Marginals in BirdFlow models are stored such that the cell [i, j] represents the probability of the bird being in state i in the prior timestep and state j in the next. Thus the number of rows in the marginal equals the number of cells within the dynamic mask for the prior timestep and the columns count is equal to the included cells for the following timestep.
See also
lookup_transitions()
will generate a list of the transitions
needed to predict or route between two points in time. get_transition()
will return a transition matrix - often calculated on the fly from a
marginal.