def testCalcPacc(self):
istate = State(np.array([1.0, 2.0]), np.array([2.0, 1.0]))
fstate = State(np.array([1.0, 2.0]) * 2.0, np.array([2.0, 1.0]) * 2.0)
pcom_fstate = fstate.clone()
pcom = SimpleProposalCommunicator(istate.clone(), pcom_fstate)
self._sampler.state.momentum = None
pacc = self._sampler._calc_pacc(pcom)
dH = self._sampler._hamiltonian(fstate) - self._sampler._hamiltonian(
istate)
assert (csb.numeric.exp(-dH / self._sampler.temperature) == pacc)
assert (pcom_fstate.momentum == None)
pcom_fstate = fstate.clone()
pcom = SimpleProposalCommunicator(istate.clone(), pcom_fstate)
self._sampler.state.momentum = np.array([1.0, 4.0])
pacc = self._sampler._calc_pacc(pcom)
dH = self._sampler._hamiltonian(fstate) - self._sampler._hamiltonian(
istate)
assert (csb.numeric.exp(-dH / self._sampler.temperature) == pacc)
assert (np.all(pcom_fstate.momentum == np.array([1.0, 4.0])))
def testCalcPacc(self):
istate = State(np.array([1.0, 2.0]), np.array([2.0, 1.0]))
fstate = State(np.array([1.0, 2.0]) * 2.0, np.array([2.0, 1.0]) * 2.0)
pcom_fstate = fstate.clone()
pcom = SimpleProposalCommunicator(istate.clone(), pcom_fstate)
self._sampler.state.momentum = None
pacc = self._sampler._calc_pacc(pcom)
dH = self._sampler._hamiltonian(fstate) - self._sampler._hamiltonian(istate)
assert(csb.numeric.exp(-dH / self._sampler.temperature) == pacc)
assert(pcom_fstate.momentum == None)
pcom_fstate = fstate.clone()
pcom = SimpleProposalCommunicator(istate.clone(), pcom_fstate)
self._sampler.state.momentum = np.array([1.0, 4.0])
pacc = self._sampler._calc_pacc(pcom)
dH = self._sampler._hamiltonian(fstate) - self._sampler._hamiltonian(istate)
assert(csb.numeric.exp(-dH / self._sampler.temperature) == pacc)
assert(np.all(pcom_fstate.momentum == np.array([1.0, 4.0])))
class TestHMCSampler(test.Case):
def setUp(self):
self._mass_matrix = InvertibleMatrix(np.array([[2.0, 0.0], [1.0, 3.0]]))
self._initstate = State(np.array([1.0, 2.0]))
self._sampler = MockedHMCSampler(pdf=SamplePDF(), state=self._initstate.clone(),
gradient=SamplePDF().grad,
timestep=0.3, nsteps=25, mass_matrix=self._mass_matrix)
def testPropose(self):
np.random.seed(5)
initmom = np.random.multivariate_normal(mean=np.zeros(len(self._initstate.position)),
cov=self._mass_matrix)
self._sampler.state = self._initstate.clone()
np.random.seed(5)
res = self._sampler._propose()
assert(np.all(res.current_state.position == self._initstate.position))
assert(np.all(res.current_state.momentum == initmom))
assert(np.all(res.proposal_state.position == self._initstate.position * 2.0))
assert(np.all(res.proposal_state.momentum == initmom * 2))
def testHamiltonian(self):
state = State(np.array([1.0, 2.0]), np.array([2.0, 1.0]))
assert(self._sampler._hamiltonian(state) == 3.5 - np.log(1.0 / (2.0 * np.pi)))
def testCalcPacc(self):
istate = State(np.array([1.0, 2.0]), np.array([2.0, 1.0]))
fstate = State(np.array([1.0, 2.0]) * 2.0, np.array([2.0, 1.0]) * 2.0)
pcom_fstate = fstate.clone()
pcom = SimpleProposalCommunicator(istate.clone(), pcom_fstate)
self._sampler.state.momentum = None
pacc = self._sampler._calc_pacc(pcom)
dH = self._sampler._hamiltonian(fstate) - self._sampler._hamiltonian(istate)
assert(csb.numeric.exp(-dH / self._sampler.temperature) == pacc)
assert(pcom_fstate.momentum == None)
pcom_fstate = fstate.clone()
pcom = SimpleProposalCommunicator(istate.clone(), pcom_fstate)
self._sampler.state.momentum = np.array([1.0, 4.0])
pacc = self._sampler._calc_pacc(pcom)
dH = self._sampler._hamiltonian(fstate) - self._sampler._hamiltonian(istate)
assert(csb.numeric.exp(-dH / self._sampler.temperature) == pacc)
assert(np.all(pcom_fstate.momentum == np.array([1.0, 4.0])))
class TestHMCSampler(test.Case):
def setUp(self):
self._mass_matrix = InvertibleMatrix(np.array([[2.0, 0.0], [1.0,
3.0]]))
self._initstate = State(np.array([1.0, 2.0]))
self._sampler = MockedHMCSampler(pdf=SamplePDF(),
state=self._initstate.clone(),
gradient=SamplePDF().grad,
timestep=0.3,
nsteps=25,
mass_matrix=self._mass_matrix)
def testPropose(self):
np.random.seed(5)
initmom = np.random.multivariate_normal(mean=np.zeros(
len(self._initstate.position)),
cov=self._mass_matrix)
self._sampler.state = self._initstate.clone()
np.random.seed(5)
res = self._sampler._propose()
assert (np.all(res.current_state.position == self._initstate.position))
assert (np.all(res.current_state.momentum == initmom))
assert (np.all(
res.proposal_state.position == self._initstate.position * 2.0))
assert (np.all(res.proposal_state.momentum == initmom * 2))
def testHamiltonian(self):
state = State(np.array([1.0, 2.0]), np.array([2.0, 1.0]))
assert (self._sampler._hamiltonian(state) == 3.5 -
np.log(1.0 / (2.0 * np.pi)))
def testCalcPacc(self):
istate = State(np.array([1.0, 2.0]), np.array([2.0, 1.0]))
fstate = State(np.array([1.0, 2.0]) * 2.0, np.array([2.0, 1.0]) * 2.0)
pcom_fstate = fstate.clone()
pcom = SimpleProposalCommunicator(istate.clone(), pcom_fstate)
self._sampler.state.momentum = None
pacc = self._sampler._calc_pacc(pcom)
dH = self._sampler._hamiltonian(fstate) - self._sampler._hamiltonian(
istate)
assert (csb.numeric.exp(-dH / self._sampler.temperature) == pacc)
assert (pcom_fstate.momentum == None)
pcom_fstate = fstate.clone()
pcom = SimpleProposalCommunicator(istate.clone(), pcom_fstate)
self._sampler.state.momentum = np.array([1.0, 4.0])
pacc = self._sampler._calc_pacc(pcom)
dH = self._sampler._hamiltonian(fstate) - self._sampler._hamiltonian(
istate)
assert (csb.numeric.exp(-dH / self._sampler.temperature) == pacc)
assert (np.all(pcom_fstate.momentum == np.array([1.0, 4.0])))
