From f2340cd4ee2492dd9d74b611564c67b6ec54582f Mon Sep 17 00:00:00 2001 From: Nicola Demo Date: Thu, 16 Jan 2025 19:03:18 +0100 Subject: [PATCH] fix some tests --- pina/problem/zoo/__init__.py | 5 ++ pina/problem/zoo/poisson_2d_square.py | 44 ++++++++++++++++ .../test_adaptive_refinment_callbacks.py | 52 ++----------------- tests/test_callbacks/test_metric_tracker.py | 50 +----------------- .../test_optimizer_callbacks.py | 48 +---------------- tests/test_callbacks/test_progress_bar.py | 50 +----------------- tests/test_package.py | 2 +- .../test_poisson_2d_square.py | 7 +++ 8 files changed, 66 insertions(+), 192 deletions(-) create mode 100644 pina/problem/zoo/__init__.py create mode 100644 pina/problem/zoo/poisson_2d_square.py create mode 100644 tests/test_problem_zoo/test_poisson_2d_square.py diff --git a/pina/problem/zoo/__init__.py b/pina/problem/zoo/__init__.py new file mode 100644 index 0000000..ea9aa78 --- /dev/null +++ b/pina/problem/zoo/__init__.py @@ -0,0 +1,5 @@ +__all__ = [ + 'Poisson2DSquareProblem' +] + +from .poisson_2d_square import Poisson2DSquareProblem \ No newline at end of file diff --git a/pina/problem/zoo/poisson_2d_square.py b/pina/problem/zoo/poisson_2d_square.py new file mode 100644 index 0000000..16329ab --- /dev/null +++ b/pina/problem/zoo/poisson_2d_square.py @@ -0,0 +1,44 @@ +""" Definition of the Poisson problem on a square domain.""" + +from pina.problem import SpatialProblem +from pina.operators import laplacian +from pina import LabelTensor, Condition +from pina.domain import CartesianDomain +from pina.equation.equation import Equation +from pina.equation.equation_factory import FixedValue +import torch + +def laplace_equation(input_, output_): + force_term = (torch.sin(input_.extract(['x']) * torch.pi) * + torch.sin(input_.extract(['y']) * torch.pi)) + delta_u = laplacian(output_.extract(['u']), input_) + return delta_u - force_term + + +my_laplace = Equation(laplace_equation) + + +class Poisson2DSquareProblem(SpatialProblem): + output_variables = ['u'] + spatial_domain = CartesianDomain({'x': [0, 1], 'y': [0, 1]}) + + domains = { + 'D': CartesianDomain({'x': [0, 1], 'y': [0, 1]}), + 'g1': CartesianDomain({'x': [0, 1], 'y': 1}), + 'g2': CartesianDomain({'x': [0, 1], 'y': 0}), + 'g3': CartesianDomain({'x': 1, 'y': [0, 1]}), + 'g4': CartesianDomain({'x': 0, 'y': [0, 1]}), + } + + conditions = { + 'nil_g1': Condition(domain='D', equation=FixedValue(0.0)), + 'nil_g2': Condition(domain='D', equation=FixedValue(0.0)), + 'nil_g3': Condition(domain='D', equation=FixedValue(0.0)), + 'nil_g4': Condition(domain='D', equation=FixedValue(0.0)), + 'laplace_D': Condition(domain='D', equation=my_laplace), + } + + def poisson_sol(self, pts): + return -(torch.sin(pts.extract(['x']) * torch.pi) * + torch.sin(pts.extract(['y']) * torch.pi)) + diff --git a/tests/test_callbacks/test_adaptive_refinment_callbacks.py b/tests/test_callbacks/test_adaptive_refinment_callbacks.py index 67732b3..564aab9 100644 --- a/tests/test_callbacks/test_adaptive_refinment_callbacks.py +++ b/tests/test_callbacks/test_adaptive_refinment_callbacks.py @@ -1,59 +1,13 @@ -from pina.callbacks import R3Refinement -import torch -import pytest - -from pina.problem import SpatialProblem -from pina.operators import laplacian -from pina.domain import CartesianDomain -from pina import Condition, LabelTensor from pina.solvers import PINN from pina.trainer import Trainer from pina.model import FeedForward -from pina.equation.equation import Equation -from pina.equation.equation_factory import FixedValue - - -def laplace_equation(input_, output_): - force_term = (torch.sin(input_.extract(['x']) * torch.pi) * - torch.sin(input_.extract(['y']) * torch.pi)) - delta_u = laplacian(output_.extract(['u']), input_) - return delta_u - force_term - - -my_laplace = Equation(laplace_equation) -in_ = LabelTensor(torch.tensor([[0., 1.]]), ['x', 'y']) -out_ = LabelTensor(torch.tensor([[0.]]), ['u']) - - -class Poisson(SpatialProblem): - output_variables = ['u'] - spatial_domain = CartesianDomain({'x': [0, 1], 'y': [0, 1]}) - - conditions = { - 'gamma1': Condition( - location=CartesianDomain({'x': [0, 1], 'y': 1}), - equation=FixedValue(0.0)), - 'gamma2': Condition( - location=CartesianDomain({'x': [0, 1], 'y': 0}), - equation=FixedValue(0.0)), - 'gamma3': Condition( - location=CartesianDomain({'x': 1, 'y': [0, 1]}), - equation=FixedValue(0.0)), - 'gamma4': Condition( - location=CartesianDomain({'x': 0, 'y': [0, 1]}), - equation=FixedValue(0.0)), - 'D': Condition( - input_points=LabelTensor(torch.rand(size=(100, 2)), ['x', 'y']), - equation=my_laplace), - # 'data': Condition( - # input_points=in_, - # output_points=out_) - } +from pina.problem.zoo import Poisson2DSquareProblem as Poisson +from pina.callbacks import R3Refinement # make the problem poisson_problem = Poisson() -boundaries = ['gamma1', 'gamma2', 'gamma3', 'gamma4'] +boundaries = ['nil_g1', 'nil_g2', 'nil_g3', 'nil_g4'] n = 10 poisson_problem.discretise_domain(n, 'grid', locations=boundaries) model = FeedForward(len(poisson_problem.input_variables), diff --git a/tests/test_callbacks/test_metric_tracker.py b/tests/test_callbacks/test_metric_tracker.py index c380245..d67e06b 100644 --- a/tests/test_callbacks/test_metric_tracker.py +++ b/tests/test_callbacks/test_metric_tracker.py @@ -1,59 +1,13 @@ -import torch -import pytest - -from pina.problem import SpatialProblem -from pina.operators import laplacian -from pina.geometry import CartesianDomain -from pina import Condition, LabelTensor from pina.solvers import PINN from pina.trainer import Trainer from pina.model import FeedForward -from pina.equation.equation import Equation -from pina.equation.equation_factory import FixedValue from pina.callbacks import MetricTracker - - -def laplace_equation(input_, output_): - force_term = (torch.sin(input_.extract(['x']) * torch.pi) * - torch.sin(input_.extract(['y']) * torch.pi)) - delta_u = laplacian(output_.extract(['u']), input_) - return delta_u - force_term - - -my_laplace = Equation(laplace_equation) -in_ = LabelTensor(torch.tensor([[0., 1.]]), ['x', 'y']) -out_ = LabelTensor(torch.tensor([[0.]]), ['u']) - - -class Poisson(SpatialProblem): - output_variables = ['u'] - spatial_domain = CartesianDomain({'x': [0, 1], 'y': [0, 1]}) - - conditions = { - 'gamma1': Condition( - location=CartesianDomain({'x': [0, 1], 'y': 1}), - equation=FixedValue(0.0)), - 'gamma2': Condition( - location=CartesianDomain({'x': [0, 1], 'y': 0}), - equation=FixedValue(0.0)), - 'gamma3': Condition( - location=CartesianDomain({'x': 1, 'y': [0, 1]}), - equation=FixedValue(0.0)), - 'gamma4': Condition( - location=CartesianDomain({'x': 0, 'y': [0, 1]}), - equation=FixedValue(0.0)), - 'D': Condition( - input_points=LabelTensor(torch.rand(size=(100, 2)), ['x', 'y']), - equation=my_laplace), - 'data': Condition( - input_points=in_, - output_points=out_) - } +from pina.problem.zoo import Poisson2DSquareProblem as Poisson # make the problem poisson_problem = Poisson() -boundaries = ['gamma1', 'gamma2', 'gamma3', 'gamma4'] +boundaries = ['nil_g1', 'nil_g2', 'nil_g3', 'nil_g4'] n = 10 poisson_problem.discretise_domain(n, 'grid', locations=boundaries) model = FeedForward(len(poisson_problem.input_variables), diff --git a/tests/test_callbacks/test_optimizer_callbacks.py b/tests/test_callbacks/test_optimizer_callbacks.py index 898d3f5..a57bda3 100644 --- a/tests/test_callbacks/test_optimizer_callbacks.py +++ b/tests/test_callbacks/test_optimizer_callbacks.py @@ -2,58 +2,14 @@ from pina.callbacks import SwitchOptimizer import torch import pytest -from pina.problem import SpatialProblem -from pina.operators import laplacian -from pina.domain import CartesianDomain -from pina import Condition, LabelTensor from pina.solvers import PINN from pina.trainer import Trainer from pina.model import FeedForward -from pina.equation.equation import Equation -from pina.equation.equation_factory import FixedValue - - -def laplace_equation(input_, output_): - force_term = (torch.sin(input_.extract(['x']) * torch.pi) * - torch.sin(input_.extract(['y']) * torch.pi)) - delta_u = laplacian(output_.extract(['u']), input_) - return delta_u - force_term - - -my_laplace = Equation(laplace_equation) -in_ = LabelTensor(torch.tensor([[0., 1.]]), ['x', 'y']) -out_ = LabelTensor(torch.tensor([[0.]]), ['u']) - - -class Poisson(SpatialProblem): - output_variables = ['u'] - spatial_domain = CartesianDomain({'x': [0, 1], 'y': [0, 1]}) - - conditions = { - 'gamma1': Condition( - location=CartesianDomain({'x': [0, 1], 'y': 1}), - equation=FixedValue(0.0)), - 'gamma2': Condition( - location=CartesianDomain({'x': [0, 1], 'y': 0}), - equation=FixedValue(0.0)), - 'gamma3': Condition( - location=CartesianDomain({'x': 1, 'y': [0, 1]}), - equation=FixedValue(0.0)), - 'gamma4': Condition( - location=CartesianDomain({'x': 0, 'y': [0, 1]}), - equation=FixedValue(0.0)), - 'D': Condition( - input_points=LabelTensor(torch.rand(size=(100, 2)), ['x', 'y']), - equation=my_laplace), - # 'data': Condition( - # input_points=in_, - # output_points=out_) - } - +from pina.problem.zoo import Poisson2DSquareProblem as Poisson # make the problem poisson_problem = Poisson() -boundaries = ['gamma1', 'gamma2', 'gamma3', 'gamma4'] +boundaries = ['nil_g1', 'nil_g2', 'nil_g3', 'nil_g4'] n = 10 poisson_problem.discretise_domain(n, 'grid', locations=boundaries) model = FeedForward(len(poisson_problem.input_variables), diff --git a/tests/test_callbacks/test_progress_bar.py b/tests/test_callbacks/test_progress_bar.py index 990b471..5c2cae4 100644 --- a/tests/test_callbacks/test_progress_bar.py +++ b/tests/test_callbacks/test_progress_bar.py @@ -1,59 +1,13 @@ -import torch -import pytest - -from pina.problem import SpatialProblem -from pina.operators import laplacian -from pina.geometry import CartesianDomain -from pina import Condition, LabelTensor from pina.solvers import PINN from pina.trainer import Trainer from pina.model import FeedForward -from pina.equation.equation import Equation -from pina.equation.equation_factory import FixedValue from pina.callbacks.processing_callbacks import PINAProgressBar - - -def laplace_equation(input_, output_): - force_term = (torch.sin(input_.extract(['x']) * torch.pi) * - torch.sin(input_.extract(['y']) * torch.pi)) - delta_u = laplacian(output_.extract(['u']), input_) - return delta_u - force_term - - -my_laplace = Equation(laplace_equation) -in_ = LabelTensor(torch.tensor([[0., 1.]]), ['x', 'y']) -out_ = LabelTensor(torch.tensor([[0.]]), ['u']) - - -class Poisson(SpatialProblem): - output_variables = ['u'] - spatial_domain = CartesianDomain({'x': [0, 1], 'y': [0, 1]}) - - conditions = { - 'gamma1': Condition( - location=CartesianDomain({'x': [0, 1], 'y': 1}), - equation=FixedValue(0.0)), - 'gamma2': Condition( - location=CartesianDomain({'x': [0, 1], 'y': 0}), - equation=FixedValue(0.0)), - 'gamma3': Condition( - location=CartesianDomain({'x': 1, 'y': [0, 1]}), - equation=FixedValue(0.0)), - 'gamma4': Condition( - location=CartesianDomain({'x': 0, 'y': [0, 1]}), - equation=FixedValue(0.0)), - 'D': Condition( - input_points=LabelTensor(torch.rand(size=(100, 2)), ['x', 'y']), - equation=my_laplace), - 'data': Condition( - input_points=in_, - output_points=out_) - } +from pina.problem.zoo import Poisson2DSquareProblem as Poisson # make the problem poisson_problem = Poisson() -boundaries = ['gamma1', 'gamma2', 'gamma3', 'gamma4'] +boundaries = ['nil_g1', 'nil_g2', 'nil_g3', 'nil_g4'] n = 10 poisson_problem.discretise_domain(n, 'grid', locations=boundaries) model = FeedForward(len(poisson_problem.input_variables), diff --git a/tests/test_package.py b/tests/test_package.py index f59bd6c..f85bed5 100644 --- a/tests/test_package.py +++ b/tests/test_package.py @@ -1,2 +1,2 @@ def test_import(): - import pina + import pina \ No newline at end of file diff --git a/tests/test_problem_zoo/test_poisson_2d_square.py b/tests/test_problem_zoo/test_poisson_2d_square.py new file mode 100644 index 0000000..6541a6e --- /dev/null +++ b/tests/test_problem_zoo/test_poisson_2d_square.py @@ -0,0 +1,7 @@ +import torch +import pytest + +from pina.problem.zoo import Poisson2DSquareProblem + +def test_constructor(): + Poisson2DSquareProblem() \ No newline at end of file