Rename files

tests/test_callback/test_adaptive_refinement_callback.py

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+from pina.solver import PINN
+from pina.trainer import Trainer
+from pina.model import FeedForward
+from pina.problem.zoo import Poisson2DSquareProblem as Poisson
+from pina.callback import R3Refinement
+
+
+# make the problem
+poisson_problem = Poisson()
+boundaries = ['g1', 'g2', 'g3', 'g4']
+n = 10
+poisson_problem.discretise_domain(n, 'grid', domains=boundaries)
+poisson_problem.discretise_domain(n, 'grid', domains='D')
+model = FeedForward(len(poisson_problem.input_variables),
+                    len(poisson_problem.output_variables))
+
+# make the solver
+solver = PINN(problem=poisson_problem, model=model)
+
+
+# def test_r3constructor():
+#     R3Refinement(sample_every=10)
+
+
+# def test_r3refinment_routine():
+#     # make the trainer
+#     trainer = Trainer(solver=solver,
+#                       callback=[R3Refinement(sample_every=1)],
+#                       accelerator='cpu',
+#                       max_epochs=5)
+#     trainer.train()
+
+# def test_r3refinment_routine():
+#     model = FeedForward(len(poisson_problem.input_variables),
+#                     len(poisson_problem.output_variables))
+#     solver = PINN(problem=poisson_problem, model=model)
+#     trainer = Trainer(solver=solver,
+#                       callback=[R3Refinement(sample_every=1)],
+#                       accelerator='cpu',
+#                       max_epochs=5)
+#     before_n_points = {loc : len(pts) for loc, pts in trainer.solver.problem.input_pts.items()}
+#     trainer.train()
+#     after_n_points = {loc : len(pts) for loc, pts in trainer.solver.problem.input_pts.items()}
+#     assert before_n_points == after_n_points