Lightining update (#104)

* multiple functions for version 0.0 * lightining update * minor changes * data pinn loss added --------- Co-authored-by: Nicola Demo <demo.nicola@gmail.com> Co-authored-by: Dario Coscia <dariocoscia@cli-10-110-3-125.WIFIeduroamSTUD.units.it> Co-authored-by: Dario Coscia <dariocoscia@Dario-Coscia.station> Co-authored-by: Dario Coscia <dariocoscia@Dario-Coscia.local> Co-authored-by: Dario Coscia <dariocoscia@192.168.1.38>
2023-06-07 15:34:43 +02:00
parent 0e3625de80
commit 63fd068988
16 changed files with 710 additions and 603 deletions
--- a/tests/test_problem.py
+++ b/tests/test_problem.py
@@ -0,0 +1,97 @@
+import torch
+import pytest
+
+from pina.problem import SpatialProblem
+from pina.operators import nabla
+from pina import LabelTensor, Condition
+from pina.geometry import CartesianDomain
+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))
+    nabla_u = nabla(output_.extract(['u']), input_)
+    return nabla_u - force_term
+
+my_laplace = Equation(laplace_equation)
+in_ = LabelTensor(torch.tensor([[0., 1.]], requires_grad=True), ['x', 'y'])
+out_ = LabelTensor(torch.tensor([[0.]], requires_grad=True), ['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(
+            location=CartesianDomain({'x': [0, 1], 'y': [0, 1]}),
+            equation=my_laplace),
+        'data': Condition(
+            input_points=in_,
+            output_points=out_)
+    }
+
+    def poisson_sol(self, pts):
+        return -(
+            torch.sin(pts.extract(['x'])*torch.pi) *
+            torch.sin(pts.extract(['y'])*torch.pi)
+        )/(2*torch.pi**2)
+
+    truth_solution = poisson_sol
+
+
+# make the problem
+poisson_problem = Poisson()
+
+
+def test_discretise_domain():
+    n = 10
+    boundaries = ['gamma1', 'gamma2', 'gamma3', 'gamma4']
+    poisson_problem.discretise_domain(n, 'grid', locations=boundaries)
+    for b in boundaries:
+        assert poisson_problem.input_pts[b].shape[0] == n
+    poisson_problem.discretise_domain(n, 'random', locations=boundaries)
+    for b in boundaries:
+        assert poisson_problem.input_pts[b].shape[0] == n
+
+    poisson_problem.discretise_domain(n, 'grid', locations=['D'])
+    assert poisson_problem.input_pts['D'].shape[0] == n**2
+    poisson_problem.discretise_domain(n, 'random', locations=['D'])
+    assert poisson_problem.input_pts['D'].shape[0] == n
+
+    poisson_problem.discretise_domain(n, 'latin', locations=['D'])
+    assert poisson_problem.input_pts['D'].shape[0] == n
+
+    poisson_problem.discretise_domain(n, 'lh', locations=['D'])
+    assert poisson_problem.input_pts['D'].shape[0] == n
+
+def test_sampling_all_args():
+    n = 10
+    poisson_problem.discretise_domain(n, 'grid', locations=['D'])
+
+def test_sampling_all_kwargs():
+    n = 10
+    poisson_problem.discretise_domain(n=n, mode='latin', locations=['D'])
+
+def test_sampling_dict():
+    n = 10
+    poisson_problem.discretise_domain(
+        {'variables': ['x', 'y'], 'mode': 'grid', 'n': n}, locations=['D'])
+
+def test_sampling_mixed_args_kwargs():
+    n = 10
+    with pytest.raises(ValueError):
+        poisson_problem.discretise_domain(n, mode='latin', locations=['D'])