spateo.tdr.interpolations.utils
===============================

.. py:module:: spateo.tdr.interpolations.utils


Functions
---------

.. autoapisummary::

   spateo.tdr.interpolations.utils.get_X_Y_grid


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

.. py:function:: get_X_Y_grid(adata: Optional[anndata.AnnData] = None, genes: Optional[List] = None, X: Optional[numpy.ndarray] = None, Y: Optional[numpy.ndarray] = None, grid_num: List = [50, 50, 50]) -> Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray, numpy.ndarray]

   Prepare the X (spatial coordinates), Y (gene expression) and grid points for the kernel or deep model.

   :param adata: AnnData object that contains spatial (numpy.ndarray) in the `obsm` attribute.
   :param genes: Gene list whose interpolate expression across space needs to learned. If Y is provided, genes will only
                 be used to retrive the gene annotation info.
   :param X: The spatial coordinates of each data point.
   :param Y: The gene expression of the corresponding data point.
   :param grid_num: Number of grid to generate. Default is 50 for each dimension. Must be non-negative.

   :returns: spatial coordinates.
             Y: gene expression of the associated spatial coordinates.
             Grid: grid points formed with the input spatial coordinates.
             grid_in_hull: A list of booleans indicates whether the current grid points is within the convex hull formed by
                 the input data points.
   :rtype: X