def test_ask_tell_flow(self):
# Tests the ask-and-tell pattern
# Create problem
x0 = np.array([2, 4])
log_pdf = pints.toy.GaussianLogPDF([2, 4], [[1, 0], [0, 3]])
# Ask must return initial point
mcmc = pints.SliceDoublingMCMC(x0)
self.assertTrue(np.all(mcmc.ask() == x0))
# Ask can't be called twice
self.assertRaises(RuntimeError, mcmc.ask)
# Tell
fx = log_pdf(x0)
x1 = mcmc.tell(fx)
self.assertTrue(np.all(x0 == x1))
self.assertTrue(mcmc.current_log_pdf() == fx)
# Check that the new slice has been constructed appropriately
self.assertTrue(mcmc.current_slice_height() < mcmc.current_log_pdf())
# Can't tell twice
self.assertRaises(RuntimeError, mcmc.tell, log_pdf(x0))
# First point must be finite
mcmc = pints.SliceDoublingMCMC(x0)
mcmc.ask()
self.assertRaises(ValueError, mcmc.tell, np.inf)
def test_run(self):
# Test a short run
# Create log pdf
log_pdf = pints.toy.MultimodalGaussianLogPDF(
modes=[[1, 1], [1, 4], [5, 4], [1, 4]])
# Create mcmc
mcmc = pints.SliceDoublingMCMC(np.array([1, 2]))
mcmc.set_width(2)
# Run a few iterations of the sampler
# But enough to hit all branches...
np.random.seed(123)
n = 42
chain = []
while len(chain) < n:
x = mcmc.ask()
fx = log_pdf(x)
reply = mcmc.tell(fx)
if reply is not None:
y, fy, ac = reply
chain.append(y)
self.assertTrue(np.all(x == y))
self.assertTrue(np.all(fx == fy))
self.assertEqual(np.shape(chain), (n, 2))
def test_hyper_parameters(self):
# Test the hyper parameter interface
mcmc = pints.SliceDoublingMCMC(np.array([1, 2]))
self.assertEqual(mcmc.n_hyper_parameters(), 2)
mcmc.set_hyper_parameters([3, 100])
self.assertTrue((np.all(mcmc.width() == np.array([3, 3]))))
self.assertEqual(mcmc.expansion_steps(), 100)
def test_expansion(self):
# Test expansion step methods
mcmc = pints.SliceDoublingMCMC(np.array([1, 2]))
mcmc.set_expansion_steps(3)
self.assertEqual(mcmc.expansion_steps(), 3.)
with self.assertRaises(ValueError):
mcmc.set_expansion_steps(-1)
def test_first_run(self):
# Tests the very first run of the sampler.
# Create log pdf
log_pdf = pints.toy.GaussianLogPDF([2, 4], [[1, 0], [0, 3]])
# Create mcmc
x0 = np.array([2., 4.])
mcmc = pints.SliceDoublingMCMC(x0)
# Ask should fail if _ready_for_tell flag is True
x = mcmc.ask()
with self.assertRaises(RuntimeError):
mcmc.ask()
# Check whether _running flag becomes True when ask() is called
# Check whether first iteration of ask() returns x0
self.assertTrue(np.all(x == x0))
self.assertTrue(mcmc._running)
self.assertTrue(mcmc._ready_for_tell)
# Calculate log pdf for x0
fx = log_pdf.evaluateS1(x0)[0]
# Test first iteration of tell(). The first point in the chain
# should be x0
sample = mcmc.tell(fx)
self.assertTrue(np.all(sample == x0))
# We update the _current_log_pdf value used to generate the new slice
self.assertEqual(mcmc.current_log_pdf(), fx)
# Check that the new slice has been constructed appropriately
self.assertTrue(mcmc.current_slice_height() < mcmc.current_log_pdf())
# Tell() should fail when fx is infinite
mcmc = pints.SliceDoublingMCMC(x0)
mcmc.ask()
with self.assertRaises(ValueError):
fx = np.inf
mcmc.tell(fx)
# Tell() should fail when _ready_for_tell is False
with self.assertRaises(RuntimeError):
mcmc.tell(fx)
def test_width(self):
# Test width methods
mcmc = pints.SliceDoublingMCMC(np.array([1, 2]))
# Test set_width(), width()
mcmc.set_width(2)
self.assertTrue(np.all(mcmc.width() == np.array([2, 2])))
mcmc.set_width([5, 8])
self.assertTrue(np.all(mcmc.width() == np.array([5, 8])))
with self.assertRaises(ValueError):
mcmc.set_width(-1)
with self.assertRaises(ValueError):
mcmc.set_width([3, 3, 3, 3])
def test_multimodal_run(self):
# Create log pdf
log_pdf = pints.toy.MultimodalGaussianLogPDF(
modes=[[1, 1], [1, 4], [5, 4], [1, 4]])
# Create mcmc
x0 = np.array([1, 1])
mcmc = pints.SliceDoublingMCMC(x0)
mcmc.set_width(2)
# Run multiple iterations of the sampler
chain = []
while len(chain) < 200:
x = mcmc.ask()
fx = log_pdf.evaluateS1(x)[0]
sample = mcmc.tell(fx)
if sample is not None:
chain.append(np.copy(sample))
self.assertEqual(np.shape(chain), (200, 2))
def test_run(self):
# Test a short run
# Create log pdf
log_pdf = pints.toy.MultimodalGaussianLogPDF(
modes=[[1, 1], [1, 4], [5, 4], [1, 4]])
# Create mcmc
mcmc = pints.SliceDoublingMCMC(np.array([1, 2]))
mcmc.set_width(2)
# Run a few iterations of the sampler
# But enough to hit all branches...
np.random.seed(123)
n = 42
chain = []
while len(chain) < n:
sample = mcmc.tell(log_pdf(mcmc.ask()))
if sample is not None:
chain.append(np.copy(sample))
self.assertEqual(np.shape(chain), (n, 2))
def test_basic(self):
# Test basic methods of the class.
# Create mcmc
x0 = np.array([1, 1])
mcmc = pints.SliceDoublingMCMC(x0)
# Test name
self.assertEqual(mcmc.name(), 'Slice Sampling - Doubling')
# Test set_width(), width()
mcmc.set_width(2)
self.assertTrue(np.all(mcmc.width() == np.array([2, 2])))
mcmc.set_width([5, 8])
self.assertTrue(np.all(mcmc.width() == np.array([5, 8])))
with self.assertRaises(ValueError):
mcmc.set_width(-1)
with self.assertRaises(ValueError):
mcmc.set_width([3, 3, 3, 3])
# Test set_expansion_steps(), expansion_steps()
mcmc.set_expansion_steps(3)
self.assertEqual(mcmc.expansion_steps(), 3.)
with self.assertRaises(ValueError):
mcmc.set_expansion_steps(-1)
# Test current_slice height
self.assertEqual(mcmc.current_slice_height(), mcmc._current_log_y)
# Test number of hyperparameters
self.assertEqual(mcmc.n_hyper_parameters(), 2)
# Test setting hyperparameters
mcmc.set_hyper_parameters([3, 100])
self.assertTrue((np.all(mcmc.width() == np.array([3, 3]))))
self.assertEqual(mcmc.expansion_steps(), 100)
def test_name(self):
# Tests the sampler's name
mcmc = pints.SliceDoublingMCMC(np.array([1, 2]))
self.assertEqual(mcmc.name(), 'Slice Sampling - Doubling')