cellrank.tl.estimators.CFLARE.compute_eigendecomposition
- CFLARE.compute_eigendecomposition(k=20, which='LR', alpha=1.0, only_evals=False, ncv=None)
Compute eigendecomposition of
transition_matrix
.Uses a sparse implementation, if possible, and only computes the top \(k\) eigenvectors to speed up the computation. Computes both left and right eigenvectors.
- Parameters
k (
int
) – Number of eigenvectors or eigenvalues to compute.which (
Literal
[‘LR’, ‘LM’]) –How to sort the eigenvalues. Valid option are:
’LR’ - the largest real part.
’LM’ - the largest magnitude.
alpha (
float
) – Used to compute the eigengap.alpha
is the weight given to the deviation of an eigenvalue from one.only_evals (
bool
) – Whether to compute only eigenvalues.
- Return type
- Returns
Nothing, just updates the following field:
eigendecomposition
- Eigendecomposition oftransition_matrix
.