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Improve conditions and refactor dataset classes (#475)

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* Reimplement conditions

* Refactor datasets and implement LabelBatch

---------

Co-authored-by: Dario Coscia <dariocos99@gmail.com>
This commit is contained in:
Filippo Olivo
2025-03-07 11:24:09 +01:00
committed by Nicola Demo
parent bdad144461
commit a0cbf1c44a
40 changed files with 943 additions and 550 deletions
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5
pina/problem/abstract_problem.py
View File

@@ -4,7 +4,6 @@ from abc import ABCMeta, abstractmethod
from ..utils import check_consistency
from ..domain import DomainInterface, CartesianDomain
from ..condition.domain_equation_condition import DomainEquationCondition
from ..condition import InputPointsEquationCondition
from copy import deepcopy
from .. import LabelTensor
from ..utils import merge_tensors
@@ -55,8 +54,8 @@ class AbstractProblem(metaclass=ABCMeta):
def input_pts(self):
to_return = {}
for cond_name, cond in self.conditions.items():
if hasattr(cond, "input_points"):
to_return[cond_name] = cond.input_points
if hasattr(cond, "input"):
to_return[cond_name] = cond.input
elif hasattr(cond, "domain"):
to_return[cond_name] = self._discretised_domains[cond.domain]
return to_return

4
pina/problem/zoo/inverse_diffusion_reaction.py
View File

@@ -46,8 +46,8 @@ class InverseDiffusionReactionProblem(
equation=Equation(diffusion_reaction),
),
"data": Condition(
input_points=LabelTensor(torch.randn(10, 2), ["x", "t"]),
output_points=LabelTensor(torch.randn(10, 1), ["u"]),
input=LabelTensor(torch.randn(10, 2), ["x", "t"]),
target=LabelTensor(torch.randn(10, 1), ["u"]),
),
}

4
pina/problem/zoo/inverse_poisson_2d_square.py
View File

@@ -50,7 +50,7 @@ class InversePoisson2DSquareProblem(SpatialProblem, InverseProblem):
"nil_g4": Condition(domain="g4", equation=FixedValue(0.0)),
"laplace_D": Condition(domain="D", equation=Equation(laplace_equation)),
"data": Condition(
input_points=data_input.extract(["x", "y"]),
output_points=data_output,
input=data_input.extract(["x", "y"]),
target=data_output,
),
}

6
pina/problem/zoo/supervised_problem.py
View File

@@ -8,7 +8,7 @@ class SupervisedProblem(AbstractProblem):
A problem definition for supervised learning in PINA.
This class allows an easy and straightforward definition of a Supervised problem,
based on a single condition of type `InputOutputPointsCondition`
based on a single condition of type `InputTargetCondition`
:Example:
>>> import torch
@@ -31,7 +31,5 @@ class SupervisedProblem(AbstractProblem):
"""
if isinstance(input_, Graph):
input_ = input_.data
self.conditions["data"] = Condition(
input_points=input_, output_points=output_
)
self.conditions["data"] = Condition(input=input_, target=output_)
super().__init__()