Files
PINA/tests/test_callback/test_adaptive_refinement_callback.py
Filippo Olivo 4177bfbb50 Fix Codacy Warnings (#477)
---------

Co-authored-by: Dario Coscia <dariocos99@gmail.com>
2025-03-19 17:48:18 +01:00

46 lines
1.6 KiB
Python

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