compute_steady_state

ludics.main.compute_steady_state(transition_matrix, tolerance=10**-6, initial_dist=None)

Approximates the steady state of a Markov chain with a numeric transition matrix by iterating through state distributions

Parameters:

  • transition_matrix: numpy.array - a square matrix of numeric transition probabilities
  • tolerance: float - how close a state distribution must be to the previous distribution to be accepted
  • initial_dist: numpy.array - the first state distribution to be considered

Returns:

  • numpy.array - the steady state of the Markov chain