Module Contents#


vtk_interpolation(→ anndata.AnnData)

Learn a continuous mapping from space to gene expression pattern with the method contained in VTK.

spateo.tdr.interpolations.interpolation_vtk.vtk_interpolation(source_adata: anndata.AnnData, target_points: numpy.ndarray | None = None, keys: str | list = None, spatial_key: str = 'spatial', layer: str = 'X', radius: float | None = None, n_points: int | None = None, kernel: Literal[shepard, gaussian, linear] = 'shepard', null_strategy: Literal[0, 1, 2] = 1, null_value: int | float = 0) anndata.AnnData[source]#

Learn a continuous mapping from space to gene expression pattern with the method contained in VTK.


AnnData object that contains spatial (numpy.ndarray) in the obsm attribute.


The spatial coordinates of new data point. If target_coords is None, generate new points based on grid_num.


Gene list or info list in the obs attribute whose interpolate expression across space needs to learned.


The key in .obsm that corresponds to the spatial coordinate of each bucket.


If 'X', uses .X, otherwise uses the representation given by .layers[layer].


Set the radius of the point cloud. If you are generating a Gaussian distribution, then this is the standard deviation for each of x, y, and z.


Specify the number of points for the source object to hold. If n_points (number of the closest points to use) is set then radius value is ignored.


The kernel of interpolations kernel. Available kernels are: * shepard: vtkShepardKernel is an interpolations kernel that uses the method of Shepard to perform

interpolations. The weights are computed as 1/r^p, where r is the distance to a neighbor point within the kernel radius R; and p (the power parameter) is a positive exponent (typically p=2).

  • gaussian: vtkGaussianKernel is an interpolations kernel that simply returns the weights for all

    points found in the sphere defined by radius R. The weights are computed as: exp(-(s*r/R)^2) where r is the distance from the point to be interpolated to a neighboring point within R. The sharpness s simply affects the rate of fall off of the Gaussian.

  • linear: vtkLinearKernel is an interpolations kernel that averages the contributions of all points in

    the basis.


Specify a strategy to use when encountering a “null” point during the interpolations process.

Null points occur when the local neighborhood(of nearby points to interpolate from) is empty.

  • Case 0: an output array is created that marks points as being valid (=1) or null (invalid =0), and

    the nullValue is set as well

  • Case 1: the output data value(s) are set to the provided nullValue

  • Case 2: simply use the closest point to perform the interpolations.


see above.


an anndata object that has interpolated expression.

Return type: