Adjust labels params (#272)

* add temporary deprecation decorator

* initial refactor

* mostly fixed tests

* fix remaining 2 tests

* some more refactor

* some more refactor

* mypy

* add images properly to elements to render

* Initial refactor

* additional refactor

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* fix tets

* fix last tests

* fix mypy

* initial refactor

* initial refactor

* additonal refactor

* remove deprecation alias functions

* adjust docstrings

* remove unused import

* update changelog

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* adjust docstring

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: melonora

CHANGELOG.md

@@ -10,6 +10,10 @@ and this project adheres to [Semantic Versioning][].
 
 ## [0.2.3] - tbd
 
+### Changed
+
+-   All parameters are now provided for a single element. If element in pl.render is None then this value will be broadcasted
+
 ### Fixed
 
 -   Fix color assignment for NaN values (#257)

src/spatialdata_plot/_utils.py

@@ -3,7 +3,7 @@
 import warnings
 from collections import abc
 from copy import copy
-from typing import Union, cast
+from typing import Union
 
 import dask
 import geopandas as gpd
@@ -45,8 +45,6 @@
     _multiscale_to_spatial_image,
     _normalize,
     _rasterize_if_necessary,
-    _return_list_list_str_none,
-    _return_list_str_none,
     _set_color_source_vec,
     to_hex,
 )
@@ -524,162 +522,156 @@ def _render_labels(
     legend_params: LegendParams,
     rasterize: bool,
 ) -> None:
-    elements = render_params.elements
-    element_table_mapping = cast(dict[str, str], render_params.element_table_mapping)
-    palettes = _return_list_list_str_none(render_params.palette)
-    colors = _return_list_str_none(render_params.color)
-    groups = _return_list_list_str_none(render_params.groups)
+    element = render_params.element
+    table_name = render_params.table_name
+    palette = render_params.palette
+    color = render_params.color
+    groups = render_params.groups
+    scale = render_params.scale
 
     if render_params.outline is False:
         render_params.outline_alpha = 0
 
     sdata_filt = sdata.filter_by_coordinate_system(
         coordinate_system=coordinate_system,
-        filter_tables=any(value is not None for value in element_table_mapping.values()),
+        filter_tables=bool(table_name),
     )
 
-    if elements is None:
-        elements = list(sdata_filt.labels.keys())
-
-    for i, e in enumerate(elements):
-        label = sdata_filt.labels[e]
-        extent = get_extent(label, coordinate_system=coordinate_system)
-        scale = render_params.scale[i] if isinstance(render_params.scale, list) else render_params.scale
-        color = colors[i]
-
-        # get best scale out of multiscale label
-        if isinstance(label, MultiscaleSpatialImage):
-            label = _multiscale_to_spatial_image(
-                multiscale_image=label,
-                dpi=fig_params.fig.dpi,
-                width=fig_params.fig.get_size_inches()[0],
-                height=fig_params.fig.get_size_inches()[1],
-                scale=scale,
-                is_label=True,
-            )
-        # rasterize spatial image if necessary to speed up performance
-        if rasterize:
-            label = _rasterize_if_necessary(
-                image=label,
-                dpi=fig_params.fig.dpi,
-                width=fig_params.fig.get_size_inches()[0],
-                height=fig_params.fig.get_size_inches()[1],
-                coordinate_system=coordinate_system,
-                extent=extent,
-            )
+    label = sdata_filt.labels[element]
+    extent = get_extent(label, coordinate_system=coordinate_system)
 
-        table_name = mapping.get(e) if isinstance((mapping := element_table_mapping), dict) else None
-        if table_name is None:
-            instance_id = np.unique(label)
-            table = None
-        else:
-            regions, region_key, instance_key = get_table_keys(sdata[table_name])
-            table = sdata[table_name][sdata[table_name].obs[region_key].isin([e])]
-
-            # get instance id based on subsetted table
-            instance_id = table.obs[instance_key].values
-
-        trans = get_transformation(label, get_all=True)[coordinate_system]
-        affine_trans = trans.to_affine_matrix(input_axes=("x", "y"), output_axes=("x", "y"))
-        trans = mtransforms.Affine2D(matrix=affine_trans)
-        trans_data = trans + ax.transData
-
-        color_source_vector, color_vector, categorical = _set_color_source_vec(
-            sdata=sdata_filt,
-            element=label,
-            element_name=e,
-            value_to_plot=color,
-            groups=groups[i],  # if isinstance(groups, list) else None,
-            palette=palettes[i],
-            na_color=render_params.cmap_params.na_color,
-            cmap_params=render_params.cmap_params,
-            table_name=cast(str, table_name),
+    # get best scale out of multiscale label
+    if isinstance(label, MultiscaleSpatialImage):
+        label = _multiscale_to_spatial_image(
+            multiscale_image=label,
+            dpi=fig_params.fig.dpi,
+            width=fig_params.fig.get_size_inches()[0],
+            height=fig_params.fig.get_size_inches()[1],
+            scale=scale,
+            is_label=True,
+        )
+    # rasterize spatial image if necessary to speed up performance
+    if rasterize:
+        label = _rasterize_if_necessary(
+            image=label,
+            dpi=fig_params.fig.dpi,
+            width=fig_params.fig.get_size_inches()[0],
+            height=fig_params.fig.get_size_inches()[1],
+            coordinate_system=coordinate_system,
+            extent=extent,
         )
 
-        if (render_params.fill_alpha != render_params.outline_alpha) and render_params.contour_px is not None:
-            # First get the labels infill and plot them
-            labels_infill = _map_color_seg(
-                seg=label.values,
-                cell_id=instance_id,
-                color_vector=color_vector,
-                color_source_vector=color_source_vector,
-                cmap_params=render_params.cmap_params,
-                seg_erosionpx=None,
-                seg_boundaries=render_params.outline,
-                na_color=render_params.cmap_params.na_color,
-            )
+    if table_name is None:
+        instance_id = np.unique(label)
+        table = None
+    else:
+        regions, region_key, instance_key = get_table_keys(sdata[table_name])
+        table = sdata[table_name][sdata[table_name].obs[region_key].isin([element])]
 
-            # Then overlay the contour
-            labels_contour = _map_color_seg(
-                seg=label.values,
-                cell_id=instance_id,
-                color_vector=color_vector,
-                color_source_vector=color_source_vector,
-                cmap_params=render_params.cmap_params,
-                seg_erosionpx=render_params.contour_px,
-                seg_boundaries=render_params.outline,
-                na_color=render_params.cmap_params.na_color,
-            )
+        # get instance id based on subsetted table
+        instance_id = table.obs[instance_key].values
 
-            _cax = ax.imshow(
-                labels_contour,
-                rasterized=True,
-                cmap=None if categorical else render_params.cmap_params.cmap,
-                norm=None if categorical else render_params.cmap_params.norm,
-                alpha=render_params.outline_alpha,
-                origin="lower",
-            )
-            _cax = ax.imshow(
-                labels_infill,
-                rasterized=True,
-                cmap=None if categorical else render_params.cmap_params.cmap,
-                norm=None if categorical else render_params.cmap_params.norm,
-                alpha=render_params.fill_alpha,
-                origin="lower",
-            )
-            _cax.set_transform(trans_data)
-            cax = ax.add_image(_cax)
-        else:
-            # Default: no alpha, contour = infill
-            label = _map_color_seg(
-                seg=label.values,
-                cell_id=instance_id,
-                color_vector=color_vector,
-                color_source_vector=color_source_vector,
-                cmap_params=render_params.cmap_params,
-                seg_erosionpx=render_params.contour_px,
-                seg_boundaries=render_params.outline,
-                na_color=render_params.cmap_params.na_color,
-            )
+    trans = get_transformation(label, get_all=True)[coordinate_system]
+    affine_trans = trans.to_affine_matrix(input_axes=("x", "y"), output_axes=("x", "y"))
+    trans = mtransforms.Affine2D(matrix=affine_trans)
+    trans_data = trans + ax.transData
 
-            _cax = ax.imshow(
-                label,
-                rasterized=True,
-                cmap=None if categorical else render_params.cmap_params.cmap,
-                norm=None if categorical else render_params.cmap_params.norm,
-                alpha=render_params.fill_alpha,
-                origin="lower",
-            )
-        _cax.set_transform(trans_data)
-        cax = ax.add_image(_cax)
+    color_source_vector, color_vector, categorical = _set_color_source_vec(
+        sdata=sdata_filt,
+        element=label,
+        element_name=element,
+        value_to_plot=color,
+        groups=groups,
+        palette=palette,
+        na_color=render_params.cmap_params.na_color,
+        cmap_params=render_params.cmap_params,
+        table_name=table_name,
+    )
 
-        _ = _decorate_axs(
-            ax=ax,
-            cax=cax,
-            fig_params=fig_params,
-            adata=table,
-            value_to_plot=color,
+    if (render_params.fill_alpha != render_params.outline_alpha) and render_params.contour_px is not None:
+        # First get the labels infill and plot them
+        labels_infill = _map_color_seg(
+            seg=label.values,
+            cell_id=instance_id,
+            color_vector=color_vector,
+            color_source_vector=color_source_vector,
+            cmap_params=render_params.cmap_params,
+            seg_erosionpx=None,
+            seg_boundaries=render_params.outline,
+            na_color=render_params.cmap_params.na_color,
+        )
+
+        # Then overlay the contour
+        labels_contour = _map_color_seg(
+            seg=label.values,
+            cell_id=instance_id,
+            color_vector=color_vector,
             color_source_vector=color_source_vector,
-            palette=palettes[i],
+            cmap_params=render_params.cmap_params,
+            seg_erosionpx=render_params.contour_px,
+            seg_boundaries=render_params.outline,
+            na_color=render_params.cmap_params.na_color,
+        )
+
+        _cax = ax.imshow(
+            labels_contour,
+            rasterized=True,
+            cmap=None if categorical else render_params.cmap_params.cmap,
+            norm=None if categorical else render_params.cmap_params.norm,
+            alpha=render_params.outline_alpha,
+            origin="lower",
+        )
+        _cax = ax.imshow(
+            labels_infill,
+            rasterized=True,
+            cmap=None if categorical else render_params.cmap_params.cmap,
+            norm=None if categorical else render_params.cmap_params.norm,
             alpha=render_params.fill_alpha,
+            origin="lower",
+        )
+        _cax.set_transform(trans_data)
+        cax = ax.add_image(_cax)
+    else:
+        # Default: no alpha, contour = infill
+        label = _map_color_seg(
+            seg=label.values,
+            cell_id=instance_id,
+            color_vector=color_vector,
+            color_source_vector=color_source_vector,
+            cmap_params=render_params.cmap_params,
+            seg_erosionpx=render_params.contour_px,
+            seg_boundaries=render_params.outline,
             na_color=render_params.cmap_params.na_color,
-            legend_fontsize=legend_params.legend_fontsize,
-            legend_fontweight=legend_params.legend_fontweight,
-            legend_loc=legend_params.legend_loc,
-            legend_fontoutline=legend_params.legend_fontoutline,
-            na_in_legend=legend_params.na_in_legend,
-            colorbar=legend_params.colorbar,
-            scalebar_dx=scalebar_params.scalebar_dx,
-            scalebar_units=scalebar_params.scalebar_units,
-            # scalebar_kwargs=scalebar_params.scalebar_kwargs,
         )
+
+        _cax = ax.imshow(
+            label,
+            rasterized=True,
+            cmap=None if categorical else render_params.cmap_params.cmap,
+            norm=None if categorical else render_params.cmap_params.norm,
+            alpha=render_params.fill_alpha,
+            origin="lower",
+        )
+    _cax.set_transform(trans_data)
+    cax = ax.add_image(_cax)
+
+    _ = _decorate_axs(
+        ax=ax,
+        cax=cax,
+        fig_params=fig_params,
+        adata=table,
+        value_to_plot=color,
+        color_source_vector=color_source_vector,
+        palette=palette,
+        alpha=render_params.fill_alpha,
+        na_color=render_params.cmap_params.na_color,
+        legend_fontsize=legend_params.legend_fontsize,
+        legend_fontweight=legend_params.legend_fontweight,
+        legend_loc=legend_params.legend_loc,
+        legend_fontoutline=legend_params.legend_fontoutline,
+        na_in_legend=legend_params.na_in_legend,
+        colorbar=legend_params.colorbar,
+        scalebar_dx=scalebar_params.scalebar_dx,
+        scalebar_units=scalebar_params.scalebar_units,
+        # scalebar_kwargs=scalebar_params.scalebar_kwargs,
+    )