cellrank.tl.kernels.PrecomputedKernel

class cellrank.tl.kernels.PrecomputedKernel(transition_matrix=None, adata=None, backward=False, compute_cond_num=False)[source]

Kernel which contains a precomputed transition matrix.

Parameters
  • transition_matrix (Union[ndarray, spmatrix, KernelExpression, str, None]) – Row-normalized transition matrix or a key in adata .obsp or a cellrank.tl.kernels.KernelExpression with the computed transition matrix. If None, try to determine the key based on backward.

  • adata (anndata.AnnData) – Annotated data object.

  • backward (bool) – Direction of the process.

  • compute_cond_num (bool) – Whether to compute condition number of the transition matrix. Note that this might be costly, since it does not use sparse implementation.

Attributes

adata

Annotated data object.

backward

Direction of the process.

condition_number

Condition number of the transition matrix.

kernels

Get the kernels of the kernel expression, except for constants.

params

Parameters which are used to compute the transition matrix.

transition_matrix

Return row-normalized transition matrix.

Methods

compute_projection([basis, key_added, copy])

Compute a projection of the transition matrix in the embedding.

compute_transition_matrix(*args, **kwargs)

Return self.

copy()

Return a copy of self.

plot_random_walks(n_sims[, max_iter, seed, …])

Plot random walks in an embedding.

read(fname)

Deserialize self from a file.

write(fname[, ext])

Serialize self to a file.

write_to_adata([key])

Write the transition matrix and parameters used for computation to the underlying adata object.