gistfile1.txt

X = predicted position 
Z = true position
lds = our learned lds on [X, Z]

# Get marginal LDS
marginal_lds = marginal(lds, (7, 8, 9, 10, 11, 12, 13)) # 

# Compile a function to calculate hidden state given position predictions.
f = marginal_lds.function(['inpt'], ['filtered_means'])

# Calculate hidden means
h = f(Z)

# Infer true positions from hiddens.
hidden_to_pos = lds.parameters['emission'][:, (0, 1, 2, 3, 4, 5, 6)]
p = np.dot(h, hidden_to_pos)

# plot p and Z.