smoother.visualization
======================

.. py:module:: smoother.visualization

.. autoapi-nested-parse::

   Visualization functions for smoother.models.deconv



Functions
---------

.. autoapisummary::

   smoother.visualization.plot_celltype_props
   smoother.visualization.clr_stable
   smoother.visualization.ilr_stable
   smoother.visualization.cluster_features
   smoother.visualization._get_cost_matrix
   smoother.visualization.align_clusters
   smoother.visualization.plot_spatial_clusters
   smoother.visualization.cluster_and_plot_celltype_props


Module Contents
---------------

.. py:function:: plot_celltype_props(p_inf, coords, cell_type_names=None, n_col=4, figsize=None)

   Plot the deconvolution results.

   :param p_inf: n_spots x n_groups. The inferred cell-type proportions.
   :param coords: n_spots x 2. The coordinates of the spots.
   :param cell_type_names: list of str. The names of the cell types.
   :param n_col: int. The number of columns in the figure.
   :param figsize: tuple. The size of the figure.


.. py:function:: clr_stable(props, epsilon=1e-08)

   Apply centre log ratio transform (clr) to transform proportions to the real space.

   :param props: n_spots x n_groups. Rowsum equals to 1 or 0. If 0, the transformed vector
                 will also be the zero vector.


.. py:function:: ilr_stable(props, epsilon=1e-08)

   Apply isometric log ratio transformation (ilr) to transform proportions to the real space.


.. py:function:: cluster_features(features, transform='pca', n_neighbors=15, res=1) -> pandas.Series

   Leiden clustering on the input features.


.. py:function:: _get_cost_matrix(clu1, clu2)

   Helper function to get the cost matrix for aligning two clusterings.


.. py:function:: align_clusters(clu_list, ref_ind=None)

   Align the clusterings in clu_list to the reference clustering.

   :param clu_list: list of clustering result.
   :param ref_ind: int. The index of the reference clustering. If None,
                   use the clustering with the largest number of clusters.


.. py:function:: plot_spatial_clusters(clu_aligned_list, coords, names=None, n_col=4)

   Plot clusters.

   :param clu_aligned_list: list of aligned clusterings.
   :param coords: n_spots x 2. Coordinates of the spots.
   :param names: list of str. Names of the deconvolution model.
   :param n_col: int. Number of columns in the plot.


.. py:function:: cluster_and_plot_celltype_props(p_inf_list, coords, names=None, n_col=4, transform='pca', n_neighbors=15, res=1, return_clu=False)

   Cluster the cell-type proportions and visualize the results.

   :param p_inf_list: list of cell-type proportions.
   :param coords: n_spots x 2. Coordinates of the spots.
   :param names: list of str. Names of the deconvolution model.
   :param transform: str. Transformation to apply to the cell-type proportions.
                     'pca', 'clr', 'ilr'.
   :param n_neighbors: int. Number of neighbors to use for clustering.
   :param res: float. Resolution for leiden clustering.
   :param return_clu: bool. Whether to return the clustering results.