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

fnn update, pinn torch models, tests update. (#88)

Browse Source 
* fnn update, remove labeltensors
* allow custom torch models
* updating tests

---------

Co-authored-by: Dario Coscia <dariocoscia@Dario-Coscia.local>
Co-authored-by: Dario Coscia <dariocoscia@dhcp-031.eduroam.sissa.it>
This commit is contained in:
Dario Coscia
2023-05-02 15:19:48 +02:00
committed by Nicola Demo
parent c8fb7715c4
commit be11110bb2
11 changed files with 149 additions and 177 deletions
Download Patch File Download Diff File Expand all files Collapse all files

58
tests/test_pinn.py
View File

@@ -1,7 +1,7 @@
import torch
import pytest
from pina import LabelTensor, Condition, Span, PINN
from pina import LabelTensor, Condition, CartesianDomain, PINN
from pina.problem import SpatialProblem
from pina.model import FeedForward
from pina.operators import nabla
@@ -11,7 +11,7 @@ out_ = LabelTensor(torch.tensor([[0.]]), ['u'])
class Poisson(SpatialProblem):
output_variables = ['u']
spatial_domain = Span({'x': [0, 1], 'y': [0, 1]})
spatial_domain = CartesianDomain({'x': [0, 1], 'y': [0, 1]})
def laplace_equation(input_, output_):
force_term = (torch.sin(input_.extract(['x'])*torch.pi) *
@@ -25,19 +25,19 @@ class Poisson(SpatialProblem):
conditions = {
'gamma1': Condition(
location=Span({'x': [0, 1], 'y': 1}),
location=CartesianDomain({'x': [0, 1], 'y': 1}),
function=nil_dirichlet),
'gamma2': Condition(
location=Span({'x': [0, 1], 'y': 0}),
location=CartesianDomain({'x': [0, 1], 'y': 0}),
function=nil_dirichlet),
'gamma3': Condition(
location=Span({'x': 1, 'y': [0, 1]}),
location=CartesianDomain({'x': 1, 'y': [0, 1]}),
function=nil_dirichlet),
'gamma4': Condition(
location=Span({'x': 0, 'y': [0, 1]}),
location=CartesianDomain({'x': 0, 'y': [0, 1]}),
function=nil_dirichlet),
'D': Condition(
location=Span({'x': [0, 1], 'y': [0, 1]}),
location=CartesianDomain({'x': [0, 1], 'y': [0, 1]}),
function=laplace_equation),
'data': Condition(
input_points=in_,
@@ -53,15 +53,33 @@ class Poisson(SpatialProblem):
truth_solution = poisson_sol
problem = Poisson()
class myFeature(torch.nn.Module):
"""
Feature: sin(x)
"""
model = FeedForward(problem.input_variables, problem.output_variables)
def __init__(self):
super(myFeature, self).__init__()
def forward(self, x):
t = (torch.sin(x.extract(['x'])*torch.pi) *
torch.sin(x.extract(['y'])*torch.pi))
return LabelTensor(t, ['sin(x)sin(y)'])
problem = Poisson()
model = FeedForward(len(problem.input_variables),len(problem.output_variables))
model_extra_feat = FeedForward(len(problem.input_variables) + 1,len(problem.output_variables))
def test_constructor():
PINN(problem, model)
def test_constructor_extra_feats():
PINN(problem, model_extra_feat, [myFeature()])
def test_span_pts():
pinn = PINN(problem, model)
n = 10
@@ -133,6 +151,28 @@ def test_train_2():
assert list(pinn.history_loss.keys()) == truth_key
def test_train_extra_feats():
pinn = PINN(problem, model_extra_feat, [myFeature()])
boundaries = ['gamma1', 'gamma2', 'gamma3', 'gamma4']
n = 10
pinn.span_pts(n, 'grid', locations=boundaries)
pinn.span_pts(n, 'grid', locations=['D'])
pinn.train(5)
def test_train_2_extra_feats():
boundaries = ['gamma1', 'gamma2', 'gamma3', 'gamma4']
n = 10
expected_keys = [[], list(range(0, 50, 3))]
param = [0, 3]
for i, truth_key in zip(param, expected_keys):
pinn = PINN(problem, model_extra_feat, [myFeature()])
pinn.span_pts(n, 'grid', locations=boundaries)
pinn.span_pts(n, 'grid', locations=['D'])
pinn.train(50, save_loss=i)
assert list(pinn.history_loss.keys()) == truth_key
def test_train_with_optimizer_kwargs():
boundaries = ['gamma1', 'gamma2', 'gamma3', 'gamma4']
n = 10