Python integration_matrix Beispiele

Beispiel #1

Datei: initialization.py Projekt: stjordanis/NGSI

def init_row_chain(data_matrix, num_iter=200):
    states, sigma_sq_D, sigma_sq_N = chains.fit_model(data_matrix, num_iter=num_iter)

    integ = chains.integration_matrix(data_matrix.m_orig)[data_matrix.row_ids, :]
    left = recursive.IntegrationNode(integ)
    
    temp = np.vstack([states[0, :][nax, :],
                      states[1:, :] - states[:-1, :]])
    right = recursive.GaussianNode(temp, 'scalar', sigma_sq_D)

    pred = states[data_matrix.row_ids, :]
    X = data_matrix.sample_latent_values(pred, sigma_sq_N)
    noise = recursive.GaussianNode(X - pred, 'scalar', sigma_sq_N)

    return recursive.SumNode([recursive.ProductNode([left, right]), noise])

Beispiel #2

Datei: initialization.py Projekt: alexjekell/compositional_structure_search

def init_row_chain(data_matrix, num_iter=200):
    states, sigma_sq_D, sigma_sq_N = chains.fit_model(data_matrix, num_iter=num_iter)

    integ = chains.integration_matrix(data_matrix.m_orig)[data_matrix.row_ids, :]
    left = recursive.IntegrationNode(integ)
    
    temp = np.vstack([states[0, :][nax, :],
                      states[1:, :] - states[:-1, :]])
    right = recursive.GaussianNode(temp, 'scalar', sigma_sq_D)

    pred = states[data_matrix.row_ids, :]
    X = data_matrix.sample_latent_values(pred, sigma_sq_N)
    noise = recursive.GaussianNode(X - pred, 'scalar', sigma_sq_N)

    return recursive.SumNode([recursive.ProductNode([left, right]), noise])

Beispiel #3

Datei: recursive.py Projekt: pandasasa/compositional_structure_search

 def dummy():
     return IntegrationTNode(chains.integration_matrix(5).T)