def sample_data(hp, ss):
post = _sample_post(hp, ss)
index = discrete_draw(post)
if index == len(hp.betas):
return OTHER
else:
return index
def sample_data(hp, ss):
post = _sample_post(hp, ss)
index = discrete_draw(post)
if index == len(hp.betas):
return OTHER
else:
return index
def sample_data(pm, N):
if N == 1:
return np.array([discrete_draw(pm['p']) for _ in range(N)])
else:
a = np.array(pm['p'])
a = a / np.sum(a)
zs = np.cumsum(a)
a = np.random.rand(N)
zs[-1] = 1.1 # sentinal
q = np.searchsorted(zs, a)
return q
def sample_data(pm, N):
if N == 1:
return np.array([discrete_draw(pm['p']) for _ in range(N)])
else:
a = np.array(pm['p'])
a = a / np.sum(a)
zs = np.cumsum(a)
a = np.random.rand(N)
zs[-1] = 1.1 # sentinal
q = np.searchsorted(zs, a)
return q
def sample_data(hp, ss):
return discrete_draw(sample_post(hp, ss))
