pl

Spatial network

`pl.show_network`(adata[, sample_key, ...])	Show the spatial network.
`pl.show_voronoi`(adata, cluster_key[, ...])	Draw a Voronoi plot of the cell distribution.

Show a Moran scatter plot.

`pl.show_tendency`(adata, gene_name[, method, ...])	Plot the tendency curve of the genes.
`pl.show_curves_cluster`(adata[, method, ...])	Plot the tendency curve of the gene clusters.
`pl.show_box_plot`(adata, cluster_key, score_key)	Boxplot of gene expression for each cluster is shown

`pl.show_neighborhood_analysis`(adata[, ...])	Use heatmap to display the results of neighbor analysis
`pl.show_infiltration_analysis`(adata, ...[, ...])	Use barplot to display infiltration scores and the number of non-parenchymal cells.

`pl.show_niche_environment`(adata, niche[, ...])	Show the environment composition of a niche.
`pl.show_niche_sample_heatmap`(adata[, ...])	The heatmap shows the niche composition in each sample, and the bar plot shows the total number of each niche and the total number of cells in each sample, respectively.
`pl.show_celltype_niche_heatmap`(adata[, ...])	The heatmap shows the cell composition of each niche, and the bar plot graph shows the number of each niche in all samples.
`pl.show_celltype_sample_heatmap`(adata[, ...])	Heatmap show the cell composition of each sample.

`pl.show_ccc_netplot`(adata[, sample_id, ...])	Visualize ligand-receptor interactions between two cell types in spatial omics data using network plot.
`pl.show_ccc_dotplot`(adata[, sample, ...])	Dotplot for cell communication analysis are presented, either specifying the cell type pairs and ligand-receptor pairs to be presented or showing the most significant cell type pairs and ligand-receptor pairs after ranking by significance level.
`pl.show_ccc_embedding`(adata, ligand, ...[, ...])	To map the distribution of ligands and receptors expression of different cell type in a situ map of tissue.

`pl.show_factor_matrix_in_CP_tensor`(tensor, ...)	Visualizes a factor in the CP decomposition tensor.
`pl.show_factor_matrix_in_tucker_tensor`(...)	Visualizes a factor in the Tucker decomposition tensor.
`pl.show_proportion_in_tucker`(tensor, module)	Visualizes the proportion in a Tucker decomposition.
`pl.show_proportion_in_CP`(tensor, module[, ...])	Visualizes the proportion in a CP decomposition.