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Make MALA allow repeated ask() #994

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Make MALA allow repeated ask() #994

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6dd4b7b
Made MALA allow repeated ask
MichaelClerx Oct 8, 2019
c211e33
Updated test for MALA
MichaelClerx Oct 8, 2019
e554211
Merge branch 'master' into mala-repeated-ask
MichaelClerx Feb 8, 2021
17feb6e
Update _mala.py
MichaelClerx Feb 8, 2021
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4 changes: 1 addition & 3 deletions pints/_mcmc/_mala.py
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Original file line number Diff line number Diff line change
Expand Up @@ -84,7 +84,6 @@ def __init__(self, x0, sigma0=None):

# Set initial state
self._running = False
self._ready_for_tell = False

# Current point and proposed point
self._current = None
Expand Down Expand Up @@ -225,9 +224,8 @@ def tell(self, reply):
""" See :meth:`pints.SingleChainMCMC.tell()`. """

# Check if we had a proposal
if not self._ready_for_tell:
if self._proposed is None:
raise RuntimeError('Tell called before proposal was set.')
self._ready_for_tell = False

Comment on lines -228 to 229
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@ben18785 ben18785 Oct 8, 2019

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Sorry, probably not getting something but don't quite get why we'd remove these checks.

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@MichaelClerx MichaelClerx Oct 8, 2019

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It's more in line with what we have in the other MCMC methods, with the exception of the ones that do more complicated stuff in ask() than just set a proposal.

So no very strong reason! Just that it's possible to let users ask() as often as they like in this case (and always get the same result), and it lets us remove a variable...

We might want to disallow this everywhere instead though? In which case we'd have to update the documentation for SingleChainMCMC and MultiChainMCMC a bit to make this explicit...

# Unpack reply
fx, log_gradient = reply
Expand Down
61 changes: 37 additions & 24 deletions pints/tests/test_mcmc_mala.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,8 @@ class TestMALAMCMC(unittest.TestCase):
Tests the basic methods of the MALA MCMC routine.
"""

def test_method(self):
def test_short_run(self):
# Test a short run with MALA

# Create log pdf
log_pdf = pints.toy.GaussianLogPDF([5, 5], [[4, 1], [1, 3]])
Expand All @@ -30,9 +31,6 @@ def test_method(self):
sigma = [[3, 0], [0, 3]]
mcmc = pints.MALAMCMC(x0, sigma)

# This method needs sensitivities
self.assertTrue(mcmc.needs_sensitivities())

# Perform short run
chain = []
for i in range(100):
Expand All @@ -47,41 +45,49 @@ def test_method(self):
chain = np.array(chain)
self.assertEqual(chain.shape[0], 50)
self.assertEqual(chain.shape[1], len(x0))
self.assertTrue(mcmc.acceptance_rate() >= 0.0 and
mcmc.acceptance_rate() <= 1.0)
self.assertTrue(0 <= mcmc.acceptance_rate() <= 1.0)

def test_needs_sensitivities(self):
# This method needs sensitivities

mcmc._proposed = [1, 3]
self.assertRaises(RuntimeError, mcmc.tell, (fx, gr))
mcmc = pints.MALAMCMC(np.array([2, 2]))
self.assertTrue(mcmc.needs_sensitivities())

def test_logging(self):
# Test logging includes name and custom fields.

log_pdf = pints.toy.GaussianLogPDF([5, 5], [[4, 1], [1, 3]])
x0 = [np.array([2, 2]), np.array([8, 8])]

mcmc = pints.MCMCSampling(log_pdf, 2, x0, method=pints.MALAMCMC)
mcmc = pints.MCMCController(log_pdf, 2, x0, method=pints.MALAMCMC)
mcmc.set_max_iterations(5)
with StreamCapture() as c:
mcmc.run()
text = c.text()

self.assertIn('Metropolis-Adjusted Langevin Algorithm (MALA)',
text)
self.assertIn('Metropolis-Adjusted Langevin Algorithm (MALA)', text)
self.assertIn(' Accept.', text)

def test_flow(self):
# Test the ask-and-tell flow

log_pdf = pints.toy.GaussianLogPDF([5, 5], [[4, 1], [1, 3]])
x0 = np.array([2, 2])

# Test initial proposal is first point
mcmc = pints.MALAMCMC(x0)
self.assertTrue(np.all(mcmc.ask() == mcmc._x0))

# Repeated asks
self.assertRaises(RuntimeError, mcmc.ask)

# Tell without ask
self.assertTrue(np.all(mcmc.ask() == x0))

# Repeated asks return same point
self.assertTrue(np.all(mcmc.ask() == x0))
self.assertTrue(np.all(mcmc.ask() == x0))
self.assertTrue(np.all(mcmc.ask() == x0))
for i in range(5):
mcmc.tell(log_pdf.evaluateS1(mcmc.ask()))
x1 = mcmc.ask()
self.assertTrue(np.all(mcmc.ask() == x1))

# Tell without ask should fail
mcmc = pints.MALAMCMC(x0)
self.assertRaises(RuntimeError, mcmc.tell, 0)

Expand All @@ -101,8 +107,8 @@ def test_flow(self):
mcmc._running = True
self.assertRaises(RuntimeError, mcmc._initialise)

def test_set_hyper_parameters(self):
# Tests the parameter interface for this sampler.
def test_hyper_parameters(self):
# Tests the hyper parameter interface for this sampler.

x0 = np.array([2, 2])
mcmc = pints.MALAMCMC(x0)
Expand All @@ -113,17 +119,24 @@ def test_set_hyper_parameters(self):
self.assertTrue(np.array_equal(mcmc.epsilon(),
0.2 * np.diag(mcmc._sigma0)))

mcmc = pints.MALAMCMC(np.array([2, 2]))
self.assertEqual(mcmc.n_hyper_parameters(), 1)
mcmc.set_hyper_parameters([[3, 2]])
self.assertTrue(np.array_equal(mcmc.epsilon(), [3, 2]))
mcmc.set_hyper_parameters([[5, 5]])
self.assertTrue(np.array_equal(mcmc.epsilon(), [5, 5]))

mcmc._step_size = 5
mcmc._scale_vector = np.array([3, 7])
mcmc._epsilon = None
def test_epsilon(self):
# Test the epsilon methods

mcmc = pints.MALAMCMC(np.array([2, 2]), np.array([3, 3]))
mcmc.set_epsilon()
self.assertTrue(np.array_equal(mcmc.epsilon(), [15, 35]))
x = mcmc.epsilon()
self.assertAlmostEqual(x[0], 0.6)
self.assertAlmostEqual(x[1], 0.6)
mcmc.set_epsilon([0.4, 0.5])
self.assertTrue(np.array_equal(mcmc.epsilon(), [0.4, 0.5]))
self.assertTrue(np.all(mcmc.epsilon() == [0.4, 0.5]))

self.assertRaises(ValueError, mcmc.set_epsilon, 3.0)
self.assertRaises(ValueError, mcmc.set_epsilon, [-2.0, 1])

Expand Down