scanpy.Neighbors.compute_eigen
- Neighbors.compute_eigen(n_comps=15, sym=None, sort='decrease', random_state=0)
Compute eigen decomposition of transition matrix.
- Parameters
- n_comps :
int(default:15) Number of eigenvalues/vectors to be computed, set
n_comps = 0if you need all eigenvectors.- sym :
Optional[bool] (default:None) Instead of computing the eigendecomposition of the assymetric transition matrix, computed the eigendecomposition of the symmetric Ktilde matrix.
- random_state :
Union[None,int,RandomState] (default:0) A numpy random seed
- n_comps :
- Returns
Writes the following attributes.
- eigen_values
ndarray Eigenvalues of transition matrix.
- eigen_basis
ndarray Matrix of eigenvectors (stored in columns).
.eigen_basisis projection of data matrix on right eigenvectors, that is, the projection on the diffusion components. these are simply the components of the right eigenvectors and can directly be used for plotting.
- eigen_values