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Introduce add_points method in AbstractProblem, removed unused comments in Collector class and add the test for add_points and codacy corrections

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FilippoOlivo
2025-02-06 17:29:37 +01:00
committed by Nicola Demo
parent 004cbc00c0
commit f578b2ed12
4 changed files with 56 additions and 109 deletions
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32
tests/test_problem.py
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@@ -1,6 +1,8 @@
import torch
import pytest
from pina.problem.zoo import Poisson2DSquareProblem as Poisson
from pina import LabelTensor
def test_discretise_domain():
n = 10
@@ -14,7 +16,7 @@ def test_discretise_domain():
assert poisson_problem.discretised_domains[b].shape[0] == n
poisson_problem.discretise_domain(n, 'grid', domains=['D'])
assert poisson_problem.discretised_domains['D'].shape[0] == n**2
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
@@ -25,6 +27,8 @@ def test_discretise_domain():
assert poisson_problem.discretised_domains['D'].shape[0] == n
poisson_problem.discretise_domain(n)
'''
def test_sampling_few_variables():
n = 10
@@ -36,8 +40,8 @@ def test_sampling_few_variables():
assert poisson_problem.discretised_domains['D'].shape[1] == 1
'''
def test_variables_correct_order_sampling():
def test_variables_correct_order_sampling():
n = 10
poisson_problem = Poisson()
poisson_problem.discretise_domain(n,
@@ -50,15 +54,15 @@ def test_variables_correct_order_sampling():
assert poisson_problem.discretised_domains['D'].labels == sorted(
poisson_problem.input_variables)
# def test_add_points():
# poisson_problem = Poisson()
# poisson_problem.discretise_domain(0,
# 'random',
# domains=['D'],
# variables=['x', 'y'])
# new_pts = LabelTensor(torch.tensor([[0.5, -0.5]]), labels=['x', 'y'])
# poisson_problem.add_points({'D': new_pts})
# assert torch.isclose(poisson_problem.discretised_domain['D'].extract('x'),
# new_pts.extract('x'))
# assert torch.isclose(poisson_problem.discretised_domain['D'].extract('y'),
# new_pts.extract('y'))
def test_add_points():
poisson_problem = Poisson()
poisson_problem.discretise_domain(0,
'random',
domains=['D'])
new_pts = LabelTensor(torch.tensor([[0.5, -0.5]]), labels=['x', 'y'])
poisson_problem.add_points({'D': new_pts})
assert torch.isclose(poisson_problem.discretised_domains['D'].extract('x'),
new_pts.extract('x'))
assert torch.isclose(poisson_problem.discretised_domains['D'].extract('y'),
new_pts.extract('y'))