generalize CH from periodic

docs/notebooks/01-using-solvers.ipynb

@@ -128,7 +128,7 @@
    "source": [
     "## Assembling custom solvers\n",
     "\n",
-    "We can unwrap what is actually happening under the hood a bit more by manually assembling this solver based on the predefined problem definition, timestepper and solver framework. The `TimeDependentSolver` is a pre-defined class which initialises a scalar field and solves a time-dependent PDE (as opposed to a steady-state problem). This is done by combining a backend (`torch/jax`) with a timestepper class (e.g. `PseudoSpectralIMEX`) and a problem class which defines the numerical discretisation of the right-hand side of a PDE (e.g. `PeriodicCahnHilliard`)."
+    "We can unwrap what is actually happening under the hood a bit more by manually assembling this solver based on the predefined problem definition, timestepper and solver framework. The `TimeDependentSolver` is a pre-defined class which initialises a scalar field and solves a time-dependent PDE (as opposed to a steady-state problem). This is done by combining a backend (`torch/jax`) with a timestepper class (e.g. `PseudoSpectralIMEX`) and a problem class which defines the numerical discretisation of the right-hand side of a PDE (e.g. `CahnHilliard`)."
    ]
   },
   {
@@ -148,7 +148,7 @@
     }
    ],
    "source": [
-    "from evoxels.problem_definition import PeriodicCahnHilliard\n",
+    "from evoxels.problem_definition import CahnHilliard\n",
     "from evoxels.solvers import TimeDependentSolver\n",
     "from evoxels.timesteppers import PseudoSpectralIMEX\n",
     "\n",
@@ -160,7 +160,7 @@
     "        vf,      # VoxelFields object\n",
     "        'c2',    # Name of initial field\n",
     "        'torch', # Backend\n",
-    "        problem_cls = PeriodicCahnHilliard,   # Problem definition\n",
+    "        problem_cls = CahnHilliard,   # Problem definition\n",
     "        timestepper_cls = PseudoSpectralIMEX, # Timestepping scheme\n",
     "        device='cuda',\n",
     "    )\n",
@@ -244,7 +244,7 @@
     "\n",
     "solver = TimeDependentSolver(\n",
     "        vf, 'c3', 'torch', device='cuda',\n",
-    "        problem_cls = PeriodicCahnHilliard,\n",
+    "        problem_cls = CahnHilliard,\n",
     "        timestepper_cls = PseudoSpectralIMEX\n",
     "    )\n",
     "\n",
@@ -306,7 +306,7 @@
     "\n",
     "solver = TimeDependentSolver(\n",
     "        vf, 'c4', 'torch', device='cuda',\n",
-    "        problem_cls = PeriodicCahnHilliard,\n",
+    "        problem_cls = CahnHilliard,\n",
     "        timestepper_cls = ForwardEuler\n",
     "    )\n",
     "\n",

docs/notebooks/04-parameter-estimation.ipynb

@@ -62,7 +62,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We create an `InversionModel` for the ``PeriodicCahnHilliard`` problem which sets up the voxel grid and the parameters of the PDE."
+    "We create an `InversionModel` for the ``CahnHilliard`` problem which sets up the voxel grid and the parameters of the PDE."
    ]
   },
   {
@@ -71,10 +71,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from evoxels.problem_definition import PeriodicCahnHilliard\n",
+    "from evoxels.problem_definition import CahnHilliard\n",
     "fixed_problem_kwargs={\"mu_hom\": None}\n",
     "pos_params = [\"D\", \"eps\"]\n",
-    "model = evo.InversionModel(vf, PeriodicCahnHilliard, pos_params, fixed_problem_kwargs)"
+    "model = evo.InversionModel(vf, CahnHilliard, pos_params, fixed_problem_kwargs)"
    ]
   },
   {

evoxels/boundary_conditions.py

@@ -46,11 +46,11 @@ def pad_fft_periodic(self, field):
 
     def pad_fft_dirichlet_periodic(self, field):
         """Pad with inverse of flipped field in x direction."""
-        return self.vg.concatenate((field, -self.vg.lib.flip(field, [0])), 1)
+        return self.vg.concatenate((field, -self.vg.lib.flip(field, [1])), 1)
 
     def pad_fft_zero_flux_periodic(self, field):
         """Pad with flipped field in x direction."""
-        return self.vg.concatenate((field, self.vg.lib.flip(field, [0])), 1)
+        return self.vg.concatenate((field, self.vg.lib.flip(field, [1])), 1)
 
     def trim_boundary_nodes(self, field):
         return field
@@ -114,7 +114,7 @@ def pad_fft_periodic(self, field):
     def pad_fft_dirichlet_periodic(self, field):
         """Pad with inverse of flipped field in x direction."""
         bc = self.vg.lib.zeros_like(field[:,0:1])
-        return self.vg.concatenate((field, bc, -self.vg.lib.flip(field, [0]), bc), 1)
+        return self.vg.concatenate((field, bc, -self.vg.lib.flip(field, [1]), bc), 1)
 
     def pad_fft_zero_flux_periodic(self, field):
         """Pad with flipped field in x direction."""

evoxels/precompiled_solvers/cahn_hilliard.py

@@ -1,4 +1,4 @@
-from ..problem_definition import PeriodicCahnHilliard
+from ..problem_definition import CahnHilliard
 from ..solvers import TimeDependentSolver
 from ..timesteppers import PseudoSpectralIMEX
 from typing import Callable
@@ -26,7 +26,7 @@ def run_cahn_hilliard_solver(
         voxelfields,
         fieldnames,
         backend,
-        problem_cls = PeriodicCahnHilliard,
+        problem_cls = CahnHilliard,
         timestepper_cls = PseudoSpectralIMEX,
         device=device,
     )

evoxels/problem_definition.py

@@ -281,12 +281,13 @@ def rhs(self, t, u):
 
 
 @dataclass
-class PeriodicCahnHilliard(SemiLinearODE):
+class CahnHilliard(SemiLinearODE):
     vg: VoxelGrid
     eps: float = 3.0
     D: float = 1.0
     mu_hom: Callable | None = None
     A: float = 0.25
+    bc: tuple = ('periodic', 'periodic', 'periodic')
     _fourier_symbol: Any = field(init=False, repr=False)
 
     def __post_init__(self):

tests/test_inversion.py

@@ -5,13 +5,13 @@
 import pytest
 import evoxels as evo
 from evoxels.inversion import InversionModel
-from evoxels.problem_definition import PeriodicCahnHilliard
+from evoxels.problem_definition import CahnHilliard
 
 diffrax_available = importlib.util.find_spec("diffrax") is not None
 
 def test_train_validates_sequence_length():
     vf = evo.VoxelFields((4, 4, 4))
-    model = InversionModel(vf, PeriodicCahnHilliard)
+    model = InversionModel(vf, CahnHilliard)
     data = {
         "ts": np.array([0.0, 1.0, 2.0]),
         "ys": np.zeros((3, 4, 4, 4), dtype=np.float32),
@@ -27,7 +27,7 @@ def test_inversion_forward_solve_constant_solution():
 
     vf = evo.VoxelFields((4, 4, 4))
     vf.add_field('c', np.full((4, 4, 4), 0.5, dtype=np.float32))
-    model = InversionModel(vf, PeriodicCahnHilliard, {'eps': 3.0})
+    model = InversionModel(vf, CahnHilliard, {'eps': 3.0})
     saveat = dfx.SaveAt(ts=jnp.array([0.0, 0.1, 0.2], dtype=jnp.float32))
     sol = model.forward_solve({'D': 1.0}, 'c', saveat, dt0=0.1, verbose=False)
     assert sol.shape == (3, 4, 4, 4)

tests/test_rhs.py

@@ -2,7 +2,7 @@
 
 import sympy as sp
 import sympy.vector as spv
-from evoxels.problem_definition import PeriodicCahnHilliard, \
+from evoxels.problem_definition import CahnHilliard, \
     TwoPhaseAllenCahn, CoupledReactionDiffusion, ReactionDiffusionSBM, \
     MultiPhaseAllenCahn
 from evoxels.utils import rhs_convergence_test
@@ -12,7 +12,7 @@
 
 def test_Cahn_Hilliard_rhs():
     _ ,_ , slope, order = rhs_convergence_test(
-        ODE_class      = PeriodicCahnHilliard,
+        ODE_class      = CahnHilliard,
         problem_kwargs = {'eps': 3.0, 'D': 1.0, 'A': 0.25},
         test_function  = test_fun_ch,
         convention     = 'cell_center',