Image render param refactor

src/spatialdata_plot/_utils.py

@@ -0,0 +1,69 @@
+from __future__ import annotations
+
+import functools
+import warnings
+from typing import Any, Callable, TypeVar
+
+RT = TypeVar("RT")
+
+
+def deprecation_alias(**aliases: str) -> Callable[[Callable[..., RT]], Callable[..., RT]]:
+ """
+ Decorate a function to warn user of use of arguments set for deprecation.
+
+ Parameters
+ ----------
+ aliases
+ Deprecation argument aliases to be mapped to the new arguments.
+
+ Returns
+ -------
+ A decorator that can be used to mark an argument for deprecation and substituting it with the new argument.
+
+ Raises
+ ------
+ TypeError
+ If the provided aliases are not of string type.
+
+ Example
+ -------
+ Assuming we have an argument 'table' set for deprecation and we want to warn the user and substitute with 'tables':
+
+ ```python
+ @deprecation_alias(table="tables")
+ def my_function(tables: AnnData | dict[str, AnnData]):
+ pass
+ ```
+ """
+
+ def deprecation_decorator(f: Callable[..., RT]) -> Callable[..., RT]:
+ @functools.wraps(f)
+ def wrapper(*args: Any, **kwargs: Any) -> RT:
+ class_name = f.__qualname__
+ rename_kwargs(f.__name__, kwargs, aliases, class_name)
+ return f(*args, **kwargs)
+
+ return wrapper
+
+ return deprecation_decorator
+
+
+def rename_kwargs(func_name: str, kwargs: dict[str, Any], aliases: dict[str, str], class_name: None | str) -> None:
+ """Rename function arguments set for deprecation and gives warning in case of usage of these arguments."""
+ for alias, new in aliases.items():
+ if alias in kwargs:
+ class_name = class_name + "." if class_name else ""
+ if new in kwargs:
+ raise TypeError(
+ f"{class_name}{func_name} received both {alias} and {new} as arguments!"
+ f" {alias} is being deprecated in spatialdata-plot version 0.3, only use {new} instead."
+ )
+ warnings.warn(
+ message=(
+ f"`{alias}` is being deprecated as an argument to `{class_name}{func_name}` in spatialdata-plot "
+ f"version 0.3, switch to `{new}` instead."
+ ),
+ category=DeprecationWarning,
+ stacklevel=3,
+ )
+ kwargs[new] = kwargs.pop(alias)

src/spatialdata_plot/pl/basic.py

@@ -23,6 +23,7 @@
 from spatialdata._core.data_extent import get_extent
 
 from spatialdata_plot._accessor import register_spatial_data_accessor
+from spatialdata_plot._utils import deprecation_alias
 from spatialdata_plot.pl.render import (
  _render_images,
  _render_labels,
@@ -50,6 +51,7 @@
  _prepare_params_plot,
  _set_outline,
  _update_params,
+ _validate_image_render_params,
  _validate_render_params,
  _validate_show_parameters,
  save_fig,
@@ -390,59 +392,63 @@ def render_points(
 
  return sdata
 
+ @deprecation_alias(elements="element", quantiles_for_norm="percentiles_for_norm", version="version 0.3.0")
  def render_images(
  self,
-elements: list[str] | str | None = None,
+element: str | None = None,
  channel: list[str] | list[int] | str | int | None = None,
- cmap: list[Colormap] | Colormap | str | None = None,
+ cmap: list[Colormap | str] | Colormap | str | None = None,
  norm: Normalize | None = None,
  na_color: ColorLike | None = (0.0, 0.0, 0.0, 0.0),
- palette: list[list[str | None]] | list[str | None] | str | None = None,
+ palette: list[str] | str | None = None,
  alpha: float | int = 1.0,
-quantiles_for_norm: tuple[float | None, float | None] | None = None,
- scale: list[str] | str | None = None,
+percentiles_for_norm: tuple[float, float] | None = None,
+ scale: str | None = None,
  **kwargs: Any,
  ) -> sd.SpatialData:
  """
  Render image elements in SpatialData.
 
+ In case of no elements specified, "broadcasting" of parameters is applied. This means that for any particular
+ SpatialElement, we validate whether a given parameter is valid. If not valid for a particular SpatialElement the
+ specific parameter for that particular SpatialElement will be ignored. If you want to set specific parameters
+ for specific elements please chain the render functions: `pl.render_images(...).pl.render_images(...).pl.show()`
+ .
+
  Parameters
  ----------
- elements : list[str] | str | None, optional
- The name(s) of the image element(s) to render. If `None`, all image
- elements in the `SpatialData` object will be used. If a string is provided,
- it is converted into a single-element list.
- channel : list[str] | list[int] | str | int | None, optional
+ element : str | None
+ The name of the image element to render. If `None`, all image
+ elements in the `SpatialData` object will be used.
+ channels : list[str] | list[int] | str | int | None, optional
  To select specific channels to plot. Can be a single channel name/int or a
  list of channel names/ints. If `None`, all channels will be used.
- cmap : list[Colormap] | Colormap | str | None, optional
+ cmap : list[Colormap | str] | Colormap | str | None, optional
  Colormap or list of colormaps for continuous annotations, see :class:`matplotlib.colors.Colormap`.
  Each colormap applies to a corresponding channel.
  norm : Normalize | None, optional
  Colormap normalization for continuous annotations, see :class:`matplotlib.colors.Normalize`.
  Applies to all channels if set.
  na_color : ColorLike | None, default (0.0, 0.0, 0.0, 0.0)
  Color to be used for NA values. Accepts color-like values (string, hex, RGB(A)).
- palette : list[list[str | None]] | list[str | None] | str | None
+ palette : list[str] | None
  Palette to color images. In the case of a list of
  lists means that there is one list per element to be plotted in the list and this list contains the string
  indicating the palette to be used. If not provided as list of lists, broadcasting behaviour is
  attempted (use the same values for all elements).
  alpha : float | int, default 1.0
  Alpha value for the images. Must be a numeric between 0 and 1.
-quantiles_for_norm : tuple[float | None, float | None] | None, optional
+percentiles_for_norm : tuple[float, float] | None
  Optional pair of floats (pmin < pmax, 0-100) which will be used for quantile normalization.
- scale : list[str] | str | None, optional
+ scale : str | None
  Influences the resolution of the rendering. Possibilities include:
  1) `None` (default): The image is rasterized to fit the canvas size. For
  multiscale images, the best scale is selected before rasterization.
- 2) A scale name: Renders the specified scale as-is (with adjustments for dpi
- in `show()`).
+ 2) A scale name: Renders the specified scale ( of a multiscale image) as-is
+(with adjustments for dpi in `show()`).
  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.
- 4) A list matching the list of elements. Can contain `None`, scale names, or
- "full". Each scale applies to the corresponding element.
  kwargs
  Additional arguments to be passed to cmap, norm, and other rendering functions.
 
@@ -451,19 +457,19 @@ def render_images(
  sd.SpatialData
  The SpatialData object with the rendered images.
  """
- params_dict = _validate_render_params(
- "images",
+ params_dict = _validate_image_render_params(
  self._sdata,
-elements=elements,
+element=element,
  channel=channel,
  alpha=alpha,
  palette=palette,
  na_color=na_color,
  cmap=cmap,
  norm=norm,
  scale=scale,
-quantiles_for_norm=quantiles_for_norm,
+percentiles_for_norm=percentiles_for_norm,
  )
+
  sdata = self._copy()
  sdata = _verify_plotting_tree(sdata)
  n_steps = len(sdata.plotting_tree.keys())
@@ -488,15 +494,17 @@ def render_images(
  **kwargs,
  )
 
- sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
- elements=params_dict["elements"],
- channel=channel,
- cmap_params=cmap_params,
- palette=params_dict["palette"],
- alpha=alpha,
- quantiles_for_norm=params_dict["quantiles_for_norm"],
- scale=params_dict["scale"],
- )
+ for element, param_values in params_dict.items():
+ sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
+ element=element,
+ channel=param_values["channel"],
+ cmap_params=cmap_params,
+ palette=param_values["palette"],
+ alpha=param_values["alpha"],
+ percentiles_for_norm=param_values["percentiles_for_norm"],
+ scale=param_values["scale"],
+ )
+ n_steps += 1
 
  return sdata
 

src/spatialdata_plot/_utils.py

@@ -0,0 +1,69 @@
+from __future__ import annotations
+
+import functools
+import warnings
+from typing import Any, Callable, TypeVar
+
+RT = TypeVar("RT")
+
+
+def deprecation_alias(**aliases: str) -> Callable[[Callable[..., RT]], Callable[..., RT]]:
+ """
+ Decorate a function to warn user of use of arguments set for deprecation.
+
+ Parameters
+ ----------
+ aliases
+ Deprecation argument aliases to be mapped to the new arguments.
+
+ Returns
+ -------
+ A decorator that can be used to mark an argument for deprecation and substituting it with the new argument.
+
+ Raises
+ ------
+ TypeError
+ If the provided aliases are not of string type.
+
+ Example
+ -------
+ Assuming we have an argument 'table' set for deprecation and we want to warn the user and substitute with 'tables':
+
+ ```python
+ @deprecation_alias(table="tables")
+ def my_function(tables: AnnData | dict[str, AnnData]):
+ pass
+ ```
+ """
+
+ def deprecation_decorator(f: Callable[..., RT]) -> Callable[..., RT]:
+ @functools.wraps(f)
+ def wrapper(*args: Any, **kwargs: Any) -> RT:
+ class_name = f.__qualname__
+ rename_kwargs(f.__name__, kwargs, aliases, class_name)
+ return f(*args, **kwargs)
+
+ return wrapper
+
+ return deprecation_decorator
+
+
+def rename_kwargs(func_name: str, kwargs: dict[str, Any], aliases: dict[str, str], class_name: None | str) -> None:
+ """Rename function arguments set for deprecation and gives warning in case of usage of these arguments."""
+ for alias, new in aliases.items():
+ if alias in kwargs:
+ class_name = class_name + "." if class_name else ""
+ if new in kwargs:
+ raise TypeError(
+ f"{class_name}{func_name} received both {alias} and {new} as arguments!"
+ f" {alias} is being deprecated in spatialdata-plot version 0.3, only use {new} instead."
+ )
+ warnings.warn(
+ message=(
+ f"`{alias}` is being deprecated as an argument to `{class_name}{func_name}` in spatialdata-plot "
+ f"version 0.3, switch to `{new}` instead."
+ ),
+ category=DeprecationWarning,
+ stacklevel=3,
+ )
+ kwargs[new] = kwargs.pop(alias)

src/spatialdata_plot/pl/basic.py

@@ -23,6 +23,7 @@
 from spatialdata._core.data_extent import get_extent
 
 from spatialdata_plot._accessor import register_spatial_data_accessor
+from spatialdata_plot._utils import deprecation_alias
 from spatialdata_plot.pl.render import (
  _render_images,
  _render_labels,
@@ -50,6 +51,7 @@
  _prepare_params_plot,
  _set_outline,
  _update_params,
+ _validate_image_render_params,
  _validate_render_params,
  _validate_show_parameters,
  save_fig,
@@ -390,59 +392,63 @@ def render_points(
 
  return sdata
 
+ @deprecation_alias(elements="element", quantiles_for_norm="percentiles_for_norm", version="version 0.3.0")
  def render_images(
  self,
-elements: list[str] | str | None = None,
+element: str | None = None,
  channel: list[str] | list[int] | str | int | None = None,
- cmap: list[Colormap] | Colormap | str | None = None,
+ cmap: list[Colormap | str] | Colormap | str | None = None,
  norm: Normalize | None = None,
  na_color: ColorLike | None = (0.0, 0.0, 0.0, 0.0),
- palette: list[list[str | None]] | list[str | None] | str | None = None,
+ palette: list[str] | str | None = None,
  alpha: float | int = 1.0,
-quantiles_for_norm: tuple[float | None, float | None] | None = None,
- scale: list[str] | str | None = None,
+percentiles_for_norm: tuple[float, float] | None = None,
+ scale: str | None = None,
  **kwargs: Any,
  ) -> sd.SpatialData:
  """
  Render image elements in SpatialData.
 
+ In case of no elements specified, "broadcasting" of parameters is applied. This means that for any particular
+ SpatialElement, we validate whether a given parameter is valid. If not valid for a particular SpatialElement the
+ specific parameter for that particular SpatialElement will be ignored. If you want to set specific parameters
+ for specific elements please chain the render functions: `pl.render_images(...).pl.render_images(...).pl.show()`
+ .
+
  Parameters
  ----------
- elements : list[str] | str | None, optional
- The name(s) of the image element(s) to render. If `None`, all image
- elements in the `SpatialData` object will be used. If a string is provided,
- it is converted into a single-element list.
- channel : list[str] | list[int] | str | int | None, optional
+ element : str | None
+ The name of the image element to render. If `None`, all image
+ elements in the `SpatialData` object will be used.
+ channels : list[str] | list[int] | str | int | None, optional
  To select specific channels to plot. Can be a single channel name/int or a
  list of channel names/ints. If `None`, all channels will be used.
- cmap : list[Colormap] | Colormap | str | None, optional
+ cmap : list[Colormap | str] | Colormap | str | None, optional
  Colormap or list of colormaps for continuous annotations, see :class:`matplotlib.colors.Colormap`.
  Each colormap applies to a corresponding channel.
  norm : Normalize | None, optional
  Colormap normalization for continuous annotations, see :class:`matplotlib.colors.Normalize`.
  Applies to all channels if set.
  na_color : ColorLike | None, default (0.0, 0.0, 0.0, 0.0)
  Color to be used for NA values. Accepts color-like values (string, hex, RGB(A)).
- palette : list[list[str | None]] | list[str | None] | str | None
+ palette : list[str] | None
  Palette to color images. In the case of a list of
  lists means that there is one list per element to be plotted in the list and this list contains the string
  indicating the palette to be used. If not provided as list of lists, broadcasting behaviour is
  attempted (use the same values for all elements).
  alpha : float | int, default 1.0
  Alpha value for the images. Must be a numeric between 0 and 1.
-quantiles_for_norm : tuple[float | None, float | None] | None, optional
+percentiles_for_norm : tuple[float, float] | None
  Optional pair of floats (pmin < pmax, 0-100) which will be used for quantile normalization.
- scale : list[str] | str | None, optional
+ scale : str | None
  Influences the resolution of the rendering. Possibilities include:
  1) `None` (default): The image is rasterized to fit the canvas size. For
  multiscale images, the best scale is selected before rasterization.
- 2) A scale name: Renders the specified scale as-is (with adjustments for dpi
- in `show()`).
+ 2) A scale name: Renders the specified scale ( of a multiscale image) as-is
+(with adjustments for dpi in `show()`).
  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.
- 4) A list matching the list of elements. Can contain `None`, scale names, or
- "full". Each scale applies to the corresponding element.
  kwargs
  Additional arguments to be passed to cmap, norm, and other rendering functions.
 
@@ -451,19 +457,19 @@ def render_images(
  sd.SpatialData
  The SpatialData object with the rendered images.
  """
- params_dict = _validate_render_params(
- "images",
+ params_dict = _validate_image_render_params(
  self._sdata,
-elements=elements,
+element=element,
  channel=channel,
  alpha=alpha,
  palette=palette,
  na_color=na_color,
  cmap=cmap,
  norm=norm,
  scale=scale,
-quantiles_for_norm=quantiles_for_norm,
+percentiles_for_norm=percentiles_for_norm,
  )
+
  sdata = self._copy()
  sdata = _verify_plotting_tree(sdata)
  n_steps = len(sdata.plotting_tree.keys())
@@ -488,15 +494,17 @@ def render_images(
  **kwargs,
  )
 
- sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
- elements=params_dict["elements"],
- channel=channel,
- cmap_params=cmap_params,
- palette=params_dict["palette"],
- alpha=alpha,
- quantiles_for_norm=params_dict["quantiles_for_norm"],
- scale=params_dict["scale"],
- )
+ for element, param_values in params_dict.items():
+ sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
+ element=element,
+ channel=param_values["channel"],
+ cmap_params=cmap_params,
+ palette=param_values["palette"],
+ alpha=param_values["alpha"],
+ percentiles_for_norm=param_values["percentiles_for_norm"],
+ scale=param_values["scale"],
+ )
+ n_steps += 1
 
  return sdata
 

src/spatialdata_plot/_utils.py

@@ -0,0 +1,69 @@
+from __future__ import annotations
+
+import functools
+import warnings
+from typing import Any, Callable, TypeVar
+
+RT = TypeVar("RT")
+
+
+def deprecation_alias(**aliases: str) -> Callable[[Callable[..., RT]], Callable[..., RT]]:
+ """
+ Decorate a function to warn user of use of arguments set for deprecation.
+
+ Parameters
+ ----------
+ aliases
+ Deprecation argument aliases to be mapped to the new arguments.
+
+ Returns
+ -------
+ A decorator that can be used to mark an argument for deprecation and substituting it with the new argument.
+
+ Raises
+ ------
+ TypeError
+ If the provided aliases are not of string type.
+
+ Example
+ -------
+ Assuming we have an argument 'table' set for deprecation and we want to warn the user and substitute with 'tables':
+
+ ```python
+ @deprecation_alias(table="tables")
+ def my_function(tables: AnnData | dict[str, AnnData]):
+ pass
+ ```
+ """
+
+ def deprecation_decorator(f: Callable[..., RT]) -> Callable[..., RT]:
+ @functools.wraps(f)
+ def wrapper(*args: Any, **kwargs: Any) -> RT:
+ class_name = f.__qualname__
+ rename_kwargs(f.__name__, kwargs, aliases, class_name)
+ return f(*args, **kwargs)
+
+ return wrapper
+
+ return deprecation_decorator
+
+
+def rename_kwargs(func_name: str, kwargs: dict[str, Any], aliases: dict[str, str], class_name: None | str) -> None:
+ """Rename function arguments set for deprecation and gives warning in case of usage of these arguments."""
+ for alias, new in aliases.items():
+ if alias in kwargs:
+ class_name = class_name + "." if class_name else ""
+ if new in kwargs:
+ raise TypeError(
+ f"{class_name}{func_name} received both {alias} and {new} as arguments!"
+ f" {alias} is being deprecated in spatialdata-plot version 0.3, only use {new} instead."
+ )
+ warnings.warn(
+ message=(
+ f"`{alias}` is being deprecated as an argument to `{class_name}{func_name}` in spatialdata-plot "
+ f"version 0.3, switch to `{new}` instead."
+ ),
+ category=DeprecationWarning,
+ stacklevel=3,
+ )
+ kwargs[new] = kwargs.pop(alias)

src/spatialdata_plot/pl/basic.py

@@ -23,6 +23,7 @@
 from spatialdata._core.data_extent import get_extent
 
 from spatialdata_plot._accessor import register_spatial_data_accessor
+from spatialdata_plot._utils import deprecation_alias
 from spatialdata_plot.pl.render import (
  _render_images,
  _render_labels,
@@ -50,6 +51,7 @@
  _prepare_params_plot,
  _set_outline,
  _update_params,
+ _validate_image_render_params,
  _validate_render_params,
  _validate_show_parameters,
  save_fig,
@@ -390,59 +392,63 @@ def render_points(
 
  return sdata
 
+ @deprecation_alias(elements="element", quantiles_for_norm="percentiles_for_norm", version="version 0.3.0")
  def render_images(
  self,
-elements: list[str] | str | None = None,
+element: str | None = None,
  channel: list[str] | list[int] | str | int | None = None,
- cmap: list[Colormap] | Colormap | str | None = None,
+ cmap: list[Colormap | str] | Colormap | str | None = None,
  norm: Normalize | None = None,
  na_color: ColorLike | None = (0.0, 0.0, 0.0, 0.0),
- palette: list[list[str | None]] | list[str | None] | str | None = None,
+ palette: list[str] | str | None = None,
  alpha: float | int = 1.0,
-quantiles_for_norm: tuple[float | None, float | None] | None = None,
- scale: list[str] | str | None = None,
+percentiles_for_norm: tuple[float, float] | None = None,
+ scale: str | None = None,
  **kwargs: Any,
  ) -> sd.SpatialData:
  """
  Render image elements in SpatialData.
 
+ In case of no elements specified, "broadcasting" of parameters is applied. This means that for any particular
+ SpatialElement, we validate whether a given parameter is valid. If not valid for a particular SpatialElement the
+ specific parameter for that particular SpatialElement will be ignored. If you want to set specific parameters
+ for specific elements please chain the render functions: `pl.render_images(...).pl.render_images(...).pl.show()`
+ .
+
  Parameters
  ----------
- elements : list[str] | str | None, optional
- The name(s) of the image element(s) to render. If `None`, all image
- elements in the `SpatialData` object will be used. If a string is provided,
- it is converted into a single-element list.
- channel : list[str] | list[int] | str | int | None, optional
+ element : str | None
+ The name of the image element to render. If `None`, all image
+ elements in the `SpatialData` object will be used.
+ channels : list[str] | list[int] | str | int | None, optional
  To select specific channels to plot. Can be a single channel name/int or a
  list of channel names/ints. If `None`, all channels will be used.
- cmap : list[Colormap] | Colormap | str | None, optional
+ cmap : list[Colormap | str] | Colormap | str | None, optional
  Colormap or list of colormaps for continuous annotations, see :class:`matplotlib.colors.Colormap`.
  Each colormap applies to a corresponding channel.
  norm : Normalize | None, optional
  Colormap normalization for continuous annotations, see :class:`matplotlib.colors.Normalize`.
  Applies to all channels if set.
  na_color : ColorLike | None, default (0.0, 0.0, 0.0, 0.0)
  Color to be used for NA values. Accepts color-like values (string, hex, RGB(A)).
- palette : list[list[str | None]] | list[str | None] | str | None
+ palette : list[str] | None
  Palette to color images. In the case of a list of
  lists means that there is one list per element to be plotted in the list and this list contains the string
  indicating the palette to be used. If not provided as list of lists, broadcasting behaviour is
  attempted (use the same values for all elements).
  alpha : float | int, default 1.0
  Alpha value for the images. Must be a numeric between 0 and 1.
-quantiles_for_norm : tuple[float | None, float | None] | None, optional
+percentiles_for_norm : tuple[float, float] | None
  Optional pair of floats (pmin < pmax, 0-100) which will be used for quantile normalization.
- scale : list[str] | str | None, optional
+ scale : str | None
  Influences the resolution of the rendering. Possibilities include:
  1) `None` (default): The image is rasterized to fit the canvas size. For
  multiscale images, the best scale is selected before rasterization.
- 2) A scale name: Renders the specified scale as-is (with adjustments for dpi
- in `show()`).
+ 2) A scale name: Renders the specified scale ( of a multiscale image) as-is
+(with adjustments for dpi in `show()`).
  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.
- 4) A list matching the list of elements. Can contain `None`, scale names, or
- "full". Each scale applies to the corresponding element.
  kwargs
  Additional arguments to be passed to cmap, norm, and other rendering functions.
 
@@ -451,19 +457,19 @@ def render_images(
  sd.SpatialData
  The SpatialData object with the rendered images.
  """
- params_dict = _validate_render_params(
- "images",
+ params_dict = _validate_image_render_params(
  self._sdata,
-elements=elements,
+element=element,
  channel=channel,
  alpha=alpha,
  palette=palette,
  na_color=na_color,
  cmap=cmap,
  norm=norm,
  scale=scale,
-quantiles_for_norm=quantiles_for_norm,
+percentiles_for_norm=percentiles_for_norm,
  )
+
  sdata = self._copy()
  sdata = _verify_plotting_tree(sdata)
  n_steps = len(sdata.plotting_tree.keys())
@@ -488,15 +494,17 @@ def render_images(
  **kwargs,
  )
 
- sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
- elements=params_dict["elements"],
- channel=channel,
- cmap_params=cmap_params,
- palette=params_dict["palette"],
- alpha=alpha,
- quantiles_for_norm=params_dict["quantiles_for_norm"],
- scale=params_dict["scale"],
- )
+ for element, param_values in params_dict.items():
+ sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
+ element=element,
+ channel=param_values["channel"],
+ cmap_params=cmap_params,
+ palette=param_values["palette"],
+ alpha=param_values["alpha"],
+ percentiles_for_norm=param_values["percentiles_for_norm"],
+ scale=param_values["scale"],
+ )
+ n_steps += 1
 
  return sdata
 

src/spatialdata_plot/_utils.py

@@ -0,0 +1,69 @@
+from __future__ import annotations
+
+import functools
+import warnings
+from typing import Any, Callable, TypeVar
+
+RT = TypeVar("RT")
+
+
+def deprecation_alias(**aliases: str) -> Callable[[Callable[..., RT]], Callable[..., RT]]:
+ """
+ Decorate a function to warn user of use of arguments set for deprecation.
+
+ Parameters
+ ----------
+ aliases
+ Deprecation argument aliases to be mapped to the new arguments.
+
+ Returns
+ -------
+ A decorator that can be used to mark an argument for deprecation and substituting it with the new argument.
+
+ Raises
+ ------
+ TypeError
+ If the provided aliases are not of string type.
+
+ Example
+ -------
+ Assuming we have an argument 'table' set for deprecation and we want to warn the user and substitute with 'tables':
+
+ ```python
+ @deprecation_alias(table="tables")
+ def my_function(tables: AnnData | dict[str, AnnData]):
+ pass
+ ```
+ """
+
+ def deprecation_decorator(f: Callable[..., RT]) -> Callable[..., RT]:
+ @functools.wraps(f)
+ def wrapper(*args: Any, **kwargs: Any) -> RT:
+ class_name = f.__qualname__
+ rename_kwargs(f.__name__, kwargs, aliases, class_name)
+ return f(*args, **kwargs)
+
+ return wrapper
+
+ return deprecation_decorator
+
+
+def rename_kwargs(func_name: str, kwargs: dict[str, Any], aliases: dict[str, str], class_name: None | str) -> None:
+ """Rename function arguments set for deprecation and gives warning in case of usage of these arguments."""
+ for alias, new in aliases.items():
+ if alias in kwargs:
+ class_name = class_name + "." if class_name else ""
+ if new in kwargs:
+ raise TypeError(
+ f"{class_name}{func_name} received both {alias} and {new} as arguments!"
+ f" {alias} is being deprecated in spatialdata-plot version 0.3, only use {new} instead."
+ )
+ warnings.warn(
+ message=(
+ f"`{alias}` is being deprecated as an argument to `{class_name}{func_name}` in spatialdata-plot "
+ f"version 0.3, switch to `{new}` instead."
+ ),
+ category=DeprecationWarning,
+ stacklevel=3,
+ )
+ kwargs[new] = kwargs.pop(alias)

src/spatialdata_plot/pl/basic.py

@@ -23,6 +23,7 @@
 from spatialdata._core.data_extent import get_extent
 
 from spatialdata_plot._accessor import register_spatial_data_accessor
+from spatialdata_plot._utils import deprecation_alias
 from spatialdata_plot.pl.render import (
  _render_images,
  _render_labels,
@@ -50,6 +51,7 @@
  _prepare_params_plot,
  _set_outline,
  _update_params,
+ _validate_image_render_params,
  _validate_render_params,
  _validate_show_parameters,
  save_fig,
@@ -390,59 +392,63 @@ def render_points(
 
  return sdata
 
+ @deprecation_alias(elements="element", quantiles_for_norm="percentiles_for_norm", version="version 0.3.0")
  def render_images(
  self,
-elements: list[str] | str | None = None,
+element: str | None = None,
  channel: list[str] | list[int] | str | int | None = None,
- cmap: list[Colormap] | Colormap | str | None = None,
+ cmap: list[Colormap | str] | Colormap | str | None = None,
  norm: Normalize | None = None,
  na_color: ColorLike | None = (0.0, 0.0, 0.0, 0.0),
- palette: list[list[str | None]] | list[str | None] | str | None = None,
+ palette: list[str] | str | None = None,
  alpha: float | int = 1.0,
-quantiles_for_norm: tuple[float | None, float | None] | None = None,
- scale: list[str] | str | None = None,
+percentiles_for_norm: tuple[float, float] | None = None,
+ scale: str | None = None,
  **kwargs: Any,
  ) -> sd.SpatialData:
  """
  Render image elements in SpatialData.
 
+ In case of no elements specified, "broadcasting" of parameters is applied. This means that for any particular
+ SpatialElement, we validate whether a given parameter is valid. If not valid for a particular SpatialElement the
+ specific parameter for that particular SpatialElement will be ignored. If you want to set specific parameters
+ for specific elements please chain the render functions: `pl.render_images(...).pl.render_images(...).pl.show()`
+ .
+
  Parameters
  ----------
- elements : list[str] | str | None, optional
- The name(s) of the image element(s) to render. If `None`, all image
- elements in the `SpatialData` object will be used. If a string is provided,
- it is converted into a single-element list.
- channel : list[str] | list[int] | str | int | None, optional
+ element : str | None
+ The name of the image element to render. If `None`, all image
+ elements in the `SpatialData` object will be used.
+ channels : list[str] | list[int] | str | int | None, optional
  To select specific channels to plot. Can be a single channel name/int or a
  list of channel names/ints. If `None`, all channels will be used.
- cmap : list[Colormap] | Colormap | str | None, optional
+ cmap : list[Colormap | str] | Colormap | str | None, optional
  Colormap or list of colormaps for continuous annotations, see :class:`matplotlib.colors.Colormap`.
  Each colormap applies to a corresponding channel.
  norm : Normalize | None, optional
  Colormap normalization for continuous annotations, see :class:`matplotlib.colors.Normalize`.
  Applies to all channels if set.
  na_color : ColorLike | None, default (0.0, 0.0, 0.0, 0.0)
  Color to be used for NA values. Accepts color-like values (string, hex, RGB(A)).
- palette : list[list[str | None]] | list[str | None] | str | None
+ palette : list[str] | None
  Palette to color images. In the case of a list of
  lists means that there is one list per element to be plotted in the list and this list contains the string
  indicating the palette to be used. If not provided as list of lists, broadcasting behaviour is
  attempted (use the same values for all elements).
  alpha : float | int, default 1.0
  Alpha value for the images. Must be a numeric between 0 and 1.
-quantiles_for_norm : tuple[float | None, float | None] | None, optional
+percentiles_for_norm : tuple[float, float] | None
  Optional pair of floats (pmin < pmax, 0-100) which will be used for quantile normalization.
- scale : list[str] | str | None, optional
+ scale : str | None
  Influences the resolution of the rendering. Possibilities include:
  1) `None` (default): The image is rasterized to fit the canvas size. For
  multiscale images, the best scale is selected before rasterization.
- 2) A scale name: Renders the specified scale as-is (with adjustments for dpi
- in `show()`).
+ 2) A scale name: Renders the specified scale ( of a multiscale image) as-is
+(with adjustments for dpi in `show()`).
  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.
- 4) A list matching the list of elements. Can contain `None`, scale names, or
- "full". Each scale applies to the corresponding element.
  kwargs
  Additional arguments to be passed to cmap, norm, and other rendering functions.
 
@@ -451,19 +457,19 @@ def render_images(
  sd.SpatialData
  The SpatialData object with the rendered images.
  """
- params_dict = _validate_render_params(
- "images",
+ params_dict = _validate_image_render_params(
  self._sdata,
-elements=elements,
+element=element,
  channel=channel,
  alpha=alpha,
  palette=palette,
  na_color=na_color,
  cmap=cmap,
  norm=norm,
  scale=scale,
-quantiles_for_norm=quantiles_for_norm,
+percentiles_for_norm=percentiles_for_norm,
  )
+
  sdata = self._copy()
  sdata = _verify_plotting_tree(sdata)
  n_steps = len(sdata.plotting_tree.keys())
@@ -488,15 +494,17 @@ def render_images(
  **kwargs,
  )
 
- sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
- elements=params_dict["elements"],
- channel=channel,
- cmap_params=cmap_params,
- palette=params_dict["palette"],
- alpha=alpha,
- quantiles_for_norm=params_dict["quantiles_for_norm"],
- scale=params_dict["scale"],
- )
+ for element, param_values in params_dict.items():
+ sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
+ element=element,
+ channel=param_values["channel"],
+ cmap_params=cmap_params,
+ palette=param_values["palette"],
+ alpha=param_values["alpha"],
+ percentiles_for_norm=param_values["percentiles_for_norm"],
+ scale=param_values["scale"],
+ )
+ n_steps += 1
 
  return sdata
 

src/spatialdata_plot/_utils.py

@@ -0,0 +1,69 @@
+from __future__ import annotations
+
+import functools
+import warnings
+from typing import Any, Callable, TypeVar
+
+RT = TypeVar("RT")
+
+
+def deprecation_alias(**aliases: str) -> Callable[[Callable[..., RT]], Callable[..., RT]]:
+ """
+ Decorate a function to warn user of use of arguments set for deprecation.
+
+ Parameters
+ ----------
+ aliases
+ Deprecation argument aliases to be mapped to the new arguments.
+
+ Returns
+ -------
+ A decorator that can be used to mark an argument for deprecation and substituting it with the new argument.
+
+ Raises
+ ------
+ TypeError
+ If the provided aliases are not of string type.
+
+ Example
+ -------
+ Assuming we have an argument 'table' set for deprecation and we want to warn the user and substitute with 'tables':
+
+ ```python
+ @deprecation_alias(table="tables")
+ def my_function(tables: AnnData | dict[str, AnnData]):
+ pass
+ ```
+ """
+
+ def deprecation_decorator(f: Callable[..., RT]) -> Callable[..., RT]:
+ @functools.wraps(f)
+ def wrapper(*args: Any, **kwargs: Any) -> RT:
+ class_name = f.__qualname__
+ rename_kwargs(f.__name__, kwargs, aliases, class_name)
+ return f(*args, **kwargs)
+
+ return wrapper
+
+ return deprecation_decorator
+
+
+def rename_kwargs(func_name: str, kwargs: dict[str, Any], aliases: dict[str, str], class_name: None | str) -> None:
+ """Rename function arguments set for deprecation and gives warning in case of usage of these arguments."""
+ for alias, new in aliases.items():
+ if alias in kwargs:
+ class_name = class_name + "." if class_name else ""
+ if new in kwargs:
+ raise TypeError(
+ f"{class_name}{func_name} received both {alias} and {new} as arguments!"
+ f" {alias} is being deprecated in spatialdata-plot version 0.3, only use {new} instead."
+ )
+ warnings.warn(
+ message=(
+ f"`{alias}` is being deprecated as an argument to `{class_name}{func_name}` in spatialdata-plot "
+ f"version 0.3, switch to `{new}` instead."
+ ),
+ category=DeprecationWarning,
+ stacklevel=3,
+ )
+ kwargs[new] = kwargs.pop(alias)

src/spatialdata_plot/pl/basic.py

@@ -23,6 +23,7 @@
 from spatialdata._core.data_extent import get_extent
 
 from spatialdata_plot._accessor import register_spatial_data_accessor
+from spatialdata_plot._utils import deprecation_alias
 from spatialdata_plot.pl.render import (
  _render_images,
  _render_labels,
@@ -50,6 +51,7 @@
  _prepare_params_plot,
  _set_outline,
  _update_params,
+ _validate_image_render_params,
  _validate_render_params,
  _validate_show_parameters,
  save_fig,
@@ -390,59 +392,63 @@ def render_points(
 
  return sdata
 
+ @deprecation_alias(elements="element", quantiles_for_norm="percentiles_for_norm", version="version 0.3.0")
  def render_images(
  self,
-elements: list[str] | str | None = None,
+element: str | None = None,
  channel: list[str] | list[int] | str | int | None = None,
- cmap: list[Colormap] | Colormap | str | None = None,
+ cmap: list[Colormap | str] | Colormap | str | None = None,
  norm: Normalize | None = None,
  na_color: ColorLike | None = (0.0, 0.0, 0.0, 0.0),
- palette: list[list[str | None]] | list[str | None] | str | None = None,
+ palette: list[str] | str | None = None,
  alpha: float | int = 1.0,
-quantiles_for_norm: tuple[float | None, float | None] | None = None,
- scale: list[str] | str | None = None,
+percentiles_for_norm: tuple[float, float] | None = None,
+ scale: str | None = None,
  **kwargs: Any,
  ) -> sd.SpatialData:
  """
  Render image elements in SpatialData.
 
+ In case of no elements specified, "broadcasting" of parameters is applied. This means that for any particular
+ SpatialElement, we validate whether a given parameter is valid. If not valid for a particular SpatialElement the
+ specific parameter for that particular SpatialElement will be ignored. If you want to set specific parameters
+ for specific elements please chain the render functions: `pl.render_images(...).pl.render_images(...).pl.show()`
+ .
+
  Parameters
  ----------
- elements : list[str] | str | None, optional
- The name(s) of the image element(s) to render. If `None`, all image
- elements in the `SpatialData` object will be used. If a string is provided,
- it is converted into a single-element list.
- channel : list[str] | list[int] | str | int | None, optional
+ element : str | None
+ The name of the image element to render. If `None`, all image
+ elements in the `SpatialData` object will be used.
+ channels : list[str] | list[int] | str | int | None, optional
  To select specific channels to plot. Can be a single channel name/int or a
  list of channel names/ints. If `None`, all channels will be used.
- cmap : list[Colormap] | Colormap | str | None, optional
+ cmap : list[Colormap | str] | Colormap | str | None, optional
  Colormap or list of colormaps for continuous annotations, see :class:`matplotlib.colors.Colormap`.
  Each colormap applies to a corresponding channel.
  norm : Normalize | None, optional
  Colormap normalization for continuous annotations, see :class:`matplotlib.colors.Normalize`.
  Applies to all channels if set.
  na_color : ColorLike | None, default (0.0, 0.0, 0.0, 0.0)
  Color to be used for NA values. Accepts color-like values (string, hex, RGB(A)).
- palette : list[list[str | None]] | list[str | None] | str | None
+ palette : list[str] | None
  Palette to color images. In the case of a list of
  lists means that there is one list per element to be plotted in the list and this list contains the string
  indicating the palette to be used. If not provided as list of lists, broadcasting behaviour is
  attempted (use the same values for all elements).
  alpha : float | int, default 1.0
  Alpha value for the images. Must be a numeric between 0 and 1.
-quantiles_for_norm : tuple[float | None, float | None] | None, optional
+percentiles_for_norm : tuple[float, float] | None
  Optional pair of floats (pmin < pmax, 0-100) which will be used for quantile normalization.
- scale : list[str] | str | None, optional
+ scale : str | None
  Influences the resolution of the rendering. Possibilities include:
  1) `None` (default): The image is rasterized to fit the canvas size. For
  multiscale images, the best scale is selected before rasterization.
- 2) A scale name: Renders the specified scale as-is (with adjustments for dpi
- in `show()`).
+ 2) A scale name: Renders the specified scale ( of a multiscale image) as-is
+(with adjustments for dpi in `show()`).
  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.
- 4) A list matching the list of elements. Can contain `None`, scale names, or
- "full". Each scale applies to the corresponding element.
  kwargs
  Additional arguments to be passed to cmap, norm, and other rendering functions.
 
@@ -451,19 +457,19 @@ def render_images(
  sd.SpatialData
  The SpatialData object with the rendered images.
  """
- params_dict = _validate_render_params(
- "images",
+ params_dict = _validate_image_render_params(
  self._sdata,
-elements=elements,
+element=element,
  channel=channel,
  alpha=alpha,
  palette=palette,
  na_color=na_color,
  cmap=cmap,
  norm=norm,
  scale=scale,
-quantiles_for_norm=quantiles_for_norm,
+percentiles_for_norm=percentiles_for_norm,
  )
+
  sdata = self._copy()
  sdata = _verify_plotting_tree(sdata)
  n_steps = len(sdata.plotting_tree.keys())
@@ -488,15 +494,17 @@ def render_images(
  **kwargs,
  )
 
- sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
- elements=params_dict["elements"],
- channel=channel,
- cmap_params=cmap_params,
- palette=params_dict["palette"],
- alpha=alpha,
- quantiles_for_norm=params_dict["quantiles_for_norm"],
- scale=params_dict["scale"],
- )
+ for element, param_values in params_dict.items():
+ sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
+ element=element,
+ channel=param_values["channel"],
+ cmap_params=cmap_params,
+ palette=param_values["palette"],
+ alpha=param_values["alpha"],
+ percentiles_for_norm=param_values["percentiles_for_norm"],
+ scale=param_values["scale"],
+ )
+ n_steps += 1
 
  return sdata
 

src/spatialdata_plot/_utils.py

@@ -0,0 +1,69 @@
+from __future__ import annotations
+
+import functools
+import warnings
+from typing import Any, Callable, TypeVar
+
+RT = TypeVar("RT")
+
+
+def deprecation_alias(**aliases: str) -> Callable[[Callable[..., RT]], Callable[..., RT]]:
+ """
+ Decorate a function to warn user of use of arguments set for deprecation.
+
+ Parameters
+ ----------
+ aliases
+ Deprecation argument aliases to be mapped to the new arguments.
+
+ Returns
+ -------
+ A decorator that can be used to mark an argument for deprecation and substituting it with the new argument.
+
+ Raises
+ ------
+ TypeError
+ If the provided aliases are not of string type.
+
+ Example
+ -------
+ Assuming we have an argument 'table' set for deprecation and we want to warn the user and substitute with 'tables':
+
+ ```python
+ @deprecation_alias(table="tables")
+ def my_function(tables: AnnData | dict[str, AnnData]):
+ pass
+ ```
+ """
+
+ def deprecation_decorator(f: Callable[..., RT]) -> Callable[..., RT]:
+ @functools.wraps(f)
+ def wrapper(*args: Any, **kwargs: Any) -> RT:
+ class_name = f.__qualname__
+ rename_kwargs(f.__name__, kwargs, aliases, class_name)
+ return f(*args, **kwargs)
+
+ return wrapper
+
+ return deprecation_decorator
+
+
+def rename_kwargs(func_name: str, kwargs: dict[str, Any], aliases: dict[str, str], class_name: None | str) -> None:
+ """Rename function arguments set for deprecation and gives warning in case of usage of these arguments."""
+ for alias, new in aliases.items():
+ if alias in kwargs:
+ class_name = class_name + "." if class_name else ""
+ if new in kwargs:
+ raise TypeError(
+ f"{class_name}{func_name} received both {alias} and {new} as arguments!"
+ f" {alias} is being deprecated in spatialdata-plot version 0.3, only use {new} instead."
+ )
+ warnings.warn(
+ message=(
+ f"`{alias}` is being deprecated as an argument to `{class_name}{func_name}` in spatialdata-plot "
+ f"version 0.3, switch to `{new}` instead."
+ ),
+ category=DeprecationWarning,
+ stacklevel=3,
+ )
+ kwargs[new] = kwargs.pop(alias)

src/spatialdata_plot/pl/basic.py

@@ -23,6 +23,7 @@
 from spatialdata._core.data_extent import get_extent
 
 from spatialdata_plot._accessor import register_spatial_data_accessor
+from spatialdata_plot._utils import deprecation_alias
 from spatialdata_plot.pl.render import (
  _render_images,
  _render_labels,
@@ -50,6 +51,7 @@
  _prepare_params_plot,
  _set_outline,
  _update_params,
+ _validate_image_render_params,
  _validate_render_params,
  _validate_show_parameters,
  save_fig,
@@ -390,59 +392,63 @@ def render_points(
 
  return sdata
 
+ @deprecation_alias(elements="element", quantiles_for_norm="percentiles_for_norm", version="version 0.3.0")
  def render_images(
  self,
-elements: list[str] | str | None = None,
+element: str | None = None,
  channel: list[str] | list[int] | str | int | None = None,
- cmap: list[Colormap] | Colormap | str | None = None,
+ cmap: list[Colormap | str] | Colormap | str | None = None,
  norm: Normalize | None = None,
  na_color: ColorLike | None = (0.0, 0.0, 0.0, 0.0),
- palette: list[list[str | None]] | list[str | None] | str | None = None,
+ palette: list[str] | str | None = None,
  alpha: float | int = 1.0,
-quantiles_for_norm: tuple[float | None, float | None] | None = None,
- scale: list[str] | str | None = None,
+percentiles_for_norm: tuple[float, float] | None = None,
+ scale: str | None = None,
  **kwargs: Any,
  ) -> sd.SpatialData:
  """
  Render image elements in SpatialData.
 
+ In case of no elements specified, "broadcasting" of parameters is applied. This means that for any particular
+ SpatialElement, we validate whether a given parameter is valid. If not valid for a particular SpatialElement the
+ specific parameter for that particular SpatialElement will be ignored. If you want to set specific parameters
+ for specific elements please chain the render functions: `pl.render_images(...).pl.render_images(...).pl.show()`
+ .
+
  Parameters
  ----------
- elements : list[str] | str | None, optional
- The name(s) of the image element(s) to render. If `None`, all image
- elements in the `SpatialData` object will be used. If a string is provided,
- it is converted into a single-element list.
- channel : list[str] | list[int] | str | int | None, optional
+ element : str | None
+ The name of the image element to render. If `None`, all image
+ elements in the `SpatialData` object will be used.
+ channels : list[str] | list[int] | str | int | None, optional
  To select specific channels to plot. Can be a single channel name/int or a
  list of channel names/ints. If `None`, all channels will be used.
- cmap : list[Colormap] | Colormap | str | None, optional
+ cmap : list[Colormap | str] | Colormap | str | None, optional
  Colormap or list of colormaps for continuous annotations, see :class:`matplotlib.colors.Colormap`.
  Each colormap applies to a corresponding channel.
  norm : Normalize | None, optional
  Colormap normalization for continuous annotations, see :class:`matplotlib.colors.Normalize`.
  Applies to all channels if set.
  na_color : ColorLike | None, default (0.0, 0.0, 0.0, 0.0)
  Color to be used for NA values. Accepts color-like values (string, hex, RGB(A)).
- palette : list[list[str | None]] | list[str | None] | str | None
+ palette : list[str] | None
  Palette to color images. In the case of a list of
  lists means that there is one list per element to be plotted in the list and this list contains the string
  indicating the palette to be used. If not provided as list of lists, broadcasting behaviour is
  attempted (use the same values for all elements).
  alpha : float | int, default 1.0
  Alpha value for the images. Must be a numeric between 0 and 1.
-quantiles_for_norm : tuple[float | None, float | None] | None, optional
+percentiles_for_norm : tuple[float, float] | None
  Optional pair of floats (pmin < pmax, 0-100) which will be used for quantile normalization.
- scale : list[str] | str | None, optional
+ scale : str | None
  Influences the resolution of the rendering. Possibilities include:
  1) `None` (default): The image is rasterized to fit the canvas size. For
  multiscale images, the best scale is selected before rasterization.
- 2) A scale name: Renders the specified scale as-is (with adjustments for dpi
- in `show()`).
+ 2) A scale name: Renders the specified scale ( of a multiscale image) as-is
+(with adjustments for dpi in `show()`).
  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.
- 4) A list matching the list of elements. Can contain `None`, scale names, or
- "full". Each scale applies to the corresponding element.
  kwargs
  Additional arguments to be passed to cmap, norm, and other rendering functions.
 
@@ -451,19 +457,19 @@ def render_images(
  sd.SpatialData
  The SpatialData object with the rendered images.
  """
- params_dict = _validate_render_params(
- "images",
+ params_dict = _validate_image_render_params(
  self._sdata,
-elements=elements,
+element=element,
  channel=channel,
  alpha=alpha,
  palette=palette,
  na_color=na_color,
  cmap=cmap,
  norm=norm,
  scale=scale,
-quantiles_for_norm=quantiles_for_norm,
+percentiles_for_norm=percentiles_for_norm,
  )
+
  sdata = self._copy()
  sdata = _verify_plotting_tree(sdata)
  n_steps = len(sdata.plotting_tree.keys())
@@ -488,15 +494,17 @@ def render_images(
  **kwargs,
  )
 
- sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
- elements=params_dict["elements"],
- channel=channel,
- cmap_params=cmap_params,
- palette=params_dict["palette"],
- alpha=alpha,
- quantiles_for_norm=params_dict["quantiles_for_norm"],
- scale=params_dict["scale"],
- )
+ for element, param_values in params_dict.items():
+ sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
+ element=element,
+ channel=param_values["channel"],
+ cmap_params=cmap_params,
+ palette=param_values["palette"],
+ alpha=param_values["alpha"],
+ percentiles_for_norm=param_values["percentiles_for_norm"],
+ scale=param_values["scale"],
+ )
+ n_steps += 1
 
  return sdata
 

src/spatialdata_plot/_utils.py

@@ -0,0 +1,69 @@
+from __future__ import annotations
+
+import functools
+import warnings
+from typing import Any, Callable, TypeVar
+
+RT = TypeVar("RT")
+
+
+def deprecation_alias(**aliases: str) -> Callable[[Callable[..., RT]], Callable[..., RT]]:
+ """
+ Decorate a function to warn user of use of arguments set for deprecation.
+
+ Parameters
+ ----------
+ aliases
+ Deprecation argument aliases to be mapped to the new arguments.
+
+ Returns
+ -------
+ A decorator that can be used to mark an argument for deprecation and substituting it with the new argument.
+
+ Raises
+ ------
+ TypeError
+ If the provided aliases are not of string type.
+
+ Example
+ -------
+ Assuming we have an argument 'table' set for deprecation and we want to warn the user and substitute with 'tables':
+
+ ```python
+ @deprecation_alias(table="tables")
+ def my_function(tables: AnnData | dict[str, AnnData]):
+ pass
+ ```
+ """
+
+ def deprecation_decorator(f: Callable[..., RT]) -> Callable[..., RT]:
+ @functools.wraps(f)
+ def wrapper(*args: Any, **kwargs: Any) -> RT:
+ class_name = f.__qualname__
+ rename_kwargs(f.__name__, kwargs, aliases, class_name)
+ return f(*args, **kwargs)
+
+ return wrapper
+
+ return deprecation_decorator
+
+
+def rename_kwargs(func_name: str, kwargs: dict[str, Any], aliases: dict[str, str], class_name: None | str) -> None:
+ """Rename function arguments set for deprecation and gives warning in case of usage of these arguments."""
+ for alias, new in aliases.items():
+ if alias in kwargs:
+ class_name = class_name + "." if class_name else ""
+ if new in kwargs:
+ raise TypeError(
+ f"{class_name}{func_name} received both {alias} and {new} as arguments!"
+ f" {alias} is being deprecated in spatialdata-plot version 0.3, only use {new} instead."
+ )
+ warnings.warn(
+ message=(
+ f"`{alias}` is being deprecated as an argument to `{class_name}{func_name}` in spatialdata-plot "
+ f"version 0.3, switch to `{new}` instead."
+ ),
+ category=DeprecationWarning,
+ stacklevel=3,
+ )
+ kwargs[new] = kwargs.pop(alias)

src/spatialdata_plot/pl/basic.py

@@ -23,6 +23,7 @@
 from spatialdata._core.data_extent import get_extent
 
 from spatialdata_plot._accessor import register_spatial_data_accessor
+from spatialdata_plot._utils import deprecation_alias
 from spatialdata_plot.pl.render import (
  _render_images,
  _render_labels,
@@ -50,6 +51,7 @@
  _prepare_params_plot,
  _set_outline,
  _update_params,
+ _validate_image_render_params,
  _validate_render_params,
  _validate_show_parameters,
  save_fig,
@@ -390,59 +392,63 @@ def render_points(
 
  return sdata
 
+ @deprecation_alias(elements="element", quantiles_for_norm="percentiles_for_norm", version="version 0.3.0")
  def render_images(
  self,
-elements: list[str] | str | None = None,
+element: str | None = None,
  channel: list[str] | list[int] | str | int | None = None,
- cmap: list[Colormap] | Colormap | str | None = None,
+ cmap: list[Colormap | str] | Colormap | str | None = None,
  norm: Normalize | None = None,
  na_color: ColorLike | None = (0.0, 0.0, 0.0, 0.0),
- palette: list[list[str | None]] | list[str | None] | str | None = None,
+ palette: list[str] | str | None = None,
  alpha: float | int = 1.0,
-quantiles_for_norm: tuple[float | None, float | None] | None = None,
- scale: list[str] | str | None = None,
+percentiles_for_norm: tuple[float, float] | None = None,
+ scale: str | None = None,
  **kwargs: Any,
  ) -> sd.SpatialData:
  """
  Render image elements in SpatialData.
 
+ In case of no elements specified, "broadcasting" of parameters is applied. This means that for any particular
+ SpatialElement, we validate whether a given parameter is valid. If not valid for a particular SpatialElement the
+ specific parameter for that particular SpatialElement will be ignored. If you want to set specific parameters
+ for specific elements please chain the render functions: `pl.render_images(...).pl.render_images(...).pl.show()`
+ .
+
  Parameters
  ----------
- elements : list[str] | str | None, optional
- The name(s) of the image element(s) to render. If `None`, all image
- elements in the `SpatialData` object will be used. If a string is provided,
- it is converted into a single-element list.
- channel : list[str] | list[int] | str | int | None, optional
+ element : str | None
+ The name of the image element to render. If `None`, all image
+ elements in the `SpatialData` object will be used.
+ channels : list[str] | list[int] | str | int | None, optional
  To select specific channels to plot. Can be a single channel name/int or a
  list of channel names/ints. If `None`, all channels will be used.
- cmap : list[Colormap] | Colormap | str | None, optional
+ cmap : list[Colormap | str] | Colormap | str | None, optional
  Colormap or list of colormaps for continuous annotations, see :class:`matplotlib.colors.Colormap`.
  Each colormap applies to a corresponding channel.
  norm : Normalize | None, optional
  Colormap normalization for continuous annotations, see :class:`matplotlib.colors.Normalize`.
  Applies to all channels if set.
  na_color : ColorLike | None, default (0.0, 0.0, 0.0, 0.0)
  Color to be used for NA values. Accepts color-like values (string, hex, RGB(A)).
- palette : list[list[str | None]] | list[str | None] | str | None
+ palette : list[str] | None
  Palette to color images. In the case of a list of
  lists means that there is one list per element to be plotted in the list and this list contains the string
  indicating the palette to be used. If not provided as list of lists, broadcasting behaviour is
  attempted (use the same values for all elements).
  alpha : float | int, default 1.0
  Alpha value for the images. Must be a numeric between 0 and 1.
-quantiles_for_norm : tuple[float | None, float | None] | None, optional
+percentiles_for_norm : tuple[float, float] | None
  Optional pair of floats (pmin < pmax, 0-100) which will be used for quantile normalization.
- scale : list[str] | str | None, optional
+ scale : str | None
  Influences the resolution of the rendering. Possibilities include:
  1) `None` (default): The image is rasterized to fit the canvas size. For
  multiscale images, the best scale is selected before rasterization.
- 2) A scale name: Renders the specified scale as-is (with adjustments for dpi
- in `show()`).
+ 2) A scale name: Renders the specified scale ( of a multiscale image) as-is
+(with adjustments for dpi in `show()`).
  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.
- 4) A list matching the list of elements. Can contain `None`, scale names, or
- "full". Each scale applies to the corresponding element.
  kwargs
  Additional arguments to be passed to cmap, norm, and other rendering functions.
 
@@ -451,19 +457,19 @@ def render_images(
  sd.SpatialData
  The SpatialData object with the rendered images.
  """
- params_dict = _validate_render_params(
- "images",
+ params_dict = _validate_image_render_params(
  self._sdata,
-elements=elements,
+element=element,
  channel=channel,
  alpha=alpha,
  palette=palette,
  na_color=na_color,
  cmap=cmap,
  norm=norm,
  scale=scale,
-quantiles_for_norm=quantiles_for_norm,
+percentiles_for_norm=percentiles_for_norm,
  )
+
  sdata = self._copy()
  sdata = _verify_plotting_tree(sdata)
  n_steps = len(sdata.plotting_tree.keys())
@@ -488,15 +494,17 @@ def render_images(
  **kwargs,
  )
 
- sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
- elements=params_dict["elements"],
- channel=channel,
- cmap_params=cmap_params,
- palette=params_dict["palette"],
- alpha=alpha,
- quantiles_for_norm=params_dict["quantiles_for_norm"],
- scale=params_dict["scale"],
- )
+ for element, param_values in params_dict.items():
+ sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
+ element=element,
+ channel=param_values["channel"],
+ cmap_params=cmap_params,
+ palette=param_values["palette"],
+ alpha=param_values["alpha"],
+ percentiles_for_norm=param_values["percentiles_for_norm"],
+ scale=param_values["scale"],
+ )
+ n_steps += 1
 
  return sdata
 

src/spatialdata_plot/_utils.py

@@ -0,0 +1,69 @@
+from __future__ import annotations
+
+import functools
+import warnings
+from typing import Any, Callable, TypeVar
+
+RT = TypeVar("RT")
+
+
+def deprecation_alias(**aliases: str) -> Callable[[Callable[..., RT]], Callable[..., RT]]:
+ """
+ Decorate a function to warn user of use of arguments set for deprecation.
+
+ Parameters
+ ----------
+ aliases
+ Deprecation argument aliases to be mapped to the new arguments.
+
+ Returns
+ -------
+ A decorator that can be used to mark an argument for deprecation and substituting it with the new argument.
+
+ Raises
+ ------
+ TypeError
+ If the provided aliases are not of string type.
+
+ Example
+ -------
+ Assuming we have an argument 'table' set for deprecation and we want to warn the user and substitute with 'tables':
+
+ ```python
+ @deprecation_alias(table="tables")
+ def my_function(tables: AnnData | dict[str, AnnData]):
+ pass
+ ```
+ """
+
+ def deprecation_decorator(f: Callable[..., RT]) -> Callable[..., RT]:
+ @functools.wraps(f)
+ def wrapper(*args: Any, **kwargs: Any) -> RT:
+ class_name = f.__qualname__
+ rename_kwargs(f.__name__, kwargs, aliases, class_name)
+ return f(*args, **kwargs)
+
+ return wrapper
+
+ return deprecation_decorator
+
+
+def rename_kwargs(func_name: str, kwargs: dict[str, Any], aliases: dict[str, str], class_name: None | str) -> None:
+ """Rename function arguments set for deprecation and gives warning in case of usage of these arguments."""
+ for alias, new in aliases.items():
+ if alias in kwargs:
+ class_name = class_name + "." if class_name else ""
+ if new in kwargs:
+ raise TypeError(
+ f"{class_name}{func_name} received both {alias} and {new} as arguments!"
+ f" {alias} is being deprecated in spatialdata-plot version 0.3, only use {new} instead."
+ )
+ warnings.warn(
+ message=(
+ f"`{alias}` is being deprecated as an argument to `{class_name}{func_name}` in spatialdata-plot "
+ f"version 0.3, switch to `{new}` instead."
+ ),
+ category=DeprecationWarning,
+ stacklevel=3,
+ )
+ kwargs[new] = kwargs.pop(alias)

src/spatialdata_plot/pl/basic.py

@@ -23,6 +23,7 @@
 from spatialdata._core.data_extent import get_extent
 
 from spatialdata_plot._accessor import register_spatial_data_accessor
+from spatialdata_plot._utils import deprecation_alias
 from spatialdata_plot.pl.render import (
  _render_images,
  _render_labels,
@@ -50,6 +51,7 @@
  _prepare_params_plot,
  _set_outline,
  _update_params,
+ _validate_image_render_params,
  _validate_render_params,
  _validate_show_parameters,
  save_fig,
@@ -390,59 +392,63 @@ def render_points(
 
  return sdata
 
+ @deprecation_alias(elements="element", quantiles_for_norm="percentiles_for_norm", version="version 0.3.0")
  def render_images(
  self,
-elements: list[str] | str | None = None,
+element: str | None = None,
  channel: list[str] | list[int] | str | int | None = None,
- cmap: list[Colormap] | Colormap | str | None = None,
+ cmap: list[Colormap | str] | Colormap | str | None = None,
  norm: Normalize | None = None,
  na_color: ColorLike | None = (0.0, 0.0, 0.0, 0.0),
- palette: list[list[str | None]] | list[str | None] | str | None = None,
+ palette: list[str] | str | None = None,
  alpha: float | int = 1.0,
-quantiles_for_norm: tuple[float | None, float | None] | None = None,
- scale: list[str] | str | None = None,
+percentiles_for_norm: tuple[float, float] | None = None,
+ scale: str | None = None,
  **kwargs: Any,
  ) -> sd.SpatialData:
  """
  Render image elements in SpatialData.
 
+ In case of no elements specified, "broadcasting" of parameters is applied. This means that for any particular
+ SpatialElement, we validate whether a given parameter is valid. If not valid for a particular SpatialElement the
+ specific parameter for that particular SpatialElement will be ignored. If you want to set specific parameters
+ for specific elements please chain the render functions: `pl.render_images(...).pl.render_images(...).pl.show()`
+ .
+
  Parameters
  ----------
- elements : list[str] | str | None, optional
- The name(s) of the image element(s) to render. If `None`, all image
- elements in the `SpatialData` object will be used. If a string is provided,
- it is converted into a single-element list.
- channel : list[str] | list[int] | str | int | None, optional
+ element : str | None
+ The name of the image element to render. If `None`, all image
+ elements in the `SpatialData` object will be used.
+ channels : list[str] | list[int] | str | int | None, optional
  To select specific channels to plot. Can be a single channel name/int or a
  list of channel names/ints. If `None`, all channels will be used.
- cmap : list[Colormap] | Colormap | str | None, optional
+ cmap : list[Colormap | str] | Colormap | str | None, optional
  Colormap or list of colormaps for continuous annotations, see :class:`matplotlib.colors.Colormap`.
  Each colormap applies to a corresponding channel.
  norm : Normalize | None, optional
  Colormap normalization for continuous annotations, see :class:`matplotlib.colors.Normalize`.
  Applies to all channels if set.
  na_color : ColorLike | None, default (0.0, 0.0, 0.0, 0.0)
  Color to be used for NA values. Accepts color-like values (string, hex, RGB(A)).
- palette : list[list[str | None]] | list[str | None] | str | None
+ palette : list[str] | None
  Palette to color images. In the case of a list of
  lists means that there is one list per element to be plotted in the list and this list contains the string
  indicating the palette to be used. If not provided as list of lists, broadcasting behaviour is
  attempted (use the same values for all elements).
  alpha : float | int, default 1.0
  Alpha value for the images. Must be a numeric between 0 and 1.
-quantiles_for_norm : tuple[float | None, float | None] | None, optional
+percentiles_for_norm : tuple[float, float] | None
  Optional pair of floats (pmin < pmax, 0-100) which will be used for quantile normalization.
- scale : list[str] | str | None, optional
+ scale : str | None
  Influences the resolution of the rendering. Possibilities include:
  1) `None` (default): The image is rasterized to fit the canvas size. For
  multiscale images, the best scale is selected before rasterization.
- 2) A scale name: Renders the specified scale as-is (with adjustments for dpi
- in `show()`).
+ 2) A scale name: Renders the specified scale ( of a multiscale image) as-is
+(with adjustments for dpi in `show()`).
  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.
- 4) A list matching the list of elements. Can contain `None`, scale names, or
- "full". Each scale applies to the corresponding element.
  kwargs
  Additional arguments to be passed to cmap, norm, and other rendering functions.
 
@@ -451,19 +457,19 @@ def render_images(
  sd.SpatialData
  The SpatialData object with the rendered images.
  """
- params_dict = _validate_render_params(
- "images",
+ params_dict = _validate_image_render_params(
  self._sdata,
-elements=elements,
+element=element,
  channel=channel,
  alpha=alpha,
  palette=palette,
  na_color=na_color,
  cmap=cmap,
  norm=norm,
  scale=scale,
-quantiles_for_norm=quantiles_for_norm,
+percentiles_for_norm=percentiles_for_norm,
  )
+
  sdata = self._copy()
  sdata = _verify_plotting_tree(sdata)
  n_steps = len(sdata.plotting_tree.keys())
@@ -488,15 +494,17 @@ def render_images(
  **kwargs,
  )
 
- sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
- elements=params_dict["elements"],
- channel=channel,
- cmap_params=cmap_params,
- palette=params_dict["palette"],
- alpha=alpha,
- quantiles_for_norm=params_dict["quantiles_for_norm"],
- scale=params_dict["scale"],
- )
+ for element, param_values in params_dict.items():
+ sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
+ element=element,
+ channel=param_values["channel"],
+ cmap_params=cmap_params,
+ palette=param_values["palette"],
+ alpha=param_values["alpha"],
+ percentiles_for_norm=param_values["percentiles_for_norm"],
+ scale=param_values["scale"],
+ )
+ n_steps += 1
 
  return sdata