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)