64 lines
2.6 KiB
Python
64 lines
2.6 KiB
Python
import torch
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import pytest
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from pina.problem.zoo import Poisson2DSquareProblem as Poisson
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def test_discretise_domain():
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n = 10
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poisson_problem = Poisson()
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boundaries = ['g1', 'g2', 'g3', 'g4']
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poisson_problem.discretise_domain(n, 'grid', domains=boundaries)
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for b in boundaries:
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assert poisson_problem.discretised_domains[b].shape[0] == n
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poisson_problem.discretise_domain(n, 'random', domains=boundaries)
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for b in boundaries:
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assert poisson_problem.discretised_domains[b].shape[0] == n
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poisson_problem.discretise_domain(n, 'grid', domains=['D'])
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assert poisson_problem.discretised_domains['D'].shape[0] == n**2
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poisson_problem.discretise_domain(n, 'random', domains=['D'])
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assert poisson_problem.discretised_domains['D'].shape[0] == n
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poisson_problem.discretise_domain(n, 'latin', domains=['D'])
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assert poisson_problem.discretised_domains['D'].shape[0] == n
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poisson_problem.discretise_domain(n, 'lh', domains=['D'])
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assert poisson_problem.discretised_domains['D'].shape[0] == n
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poisson_problem.discretise_domain(n)
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'''
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def test_sampling_few_variables():
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n = 10
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poisson_problem = Poisson()
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poisson_problem.discretise_domain(n,
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'grid',
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domains=['D'],
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variables=['x'])
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assert poisson_problem.discretised_domains['D'].shape[1] == 1
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'''
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def test_variables_correct_order_sampling():
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n = 10
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poisson_problem = Poisson()
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poisson_problem.discretise_domain(n,
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'grid',
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domains=['D'])
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assert poisson_problem.discretised_domains['D'].labels == sorted(
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poisson_problem.input_variables)
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poisson_problem.discretise_domain(n, 'grid', domains=['D'])
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assert poisson_problem.discretised_domains['D'].labels == sorted(
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poisson_problem.input_variables)
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# def test_add_points():
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# poisson_problem = Poisson()
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# poisson_problem.discretise_domain(0,
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# 'random',
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# domains=['D'],
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# variables=['x', 'y'])
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# new_pts = LabelTensor(torch.tensor([[0.5, -0.5]]), labels=['x', 'y'])
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# poisson_problem.add_points({'D': new_pts})
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# assert torch.isclose(poisson_problem.discretised_domain['D'].extract('x'),
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# new_pts.extract('x'))
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# assert torch.isclose(poisson_problem.discretised_domain['D'].extract('y'),
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# new_pts.extract('y')) |