colorbar_label=_resolve_colorbar_label(
+            render_params.colorbar_params,
+            color if isinstance(color, str) else None,
+        ),
         scalebar_dx=scalebar_params.scalebar_dx,
         scalebar_units=scalebar_params.scalebar_units,
         # scalebar_kwargs=scalebar_params.scalebar_kwargs,

src/spatialdata_plot/pl/render_params.py

@@ -6,6 +6,7 @@
 
 import numpy as np
 from matplotlib.axes import Axes
+from matplotlib.cm import ScalarMappable
 from matplotlib.colors import Colormap, ListedColormap, Normalize, rgb2hex, to_hex
 from matplotlib.figure import Figure
 
@@ -183,6 +184,22 @@ class LegendParams:
     colorbar: bool = True
 
 
+@dataclass
+class ColorbarSpec:
+    """Data required to create a colorbar."""
+
+    ax: Axes
+    mappable: ScalarMappable
+    params: dict[str, object] | None = None
+    label: str | None = None
+    alpha: float | None = None
+
+
+CBAR_DEFAULT_LOCATION = "right"
+CBAR_DEFAULT_FRACTION = 0.075
+CBAR_DEFAULT_PAD = 0.015
+
+
 @dataclass
 class ScalebarParams:
     """Scalebar params."""
@@ -213,6 +230,8 @@ class ShapesRenderParams:
     table_layer: str | None = None
     shape: Literal["circle", "hex", "visium_hex", "square"] | None = None
     ds_reduction: Literal["sum", "mean", "any", "count", "std", "var", "max", "min"] | None = None
+    colorbar: bool | str | None = "auto"
+    colorbar_params: dict[str, object] | None = None
 
 
 @dataclass
@@ -233,6 +252,8 @@ class PointsRenderParams:
     table_name: str | None = None
     table_layer: str | None = None
     ds_reduction: Literal["sum", "mean", "any", "count", "std", "var", "max", "min"] | None = None
+    colorbar: bool | str | None = "auto"
+    colorbar_params: dict[str, object] | None = None
 
 
 @dataclass
@@ -247,6 +268,8 @@ class ImageRenderParams:
     percentiles_for_norm: tuple[float | None, float | None] = (None, None)
     scale: str | None = None
     zorder: int = 0
+    colorbar: bool | str | None = "auto"
+    colorbar_params: dict[str, object] | None = None
 
 
 @dataclass
@@ -267,3 +290,5 @@ class LabelsRenderParams:
     table_name: str | None = None
     table_layer: str | None = None
     zorder: int = 0
+    colorbar: bool | str | None = "auto"
+    colorbar_params: dict[str, object] | None = None