helper.py 文件源码

def sample_gaussian_2d_train(mux, muy, sx, sy, corr, nodesPresent):
    o_mux, o_muy, o_sx, o_sy, o_corr = mux, muy, sx, sy, corr

    numNodes = mux.size()[0]

    next_x = torch.zeros(numNodes)
    next_y = torch.zeros(numNodes)
    for node in range(numNodes):
        if node not in nodesPresent:
            continue
        mean = [o_mux[node], o_muy[node]]

        cov = [[o_sx[node]*o_sx[node], o_corr[node]*o_sx[node]*o_sy[node]], [o_corr[node]*o_sx[node]*o_sy[node], o_sy[node]*o_sy[node]]]

        next_values = np.random.multivariate_normal(mean, cov, 1)
        next_x[node] = next_values[0][0]
        next_y[node] = next_values[0][1]

    return next_x, next_y