improved cmap handling for images

Author: Sonja Stockhaus

src/spatialdata_plot/pl/basic.py

@@ -362,8 +362,8 @@ def render_images(
         sdata = _verify_plotting_tree(sdata)
         n_steps = len(sdata.plotting_tree.keys())
 
-        if channel is None and cmap is None:
-            cmap = "brg"
+        # if channel is None and cmap is None:
+        #     cmap = "brg"
 
         cmap_params: list[CmapParams] | CmapParams
         if isinstance(cmap, list):

src/spatialdata_plot/pl/render.py

@@ -434,10 +434,29 @@ def _render_images(
                     if render_params.cmap_params[i].norm is not None:
                         layers[c] = render_params.cmap_params[i].norm(layers[c])
 
-            # 2A) Image has 3 channels, no palette/cmap info -> use RGB
-            if n_channels == 3 and render_params.palette is None and not got_multiple_cmaps:
+            # 2A) Image has 3 channels, no palette info, and no/only one cmap was given
+            if n_channels == 3 and render_params.palette is None and not isinstance(render_params.cmap_params, list):
+                if render_params.cmap_params.is_default:  # -> use RGB
+                    stacked = np.stack([layers[c] for c in channels], axis=-1)
+                else:  # -> use given cmap for each channel
+                    channel_cmaps = [render_params.cmap_params.cmap] * n_channels
+                    # Apply cmaps to each channel, add up and normalize to [0, 1]
+                    stacked = (
+                        np.stack([channel_cmaps[i](layers[c]) for i, c in enumerate(channels)], 0).sum(0) / n_channels
+                    )
+                    # Remove alpha channel so we can overwrite it from render_params.alpha
+                    stacked = stacked[:, :, :3]
+                    logger.warning(
+                        "One cmap was given for multiple channels and is now used for each channel. "
+                        "You're blending multiple cmaps. "
+                        "If the plot doesn't look like you expect, it might be because your "
+                        "cmaps go from a given color to 'white', and not to 'transparent'. "
+                        "Therefore, the 'white' of higher layers will overlay the lower layers. "
+                        "Consider using 'palette' instead."
+                    )
+
                 im = ax.imshow(
-                    np.stack([layers[c] for c in channels], axis=-1),
+                    stacked,
                     alpha=render_params.alpha,
                 )
                 im.set_transform(trans_data)

src/spatialdata_plot/pl/utils.py

@@ -344,7 +344,13 @@ def _prepare_cmap_norm(
     **kwargs: Any,
 ) -> CmapParams:
     is_default = cmap is None
-    cmap = copy(matplotlib.colormaps[rcParams["image.cmap"] if cmap is None else cmap])
+    if cmap is None:
+        cmap = rcParams["image.cmap"]
+    if isinstance(cmap, str):
+        cmap = matplotlib.colormaps[cmap]
+
+    cmap = copy(cmap)
+
     cmap.set_bad("lightgray" if na_color is None else na_color)
 
     if isinstance(norm, Normalize) or not norm: