stlearn.pl.cluster_plot¶
- stlearn.pl.cluster_plot(adata: AnnData, title: Optional[str] = None, figsize: Optional[Tuple[float, float]] = None, cmap: Optional[str] = 'default', use_label: Optional[str] = None, list_clusters: Optional[list] = None, ax: Optional[Axes] = None, fig: Optional[Figure] = None, show_plot: Optional[bool] = True, show_axis: Optional[bool] = False, show_image: Optional[bool] = True, show_color_bar: Optional[bool] = True, zoom_coord: Optional[float] = None, crop: Optional[bool] = True, margin: Optional[bool] = 100, size: Optional[float] = 5, image_alpha: Optional[float] = 1.0, cell_alpha: Optional[float] = 1.0, fname: Optional[str] = None, dpi: Optional[int] = 120, show_subcluster: Optional[bool] = False, show_cluster_labels: Optional[bool] = False, show_trajectories: Optional[bool] = False, reverse: Optional[bool] = False, show_node: Optional[bool] = False, threshold_spots: Optional[int] = 5, text_box_size: Optional[float] = 5, color_bar_size: Optional[float] = 10, bbox_to_anchor: Optional[Tuple[float, float]] = (1, 1), trajectory_node_size: Optional[int] = 10, trajectory_alpha: Optional[float] = 1.0, trajectory_width: Optional[float] = 2.5, trajectory_edge_color: Optional[str] = '#f4efd3', trajectory_arrowsize: Optional[int] = 17) Optional[AnnData] [source]¶
Allows the visualization of a cluster results as the discretes values of dot points in the Spatial transcriptomics array. We also support to visualize the spatial trajectory results
- Parameters:
adata – Annotated data matrix.
title – Title name of the figure.
figsize – Figure size with the format (width,height).
cmap – Color map to use for continous variables or discretes variables (e.g. viridis, Set1,…).
use_label – Key for the label use in adata.obs (e.g. leiden, louvain,…).
list_clusters – A set of cluster to be displayed in the figure (e.g. [0,1,2,3]).
ax – A matplotlib axes object.
show_plot – Option to display the figure.
show_image – Option to display the H&E image.
show_color_bar – Option to display color bar.
crop – Option to crop the figure based on the spot locations.
margin – Margin to crop.
size – Spot size to display in figure.
image_alpha – Opacity of H&E image.
cell_alpha – Opacity of spots/cells.
use_raw – Option to use adata.raw data.
fname – Output path to the output if user want to save the figure.
dpi – Dots per inch values for the output.
show_subcluster – Display the subcluster in the figure.
show_cluster_labels – Display the labels of clusters.
show_trajectories – Display the spatial trajectory analysis results.
reverse – Reverse the direction of spatial trajectories.
show_node – Show node of PAGA graph mapping in spatial.
threshold_spots – The number of spots threshold for not display the subcluster labels
text_box_size – The font size in the box of labels.
color_bar_size – The size of color bar.
bbox_to_anchor – Set the position of box of color bar. Default is (1,1)
Examples
>>> import stlearn as st >>> adata = st.datasets.example_bcba() >>> label = "louvain" >>> st.pl.cluster_plot(adata, use_label = label, show_trajectories = True)