folivo/PINA
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Refactoring solvers (#541)

Browse Source 
* Refactoring solvers

* Simplify logic compile
* Improve and update doc
* Create SupervisedSolverInterface
* Specialize SupervisedSolver and ReducedOrderModelSolver
* Create EnsembleSolverInterface + EnsembleSupervisedSolver
* Create tests ensemble solvers

* formatter

* codacy

* fix issues + speedup test
This commit is contained in:
Dario Coscia
2025-04-09 14:51:42 +02:00
parent 485c8dd789
commit 6dd7bd2825
37 changed files with 1514 additions and 510 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
tests/test_solver/test_gradient_pinn.py
View File

@@ -30,9 +30,9 @@ class DummyTimeProblem(TimeDependentProblem):
# define problems
problem = Poisson()
problem.discretise_domain(50)
problem.discretise_domain(10)
inverse_problem = InversePoisson()
inverse_problem.discretise_domain(50)
inverse_problem.discretise_domain(10)
# reduce the number of data points to speed up testing
data_condition = inverse_problem.conditions["data"]
@@ -40,9 +40,9 @@ data_condition.input = data_condition.input[:10]
data_condition.target = data_condition.target[:10]
# add input-output condition to test supervised learning
input_pts = torch.rand(50, len(problem.input_variables))
input_pts = torch.rand(10, len(problem.input_variables))
input_pts = LabelTensor(input_pts, problem.input_variables)
output_pts = torch.rand(50, len(problem.output_variables))
output_pts = torch.rand(10, len(problem.output_variables))
output_pts = LabelTensor(output_pts, problem.output_variables)
problem.conditions["data"] = Condition(input=input_pts, target=output_pts)