String column names in [0, 1] are now no longer interpreted as colors

src/spatialdata_plot/pl/utils.py

@@ -83,6 +83,28 @@
 ColorLike = Union[tuple[float, ...], str]
 
 
+def _is_color_like(color: Any) -> bool:
+ """Check if a value is a valid color, returns False for pseudo-bools.
+
+ For discussion, see: https://github.com/scverse/spatialdata-plot/issues/327.
+ matplotlib accepts strings in [0, 1] as grey-scale values - therefore,
+ "0" and "1" are considered valid colors. However, we won't do that
+ so we're filtering these out.
+ """
+ if isinstance(color, bool):
+ return False
+ if isinstance(color, str):
+ try:
+ num_value = float(color)
+ if 0 <= num_value <= 1:
+ return False
+ except ValueError:
+ # we're not dealing with what matplotlib considers greyscale
+ pass
+
+ return bool(colors.is_color_like(color))
+
+
 def _prepare_params_plot(
  # this param is inferred when `pl.show`` is called
  num_panels: int,
@@ -532,7 +554,15 @@ def _normalize(
 
  perc = np.percentile(img, [pmin, pmax])
 
- norm = (img - perc[0]) / (perc[1] - perc[0] + eps)
+ # Ensure perc is an array of two elements
+ if np.isscalar(perc):
+ logger.warning(
+ "Percentile range is too small, using the same percentile for both min "
+ "and max. Consider using a larger percentile range."
+ )
+ perc = np.array([perc, perc])
+
+ norm = (img - perc[0]) / (perc[1] - perc[0] + eps) # type: ignore
 
  if clip:
  norm = np.clip(norm, 0, 1)
@@ -727,7 +757,7 @@ def _map_color_seg(
  val_im = np.squeeze(val_im, axis=0)
  if "#" in str(color_vector[0]):
  # we have hex colors
- assert all(colors.is_color_like(c) for c in color_vector), "Not all values are color-like."
+ assert all(_is_color_like(c) for c in color_vector), "Not all values are color-like."
  cols = colors.to_rgba_array(color_vector)
  else:
  cols = cmap_params.cmap(cmap_params.norm(color_vector))
@@ -1557,15 +1587,11 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  if (contour_px := param_dict.get("contour_px")) and not isinstance(contour_px, int):
  raise TypeError("Parameter 'contour_px' must be an integer.")
 
- if (color := param_dict.get("color")) and element_type in {
- "shapes",
- "points",
- "labels",
- }:
+ if (color := param_dict.get("color")) and element_type in {"shapes", "points", "labels"}:
  if not isinstance(color, str):
  raise TypeError("Parameter 'color' must be a string.")
  if element_type in {"shapes", "points"}:
- if colors.is_color_like(color):
+ if _is_color_like(color):
  logger.info("Value for parameter 'color' appears to be a color, using it as such.")
  param_dict["col_for_color"] = None
  else:
@@ -1645,7 +1671,7 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  raise TypeError("Parameter 'cmap' must be a string, a Colormap, or a list of these types.")
 
  if (na_color := param_dict.get("na_color")) != "default" and (
- na_color is not None and not colors.is_color_like(na_color)
+ na_color is not None and not _is_color_like(na_color)
  ):
  raise ValueError("Parameter 'na_color' must be color-like.")
 

tests/pl/test_render_shapes.py

@@ -7,7 +7,7 @@
 import spatialdata_plot # noqa: F401
 from anndata import AnnData
 from shapely.geometry import MultiPolygon, Point, Polygon
-from spatialdata import SpatialData
+from spatialdata import SpatialData, deepcopy
 from spatialdata.models import ShapesModel, TableModel
 
 from tests.conftest import DPI, PlotTester, PlotTesterMeta
@@ -94,7 +94,7 @@ def _make_multi():
  sdata.pl.render_shapes(color="val", outline=True, fill_alpha=0.3).pl.show()
 
  def test_plot_can_color_from_geodataframe(self, sdata_blobs: SpatialData):
- blob = sdata_blobs
+ blob = deepcopy(sdata_blobs)
  blob["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
  blob["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
  blob.shapes["blobs_polygons"]["value"] = [1, 10, 1, 20, 1]

tests/pl/test_utils.py

@@ -1,3 +1,5 @@
+from typing import Union
+
 import matplotlib
 import matplotlib.pyplot as plt
 import numpy as np
@@ -23,6 +25,11 @@
 # the comp. function can be accessed as `self.compare(<your_filename>, tolerance=<your_tolerance>)`
 # ".png" is appended to <your_filename>, no need to set it
 
+# replace with
+# from spatialdata._types import ColorLike
+# once https://github.com/scverse/spatialdata/pull/689/ is in a release
+ColorLike = Union[tuple[float, ...], str]
+
 
 class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  @pytest.mark.parametrize(
@@ -35,6 +42,18 @@ class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  def test_plot_set_outline_accepts_str_or_float_or_list_thereof(self, sdata_blobs: SpatialData, outline_color):
  sdata_blobs.pl.render_shapes(element="blobs_polygons", outline=True, outline_color=outline_color).pl.show()
 
+ @pytest.mark.parametrize(
+ "colname",
+ ["0", "0.5", "1"],
+ )
+ def test_plot_colnames_that_are_valid_matplotlib_greyscale_colors_are_not_evaluated_as_colors(
+ self, sdata_blobs: SpatialData, colname: str
+ ):
+ sdata_blobs["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
+ sdata_blobs["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
+ sdata_blobs.shapes["blobs_polygons"][colname] = [1, 2, 3, 5, 20]
+ sdata_blobs.pl.render_shapes("blobs_polygons", color=colname).pl.show()
+
  def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData):
  from spatialdata_plot.pl.utils import set_zero_in_cmap_to_transparent
 
@@ -60,6 +79,23 @@ def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData
  ).pl.show(ax=axs[1], colorbar=False)
 
 
+@pytest.mark.parametrize(
+ "color_result",
+ [
+ ("0", False),
+ ("0.5", False),
+ ("1", False),
+ ("#00ff00", True),
+ ((0.0, 1.0, 0.0, 1.0), True),
+ ],
+)
+def test_is_color_like(color_result: tuple[ColorLike, bool]):
+
+ color, result = color_result
+
+ assert spatialdata_plot.pl.utils._is_color_like(color) == result
+
+
 @pytest.mark.parametrize(
  "input_output",
  [

src/spatialdata_plot/pl/utils.py

@@ -83,6 +83,28 @@
 ColorLike = Union[tuple[float, ...], str]
 
 
+def _is_color_like(color: Any) -> bool:
+ """Check if a value is a valid color, returns False for pseudo-bools.
+
+ For discussion, see: https://github.com/scverse/spatialdata-plot/issues/327.
+ matplotlib accepts strings in [0, 1] as grey-scale values - therefore,
+ "0" and "1" are considered valid colors. However, we won't do that
+ so we're filtering these out.
+ """
+ if isinstance(color, bool):
+ return False
+ if isinstance(color, str):
+ try:
+ num_value = float(color)
+ if 0 <= num_value <= 1:
+ return False
+ except ValueError:
+ # we're not dealing with what matplotlib considers greyscale
+ pass
+
+ return bool(colors.is_color_like(color))
+
+
 def _prepare_params_plot(
  # this param is inferred when `pl.show`` is called
  num_panels: int,
@@ -532,7 +554,15 @@ def _normalize(
 
  perc = np.percentile(img, [pmin, pmax])
 
- norm = (img - perc[0]) / (perc[1] - perc[0] + eps)
+ # Ensure perc is an array of two elements
+ if np.isscalar(perc):
+ logger.warning(
+ "Percentile range is too small, using the same percentile for both min "
+ "and max. Consider using a larger percentile range."
+ )
+ perc = np.array([perc, perc])
+
+ norm = (img - perc[0]) / (perc[1] - perc[0] + eps) # type: ignore
 
  if clip:
  norm = np.clip(norm, 0, 1)
@@ -727,7 +757,7 @@ def _map_color_seg(
  val_im = np.squeeze(val_im, axis=0)
  if "#" in str(color_vector[0]):
  # we have hex colors
- assert all(colors.is_color_like(c) for c in color_vector), "Not all values are color-like."
+ assert all(_is_color_like(c) for c in color_vector), "Not all values are color-like."
  cols = colors.to_rgba_array(color_vector)
  else:
  cols = cmap_params.cmap(cmap_params.norm(color_vector))
@@ -1557,15 +1587,11 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  if (contour_px := param_dict.get("contour_px")) and not isinstance(contour_px, int):
  raise TypeError("Parameter 'contour_px' must be an integer.")
 
- if (color := param_dict.get("color")) and element_type in {
- "shapes",
- "points",
- "labels",
- }:
+ if (color := param_dict.get("color")) and element_type in {"shapes", "points", "labels"}:
  if not isinstance(color, str):
  raise TypeError("Parameter 'color' must be a string.")
  if element_type in {"shapes", "points"}:
- if colors.is_color_like(color):
+ if _is_color_like(color):
  logger.info("Value for parameter 'color' appears to be a color, using it as such.")
  param_dict["col_for_color"] = None
  else:
@@ -1645,7 +1671,7 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  raise TypeError("Parameter 'cmap' must be a string, a Colormap, or a list of these types.")
 
  if (na_color := param_dict.get("na_color")) != "default" and (
- na_color is not None and not colors.is_color_like(na_color)
+ na_color is not None and not _is_color_like(na_color)
  ):
  raise ValueError("Parameter 'na_color' must be color-like.")
 

tests/pl/test_render_shapes.py

@@ -7,7 +7,7 @@
 import spatialdata_plot # noqa: F401
 from anndata import AnnData
 from shapely.geometry import MultiPolygon, Point, Polygon
-from spatialdata import SpatialData
+from spatialdata import SpatialData, deepcopy
 from spatialdata.models import ShapesModel, TableModel
 
 from tests.conftest import DPI, PlotTester, PlotTesterMeta
@@ -94,7 +94,7 @@ def _make_multi():
  sdata.pl.render_shapes(color="val", outline=True, fill_alpha=0.3).pl.show()
 
  def test_plot_can_color_from_geodataframe(self, sdata_blobs: SpatialData):
- blob = sdata_blobs
+ blob = deepcopy(sdata_blobs)
  blob["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
  blob["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
  blob.shapes["blobs_polygons"]["value"] = [1, 10, 1, 20, 1]

tests/pl/test_utils.py

@@ -1,3 +1,5 @@
+from typing import Union
+
 import matplotlib
 import matplotlib.pyplot as plt
 import numpy as np
@@ -23,6 +25,11 @@
 # the comp. function can be accessed as `self.compare(<your_filename>, tolerance=<your_tolerance>)`
 # ".png" is appended to <your_filename>, no need to set it
 
+# replace with
+# from spatialdata._types import ColorLike
+# once https://github.com/scverse/spatialdata/pull/689/ is in a release
+ColorLike = Union[tuple[float, ...], str]
+
 
 class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  @pytest.mark.parametrize(
@@ -35,6 +42,18 @@ class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  def test_plot_set_outline_accepts_str_or_float_or_list_thereof(self, sdata_blobs: SpatialData, outline_color):
  sdata_blobs.pl.render_shapes(element="blobs_polygons", outline=True, outline_color=outline_color).pl.show()
 
+ @pytest.mark.parametrize(
+ "colname",
+ ["0", "0.5", "1"],
+ )
+ def test_plot_colnames_that_are_valid_matplotlib_greyscale_colors_are_not_evaluated_as_colors(
+ self, sdata_blobs: SpatialData, colname: str
+ ):
+ sdata_blobs["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
+ sdata_blobs["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
+ sdata_blobs.shapes["blobs_polygons"][colname] = [1, 2, 3, 5, 20]
+ sdata_blobs.pl.render_shapes("blobs_polygons", color=colname).pl.show()
+
  def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData):
  from spatialdata_plot.pl.utils import set_zero_in_cmap_to_transparent
 
@@ -60,6 +79,23 @@ def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData
  ).pl.show(ax=axs[1], colorbar=False)
 
 
+@pytest.mark.parametrize(
+ "color_result",
+ [
+ ("0", False),
+ ("0.5", False),
+ ("1", False),
+ ("#00ff00", True),
+ ((0.0, 1.0, 0.0, 1.0), True),
+ ],
+)
+def test_is_color_like(color_result: tuple[ColorLike, bool]):
+
+ color, result = color_result
+
+ assert spatialdata_plot.pl.utils._is_color_like(color) == result
+
+
 @pytest.mark.parametrize(
  "input_output",
  [

src/spatialdata_plot/pl/utils.py

@@ -83,6 +83,28 @@
 ColorLike = Union[tuple[float, ...], str]
 
 
+def _is_color_like(color: Any) -> bool:
+ """Check if a value is a valid color, returns False for pseudo-bools.
+
+ For discussion, see: https://github.com/scverse/spatialdata-plot/issues/327.
+ matplotlib accepts strings in [0, 1] as grey-scale values - therefore,
+ "0" and "1" are considered valid colors. However, we won't do that
+ so we're filtering these out.
+ """
+ if isinstance(color, bool):
+ return False
+ if isinstance(color, str):
+ try:
+ num_value = float(color)
+ if 0 <= num_value <= 1:
+ return False
+ except ValueError:
+ # we're not dealing with what matplotlib considers greyscale
+ pass
+
+ return bool(colors.is_color_like(color))
+
+
 def _prepare_params_plot(
  # this param is inferred when `pl.show`` is called
  num_panels: int,
@@ -532,7 +554,15 @@ def _normalize(
 
  perc = np.percentile(img, [pmin, pmax])
 
- norm = (img - perc[0]) / (perc[1] - perc[0] + eps)
+ # Ensure perc is an array of two elements
+ if np.isscalar(perc):
+ logger.warning(
+ "Percentile range is too small, using the same percentile for both min "
+ "and max. Consider using a larger percentile range."
+ )
+ perc = np.array([perc, perc])
+
+ norm = (img - perc[0]) / (perc[1] - perc[0] + eps) # type: ignore
 
  if clip:
  norm = np.clip(norm, 0, 1)
@@ -727,7 +757,7 @@ def _map_color_seg(
  val_im = np.squeeze(val_im, axis=0)
  if "#" in str(color_vector[0]):
  # we have hex colors
- assert all(colors.is_color_like(c) for c in color_vector), "Not all values are color-like."
+ assert all(_is_color_like(c) for c in color_vector), "Not all values are color-like."
  cols = colors.to_rgba_array(color_vector)
  else:
  cols = cmap_params.cmap(cmap_params.norm(color_vector))
@@ -1557,15 +1587,11 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  if (contour_px := param_dict.get("contour_px")) and not isinstance(contour_px, int):
  raise TypeError("Parameter 'contour_px' must be an integer.")
 
- if (color := param_dict.get("color")) and element_type in {
- "shapes",
- "points",
- "labels",
- }:
+ if (color := param_dict.get("color")) and element_type in {"shapes", "points", "labels"}:
  if not isinstance(color, str):
  raise TypeError("Parameter 'color' must be a string.")
  if element_type in {"shapes", "points"}:
- if colors.is_color_like(color):
+ if _is_color_like(color):
  logger.info("Value for parameter 'color' appears to be a color, using it as such.")
  param_dict["col_for_color"] = None
  else:
@@ -1645,7 +1671,7 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  raise TypeError("Parameter 'cmap' must be a string, a Colormap, or a list of these types.")
 
  if (na_color := param_dict.get("na_color")) != "default" and (
- na_color is not None and not colors.is_color_like(na_color)
+ na_color is not None and not _is_color_like(na_color)
  ):
  raise ValueError("Parameter 'na_color' must be color-like.")
 

tests/pl/test_render_shapes.py

@@ -7,7 +7,7 @@
 import spatialdata_plot # noqa: F401
 from anndata import AnnData
 from shapely.geometry import MultiPolygon, Point, Polygon
-from spatialdata import SpatialData
+from spatialdata import SpatialData, deepcopy
 from spatialdata.models import ShapesModel, TableModel
 
 from tests.conftest import DPI, PlotTester, PlotTesterMeta
@@ -94,7 +94,7 @@ def _make_multi():
  sdata.pl.render_shapes(color="val", outline=True, fill_alpha=0.3).pl.show()
 
  def test_plot_can_color_from_geodataframe(self, sdata_blobs: SpatialData):
- blob = sdata_blobs
+ blob = deepcopy(sdata_blobs)
  blob["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
  blob["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
  blob.shapes["blobs_polygons"]["value"] = [1, 10, 1, 20, 1]

tests/pl/test_utils.py

@@ -1,3 +1,5 @@
+from typing import Union
+
 import matplotlib
 import matplotlib.pyplot as plt
 import numpy as np
@@ -23,6 +25,11 @@
 # the comp. function can be accessed as `self.compare(<your_filename>, tolerance=<your_tolerance>)`
 # ".png" is appended to <your_filename>, no need to set it
 
+# replace with
+# from spatialdata._types import ColorLike
+# once https://github.com/scverse/spatialdata/pull/689/ is in a release
+ColorLike = Union[tuple[float, ...], str]
+
 
 class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  @pytest.mark.parametrize(
@@ -35,6 +42,18 @@ class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  def test_plot_set_outline_accepts_str_or_float_or_list_thereof(self, sdata_blobs: SpatialData, outline_color):
  sdata_blobs.pl.render_shapes(element="blobs_polygons", outline=True, outline_color=outline_color).pl.show()
 
+ @pytest.mark.parametrize(
+ "colname",
+ ["0", "0.5", "1"],
+ )
+ def test_plot_colnames_that_are_valid_matplotlib_greyscale_colors_are_not_evaluated_as_colors(
+ self, sdata_blobs: SpatialData, colname: str
+ ):
+ sdata_blobs["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
+ sdata_blobs["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
+ sdata_blobs.shapes["blobs_polygons"][colname] = [1, 2, 3, 5, 20]
+ sdata_blobs.pl.render_shapes("blobs_polygons", color=colname).pl.show()
+
  def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData):
  from spatialdata_plot.pl.utils import set_zero_in_cmap_to_transparent
 
@@ -60,6 +79,23 @@ def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData
  ).pl.show(ax=axs[1], colorbar=False)
 
 
+@pytest.mark.parametrize(
+ "color_result",
+ [
+ ("0", False),
+ ("0.5", False),
+ ("1", False),
+ ("#00ff00", True),
+ ((0.0, 1.0, 0.0, 1.0), True),
+ ],
+)
+def test_is_color_like(color_result: tuple[ColorLike, bool]):
+
+ color, result = color_result
+
+ assert spatialdata_plot.pl.utils._is_color_like(color) == result
+
+
 @pytest.mark.parametrize(
  "input_output",
  [

src/spatialdata_plot/pl/utils.py

@@ -83,6 +83,28 @@
 ColorLike = Union[tuple[float, ...], str]
 
 
+def _is_color_like(color: Any) -> bool:
+ """Check if a value is a valid color, returns False for pseudo-bools.
+
+ For discussion, see: https://github.com/scverse/spatialdata-plot/issues/327.
+ matplotlib accepts strings in [0, 1] as grey-scale values - therefore,
+ "0" and "1" are considered valid colors. However, we won't do that
+ so we're filtering these out.
+ """
+ if isinstance(color, bool):
+ return False
+ if isinstance(color, str):
+ try:
+ num_value = float(color)
+ if 0 <= num_value <= 1:
+ return False
+ except ValueError:
+ # we're not dealing with what matplotlib considers greyscale
+ pass
+
+ return bool(colors.is_color_like(color))
+
+
 def _prepare_params_plot(
  # this param is inferred when `pl.show`` is called
  num_panels: int,
@@ -532,7 +554,15 @@ def _normalize(
 
  perc = np.percentile(img, [pmin, pmax])
 
- norm = (img - perc[0]) / (perc[1] - perc[0] + eps)
+ # Ensure perc is an array of two elements
+ if np.isscalar(perc):
+ logger.warning(
+ "Percentile range is too small, using the same percentile for both min "
+ "and max. Consider using a larger percentile range."
+ )
+ perc = np.array([perc, perc])
+
+ norm = (img - perc[0]) / (perc[1] - perc[0] + eps) # type: ignore
 
  if clip:
  norm = np.clip(norm, 0, 1)
@@ -727,7 +757,7 @@ def _map_color_seg(
  val_im = np.squeeze(val_im, axis=0)
  if "#" in str(color_vector[0]):
  # we have hex colors
- assert all(colors.is_color_like(c) for c in color_vector), "Not all values are color-like."
+ assert all(_is_color_like(c) for c in color_vector), "Not all values are color-like."
  cols = colors.to_rgba_array(color_vector)
  else:
  cols = cmap_params.cmap(cmap_params.norm(color_vector))
@@ -1557,15 +1587,11 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  if (contour_px := param_dict.get("contour_px")) and not isinstance(contour_px, int):
  raise TypeError("Parameter 'contour_px' must be an integer.")
 
- if (color := param_dict.get("color")) and element_type in {
- "shapes",
- "points",
- "labels",
- }:
+ if (color := param_dict.get("color")) and element_type in {"shapes", "points", "labels"}:
  if not isinstance(color, str):
  raise TypeError("Parameter 'color' must be a string.")
  if element_type in {"shapes", "points"}:
- if colors.is_color_like(color):
+ if _is_color_like(color):
  logger.info("Value for parameter 'color' appears to be a color, using it as such.")
  param_dict["col_for_color"] = None
  else:
@@ -1645,7 +1671,7 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  raise TypeError("Parameter 'cmap' must be a string, a Colormap, or a list of these types.")
 
  if (na_color := param_dict.get("na_color")) != "default" and (
- na_color is not None and not colors.is_color_like(na_color)
+ na_color is not None and not _is_color_like(na_color)
  ):
  raise ValueError("Parameter 'na_color' must be color-like.")
 

tests/pl/test_render_shapes.py

@@ -7,7 +7,7 @@
 import spatialdata_plot # noqa: F401
 from anndata import AnnData
 from shapely.geometry import MultiPolygon, Point, Polygon
-from spatialdata import SpatialData
+from spatialdata import SpatialData, deepcopy
 from spatialdata.models import ShapesModel, TableModel
 
 from tests.conftest import DPI, PlotTester, PlotTesterMeta
@@ -94,7 +94,7 @@ def _make_multi():
  sdata.pl.render_shapes(color="val", outline=True, fill_alpha=0.3).pl.show()
 
  def test_plot_can_color_from_geodataframe(self, sdata_blobs: SpatialData):
- blob = sdata_blobs
+ blob = deepcopy(sdata_blobs)
  blob["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
  blob["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
  blob.shapes["blobs_polygons"]["value"] = [1, 10, 1, 20, 1]

tests/pl/test_utils.py

@@ -1,3 +1,5 @@
+from typing import Union
+
 import matplotlib
 import matplotlib.pyplot as plt
 import numpy as np
@@ -23,6 +25,11 @@
 # the comp. function can be accessed as `self.compare(<your_filename>, tolerance=<your_tolerance>)`
 # ".png" is appended to <your_filename>, no need to set it
 
+# replace with
+# from spatialdata._types import ColorLike
+# once https://github.com/scverse/spatialdata/pull/689/ is in a release
+ColorLike = Union[tuple[float, ...], str]
+
 
 class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  @pytest.mark.parametrize(
@@ -35,6 +42,18 @@ class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  def test_plot_set_outline_accepts_str_or_float_or_list_thereof(self, sdata_blobs: SpatialData, outline_color):
  sdata_blobs.pl.render_shapes(element="blobs_polygons", outline=True, outline_color=outline_color).pl.show()
 
+ @pytest.mark.parametrize(
+ "colname",
+ ["0", "0.5", "1"],
+ )
+ def test_plot_colnames_that_are_valid_matplotlib_greyscale_colors_are_not_evaluated_as_colors(
+ self, sdata_blobs: SpatialData, colname: str
+ ):
+ sdata_blobs["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
+ sdata_blobs["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
+ sdata_blobs.shapes["blobs_polygons"][colname] = [1, 2, 3, 5, 20]
+ sdata_blobs.pl.render_shapes("blobs_polygons", color=colname).pl.show()
+
  def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData):
  from spatialdata_plot.pl.utils import set_zero_in_cmap_to_transparent
 
@@ -60,6 +79,23 @@ def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData
  ).pl.show(ax=axs[1], colorbar=False)
 
 
+@pytest.mark.parametrize(
+ "color_result",
+ [
+ ("0", False),
+ ("0.5", False),
+ ("1", False),
+ ("#00ff00", True),
+ ((0.0, 1.0, 0.0, 1.0), True),
+ ],
+)
+def test_is_color_like(color_result: tuple[ColorLike, bool]):
+
+ color, result = color_result
+
+ assert spatialdata_plot.pl.utils._is_color_like(color) == result
+
+
 @pytest.mark.parametrize(
  "input_output",
  [

src/spatialdata_plot/pl/utils.py

@@ -83,6 +83,28 @@
 ColorLike = Union[tuple[float, ...], str]
 
 
+def _is_color_like(color: Any) -> bool:
+ """Check if a value is a valid color, returns False for pseudo-bools.
+
+ For discussion, see: https://github.com/scverse/spatialdata-plot/issues/327.
+ matplotlib accepts strings in [0, 1] as grey-scale values - therefore,
+ "0" and "1" are considered valid colors. However, we won't do that
+ so we're filtering these out.
+ """
+ if isinstance(color, bool):
+ return False
+ if isinstance(color, str):
+ try:
+ num_value = float(color)
+ if 0 <= num_value <= 1:
+ return False
+ except ValueError:
+ # we're not dealing with what matplotlib considers greyscale
+ pass
+
+ return bool(colors.is_color_like(color))
+
+
 def _prepare_params_plot(
  # this param is inferred when `pl.show`` is called
  num_panels: int,
@@ -532,7 +554,15 @@ def _normalize(
 
  perc = np.percentile(img, [pmin, pmax])
 
- norm = (img - perc[0]) / (perc[1] - perc[0] + eps)
+ # Ensure perc is an array of two elements
+ if np.isscalar(perc):
+ logger.warning(
+ "Percentile range is too small, using the same percentile for both min "
+ "and max. Consider using a larger percentile range."
+ )
+ perc = np.array([perc, perc])
+
+ norm = (img - perc[0]) / (perc[1] - perc[0] + eps) # type: ignore
 
  if clip:
  norm = np.clip(norm, 0, 1)
@@ -727,7 +757,7 @@ def _map_color_seg(
  val_im = np.squeeze(val_im, axis=0)
  if "#" in str(color_vector[0]):
  # we have hex colors
- assert all(colors.is_color_like(c) for c in color_vector), "Not all values are color-like."
+ assert all(_is_color_like(c) for c in color_vector), "Not all values are color-like."
  cols = colors.to_rgba_array(color_vector)
  else:
  cols = cmap_params.cmap(cmap_params.norm(color_vector))
@@ -1557,15 +1587,11 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  if (contour_px := param_dict.get("contour_px")) and not isinstance(contour_px, int):
  raise TypeError("Parameter 'contour_px' must be an integer.")
 
- if (color := param_dict.get("color")) and element_type in {
- "shapes",
- "points",
- "labels",
- }:
+ if (color := param_dict.get("color")) and element_type in {"shapes", "points", "labels"}:
  if not isinstance(color, str):
  raise TypeError("Parameter 'color' must be a string.")
  if element_type in {"shapes", "points"}:
- if colors.is_color_like(color):
+ if _is_color_like(color):
  logger.info("Value for parameter 'color' appears to be a color, using it as such.")
  param_dict["col_for_color"] = None
  else:
@@ -1645,7 +1671,7 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  raise TypeError("Parameter 'cmap' must be a string, a Colormap, or a list of these types.")
 
  if (na_color := param_dict.get("na_color")) != "default" and (
- na_color is not None and not colors.is_color_like(na_color)
+ na_color is not None and not _is_color_like(na_color)
  ):
  raise ValueError("Parameter 'na_color' must be color-like.")
 

tests/pl/test_render_shapes.py

@@ -7,7 +7,7 @@
 import spatialdata_plot # noqa: F401
 from anndata import AnnData
 from shapely.geometry import MultiPolygon, Point, Polygon
-from spatialdata import SpatialData
+from spatialdata import SpatialData, deepcopy
 from spatialdata.models import ShapesModel, TableModel
 
 from tests.conftest import DPI, PlotTester, PlotTesterMeta
@@ -94,7 +94,7 @@ def _make_multi():
  sdata.pl.render_shapes(color="val", outline=True, fill_alpha=0.3).pl.show()
 
  def test_plot_can_color_from_geodataframe(self, sdata_blobs: SpatialData):
- blob = sdata_blobs
+ blob = deepcopy(sdata_blobs)
  blob["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
  blob["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
  blob.shapes["blobs_polygons"]["value"] = [1, 10, 1, 20, 1]

tests/pl/test_utils.py

@@ -1,3 +1,5 @@
+from typing import Union
+
 import matplotlib
 import matplotlib.pyplot as plt
 import numpy as np
@@ -23,6 +25,11 @@
 # the comp. function can be accessed as `self.compare(<your_filename>, tolerance=<your_tolerance>)`
 # ".png" is appended to <your_filename>, no need to set it
 
+# replace with
+# from spatialdata._types import ColorLike
+# once https://github.com/scverse/spatialdata/pull/689/ is in a release
+ColorLike = Union[tuple[float, ...], str]
+
 
 class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  @pytest.mark.parametrize(
@@ -35,6 +42,18 @@ class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  def test_plot_set_outline_accepts_str_or_float_or_list_thereof(self, sdata_blobs: SpatialData, outline_color):
  sdata_blobs.pl.render_shapes(element="blobs_polygons", outline=True, outline_color=outline_color).pl.show()
 
+ @pytest.mark.parametrize(
+ "colname",
+ ["0", "0.5", "1"],
+ )
+ def test_plot_colnames_that_are_valid_matplotlib_greyscale_colors_are_not_evaluated_as_colors(
+ self, sdata_blobs: SpatialData, colname: str
+ ):
+ sdata_blobs["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
+ sdata_blobs["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
+ sdata_blobs.shapes["blobs_polygons"][colname] = [1, 2, 3, 5, 20]
+ sdata_blobs.pl.render_shapes("blobs_polygons", color=colname).pl.show()
+
  def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData):
  from spatialdata_plot.pl.utils import set_zero_in_cmap_to_transparent
 
@@ -60,6 +79,23 @@ def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData
  ).pl.show(ax=axs[1], colorbar=False)
 
 
+@pytest.mark.parametrize(
+ "color_result",
+ [
+ ("0", False),
+ ("0.5", False),
+ ("1", False),
+ ("#00ff00", True),
+ ((0.0, 1.0, 0.0, 1.0), True),
+ ],
+)
+def test_is_color_like(color_result: tuple[ColorLike, bool]):
+
+ color, result = color_result
+
+ assert spatialdata_plot.pl.utils._is_color_like(color) == result
+
+
 @pytest.mark.parametrize(
  "input_output",
  [

src/spatialdata_plot/pl/utils.py

@@ -83,6 +83,28 @@
 ColorLike = Union[tuple[float, ...], str]
 
 
+def _is_color_like(color: Any) -> bool:
+ """Check if a value is a valid color, returns False for pseudo-bools.
+
+ For discussion, see: https://github.com/scverse/spatialdata-plot/issues/327.
+ matplotlib accepts strings in [0, 1] as grey-scale values - therefore,
+ "0" and "1" are considered valid colors. However, we won't do that
+ so we're filtering these out.
+ """
+ if isinstance(color, bool):
+ return False
+ if isinstance(color, str):
+ try:
+ num_value = float(color)
+ if 0 <= num_value <= 1:
+ return False
+ except ValueError:
+ # we're not dealing with what matplotlib considers greyscale
+ pass
+
+ return bool(colors.is_color_like(color))
+
+
 def _prepare_params_plot(
  # this param is inferred when `pl.show`` is called
  num_panels: int,
@@ -532,7 +554,15 @@ def _normalize(
 
  perc = np.percentile(img, [pmin, pmax])
 
- norm = (img - perc[0]) / (perc[1] - perc[0] + eps)
+ # Ensure perc is an array of two elements
+ if np.isscalar(perc):
+ logger.warning(
+ "Percentile range is too small, using the same percentile for both min "
+ "and max. Consider using a larger percentile range."
+ )
+ perc = np.array([perc, perc])
+
+ norm = (img - perc[0]) / (perc[1] - perc[0] + eps) # type: ignore
 
  if clip:
  norm = np.clip(norm, 0, 1)
@@ -727,7 +757,7 @@ def _map_color_seg(
  val_im = np.squeeze(val_im, axis=0)
  if "#" in str(color_vector[0]):
  # we have hex colors
- assert all(colors.is_color_like(c) for c in color_vector), "Not all values are color-like."
+ assert all(_is_color_like(c) for c in color_vector), "Not all values are color-like."
  cols = colors.to_rgba_array(color_vector)
  else:
  cols = cmap_params.cmap(cmap_params.norm(color_vector))
@@ -1557,15 +1587,11 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  if (contour_px := param_dict.get("contour_px")) and not isinstance(contour_px, int):
  raise TypeError("Parameter 'contour_px' must be an integer.")
 
- if (color := param_dict.get("color")) and element_type in {
- "shapes",
- "points",
- "labels",
- }:
+ if (color := param_dict.get("color")) and element_type in {"shapes", "points", "labels"}:
  if not isinstance(color, str):
  raise TypeError("Parameter 'color' must be a string.")
  if element_type in {"shapes", "points"}:
- if colors.is_color_like(color):
+ if _is_color_like(color):
  logger.info("Value for parameter 'color' appears to be a color, using it as such.")
  param_dict["col_for_color"] = None
  else:
@@ -1645,7 +1671,7 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  raise TypeError("Parameter 'cmap' must be a string, a Colormap, or a list of these types.")
 
  if (na_color := param_dict.get("na_color")) != "default" and (
- na_color is not None and not colors.is_color_like(na_color)
+ na_color is not None and not _is_color_like(na_color)
  ):
  raise ValueError("Parameter 'na_color' must be color-like.")
 

tests/pl/test_render_shapes.py

@@ -7,7 +7,7 @@
 import spatialdata_plot # noqa: F401
 from anndata import AnnData
 from shapely.geometry import MultiPolygon, Point, Polygon
-from spatialdata import SpatialData
+from spatialdata import SpatialData, deepcopy
 from spatialdata.models import ShapesModel, TableModel
 
 from tests.conftest import DPI, PlotTester, PlotTesterMeta
@@ -94,7 +94,7 @@ def _make_multi():
  sdata.pl.render_shapes(color="val", outline=True, fill_alpha=0.3).pl.show()
 
  def test_plot_can_color_from_geodataframe(self, sdata_blobs: SpatialData):
- blob = sdata_blobs
+ blob = deepcopy(sdata_blobs)
  blob["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
  blob["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
  blob.shapes["blobs_polygons"]["value"] = [1, 10, 1, 20, 1]

tests/pl/test_utils.py

@@ -1,3 +1,5 @@
+from typing import Union
+
 import matplotlib
 import matplotlib.pyplot as plt
 import numpy as np
@@ -23,6 +25,11 @@
 # the comp. function can be accessed as `self.compare(<your_filename>, tolerance=<your_tolerance>)`
 # ".png" is appended to <your_filename>, no need to set it
 
+# replace with
+# from spatialdata._types import ColorLike
+# once https://github.com/scverse/spatialdata/pull/689/ is in a release
+ColorLike = Union[tuple[float, ...], str]
+
 
 class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  @pytest.mark.parametrize(
@@ -35,6 +42,18 @@ class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  def test_plot_set_outline_accepts_str_or_float_or_list_thereof(self, sdata_blobs: SpatialData, outline_color):
  sdata_blobs.pl.render_shapes(element="blobs_polygons", outline=True, outline_color=outline_color).pl.show()
 
+ @pytest.mark.parametrize(
+ "colname",
+ ["0", "0.5", "1"],
+ )
+ def test_plot_colnames_that_are_valid_matplotlib_greyscale_colors_are_not_evaluated_as_colors(
+ self, sdata_blobs: SpatialData, colname: str
+ ):
+ sdata_blobs["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
+ sdata_blobs["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
+ sdata_blobs.shapes["blobs_polygons"][colname] = [1, 2, 3, 5, 20]
+ sdata_blobs.pl.render_shapes("blobs_polygons", color=colname).pl.show()
+
  def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData):
  from spatialdata_plot.pl.utils import set_zero_in_cmap_to_transparent
 
@@ -60,6 +79,23 @@ def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData
  ).pl.show(ax=axs[1], colorbar=False)
 
 
+@pytest.mark.parametrize(
+ "color_result",
+ [
+ ("0", False),
+ ("0.5", False),
+ ("1", False),
+ ("#00ff00", True),
+ ((0.0, 1.0, 0.0, 1.0), True),
+ ],
+)
+def test_is_color_like(color_result: tuple[ColorLike, bool]):
+
+ color, result = color_result
+
+ assert spatialdata_plot.pl.utils._is_color_like(color) == result
+
+
 @pytest.mark.parametrize(
  "input_output",
  [

src/spatialdata_plot/pl/utils.py

@@ -83,6 +83,28 @@
 ColorLike = Union[tuple[float, ...], str]
 
 
+def _is_color_like(color: Any) -> bool:
+ """Check if a value is a valid color, returns False for pseudo-bools.
+
+ For discussion, see: https://github.com/scverse/spatialdata-plot/issues/327.
+ matplotlib accepts strings in [0, 1] as grey-scale values - therefore,
+ "0" and "1" are considered valid colors. However, we won't do that
+ so we're filtering these out.
+ """
+ if isinstance(color, bool):
+ return False
+ if isinstance(color, str):
+ try:
+ num_value = float(color)
+ if 0 <= num_value <= 1:
+ return False
+ except ValueError:
+ # we're not dealing with what matplotlib considers greyscale
+ pass
+
+ return bool(colors.is_color_like(color))
+
+
 def _prepare_params_plot(
  # this param is inferred when `pl.show`` is called
  num_panels: int,
@@ -532,7 +554,15 @@ def _normalize(
 
  perc = np.percentile(img, [pmin, pmax])
 
- norm = (img - perc[0]) / (perc[1] - perc[0] + eps)
+ # Ensure perc is an array of two elements
+ if np.isscalar(perc):
+ logger.warning(
+ "Percentile range is too small, using the same percentile for both min "
+ "and max. Consider using a larger percentile range."
+ )
+ perc = np.array([perc, perc])
+
+ norm = (img - perc[0]) / (perc[1] - perc[0] + eps) # type: ignore
 
  if clip:
  norm = np.clip(norm, 0, 1)
@@ -727,7 +757,7 @@ def _map_color_seg(
  val_im = np.squeeze(val_im, axis=0)
  if "#" in str(color_vector[0]):
  # we have hex colors
- assert all(colors.is_color_like(c) for c in color_vector), "Not all values are color-like."
+ assert all(_is_color_like(c) for c in color_vector), "Not all values are color-like."
  cols = colors.to_rgba_array(color_vector)
  else:
  cols = cmap_params.cmap(cmap_params.norm(color_vector))
@@ -1557,15 +1587,11 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  if (contour_px := param_dict.get("contour_px")) and not isinstance(contour_px, int):
  raise TypeError("Parameter 'contour_px' must be an integer.")
 
- if (color := param_dict.get("color")) and element_type in {
- "shapes",
- "points",
- "labels",
- }:
+ if (color := param_dict.get("color")) and element_type in {"shapes", "points", "labels"}:
  if not isinstance(color, str):
  raise TypeError("Parameter 'color' must be a string.")
  if element_type in {"shapes", "points"}:
- if colors.is_color_like(color):
+ if _is_color_like(color):
  logger.info("Value for parameter 'color' appears to be a color, using it as such.")
  param_dict["col_for_color"] = None
  else:
@@ -1645,7 +1671,7 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  raise TypeError("Parameter 'cmap' must be a string, a Colormap, or a list of these types.")
 
  if (na_color := param_dict.get("na_color")) != "default" and (
- na_color is not None and not colors.is_color_like(na_color)
+ na_color is not None and not _is_color_like(na_color)
  ):
  raise ValueError("Parameter 'na_color' must be color-like.")
 

tests/pl/test_render_shapes.py

@@ -7,7 +7,7 @@
 import spatialdata_plot # noqa: F401
 from anndata import AnnData
 from shapely.geometry import MultiPolygon, Point, Polygon
-from spatialdata import SpatialData
+from spatialdata import SpatialData, deepcopy
 from spatialdata.models import ShapesModel, TableModel
 
 from tests.conftest import DPI, PlotTester, PlotTesterMeta
@@ -94,7 +94,7 @@ def _make_multi():
  sdata.pl.render_shapes(color="val", outline=True, fill_alpha=0.3).pl.show()
 
  def test_plot_can_color_from_geodataframe(self, sdata_blobs: SpatialData):
- blob = sdata_blobs
+ blob = deepcopy(sdata_blobs)
  blob["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
  blob["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
  blob.shapes["blobs_polygons"]["value"] = [1, 10, 1, 20, 1]

tests/pl/test_utils.py

@@ -1,3 +1,5 @@
+from typing import Union
+
 import matplotlib
 import matplotlib.pyplot as plt
 import numpy as np
@@ -23,6 +25,11 @@
 # the comp. function can be accessed as `self.compare(<your_filename>, tolerance=<your_tolerance>)`
 # ".png" is appended to <your_filename>, no need to set it
 
+# replace with
+# from spatialdata._types import ColorLike
+# once https://github.com/scverse/spatialdata/pull/689/ is in a release
+ColorLike = Union[tuple[float, ...], str]
+
 
 class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  @pytest.mark.parametrize(
@@ -35,6 +42,18 @@ class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  def test_plot_set_outline_accepts_str_or_float_or_list_thereof(self, sdata_blobs: SpatialData, outline_color):
  sdata_blobs.pl.render_shapes(element="blobs_polygons", outline=True, outline_color=outline_color).pl.show()
 
+ @pytest.mark.parametrize(
+ "colname",
+ ["0", "0.5", "1"],
+ )
+ def test_plot_colnames_that_are_valid_matplotlib_greyscale_colors_are_not_evaluated_as_colors(
+ self, sdata_blobs: SpatialData, colname: str
+ ):
+ sdata_blobs["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
+ sdata_blobs["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
+ sdata_blobs.shapes["blobs_polygons"][colname] = [1, 2, 3, 5, 20]
+ sdata_blobs.pl.render_shapes("blobs_polygons", color=colname).pl.show()
+
  def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData):
  from spatialdata_plot.pl.utils import set_zero_in_cmap_to_transparent
 
@@ -60,6 +79,23 @@ def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData
  ).pl.show(ax=axs[1], colorbar=False)
 
 
+@pytest.mark.parametrize(
+ "color_result",
+ [
+ ("0", False),
+ ("0.5", False),
+ ("1", False),
+ ("#00ff00", True),
+ ((0.0, 1.0, 0.0, 1.0), True),
+ ],
+)
+def test_is_color_like(color_result: tuple[ColorLike, bool]):
+
+ color, result = color_result
+
+ assert spatialdata_plot.pl.utils._is_color_like(color) == result
+
+
 @pytest.mark.parametrize(
  "input_output",
  [

src/spatialdata_plot/pl/utils.py

@@ -83,6 +83,28 @@
 ColorLike = Union[tuple[float, ...], str]
 
 
+def _is_color_like(color: Any) -> bool:
+ """Check if a value is a valid color, returns False for pseudo-bools.
+
+ For discussion, see: https://github.com/scverse/spatialdata-plot/issues/327.
+ matplotlib accepts strings in [0, 1] as grey-scale values - therefore,
+ "0" and "1" are considered valid colors. However, we won't do that
+ so we're filtering these out.
+ """
+ if isinstance(color, bool):
+ return False
+ if isinstance(color, str):
+ try:
+ num_value = float(color)
+ if 0 <= num_value <= 1:
+ return False
+ except ValueError:
+ # we're not dealing with what matplotlib considers greyscale
+ pass
+
+ return bool(colors.is_color_like(color))
+
+
 def _prepare_params_plot(
  # this param is inferred when `pl.show`` is called
  num_panels: int,
@@ -532,7 +554,15 @@ def _normalize(
 
  perc = np.percentile(img, [pmin, pmax])
 
- norm = (img - perc[0]) / (perc[1] - perc[0] + eps)
+ # Ensure perc is an array of two elements
+ if np.isscalar(perc):
+ logger.warning(
+ "Percentile range is too small, using the same percentile for both min "
+ "and max. Consider using a larger percentile range."
+ )
+ perc = np.array([perc, perc])
+
+ norm = (img - perc[0]) / (perc[1] - perc[0] + eps) # type: ignore
 
  if clip:
  norm = np.clip(norm, 0, 1)
@@ -727,7 +757,7 @@ def _map_color_seg(
  val_im = np.squeeze(val_im, axis=0)
  if "#" in str(color_vector[0]):
  # we have hex colors
- assert all(colors.is_color_like(c) for c in color_vector), "Not all values are color-like."
+ assert all(_is_color_like(c) for c in color_vector), "Not all values are color-like."
  cols = colors.to_rgba_array(color_vector)
  else:
  cols = cmap_params.cmap(cmap_params.norm(color_vector))
@@ -1557,15 +1587,11 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  if (contour_px := param_dict.get("contour_px")) and not isinstance(contour_px, int):
  raise TypeError("Parameter 'contour_px' must be an integer.")
 
- if (color := param_dict.get("color")) and element_type in {
- "shapes",
- "points",
- "labels",
- }:
+ if (color := param_dict.get("color")) and element_type in {"shapes", "points", "labels"}:
  if not isinstance(color, str):
  raise TypeError("Parameter 'color' must be a string.")
  if element_type in {"shapes", "points"}:
- if colors.is_color_like(color):
+ if _is_color_like(color):
  logger.info("Value for parameter 'color' appears to be a color, using it as such.")
  param_dict["col_for_color"] = None
  else:
@@ -1645,7 +1671,7 @@ def _type_check_params(param_dict: dict[str, Any], element_type: str) -> dict[st
  raise TypeError("Parameter 'cmap' must be a string, a Colormap, or a list of these types.")
 
  if (na_color := param_dict.get("na_color")) != "default" and (
- na_color is not None and not colors.is_color_like(na_color)
+ na_color is not None and not _is_color_like(na_color)
  ):
  raise ValueError("Parameter 'na_color' must be color-like.")
 

tests/pl/test_render_shapes.py

@@ -7,7 +7,7 @@
 import spatialdata_plot # noqa: F401
 from anndata import AnnData
 from shapely.geometry import MultiPolygon, Point, Polygon
-from spatialdata import SpatialData
+from spatialdata import SpatialData, deepcopy
 from spatialdata.models import ShapesModel, TableModel
 
 from tests.conftest import DPI, PlotTester, PlotTesterMeta
@@ -94,7 +94,7 @@ def _make_multi():
  sdata.pl.render_shapes(color="val", outline=True, fill_alpha=0.3).pl.show()
 
  def test_plot_can_color_from_geodataframe(self, sdata_blobs: SpatialData):
- blob = sdata_blobs
+ blob = deepcopy(sdata_blobs)
  blob["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
  blob["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
  blob.shapes["blobs_polygons"]["value"] = [1, 10, 1, 20, 1]

tests/pl/test_utils.py

@@ -1,3 +1,5 @@
+from typing import Union
+
 import matplotlib
 import matplotlib.pyplot as plt
 import numpy as np
@@ -23,6 +25,11 @@
 # the comp. function can be accessed as `self.compare(<your_filename>, tolerance=<your_tolerance>)`
 # ".png" is appended to <your_filename>, no need to set it
 
+# replace with
+# from spatialdata._types import ColorLike
+# once https://github.com/scverse/spatialdata/pull/689/ is in a release
+ColorLike = Union[tuple[float, ...], str]
+
 
 class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  @pytest.mark.parametrize(
@@ -35,6 +42,18 @@ class TestUtils(PlotTester, metaclass=PlotTesterMeta):
  def test_plot_set_outline_accepts_str_or_float_or_list_thereof(self, sdata_blobs: SpatialData, outline_color):
  sdata_blobs.pl.render_shapes(element="blobs_polygons", outline=True, outline_color=outline_color).pl.show()
 
+ @pytest.mark.parametrize(
+ "colname",
+ ["0", "0.5", "1"],
+ )
+ def test_plot_colnames_that_are_valid_matplotlib_greyscale_colors_are_not_evaluated_as_colors(
+ self, sdata_blobs: SpatialData, colname: str
+ ):
+ sdata_blobs["table"].obs["region"] = ["blobs_polygons"] * sdata_blobs["table"].n_obs
+ sdata_blobs["table"].uns["spatialdata_attrs"]["region"] = "blobs_polygons"
+ sdata_blobs.shapes["blobs_polygons"][colname] = [1, 2, 3, 5, 20]
+ sdata_blobs.pl.render_shapes("blobs_polygons", color=colname).pl.show()
+
  def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData):
  from spatialdata_plot.pl.utils import set_zero_in_cmap_to_transparent
 
@@ -60,6 +79,23 @@ def test_plot_can_set_zero_in_cmap_to_transparent(self, sdata_blobs: SpatialData
  ).pl.show(ax=axs[1], colorbar=False)
 
 
+@pytest.mark.parametrize(
+ "color_result",
+ [
+ ("0", False),
+ ("0.5", False),
+ ("1", False),
+ ("#00ff00", True),
+ ((0.0, 1.0, 0.0, 1.0), True),
+ ],
+)
+def test_is_color_like(color_result: tuple[ColorLike, bool]):
+
+ color, result = color_result
+
+ assert spatialdata_plot.pl.utils._is_color_like(color) == result
+
+
 @pytest.mark.parametrize(
  "input_output",
  [