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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def poisson_consensus_se(data, k, n_runs=10, **se_params):
 """ Initializes Poisson State Estimation using a consensus Poisson clustering. """

    clusters = []
    for i in range(n_runs):
        assignments, means  = poisson_cluster(data, k)
        clusters.append(assignments)
    clusterings = np.vstack(clusters)
    consensus = CE.cluster_ensembles(clusterings, verbose=False, N_clusters_max=k)
    init_m, init_w = nmf_init(data, consensus, k, 'basic')
    M, W, ll = poisson_estimate_state(data, k, init_means=init_m, init_weights=init_w, **se_params)
    return M, W, ll