simple multiscale support

src/spatialdata_plot/pl/basic.py

@@ -41,6 +41,7 @@
     _get_cs_contents,
     _get_extent,
     _maybe_set_colors,
+    _multiscale_to_image,
     _prepare_cmap_norm,
     _prepare_params_plot,
     _set_outline,
@@ -504,6 +505,9 @@ def show(
         if len(render_cmds.keys()) == 0:
             raise TypeError("Please specify what to plot using the 'render_*' functions before calling 'imshow().")
 
+        # Simplicstic solution: If the images are multiscale, just use the first
+        sdata = _multiscale_to_image(sdata)
+
         # transform all elements
         for cmd, _ in render_cmds.items():
             if cmd == "render_images" or cmd == "render_channels":

src/spatialdata_plot/pl/render.py

@@ -347,7 +347,7 @@ class LabelsRenderParams:
     layer: str | None = None
     palette: Palette_t = None
     outline_alpha: float = 1.0
-    fill_alpha: float = 0.3
+    fill_alpha: float = 0.4
 
 
 def _render_labels(

src/spatialdata_plot/pl/utils.py

@@ -10,6 +10,7 @@
 from typing import Any, Literal, Optional, Union
 
 import matplotlib.pyplot as plt
+import multiscale_spatial_image as msi
 import numpy as np
 import pandas as pd
 import spatialdata as sd
@@ -36,6 +37,9 @@
 from skimage.util import map_array
 from spatialdata._logging import logger as logging
 from spatialdata._types import ArrayLike
+from spatialdata.models import (
+    Image2DModel,
+)
 
 from spatialdata_plot.pp.utils import _get_coordinate_system_mapping
 
@@ -903,3 +907,14 @@ def _get_cs_element_map(
         # model = get_model(element_map["blobs_labels"])
         # if model in [Image2DModel, Image3DModel, Labels2DModel, Labels3DModel]
     return d
+
+
+def _multiscale_to_image(sdata: sd.SpatialData) -> sd.SpatialData:
+    if sdata.images is None:
+        raise ValueError("No images found in the SpatialData object.")
+
+    for k, v in sdata.images.items():
+        if isinstance(v, msi.multiscale_spatial_image.MultiscaleSpatialImage):
+            sdata.images[k] = Image2DModel.parse(v["scale0"].ds.to_array().squeeze(axis=0))
+
+    return sdata