58 lines
1.5 KiB
Python
58 lines
1.5 KiB
Python
from pina.equation import SystemEquation
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from pina.operator import grad, laplacian
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from pina import LabelTensor
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import torch
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import pytest
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def eq1(input_, output_):
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u_grad = grad(output_, input_)
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u1_xx = grad(u_grad, input_, components=["du1dx"], d=["x"])
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u2_xy = grad(u_grad, input_, components=["du2dx"], d=["y"])
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return torch.hstack([u1_xx, u2_xy])
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def eq2(input_, output_):
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force_term = torch.sin(input_.extract(["x"]) * torch.pi) * torch.sin(
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input_.extract(["y"]) * torch.pi
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)
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delta_u = laplacian(output_.extract(["u1"]), input_)
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return delta_u - force_term
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def foo():
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pass
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def test_constructor():
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SystemEquation([eq1, eq2])
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SystemEquation([eq1, eq2], reduction="sum")
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with pytest.raises(NotImplementedError):
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SystemEquation([eq1, eq2], reduction="foo")
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with pytest.raises(ValueError):
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SystemEquation(foo)
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def test_residual():
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pts = LabelTensor(torch.rand(10, 2), labels=["x", "y"])
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pts.requires_grad = True
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u = torch.pow(pts, 2)
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u.labels = ["u1", "u2"]
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eq_1 = SystemEquation([eq1, eq2], reduction="mean")
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res = eq_1.residual(pts, u)
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assert res.shape == torch.Size([10])
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eq_1 = SystemEquation([eq1, eq2], reduction="sum")
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res = eq_1.residual(pts, u)
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assert res.shape == torch.Size([10])
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eq_1 = SystemEquation([eq1, eq2], reduction=None)
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res = eq_1.residual(pts, u)
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assert res.shape == torch.Size([10, 3])
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eq_1 = SystemEquation([eq1, eq2])
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res = eq_1.residual(pts, u)
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assert res.shape == torch.Size([10, 3])
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