Pm.sample_ppc breaks with AttributeError

Questions
10

ok @junpenglao

I tried that however, it throws the distribution off:

# with x2model:
#     x2ppc = pm.sample_ppc(x2trace, 1000)
# A direct sample_ppc is not possible, so we have this contraption from
# @junpenglao at pymc_devs

from scipy.stats import poisson
wpost = x2trace['w']
mupost = x2trace['mu']
ndraws = wpost.shape[0]
nppc = 100
x2ppc = np.zeros((nppc, len(x2obs)))
for n in range(nppc):
    idx = np.random.randint(ndraws)
    pchoice = np.random.choice(K, len(x2obs), p=wpost[idx, :]/wpost[idx, :].sum())
#     mupost[mupost<=1] = 1
#     mupost[mupost>=70] = 70
    x2ppc[n, :] = poisson.rvs(mupost[idx, :, :])[range(len(x2obs)), pchoice]
x2ppc[x2ppc<1] = 1
x2ppc[x2ppc>70] = 70


sns.distplot(np.reshape(sp.stats.mode(x2ppc, axis=0), (-1, 1)), label='mode')
sns.distplot(np.reshape(np.mean(x2ppc, axis=0), (-1, 1)), label='mean')
sns.distplot(df['x2'].values, label='x2')
plt.legend(loc=1)

image
True data labeled ‘x2’