66d21e1fcd43323289840ce83e4193e6b9957d0c,pymc3/sampling.py,,sample_ppc_w,#Any#Any#Any#Any#Any#Any#,696

Before Change

    // ensure n sum up to min_tr
    idx = np.argmax(n)
    n[idx] = n[idx] + min_tr - np.sum(n)
    trace = np.concatenate([np.random.choice(traces[i], j)
                            for i, j in enumerate(n)])

    obs = [x for m in models for x in m.observed_RVs]
    variables = np.repeat(obs, n)

After Change

    // ensure n sum up to min_tr
    idx = np.argmax(n)
    n[idx] = n[idx] + min_tr - np.sum(n)
    trace = []
    for i, j in enumerate(n):
        tr = traces[i]
        len_trace = len(tr) 
        nchain = tr.nchains 
        indices = np.random.randint(0, nchain*len_trace, j)
        chain_idx, point_idx = np.divmod(indices, len_trace)
        for idx in zip(chain_idx, point_idx): 
            trace.append(tr._straces[idx[0]].point(idx[1]))

    obs = [x for m in models for x in m.observed_RVs]
    variables = np.repeat(obs, n)

    lenghts = list(set([np.shape(np.atleast_1d(o.distribution.default())) for o in obs]))

Instances