Add info log for float auto-range, tests for edge cases

- Log when float RGB data outside [0, 1] triggers auto-ranging
- Document _normalize_dtype_to_float as RGB-display-oriented
- Add test for float RGB outside [0, 1] auto-ranging
- Add test for explicit cmap overriding RGBA detection

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: timtreis

src/spatialdata_plot/pl/render.py

@@ -1019,7 +1019,9 @@ def _render_points(
 
 
 def _normalize_dtype_to_float(arr: np.ndarray) -> np.ndarray:
-    """Normalize an array to float64 in [0, 1] for matplotlib.
+    """Normalize an array to float64 in [0, 1] for display with matplotlib.
+
+    Intended for RGB/RGBA image data where negative values are not meaningful.
 
     - uint8 → divide by 255
     - other unsigned int → divide by dtype max
@@ -1040,6 +1042,12 @@ def _normalize_dtype_to_float(arr: np.ndarray) -> np.ndarray:
         return arr_f
     if vmin == vmax:
         return np.zeros_like(arr_f)
+    logger.info(
+        "Float RGB image has values outside [0, 1] (range [%.3f, %.3f]); "
+        "auto-ranging globally. Pass an explicit 'norm' to control contrast.",
+        vmin,
+        vmax,
+    )
     result: np.ndarray = (arr_f - vmin) / (vmax - vmin)
     return result
 

tests/pl/test_render_images.py

@@ -279,6 +279,25 @@ def test_uint16_rgba_renders(self):
         sdata.pl.render_images("img").pl.show(ax=ax)
         plt.close("all")
 
+    def test_float_rgb_outside_01_auto_ranges(self):
+        """Float RGB image with values outside [0, 1] should auto-range globally."""
+        data = np.zeros((3, 50, 50), dtype=np.float32)
+        data[0] = 2000.0  # all channels have different magnitudes
+        data[1] = 1000.0
+        data[2] = 500.0
+        img = Image2DModel.parse(data, dims=("c", "y", "x"), c_coords=["r", "g", "b"])
+        sdata = SpatialData(images={"img": img})
+        fig, ax = plt.subplots()
+        sdata.pl.render_images("img").pl.show(ax=ax)
+        plt.close("all")
+
+    def test_cmap_overrides_rgba_detection(self):
+        """Explicit single cmap should skip RGBA path and use multi-channel rendering."""
+        sdata = self._make_rgba_sdata(["r", "g", "b", "a"])
+        fig, ax = plt.subplots()
+        sdata.pl.render_images("img", cmap="Reds").pl.show(ax=ax)
+        plt.close("all")
+
 
 class TestMultiChannelClipping:
     """Regression tests: multi-channel compositing should not produce clipping warnings."""