spateo.plotting.static.three_d_plot.morphometrics_plots¶
Functions¶
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Visualize the jacobian result. |
|
Visualize the feature values. |
|
Visualize the torsion result. |
|
Visualize the torsion result. |
|
Visualize the curvature result. |
|
Visualize the curl result. |
|
Visualize the divergence result. |
Module Contents¶
- spateo.plotting.static.three_d_plot.morphometrics_plots._check_index_in_adata(adata, model)[source]¶
- spateo.plotting.static.three_d_plot.morphometrics_plots._check_key_in_adata(adata: anndata.AnnData, key: str, where: str)[source]¶
- spateo.plotting.static.three_d_plot.morphometrics_plots.jacobian(adata: anndata.AnnData, model: pyvista.PolyData | pyvista.UnstructuredGrid | pyvista.MultiBlock | list, jacobian_key: str = 'jacobian', filename: str | None = None, jupyter: bool | Literal['none', 'static', 'trame'] = False, off_screen: bool = False, shape: str | list | tuple = (3, 3), window_size: tuple | None = (512 * 3, 512 * 3), background: str = 'black', colormap: str | list | None = 'default_cmap', ambient: float | list = 0.2, opacity: float | numpy.ndarray | list = 1.0, model_style: Literal['points', 'surface', 'wireframe'] | list = 'points', model_size: float | list = 3.0, show_axes: bool = True, show_legend: bool = True, legend_kwargs: dict | None = None, text: bool | str = True, text_kwargs: dict | None = None, **kwargs)[source]¶
Visualize the jacobian result.
- Parameters:
- adata
An anndata object contain jacobian matrix in
.uns[jacobian_key]
.- model
A reconstructed model contains
obs_index
values.- jacobian_key
The key in
.uns
that corresponds to the jacobian matrix in the anndata object.- filename
Filename of output file. Writer type is inferred from the extension of the filename.
Output an image file,please enter a filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
. Whenjupyter=False
, if you want to save ‘.png’ file, please ensureoff_screen=True
.Output a gif file, please enter a filename ending with
.gif
.Output a mp4 file, please enter a filename ending with
.mp4
.
- jupyter
Whether to plot in jupyter notebook. Available
jupyter
are:'none'
- Do not display in the notebook.'trame'
- Show a trame widget'static'
- Display a static figure.
- off_screen
Renders off-screen when True. Useful for automated screenshots.
- shape
Number of sub-render windows inside the main window. By default, there are nine render window.
- window_size
Window size in pixels. The default window_size is
[512*3, 512*3]
.- background
The background color of the window.
- colormap
Name of the Matplotlib colormap to use when mapping the scalars.
When the colormap is None, use {key}_rgba to map the scalars, otherwise use the colormap to map scalars.
- ambient
When lighting is enabled, this is the amount of light in the range of 0 to 1 (default 0.0) that reaches the actor when not directed at the light source emitted from the viewer.
- opacity
Opacity of the model.
If a single float value is given, it will be the global opacity of the model and uniformly applied everywhere, elif a numpy.ndarray with single float values is given, it will be the opacity of each point. - should be between 0 and 1.
A string can also be specified to map the scalars range to a predefined opacity transfer function (options include: ‘linear’, ‘linear_r’, ‘geom’, ‘geom_r’).
- model_style
Visualization style of the model. One of the following:
model_style = 'surface'
,model_style = 'wireframe'
,model_style = 'points'
.
- model_size
If
model_style = 'points'
, point size of any nodes in the dataset plotted.If
model_style = 'wireframe'
, thickness of lines.- show_axes
Whether to add a camera orientation widget to the active renderer.
- show_legend
whether to add a legend to the plotter.
- legend_kwargs
A dictionary that will be pass to the
add_legend
function. By default, it is an empty dictionary and theadd_legend
function will use the{"legend_size": None, "legend_loc": None, "legend_size": None, "legend_loc": None, "title_font_size": None, "label_font_size": None, "font_family": "arial", "fmt": "%.2e", "n_labels": 5, "vertical": True}
as its parameters. Otherwise, you can provide a dictionary that properly modify those keys according to your needs.- text
The text to add the rendering.
- text_kwargs
A dictionary that will be pass to the
add_text
function.By default, it is an empty dictionary and the
add_legend
function will use the{ "font_family": "arial", "font_size": 12, "font_color": "black", "text_loc": "upper_left"}
as its parameters. Otherwise, you can provide a dictionary that properly modify those keys according to your needs.- **kwargs
Additional parameters that will be passed into the
st.pl.three_d_multi_plot
function.
- Returns:
- List of camera position, focal point, and view up.
Returned only if filename is None or filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
.- img: Numpy array of the last image.
Returned only if filename is None or filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
.
- Return type:
cpo
Examples
Visualize only in one model:
- st.pl.jacobian(
adata=stage_adata, model=stage_pc, jacobian_key=”jacobian”, jupyter=”static”, model_style=”points”, model_size=3
)
Visualize in multiple model:
- st.pl.jacobian(
adata=stage_adata, model=[stage_pc, trajectory_model], jacobian_key=”jacobian”, jupyter=”static”, model_style=[“points”, “wireframe”], model_size=[3, 1]
)
- spateo.plotting.static.three_d_plot.morphometrics_plots.feature(adata: anndata.AnnData, model: pyvista.PolyData | pyvista.UnstructuredGrid | pyvista.MultiBlock | list, feature_key: str, filename: str | None = None, jupyter: bool | Literal['none', 'static', 'trame'] = False, off_screen: bool = False, window_size: tuple | None = (512, 512), background: str = 'black', colormap: str | list | None = 'default_cmap', ambient: float | list = 0.2, opacity: float | numpy.ndarray | list = 1.0, model_style: Literal['points', 'surface', 'wireframe'] | list = 'points', model_size: float | list = 3.0, show_axes: bool = True, show_legend: bool = True, legend_kwargs: dict | None = dict(title=''), text: bool | str = True, text_kwargs: dict | None = None, **kwargs)[source]¶
Visualize the feature values.
- Parameters:
- adata
An anndata object contain feature values in
.obs[feature_key]
.- model
A reconstructed model contains
obs_index
values.- feature_key
The key in
.obs
that corresponds to the feature values in the anndata object.- filename
Filename of output file. Writer type is inferred from the extension of the filename.
Output an image file,please enter a filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
. Whenjupyter=False
, if you want to save ‘.png’ file, please ensureoff_screen=True
.Output a gif file, please enter a filename ending with
.gif
.Output a mp4 file, please enter a filename ending with
.mp4
.
- jupyter
Whether to plot in jupyter notebook. Available
jupyter
are:'none'
- Do not display in the notebook.'trame'
- Show a trame widget'static'
- Display a static figure.
- off_screen
Renders off-screen when True. Useful for automated screenshots.
- window_size
Window size in pixels. The default window_size is
[512, 512]
.- background
The background color of the window.
- colormap
Name of the Matplotlib colormap to use when mapping the scalars.
When the colormap is None, use {key}_rgba to map the scalars, otherwise use the colormap to map scalars.
- ambient
When lighting is enabled, this is the amount of light in the range of 0 to 1 (default 0.0) that reaches the actor when not directed at the light source emitted from the viewer.
- opacity
Opacity of the model.
If a single float value is given, it will be the global opacity of the model and uniformly applied everywhere, elif a numpy.ndarray with single float values is given, it will be the opacity of each point. - should be between 0 and 1.
A string can also be specified to map the scalars range to a predefined opacity transfer function (options include: ‘linear’, ‘linear_r’, ‘geom’, ‘geom_r’).
- model_style
Visualization style of the model. One of the following:
model_style = 'surface'
,model_style = 'wireframe'
,model_style = 'points'
.
- model_size
If
model_style = 'points'
, point size of any nodes in the dataset plotted.If
model_style = 'wireframe'
, thickness of lines.- show_axes
Whether to add a camera orientation widget to the active renderer.
- show_legend
whether to add a legend to the plotter.
- legend_kwargs
A dictionary that will be pass to the
add_legend
function. By default, it is an empty dictionary and theadd_legend
function will use the{"legend_size": None, "legend_loc": None, "legend_size": None, "legend_loc": None, "title_font_size": None, "label_font_size": None, "font_family": "arial", "fmt": "%.2e", "n_labels": 5, "vertical": True}
as its parameters. Otherwise, you can provide a dictionary that properly modify those keys according to your needs.- text
The text to add the rendering.
- text_kwargs
A dictionary that will be pass to the
add_text
function.By default, it is an empty dictionary and the
add_legend
function will use the{ "font_family": "arial", "font_size": 12, "font_color": "black", "text_loc": "upper_left"}
as its parameters. Otherwise, you can provide a dictionary that properly modify those keys according to your needs.- **kwargs
Additional parameters that will be passed into the
st.pl.three_d_plot
function.
Examples
Visualize only in one model:
- st.pl.feature(
adata=stage_adata, model=stage_pc, feature_key=”torsion”, jupyter=”static”, model_style=”points”, model_size=3
)
Visualize in multiple model:
- st.pl.feature(
adata=stage_adata, model=[stage_pc, trajectory_model], feature_key=”torsion”, jupyter=”static”, model_style=[“points”, “wireframe”], model_size=[3, 1]
)
- spateo.plotting.static.three_d_plot.morphometrics_plots.torsion(adata: anndata.AnnData, model: pyvista.PolyData | pyvista.UnstructuredGrid | pyvista.MultiBlock | list, torsion_key: str = 'torsion', filename: str | None = None, jupyter: bool | Literal['none', 'static', 'trame'] = False, colormap: str | list | None = 'default_cmap', ambient: float | list = 0.2, opacity: float | numpy.ndarray | list = 1.0, model_style: Literal['points', 'surface', 'wireframe'] | list = 'points', model_size: float | list = 3.0, **kwargs)[source]¶
Visualize the torsion result.
- Parameters:
- adata
An anndata object contain torsion values in
.obs[torsion_key]
.- model
A reconstructed model contains
obs_index
values.- torsion_key
The key in
.obs
that corresponds to the torsion values in the anndata object.- filename
Filename of output file. Writer type is inferred from the extension of the filename.
Output an image file,please enter a filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
. Whenjupyter=False
, if you want to save ‘.png’ file, please ensureoff_screen=True
.Output a gif file, please enter a filename ending with
.gif
.Output a mp4 file, please enter a filename ending with
.mp4
.
- jupyter
Whether to plot in jupyter notebook. Available
jupyter
are:'none'
- Do not display in the notebook.'trame'
- Show a trame widget'static'
- Display a static figure.
- colormap
Name of the Matplotlib colormap to use when mapping the scalars.
When the colormap is None, use {key}_rgba to map the scalars, otherwise use the colormap to map scalars.
- ambient
When lighting is enabled, this is the amount of light in the range of 0 to 1 (default 0.0) that reaches the actor when not directed at the light source emitted from the viewer.
- opacity
Opacity of the model.
If a single float value is given, it will be the global opacity of the model and uniformly applied everywhere, elif a numpy.ndarray with single float values is given, it will be the opacity of each point. - should be between 0 and 1.
A string can also be specified to map the scalars range to a predefined opacity transfer function (options include: ‘linear’, ‘linear_r’, ‘geom’, ‘geom_r’).
- model_style
Visualization style of the model. One of the following:
model_style = 'surface'
,model_style = 'wireframe'
,model_style = 'points'
.
- model_size
If
model_style = 'points'
, point size of any nodes in the dataset plotted.If
model_style = 'wireframe'
, thickness of lines.- **kwargs
Additional parameters that will be passed into the
st.pl.feature
function.
- Returns:
- List of camera position, focal point, and view up.
Returned only if filename is None or filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
.- img: Numpy array of the last image.
Returned only if filename is None or filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
.
- Return type:
cpo
Examples
Visualize only in one model:
- st.pl.torsion(
adata=stage_adata, model=stage_pc, torsion_key=”torsion”, jupyter=”static”, model_style=”points”, model_size=3
)
Visualize in multiple model:
- st.pl.torsion(
adata=stage_adata, model=[stage_pc, trajectory_model], torsion_key=”torsion”, jupyter=”static”, model_style=[“points”, “wireframe”], model_size=[3, 1]
)
- spateo.plotting.static.three_d_plot.morphometrics_plots.acceleration(adata: anndata.AnnData, model: pyvista.PolyData | pyvista.UnstructuredGrid | pyvista.MultiBlock | list, acceleration_key: str = 'acceleration', filename: str | None = None, jupyter: bool | Literal['none', 'static', 'trame'] = False, colormap: str | list | None = 'default_cmap', ambient: float | list = 0.2, opacity: float | numpy.ndarray | list = 1.0, model_style: Literal['points', 'surface', 'wireframe'] | list = 'points', model_size: float | list = 3.0, **kwargs)[source]¶
Visualize the torsion result.
- Parameters:
- adata
An anndata object contain acceleration values in
.obs[acceleration_key]
.- model
A reconstructed model contains
obs_index
values.- acceleration_key
The key in
.obs
that corresponds to the acceleration values in the anndata object.- filename
Filename of output file. Writer type is inferred from the extension of the filename.
Output an image file,please enter a filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
. Whenjupyter=False
, if you want to save ‘.png’ file, please ensureoff_screen=True
.Output a gif file, please enter a filename ending with
.gif
.Output a mp4 file, please enter a filename ending with
.mp4
.
- jupyter
Whether to plot in jupyter notebook. Available
jupyter
are:'none'
- Do not display in the notebook.'trame'
- Show a trame widget'static'
- Display a static figure.
- colormap
Name of the Matplotlib colormap to use when mapping the scalars.
When the colormap is None, use {key}_rgba to map the scalars, otherwise use the colormap to map scalars.
- ambient
When lighting is enabled, this is the amount of light in the range of 0 to 1 (default 0.0) that reaches the actor when not directed at the light source emitted from the viewer.
- opacity
Opacity of the model.
If a single float value is given, it will be the global opacity of the model and uniformly applied everywhere, elif a numpy.ndarray with single float values is given, it will be the opacity of each point. - should be between 0 and 1.
A string can also be specified to map the scalars range to a predefined opacity transfer function (options include: ‘linear’, ‘linear_r’, ‘geom’, ‘geom_r’).
- model_style
Visualization style of the model. One of the following:
model_style = 'surface'
,model_style = 'wireframe'
,model_style = 'points'
.
- model_size
If
model_style = 'points'
, point size of any nodes in the dataset plotted.If
model_style = 'wireframe'
, thickness of lines.- **kwargs
Additional parameters that will be passed into the
st.pl.feature
function.
- Returns:
- List of camera position, focal point, and view up.
Returned only if filename is None or filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
.- img: Numpy array of the last image.
Returned only if filename is None or filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
.
- Return type:
cpo
Examples
Visualize only in one model:
- st.pl.acceleration(
adata=stage_adata, model=stage_pc, acceleration_key=”acceleration”, jupyter=”static”, model_style=”points”, model_size=3
)
Visualize in multiple model:
- st.pl.acceleration(
adata=stage_adata, model=[stage_pc, trajectory_model], acceleration_key=”acceleration”, jupyter=”static”, model_style=[“points”, “wireframe”], model_size=[3, 1]
)
- spateo.plotting.static.three_d_plot.morphometrics_plots.curvature(adata: anndata.AnnData, model: pyvista.PolyData | pyvista.UnstructuredGrid | pyvista.MultiBlock | list, curvature_key: str = 'curvature', filename: str | None = None, jupyter: bool | Literal['none', 'static', 'trame'] = False, colormap: str | list | None = 'default_cmap', ambient: float | list = 0.2, opacity: float | numpy.ndarray | list = 1.0, model_style: Literal['points', 'surface', 'wireframe'] | list = 'points', model_size: float | list = 3.0, **kwargs)[source]¶
Visualize the curvature result.
- Parameters:
- adata
An anndata object contain curvature values in
.obs[curvature_key]
.- model
A reconstructed model contains
obs_index
values.- curvature_key
The key in
.obs
that corresponds to the curvature values in the anndata object.- filename
Filename of output file. Writer type is inferred from the extension of the filename.
Output an image file,please enter a filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
. Whenjupyter=False
, if you want to save ‘.png’ file, please ensureoff_screen=True
.Output a gif file, please enter a filename ending with
.gif
.Output a mp4 file, please enter a filename ending with
.mp4
.
- jupyter
Whether to plot in jupyter notebook. Available
jupyter
are:'none'
- Do not display in the notebook.'trame'
- Show a trame widget'static'
- Display a static figure.
- colormap
Name of the Matplotlib colormap to use when mapping the scalars.
When the colormap is None, use {key}_rgba to map the scalars, otherwise use the colormap to map scalars.
- ambient
When lighting is enabled, this is the amount of light in the range of 0 to 1 (default 0.0) that reaches the actor when not directed at the light source emitted from the viewer.
- opacity
Opacity of the model.
If a single float value is given, it will be the global opacity of the model and uniformly applied everywhere, elif a numpy.ndarray with single float values is given, it will be the opacity of each point. - should be between 0 and 1.
A string can also be specified to map the scalars range to a predefined opacity transfer function (options include: ‘linear’, ‘linear_r’, ‘geom’, ‘geom_r’).
- model_style
Visualization style of the model. One of the following:
model_style = 'surface'
,model_style = 'wireframe'
,model_style = 'points'
.
- model_size
If
model_style = 'points'
, point size of any nodes in the dataset plotted.If
model_style = 'wireframe'
, thickness of lines.- **kwargs
Additional parameters that will be passed into the
st.pl.feature
function.
- Returns:
- List of camera position, focal point, and view up.
Returned only if filename is None or filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
.- img: Numpy array of the last image.
Returned only if filename is None or filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
.
- Return type:
cpo
Examples
Visualize only in one model:
- st.pl.curvature(
adata=stage_adata, model=stage_pc, curvature_key=”curvature”, jupyter=”static”, model_style=”points”, model_size=3
)
Visualize in multiple model:
- st.pl.curvature(
adata=stage_adata, model=[stage_pc, trajectory_model], curvature_key=”curvature”, jupyter=”static”, model_style=[“points”, “wireframe”], model_size=[3, 1]
)
- spateo.plotting.static.three_d_plot.morphometrics_plots.curl(adata: anndata.AnnData, model: pyvista.PolyData | pyvista.UnstructuredGrid | pyvista.MultiBlock | list, curl_key: str = 'curl', filename: str | None = None, jupyter: bool | Literal['none', 'static', 'trame'] = False, colormap: str | list | None = 'default_cmap', ambient: float | list = 0.2, opacity: float | numpy.ndarray | list = 1.0, model_style: Literal['points', 'surface', 'wireframe'] | list = 'points', model_size: float | list = 3.0, **kwargs)[source]¶
Visualize the curl result.
- Parameters:
- adata
An anndata object contain curl values in
.obs[curl_key]
.- model
A reconstructed model contains
obs_index
values.- curl_key
The key in
.obs
that corresponds to the curl values in the anndata object.- filename
Filename of output file. Writer type is inferred from the extension of the filename.
Output an image file,please enter a filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
. Whenjupyter=False
, if you want to save ‘.png’ file, please ensureoff_screen=True
.Output a gif file, please enter a filename ending with
.gif
.Output a mp4 file, please enter a filename ending with
.mp4
.
- jupyter
Whether to plot in jupyter notebook. Available
jupyter
are:'none'
- Do not display in the notebook.'trame'
- Show a trame widget'static'
- Display a static figure.
- colormap
Name of the Matplotlib colormap to use when mapping the scalars.
When the colormap is None, use {key}_rgba to map the scalars, otherwise use the colormap to map scalars.
- ambient
When lighting is enabled, this is the amount of light in the range of 0 to 1 (default 0.0) that reaches the actor when not directed at the light source emitted from the viewer.
- opacity
Opacity of the model.
If a single float value is given, it will be the global opacity of the model and uniformly applied everywhere, elif a numpy.ndarray with single float values is given, it will be the opacity of each point. - should be between 0 and 1.
A string can also be specified to map the scalars range to a predefined opacity transfer function (options include: ‘linear’, ‘linear_r’, ‘geom’, ‘geom_r’).
- model_style
Visualization style of the model. One of the following:
model_style = 'surface'
,model_style = 'wireframe'
,model_style = 'points'
.
- model_size
If
model_style = 'points'
, point size of any nodes in the dataset plotted.If
model_style = 'wireframe'
, thickness of lines.- **kwargs
Additional parameters that will be passed into the
st.pl.feature
function.
- Returns:
- List of camera position, focal point, and view up.
Returned only if filename is None or filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
.- img: Numpy array of the last image.
Returned only if filename is None or filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
.
- Return type:
cpo
Examples
Visualize only in one model:
- st.pl.curl(
adata=stage_adata, model=stage_pc, curl_key=”curl”, jupyter=”static”, model_style=”points”, model_size=3
)
Visualize in multiple model:
- st.pl.curl(
adata=stage_adata, model=[stage_pc, trajectory_model], curl_key=”curl”, jupyter=”static”, model_style=[“points”, “wireframe”], model_size=[3, 1]
)
- spateo.plotting.static.three_d_plot.morphometrics_plots.divergence(adata: anndata.AnnData, model: pyvista.PolyData | pyvista.UnstructuredGrid | pyvista.MultiBlock | list, divergence_key: str = 'divergence', filename: str | None = None, jupyter: bool | Literal['none', 'static', 'trame'] = False, colormap: str | list | None = 'default_cmap', ambient: float | list = 0.2, opacity: float | numpy.ndarray | list = 1.0, model_style: Literal['points', 'surface', 'wireframe'] | list = 'points', model_size: float | list = 3.0, **kwargs)[source]¶
Visualize the divergence result.
- Parameters:
- adata
An anndata object contain curl values in
.obs[divergence_key]
.- model
A reconstructed model contains
obs_index
values.- divergence_key
The key in
.obs
that corresponds to the divergence values in the anndata object.- filename
Filename of output file. Writer type is inferred from the extension of the filename.
Output an image file,please enter a filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
. Whenjupyter=False
, if you want to save ‘.png’ file, please ensureoff_screen=True
.Output a gif file, please enter a filename ending with
.gif
.Output a mp4 file, please enter a filename ending with
.mp4
.
- jupyter
Whether to plot in jupyter notebook. Available
jupyter
are:'none'
- Do not display in the notebook.'pythreejs'
- Show a pythreejs widget'static'
- Display a static figure.'ipygany'
- Show an ipygany widget'panel'
- Show a panel widget.
- colormap
Name of the Matplotlib colormap to use when mapping the scalars.
When the colormap is None, use {key}_rgba to map the scalars, otherwise use the colormap to map scalars.
- ambient
When lighting is enabled, this is the amount of light in the range of 0 to 1 (default 0.0) that reaches the actor when not directed at the light source emitted from the viewer.
- opacity
Opacity of the model.
If a single float value is given, it will be the global opacity of the model and uniformly applied everywhere, elif a numpy.ndarray with single float values is given, it will be the opacity of each point. - should be between 0 and 1.
A string can also be specified to map the scalars range to a predefined opacity transfer function (options include: ‘linear’, ‘linear_r’, ‘geom’, ‘geom_r’).
- model_style
Visualization style of the model. One of the following:
model_style = 'surface'
,model_style = 'wireframe'
,model_style = 'points'
.
- model_size
If
model_style = 'points'
, point size of any nodes in the dataset plotted.If
model_style = 'wireframe'
, thickness of lines.- **kwargs
Additional parameters that will be passed into the
st.pl.feature
function.
- Returns:
- List of camera position, focal point, and view up.
Returned only if filename is None or filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
.- img: Numpy array of the last image.
Returned only if filename is None or filename ending with
'.png', '.tif', '.tiff', '.bmp', '.jpeg', '.jpg', '.svg', '.eps', '.ps', '.pdf', '.tex'
.
- Return type:
cpo
Examples
Visualize only in one model:
- st.pl.divergence(
adata=stage_adata, model=stage_pc, divergence_key=”divergence”, jupyter=”static”, model_style=”points”, model_size=3
)
Visualize in multiple model:
- st.pl.divergence(
adata=stage_adata, model=[stage_pc, trajectory_model], divergence_key=”divergence”, jupyter=”static”, model_style=[“points”, “wireframe”], model_size=[3, 1]
)