def __init__(self, vars, nObs, T, N, observed_jumps, model=None):
# DES Temp:
self.logp = []
self.nObs = nObs
self.T = T
self.N = N
self.zeroIndices = np.roll(self.T.cumsum(), 1)
self.zeroIndices[0] = 0
# self.max_obs = max_obs
model = modelcontext(model)
vars = inputvars(vars)
shared = make_shared_replacements(vars, model)
super(ForwardS, self).__init__(vars, shared)
self.observed_jumps = observed_jumps
step_sizes = np.sort(np.unique(observed_jumps))
self.step_sizes = step_sizes = step_sizes[step_sizes > 0]
pi = stick_breaking.backward(self.shared["pi_stickbreaking"])
lower = model.free_RVs[1].distribution.dist.lower
upper = model.free_RVs[1].distribution.dist.upper
Q = rate_matrix_one_way(lower, upper).backward(self.shared["Q_ratematrixoneway"])
B0 = logodds.backward(self.shared["B0_logodds"])
B = logodds.backward(self.shared["B_logodds"])
X = self.shared["X"]
# at this point parameters are still symbolic so we
# must create get_params function to actually evaluate them
self.get_params = evaluate_symbolic_shared(pi, Q, B0, B, X)
def test_rate_matrix_one_way():
check_matrix_transform_identity(ctrans.rate_matrix_one_way(0, 1),
RateMatrixDomain)
def test_rate_matrix_one_way(): check_matrix_transform_identity(ctrans.rate_matrix_one_way(0,1), RateMatrixDomain)
