changed default from PCA to stack

Author: timtreis

src/spatialdata_plot/pl/basic.py

@@ -468,7 +468,7 @@ def render_images(
         palette: list[str] | str | None = None,
         alpha: float | int = 1.0,
         scale: str | None = None,
-        multichannel_strategy: str = "pca",
+        multichannel_strategy: str = "stack",
         bg_threshold: float = 1e-4,
         **kwargs: Any,
     ) -> sd.SpatialData:
@@ -512,10 +512,10 @@ def render_images(
                 3) "full": Renders the full image without rasterization. In the case of
                 multiscale images, the highest resolution scale is selected. Note that
                 this may result in long computing times for large images.
-        multichannel_strategy : str, default "pca"
+        multichannel_strategy : str, default "stack"
             Method for rendering images with more than 3 channels.
-            "pca": Uses PCA to reduce the number of channels to 3.
             "stack": Samples categorical colors and stacks the channels.
+            "pca": Uses PCA to reduce the number of channels to 3.
         bg_threshold : float, default 1e-4
             Threshold below which values are considered background in the PCA dimred for images with 3+ channels.
         kwargs

src/spatialdata_plot/pl/render.py

@@ -846,6 +846,7 @@ def _render_images(
     else:
         layers = {}
         for ch_idx, ch in enumerate(channels):
+            print(channels, ch)
             layers[ch_idx] = img.sel(c=ch).copy(deep=True).squeeze()
             if isinstance(render_params.cmap_params, list):
                 ch_norm = render_params.cmap_params[ch_idx].norm

src/spatialdata_plot/pl/render_params.py

@@ -125,7 +125,7 @@ class ImageRenderParams:
     percentiles_for_norm: tuple[float | None, float | None] = (None, None)
     scale: str | None = None
     zorder: int = 0
-    multichannel_strategy: str = "pca"
+    multichannel_strategy: str = "stack"
     bg_threshold: float = 1e-4