New integrator, and add some metadata to integrators.py

.gitignore

@@ -1,8 +1,6 @@
 # Created by https://www.gitignore.io/api/python
 # Edit at https://www.gitignore.io/?templates=python
 
-explore.py
-
 ### Python ###
 # Byte-compiled / optimized / DLL files
 __pycache__/

blackjax/mcmc/integrators.py

@@ -24,12 +24,15 @@
 
 __all__ = [
     "mclachlan",
+    "omelyan",
     "velocity_verlet",
     "yoshida",
-    "implicit_midpoint",
-    "isokinetic_leapfrog",
+    "with_isokinetic_maruyama",
+    "isokinetic_velocity_verlet",
     "isokinetic_mclachlan",
+    "isokinetic_omelyan",
     "isokinetic_yoshida",
+    "implicit_midpoint",
 ]
 
 
@@ -70,7 +73,7 @@ def generalized_two_stage_integrator(
 
     .. math:: \\frac{d}{dt}f = (O_1+O_2)f
 
-    The leapfrog operator can be seen as approximating :math:`e^{\\epsilon(O_1 + O_2)}`
+    The velocity_verlet operator can be seen as approximating :math:`e^{\\epsilon(O_1 + O_2)}`
     by :math:`e^{\\epsilon O_1/2}e^{\\epsilon O_2}e^{\\epsilon O_1/2}`.
 
     In a standard Hamiltonian, the forms of :math:`e^{\\epsilon O_2}` and
@@ -210,7 +213,7 @@ def format_euclidean_state_output(
     return IntegratorState(position, momentum, logdensity, logdensity_grad)
 
 
-def generate_euclidean_integrator(cofficients):
+def generate_euclidean_integrator(coefficients):
     """Generate symplectic integrator for solving a Hamiltonian system.
 
     The resulting integrator is volume-preserve and preserves the symplectic structure
@@ -225,7 +228,7 @@ def euclidean_integrator(
         one_step = generalized_two_stage_integrator(
             momentum_update_fn,
             position_update_fn,
-            cofficients,
+            coefficients,
             format_output_fn=format_euclidean_state_output,
         )
         return one_step
@@ -251,8 +254,8 @@ def euclidean_integrator(
 of the kinetic energy. We are trading accuracy in exchange, and it is not
 clear whether this is the right tradeoff.
 """
-velocity_verlet_cofficients = [0.5, 1.0, 0.5]
-velocity_verlet = generate_euclidean_integrator(velocity_verlet_cofficients)
+velocity_verlet_coefficients = [0.5, 1.0, 0.5]
+velocity_verlet = generate_euclidean_integrator(velocity_verlet_coefficients)
 
 """
 Two-stage palindromic symplectic integrator derived in :cite:p:`blanes2014numerical`.
@@ -268,8 +271,8 @@ def euclidean_integrator(
 b1 = 0.1931833275037836
 a1 = 0.5
 b2 = 1 - 2 * b1
-mclachlan_cofficients = [b1, a1, b2, a1, b1]
-mclachlan = generate_euclidean_integrator(mclachlan_cofficients)
+mclachlan_coefficients = [b1, a1, b2, a1, b1]
+mclachlan = generate_euclidean_integrator(mclachlan_coefficients)
 
 """
 Three stages palindromic symplectic integrator derived in :cite:p:`mclachlan1995numerical`
@@ -284,8 +287,20 @@ def euclidean_integrator(
 a1 = 0.29619504261126
 b2 = 0.5 - b1
 a2 = 1 - 2 * a1
-yoshida_cofficients = [b1, a1, b2, a2, b2, a1, b1]
-yoshida = generate_euclidean_integrator(yoshida_cofficients)
+yoshida_coefficients = [b1, a1, b2, a2, b2, a1, b1]
+yoshida = generate_euclidean_integrator(yoshida_coefficients)
+
+"""11 stage Omelyan integrator [I.P. Omelyan, I.M. Mryglod and R. Folk, Comput. Phys. Commun. 151 (2003) 272.],
+4MN5FV in [Takaishi, Tetsuya, and Philippe De Forcrand. "Testing and tuning symplectic integrators for the hybrid Monte Carlo algorithm in lattice QCD." Physical Review E 73.3 (2006): 036706.]
+popular in LQCD"""
+b1 = 0.08398315262876693
+a1 = 0.2539785108410595
+b2 = 0.6822365335719091
+a2 = -0.03230286765269967
+b3 = 0.5 - b1 - b2
+a3 = 1 - 2 * (a1 + a2)
+omelyan_coefficients = [b1, a1, b2, a2, b3, a3, b3, a2, b2, a1, b1]
+omelyan = generate_euclidean_integrator(omelyan_coefficients)
 
 
 # Intergrators with non Euclidean updates
@@ -372,9 +387,12 @@ def isokinetic_integrator(
     return isokinetic_integrator
 
 
-isokinetic_leapfrog = generate_isokinetic_integrator(velocity_verlet_cofficients)
-isokinetic_yoshida = generate_isokinetic_integrator(yoshida_cofficients)
-isokinetic_mclachlan = generate_isokinetic_integrator(mclachlan_cofficients)
+isokinetic_velocity_verlet = generate_isokinetic_integrator(
+    velocity_verlet_coefficients
+)
+isokinetic_yoshida = generate_isokinetic_integrator(yoshida_coefficients)
+isokinetic_mclachlan = generate_isokinetic_integrator(mclachlan_coefficients)
+isokinetic_omelyan = generate_isokinetic_integrator(omelyan_coefficients)
 
 
 def partially_refresh_momentum(momentum, rng_key, step_size, L):

blackjax/mcmc/trajectory.py

@@ -357,7 +357,7 @@ def buildtree_integrate(
 
         """
         if tree_depth == 0:
-            # Base case - take one leapfrog step in the direction v.
+            # Base case - take one velocity_verlet step in the direction v.
             next_state = integrator(initial_state, direction * step_size)
             new_proposal = generate_proposal(initial_energy, next_state)
             is_diverging = -new_proposal.weight > divergence_threshold

tests/mcmc/test_integrators.py

@@ -136,13 +136,15 @@ def kinetic_energy(p, position=None):
     "velocity_verlet": {"algorithm": integrators.velocity_verlet, "precision": 1e-4},
     "mclachlan": {"algorithm": integrators.mclachlan, "precision": 1e-4},
     "yoshida": {"algorithm": integrators.yoshida, "precision": 1e-4},
+    "omelyan": {"algorithm": integrators.omelyan, "precision": 1e-4},
     "implicit_midpoint": {
         "algorithm": integrators.implicit_midpoint,
         "precision": 1e-4,
     },
-    "isokinetic_leapfrog": {"algorithm": integrators.isokinetic_leapfrog},
+    "isokinetic_velocity_verlet": {"algorithm": integrators.isokinetic_velocity_verlet},
     "isokinetic_mclachlan": {"algorithm": integrators.isokinetic_mclachlan},
     "isokinetic_yoshida": {"algorithm": integrators.isokinetic_yoshida},
+    "isokinetic_omelyan": {"algorithm": integrators.isokinetic_omelyan},
 }
 
 
@@ -168,6 +170,7 @@ class IntegratorTest(chex.TestCase):
                 "velocity_verlet",
                 "mclachlan",
                 "yoshida",
+                "omelyan",
                 "implicit_midpoint",
             ],
         )
@@ -241,13 +244,13 @@ def test_esh_momentum_update(self, dims):
         np.testing.assert_array_almost_equal(next_momentum, next_momentum1)
 
     @chex.all_variants(with_pmap=False)
-    def test_isokinetic_leapfrog(self):
+    def test_isokinetic_velocity_verlet(self):
         cov = jnp.asarray([[1.0, 0.5, 0.1], [0.5, 2.0, -0.1], [0.1, -0.1, 3.0]])
         logdensity_fn = lambda x: stats.multivariate_normal.logpdf(
             x, jnp.zeros([3]), cov
         )
 
-        step = self.variant(integrators.isokinetic_leapfrog(logdensity_fn))
+        step = self.variant(integrators.isokinetic_velocity_verlet(logdensity_fn))
 
         rng = jax.random.key(4263456)
         key0, key1 = jax.random.split(rng, 2)
@@ -296,9 +299,10 @@ def test_isokinetic_leapfrog(self):
     @chex.all_variants(with_pmap=False)
     @parameterized.parameters(
         [
-            "isokinetic_leapfrog",
+            "isokinetic_velocity_verlet",
             "isokinetic_mclachlan",
             "isokinetic_yoshida",
+            "isokinetic_omelyan",
         ],
     )
     def test_isokinetic_integrator(self, integrator_name):