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Merged
merged 5 commits into from
Oct 14, 2025
Merged

Use petsctools.attach_options #217

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9bff461
add [tao] optional dependency set with [petsc4py,petsctools]
JHopeCollins Jul 16, 2025
7d05952
use petsctools in the tao solver (including attach_options)
JHopeCollins Jul 16, 2025
7efda23
Merge branch 'master' into JHopeCollins/petsctools-attach_options
JHopeCollins Jul 30, 2025
6b139f1
force ci
JHopeCollins Jul 30, 2025
3aeeb7e
Merge branch 'master' into JHopeCollins/petsctools-attach_options
JHopeCollins Oct 14, 2025
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11 changes: 7 additions & 4 deletions pyadjoint/optimization/tao_solver.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,6 +41,8 @@ class PETScVecInterface:
def __init__(self, x, *, comm=None):
if PETSc is None:
raise RuntimeError("PETSc not available")
if petsctools is None:
raise RuntimeError("petsctools not available")

x = Enlist(x)
if comm is None:
Expand Down Expand Up @@ -345,8 +347,9 @@ def mult(self, A, x, y):
to_petsc(ub_vec, ubs)
tao.setVariableBounds(lb_vec, ub_vec)

self.options = OptionsManager(parameters, None)
self.options.set_from_options(tao)
petsctools.set_from_options(
tao, parameters=parameters,
options_prefix=None)

if tao.getType() in {PETSc.TAO.Type.LMVM, PETSc.TAO.Type.BLMVM}:
class InitialHessian:
Expand Down Expand Up @@ -391,7 +394,7 @@ def apply(self, pc, x, y):

x = vec_interface.new_petsc()
tao.setSolution(x)
with self.options.inserted_options():
with petsctools.inserted_options(tao):
tao.setUp()

super().__init__(problem, parameters)
Expand Down Expand Up @@ -432,7 +435,7 @@ def solve(self):
controls = self.tao_objective.reduced_functional.controls
m = tuple(control.tape_value()._ad_copy() for control in controls)
self._vec_interface.to_petsc(self.x, m)
with self.options.inserted_options():
with petsctools.inserted_options(self.tao):
self.tao.solve()
self._vec_interface.from_petsc(self.x, m)
if self.tao.getConvergedReason() <= 0:
Expand Down
39 changes: 32 additions & 7 deletions pyproject.toml
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Expand Up @@ -38,13 +38,38 @@ all = [
"sphinxcontrib-bibtex",
"tensorflow",
]
doc = ["sphinx", "sphinx-autobuild", "sphinxcontrib-bibtex"]
meshing = ["pygmsh", "meshio"]
moola = ["moola>=0.1.6"]
test = ["pytest>=3.10", "flake8", "coverage"]
visualisation = ["tensorflow", "protobuf", "networkx", "pygraphviz"]
tao = ["petsc4py", "petsctools"]
doc = [
"sphinx",
"sphinx-autobuild",
"sphinxcontrib-bibtex"
]
meshing = [
"pygmsh",
"meshio"
]
moola = [
"moola>=0.1.6"
]
test = [
"pytest>=3.10",
"flake8",
"coverage"
]
visualisation = [
"tensorflow",
"protobuf",
"networkx",
"pygraphviz"
]
tao = [
"petsc4py",
"petsctools>2025.0"
]


[tool.setuptools]
packages = ["numpy_adjoint", "pyadjoint", "pyadjoint.optimization"]
packages = [
"numpy_adjoint",
"pyadjoint",
"pyadjoint.optimization"
]