def __init__(self, full_target, current_state, schedule="in_turns", index_block=None): if not isinstance(full_target, Gaussian): raise TypeError("Given full Gaussian is not a Gaussian") FullConditionals.__init__(self, full_target, current_state, schedule, index_block) # precompute full covariance matrix for slicing later self.full_Sigma = full_target.L.dot(full_target.L.T)
def __init__(self, full_target, current_state, schedule="in_turns", index_block=None): if not isinstance(full_target, Hopfield): raise TypeError("Given full Hopfield is not a Hopfield") FullConditionals.__init__(self, full_target, current_state, schedule, index_block)
def __init__(self, full_target, current_state, schedule="in_turns", index_block=None): if not isinstance(full_target, Bernoulli): raise TypeError("Given full Bernoulli is not a Bernoulli") FullConditionals.__init__(self, full_target, current_state, schedule, index_block)