Datashader support for points and shapes

CHANGELOG.md

@@ -10,20 +10,24 @@ and this project adheres to [Semantic Versioning][].
 
 ## [0.2.3] - tbd
 
+### Added
+
+-   Datashader support for points and shapes (#244)
+
 ### Changed
 
--   All parameters are now provided for a single element. If element in pl.render is None then this value will be broadcasted
+-   All parameters are now provided for a single element (#272)
 
 ### Fixed
 
 -   Fix color assignment for NaN values (#257)
--   Fix channel str support #221
+-   Zorder of rendering now strictly follows the order of the render_x calls (#244)
 
 ## [0.2.2] - 2024-05-02
 
 ### Fixed
 
--   Fixed `fill_alpha` ignoring `alpha` channel from custom cmap
+-   Fixed `fill_alpha` ignoring `alpha` channel from custom cmap (#236)
 -   Fix channel str support (#221)
 
 ## [0.2.1] - 2024-03-26

src/spatialdata_plot/pl/basic.py

@@ -166,6 +166,7 @@ def render_shapes(
         cmap: Colormap | str | None = None,
         norm: bool | Normalize = False,
         scale: float | int = 1.0,
+        method: str | None = None,
         table_name: str | None = None,
         **kwargs: Any,
     ) -> sd.SpatialData:
@@ -219,6 +220,9 @@ def render_shapes(
             Colormap normalization for continuous annotations.
         scale : float | int, default 1.0
             Value to scale circles, if present.
+        method : str | None, optional
+            Whether to use 'matplotlib' and 'datashader'. When None, the method is
+            chosen based on the size of the data.
         table_name: str | None
             Name of the table containing the color(s) columns. If one name is given than the table is used for each
             spatial element to be plotted if the table annotates it. If you want to use different tables for particular
@@ -253,6 +257,7 @@ def render_shapes(
             norm=norm,
             scale=scale,
             table_name=table_name,
+            method=method,
         )
 
         sdata = self._copy()
@@ -281,6 +286,8 @@ def render_shapes(
                 fill_alpha=param_values["fill_alpha"],
                 transfunc=kwargs.get("transfunc", None),
                 table_name=param_values["table_name"],
+                zorder=n_steps,
+                method=method,
             )
             n_steps += 1
 
@@ -298,6 +305,7 @@ def render_points(
         cmap: Colormap | str | None = None,
         norm: None | Normalize = None,
         size: float | int = 1.0,
+        method: str | None = None,
         table_name: str | None = None,
         **kwargs: Any,
     ) -> sd.SpatialData:
@@ -342,6 +350,9 @@ def render_points(
             Colormap normalization for continuous annotations.
         size : float | int, default 1.0
             Size of the points
+        method : str | None, optional
+            Whether to use 'matplotlib' and 'datashader'. When None, the method is
+            chosen based on the size of the data.
         table_name: str | None
             Name of the table containing the color(s) columns. If one name is given than the table is used for each
             spatial element to be plotted if the table annotates it. If you want to use different tables for particular
@@ -368,6 +379,12 @@ def render_points(
             table_name=table_name,
         )
 
+        if method is not None:
+            if not isinstance(method, str):
+                raise TypeError("Parameter 'method' must be a string.")
+            if method not in ["matplotlib", "datashader"]:
+                raise ValueError("Parameter 'method' must be either 'matplotlib' or 'datashader'.")
+
         sdata = self._copy()
         sdata = _verify_plotting_tree(sdata)
         n_steps = len(sdata.plotting_tree.keys())
@@ -391,6 +408,8 @@ def render_points(
                 transfunc=kwargs.get("transfunc", None),
                 size=param_values["size"],
                 table_name=param_values["table_name"],
+                zorder=n_steps,
+                method=method,
             )
             n_steps += 1
 
@@ -504,6 +523,7 @@ def render_images(
                 alpha=param_values["alpha"],
                 percentiles_for_norm=param_values["percentiles_for_norm"],
                 scale=param_values["scale"],
+                zorder=n_steps,
             )
             n_steps += 1
 
@@ -515,14 +535,14 @@ def render_labels(
         element: str | None = None,
         color: str | None = None,
         groups: list[str] | str | None = None,
-        contour_px: int = 3,
+        contour_px: int | None = 3,
         outline: bool = False,
         palette: list[str] | str | None = None,
         cmap: Colormap | str | None = None,
         norm: Normalize | None = None,
         na_color: ColorLike | None = (0.0, 0.0, 0.0, 0.0),
         outline_alpha: float | int = 1.0,
-        fill_alpha: float | int = 0.3,
+        fill_alpha: float | int = 0.4,
         scale: str | None = None,
         table_name: str | None = None,
         **kwargs: Any,
@@ -626,6 +646,7 @@ def render_labels(
                 transfunc=kwargs.get("transfunc", None),
                 scale=param_values["scale"],
                 table_name=param_values["table_name"],
+                zorder=n_steps,
             )
             n_steps += 1
         return sdata