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Merged
GiovanniCanali merged 2 commits into from
Dec 15, 2025
Merged

Update problem/zoo and tests post domain refactory #738

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c84c7a3
update problem zoo and tests post domain refactory
GiovanniCanali Dec 4, 2025
b544098
update tutorials
GiovanniCanali Dec 15, 2025
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4 changes: 3 additions & 1 deletion pina/problem/abstract_problem.py
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Expand Up @@ -328,7 +328,9 @@ def collect_data(self):
# Only store the discretisation points if the domain is
# in the dictionary
if condition.domain in self.discretised_domains:
samples = self.discretised_domains[condition.domain]
samples = self.discretised_domains[condition.domain][
self.input_variables
]
data[condition_name] = {
"input": samples,
"equation": condition.equation,
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12 changes: 5 additions & 7 deletions pina/problem/zoo/acoustic_wave.py
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Expand Up @@ -50,19 +50,17 @@ class AcousticWaveProblem(TimeDependentProblem, SpatialProblem):
temporal_domain = CartesianDomain({"t": [0, 1]})

domains = {
"D": CartesianDomain({"x": [0, 1], "t": [0, 1]}),
"t0": CartesianDomain({"x": [0, 1], "t": 0.0}),
"g1": CartesianDomain({"x": 0.0, "t": [0, 1]}),
"g2": CartesianDomain({"x": 1.0, "t": [0, 1]}),
"D": spatial_domain.update(temporal_domain),
"t0": spatial_domain.update(CartesianDomain({"t": 0})),
"boundary": spatial_domain.partial().update(temporal_domain),
}

conditions = {
"g1": Condition(domain="g1", equation=FixedValue(value=0.0)),
"g2": Condition(domain="g2", equation=FixedValue(value=0.0)),
"boundary": Condition(domain="boundary", equation=FixedValue(0.0)),
"t0": Condition(
domain="t0",
equation=SystemEquation(
[Equation(initial_condition), FixedGradient(value=0.0, d="t")]
[Equation(initial_condition), FixedGradient(0.0, d="t")]
),
),
}
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4 changes: 2 additions & 2 deletions pina/problem/zoo/advection.py
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Expand Up @@ -42,8 +42,8 @@ class AdvectionProblem(SpatialProblem, TimeDependentProblem):
temporal_domain = CartesianDomain({"t": [0, 1]})

domains = {
"D": CartesianDomain({"x": [0, 2 * torch.pi], "t": [0, 1]}),
"t0": CartesianDomain({"x": [0, 2 * torch.pi], "t": 0.0}),
"D": spatial_domain.update(temporal_domain),
"t0": spatial_domain.update(CartesianDomain({"t": 0})),
}

conditions = {
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4 changes: 2 additions & 2 deletions pina/problem/zoo/allen_cahn.py
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Expand Up @@ -47,8 +47,8 @@ class AllenCahnProblem(TimeDependentProblem, SpatialProblem):
temporal_domain = CartesianDomain({"t": [0, 1]})

domains = {
"D": CartesianDomain({"x": [-1, 1], "t": [0, 1]}),
"t0": CartesianDomain({"x": [-1, 1], "t": 0.0}),
"D": spatial_domain.update(temporal_domain),
"t0": spatial_domain.update(CartesianDomain({"t": 0})),
}

conditions = {
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10 changes: 4 additions & 6 deletions pina/problem/zoo/diffusion_reaction.py
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Expand Up @@ -49,15 +49,13 @@ class DiffusionReactionProblem(TimeDependentProblem, SpatialProblem):
temporal_domain = CartesianDomain({"t": [0, 1]})

domains = {
"D": CartesianDomain({"x": [-torch.pi, torch.pi], "t": [0, 1]}),
"g1": CartesianDomain({"x": -torch.pi, "t": [0, 1]}),
"g2": CartesianDomain({"x": torch.pi, "t": [0, 1]}),
"t0": CartesianDomain({"x": [-torch.pi, torch.pi], "t": 0.0}),
"D": spatial_domain.update(temporal_domain),
"boundary": spatial_domain.partial().update(temporal_domain),
"t0": spatial_domain.update(CartesianDomain({"t": 0})),
}

conditions = {
"g1": Condition(domain="g1", equation=FixedValue(0.0)),
"g2": Condition(domain="g2", equation=FixedValue(0.0)),
"boundary": Condition(domain="boundary", equation=FixedValue(0.0)),
"t0": Condition(domain="t0", equation=Equation(initial_condition)),
}

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12 changes: 3 additions & 9 deletions pina/problem/zoo/helmholtz.py
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Expand Up @@ -28,18 +28,12 @@ class HelmholtzProblem(SpatialProblem):
spatial_domain = CartesianDomain({"x": [-1, 1], "y": [-1, 1]})

domains = {
"D": CartesianDomain({"x": [-1, 1], "y": [-1, 1]}),
"g1": CartesianDomain({"x": [-1, 1], "y": 1.0}),
"g2": CartesianDomain({"x": [-1, 1], "y": -1.0}),
"g3": CartesianDomain({"x": 1.0, "y": [-1, 1]}),
"g4": CartesianDomain({"x": -1.0, "y": [-1, 1]}),
"D": spatial_domain,
"boundary": spatial_domain.partial(),
}

conditions = {
"g1": Condition(domain="g1", equation=FixedValue(0.0)),
"g2": Condition(domain="g2", equation=FixedValue(0.0)),
"g3": Condition(domain="g3", equation=FixedValue(0.0)),
"g4": Condition(domain="g4", equation=FixedValue(0.0)),
"boundary": Condition(domain="boundary", equation=FixedValue(0.0)),
}

def __init__(self, alpha=3.0):
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12 changes: 3 additions & 9 deletions pina/problem/zoo/inverse_poisson_2d_square.py
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Expand Up @@ -90,19 +90,13 @@ class InversePoisson2DSquareProblem(SpatialProblem, InverseProblem):
unknown_parameter_domain = CartesianDomain({"mu1": [-1, 1], "mu2": [-1, 1]})

domains = {
"g1": CartesianDomain({"x": [x_min, x_max], "y": y_max}),
"g2": CartesianDomain({"x": [x_min, x_max], "y": y_min}),
"g3": CartesianDomain({"x": x_max, "y": [y_min, y_max]}),
"g4": CartesianDomain({"x": x_min, "y": [y_min, y_max]}),
"D": CartesianDomain({"x": [x_min, x_max], "y": [y_min, y_max]}),
"D": spatial_domain,
"boundary": spatial_domain.partial(),
}

conditions = {
"g1": Condition(domain="g1", equation=FixedValue(0.0)),
"g2": Condition(domain="g2", equation=FixedValue(0.0)),
"g3": Condition(domain="g3", equation=FixedValue(0.0)),
"g4": Condition(domain="g4", equation=FixedValue(0.0)),
"D": Condition(domain="D", equation=Equation(laplace_equation)),
"boundary": Condition(domain="boundary", equation=FixedValue(0.0)),
}

def __init__(self, load=True, data_size=1.0):
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12 changes: 3 additions & 9 deletions pina/problem/zoo/poisson_2d_square.py
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Expand Up @@ -36,18 +36,12 @@ class Poisson2DSquareProblem(SpatialProblem):
spatial_domain = CartesianDomain({"x": [0, 1], "y": [0, 1]})

domains = {
"D": CartesianDomain({"x": [0, 1], "y": [0, 1]}),
"g1": CartesianDomain({"x": [0, 1], "y": 1.0}),
"g2": CartesianDomain({"x": [0, 1], "y": 0.0}),
"g3": CartesianDomain({"x": 1.0, "y": [0, 1]}),
"g4": CartesianDomain({"x": 0.0, "y": [0, 1]}),
"D": spatial_domain,
"boundary": spatial_domain.partial(),
}

conditions = {
"g1": Condition(domain="g1", equation=FixedValue(0.0)),
"g2": Condition(domain="g2", equation=FixedValue(0.0)),
"g3": Condition(domain="g3", equation=FixedValue(0.0)),
"g4": Condition(domain="g4", equation=FixedValue(0.0)),
"boundary": Condition(domain="boundary", equation=FixedValue(0.0)),
"D": Condition(domain="D", equation=Poisson(forcing_term=forcing_term)),
}

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3 changes: 1 addition & 2 deletions tests/test_callback/test_metric_tracker.py
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Expand Up @@ -7,9 +7,8 @@

# make the problem
poisson_problem = Poisson()
boundaries = ["g1", "g2", "g3", "g4"]
n = 10
poisson_problem.discretise_domain(n, "grid", domains=boundaries)
poisson_problem.discretise_domain(n, "grid", domains="boundary")
poisson_problem.discretise_domain(n, "grid", domains="D")
model = FeedForward(
len(poisson_problem.input_variables), len(poisson_problem.output_variables)
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3 changes: 1 addition & 2 deletions tests/test_callback/test_pina_progress_bar.py
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Expand Up @@ -7,10 +7,9 @@

# make the problem
poisson_problem = Poisson()
boundaries = ["g1", "g2", "g3", "g4"]
n = 10
condition_names = list(poisson_problem.conditions.keys())
poisson_problem.discretise_domain(n, "grid", domains=boundaries)
poisson_problem.discretise_domain(n, "grid", domains="boundary")
poisson_problem.discretise_domain(n, "grid", domains="D")
model = FeedForward(
len(poisson_problem.input_variables), len(poisson_problem.output_variables)
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6 changes: 2 additions & 4 deletions tests/test_callback/test_r3_refinement.py
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Expand Up @@ -9,7 +9,7 @@

# make the problem
poisson_problem = Poisson()
poisson_problem.discretise_domain(10, "grid", domains=["g1", "g2", "g3", "g4"])
poisson_problem.discretise_domain(10, "grid", domains="boundary")
poisson_problem.discretise_domain(10, "grid", domains="D")
model = FeedForward(
len(poisson_problem.input_variables), len(poisson_problem.output_variables)
Expand All @@ -29,9 +29,7 @@ def test_constructor():
R3Refinement(sample_every=10, condition_to_update=3)


@pytest.mark.parametrize(
"condition_to_update", [["D", "g1"], ["D", "g1", "g2", "g3", "g4"]]
)
@pytest.mark.parametrize("condition_to_update", [["D"], ["boundary", "D"]])
def test_sample(condition_to_update):
trainer = Trainer(
solver=solver,
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21 changes: 10 additions & 11 deletions tests/test_problem.py
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Expand Up @@ -13,16 +13,16 @@
def test_discretise_domain():
n = 10
poisson_problem = Poisson()
boundaries = ["g1", "g2", "g3", "g4"]
poisson_problem.discretise_domain(n, "grid", domains=boundaries)
for b in boundaries:
assert poisson_problem.discretised_domains[b].shape[0] == n
poisson_problem.discretise_domain(n, "random", domains=boundaries)
for b in boundaries:
assert poisson_problem.discretised_domains[b].shape[0] == n

poisson_problem.discretise_domain(n, "grid", domains="boundary")
assert poisson_problem.discretised_domains["boundary"].shape[0] == n

poisson_problem.discretise_domain(n, "random", domains="boundary")
assert poisson_problem.discretised_domains["boundary"].shape[0] == n

poisson_problem.discretise_domain(n, "grid", domains=["D"])
assert poisson_problem.discretised_domains["D"].shape[0] == n**2

poisson_problem.discretise_domain(n, "random", domains=["D"])
assert poisson_problem.discretised_domains["D"].shape[0] == n

Expand Down Expand Up @@ -89,10 +89,9 @@ def test_custom_sampling_logic(mode):
"x": {"n": 100, "mode": mode},
"y": {"n": 50, "mode": mode},
}
poisson_problem.discretise_domain(sample_rules=sampling_rules)
for domain in ["g1", "g2", "g3", "g4"]:
assert poisson_problem.discretised_domains[domain].shape[0] == 100 * 50
assert poisson_problem.discretised_domains[domain].labels == ["x", "y"]
poisson_problem.discretise_domain(sample_rules=sampling_rules, domains="D")
assert poisson_problem.discretised_domains["D"].shape[0] == 100 * 50
assert poisson_problem.discretised_domains["D"].labels == ["x", "y"]


@pytest.mark.parametrize("mode", ["random", "grid"])
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2 changes: 1 addition & 1 deletion tutorials/README.md
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Expand Up @@ -14,7 +14,7 @@ How to build a `Problem` in PINA|[[.ipynb](tutorial16/tutorial.ipynb),[.py](tuto
Introduction to Solver classes|[[.ipynb](tutorial18/tutorial.ipynb),[.py](tutorial18/tutorial.py),[.html](http://mathlab.github.io/PINA/tutorial18/tutorial.html)]|
Introduction to `Trainer` class|[[.ipynb](tutorial11/tutorial.ipynb),[.py](tutorial11/tutorial.py),[.html](http://mathlab.github.io/PINA/tutorial11/tutorial.html)]|
Data structure for SciML: `Tensor`, `LabelTensor`, `Data` and `Graph` |[[.ipynb](tutorial19/tutorial.ipynb),[.py](tutorial19/tutorial.py),[.html](http://mathlab.github.io/PINA/tutorial19/tutorial.html)]|
Building geometries with `DomainInterface` class|[[.ipynb](tutorial6/tutorial.ipynb),[.py](tutorial6/tutorial.py),[.html](http://mathlab.github.io/PINA/tutorial6/tutorial.html)]|
Building domains with PINA's BaseDomain class|[[.ipynb](tutorial6/tutorial.ipynb),[.py](tutorial6/tutorial.py),[.html](http://mathlab.github.io/PINA/tutorial6/tutorial.html)]|
Introduction to PINA `Equation` class|[[.ipynb](tutorial12/tutorial.ipynb),[.py](tutorial12/tutorial.py),[.html](http://mathlab.github.io/PINA/tutorial12/tutorial.html)]|


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