# cellrank.tl.estimators.GPCCA.schur_vectors

property GPCCA.schur_vectors: Optional[numpy.ndarray]

Real Schur vectors of the transition matrix.

The real Schur decomposition is a generalization of the Eigendecomposition and can be computed for any real-valued, square matrix $$A$$. It is given by $$A = Q R Q^T$$, where $$Q$$ contains the real Schur vectors and $$R$$ is the Schur matrix. $$Q$$ is orthogonal and $$R$$ is quasi-upper triangular with 1x1 and 2x2 blocks on the diagonal. If PETSc and SLEPc are installed, only the leading Schur vectors are computed.

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