ab6ca78d85
* Simplifying Graph class and adjust tests --------- Co-authored-by: Dario Coscia <dariocos99@gmail.com>
35 lines
1.3 KiB
Python
35 lines
1.3 KiB
Python
import torch
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from pina.problem import AbstractProblem
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from pina.condition import InputOutputPointsCondition
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from pina.problem.zoo.supervised_problem import SupervisedProblem
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from pina.graph import RadiusGraph
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def test_constructor():
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input_ = torch.rand((100, 10))
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output_ = torch.rand((100, 10))
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problem = SupervisedProblem(input_=input_, output_=output_)
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assert isinstance(problem, AbstractProblem)
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assert hasattr(problem, "conditions")
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assert isinstance(problem.conditions, dict)
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assert list(problem.conditions.keys()) == ["data"]
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assert isinstance(problem.conditions["data"], InputOutputPointsCondition)
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def test_constructor_graph():
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x = torch.rand((20, 100, 10))
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pos = torch.rand((20, 100, 2))
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input_ = [
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RadiusGraph(x=x_, pos=pos_, radius=0.2, edge_attr=True)
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for x_, pos_ in zip(x, pos)
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]
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output_ = torch.rand((100, 10))
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problem = SupervisedProblem(input_=input_, output_=output_)
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assert isinstance(problem, AbstractProblem)
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assert hasattr(problem, "conditions")
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assert isinstance(problem.conditions, dict)
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assert list(problem.conditions.keys()) == ["data"]
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assert isinstance(problem.conditions["data"], InputOutputPointsCondition)
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assert isinstance(problem.conditions["data"].input_points, list)
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assert isinstance(problem.conditions["data"].output_points, torch.Tensor)
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