def sample(self, size, sess):
"""z ~ q(z | lambda)"""
a, b = sess.run([self.a, self.b])
z = np.zeros(size)
for d in range(self.num_vars):
z[:, d] = invgamma.rvs(a[d], b[d], size=size[0])
return z
def sample(self, size=1, sess=None):
"""z ~ q(z | lambda)"""
a, b = sess.run([self.a, self.b])
z = np.zeros((size, self.num_vars))
for d in range(self.num_vars):
z[:, d] = invgamma.rvs(a[d], b[d], size=size)
return z
def sample(self, size=1):
"""z ~ q(z | lambda)"""
sess = get_session()
a, b = sess.run([self.a, self.b])
z = np.zeros((size, self.num_vars))
for d in range(self.num_vars):
z[:, d] = invgamma.rvs(a[d], b[d], size=size)
return z
def sample(self, size=1):
"""x ~ p(x | params)"""
sess = get_session()
a, b = sess.run([self.alpha, self.beta])
x = np.zeros((size, self.num_vars))
for d in range(self.num_vars):
x[:, d] = invgamma.rvs(a[d], b[d], size=size)
return x
def sample(self, size=1):
sess = get_session()
a, b = sess.run([self.alpha, self.beta])
return invgamma.rvs(a, b, size=size)
def _test(self, a, scale, size):
val_est = invgamma.rvs(a, scale, size=size).shape
val_true = (size, ) + np.asarray(a).shape
assert val_est == val_true
def np_sample(a, scale):
# get `size` from lexical scoping
return invgamma.rvs(a, scale=scale, size=n).astype(np.float32)
def np_sample(a, scale):
# get ``n`` from lexical scoping
return invgamma.rvs(a, scale=scale, size=n).astype(np.float32)
def _test(self, a, scale, size): val_est = invgamma.rvs(a, scale, size=size).shape val_true = (size, ) + np.asarray(a).shape assert val_est == val_true
