fit(n_lineages=None, cluster_key=None, keys=None, method='krylov', compute_absorption_probabilities=True, **kwargs)¶
Run the pipeline, computing the macrostates, initial or terminal states and optionally the absorption probabilities.
It is equivalent to running:
if n_lineages is None or n_lineages == 1: compute_eigendecomposition(...) # get the stationary distribution if n_lineages > 1: compute_schur(...) compute_macrostates(...) if n_lineages is None: compute_terminal_states(...) else: set_terminal_states_from_macrostates(...) if compute_absorption_probabilities: compute_absorption_probabilities(...)
str]]) – Determines which initial or terminaltates to use by passing their names. Further, initial or terminal states can be combined. If e.g. the terminal states are [‘Neuronal_1’, ‘Neuronal_1’, ‘Astrocytes’, ‘OPC’], then passing
keys=['Neuronal_1, Neuronal_2', 'OPC']means that the two neuronal terminal states are treated as one and the ‘Astrocyte’ state is excluded.
**kwargs¶ – Keyword arguments for
Nothing, just makes available the following fields:
- Return type