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* Adding black as dev dependency
* Formatting pina code
* Formatting tests
This commit is contained in:
Dario Coscia
2025-02-24 11:26:49 +01:00
committed by Nicola Demo
parent 4c4482b155
commit 42ab1a666b
77 changed files with 1170 additions and 924 deletions
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52
pina/problem/zoo/inverse_poisson_2d_square.py
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@@ -1,4 +1,4 @@
""" Definition of the inverse Poisson problem on a square domain."""
"""Definition of the inverse Poisson problem on a square domain."""
import torch
from pina import Condition, LabelTensor
@@ -8,43 +8,49 @@ from pina.domain import CartesianDomain
from pina.equation.equation import Equation
from pina.equation.equation_factory import FixedValue
def laplace_equation(input_, output_, params_):
"""
Implementation of the laplace equation.
"""
force_term = torch.exp(- 2*(input_.extract(['x']) - params_['mu1'])**2
- 2*(input_.extract(['y']) - params_['mu2'])**2)
delta_u = laplacian(output_, input_, components=['u'], d=['x', 'y'])
force_term = torch.exp(
-2 * (input_.extract(["x"]) - params_["mu1"]) ** 2
- 2 * (input_.extract(["y"]) - params_["mu2"]) ** 2
)
delta_u = laplacian(output_, input_, components=["u"], d=["x", "y"])
return delta_u - force_term
class InversePoisson2DSquareProblem(SpatialProblem, InverseProblem):
"""
Implementation of the inverse 2-dimensional Poisson problem
Implementation of the inverse 2-dimensional Poisson problem
on a square domain, with parameter domain [-1, 1] x [-1, 1].
"""
output_variables = ['u']
output_variables = ["u"]
x_min, x_max = -2, 2
y_min, y_max = -2, 2
data_input = LabelTensor(torch.rand(10, 2), ['x', 'y'])
data_output = LabelTensor(torch.rand(10, 1), ['u'])
spatial_domain = CartesianDomain({'x': [x_min, x_max], 'y': [y_min, y_max]})
unknown_parameter_domain = CartesianDomain({'mu1': [-1, 1], 'mu2': [-1, 1]})
data_input = LabelTensor(torch.rand(10, 2), ["x", "y"])
data_output = LabelTensor(torch.rand(10, 1), ["u"])
spatial_domain = CartesianDomain({"x": [x_min, x_max], "y": [y_min, y_max]})
unknown_parameter_domain = CartesianDomain({"mu1": [-1, 1], "mu2": [-1, 1]})
domains = {
'g1': CartesianDomain({'x': [x_min, x_max], 'y': y_max}),
'g2': CartesianDomain({'x': [x_min, x_max], 'y': y_min}),
'g3': CartesianDomain({'x': x_max, 'y': [y_min, y_max]}),
'g4': CartesianDomain({'x': x_min, 'y': [y_min, y_max]}),
'D': CartesianDomain({'x': [x_min, x_max], 'y': [y_min, y_max]}),
"g1": CartesianDomain({"x": [x_min, x_max], "y": y_max}),
"g2": CartesianDomain({"x": [x_min, x_max], "y": y_min}),
"g3": CartesianDomain({"x": x_max, "y": [y_min, y_max]}),
"g4": CartesianDomain({"x": x_min, "y": [y_min, y_max]}),
"D": CartesianDomain({"x": [x_min, x_max], "y": [y_min, y_max]}),
}
conditions = {
'nil_g1': Condition(domain='g1', equation=FixedValue(0.0)),
'nil_g2': Condition(domain='g2', equation=FixedValue(0.0)),
'nil_g3': Condition(domain='g3', equation=FixedValue(0.0)),
'nil_g4': Condition(domain='g4', equation=FixedValue(0.0)),
'laplace_D': Condition(domain='D', equation=Equation(laplace_equation)),
'data': Condition(
input_points=data_input.extract(['x', 'y']),
output_points=data_output)
"nil_g1": Condition(domain="g1", equation=FixedValue(0.0)),
"nil_g2": Condition(domain="g2", equation=FixedValue(0.0)),
"nil_g3": Condition(domain="g3", equation=FixedValue(0.0)),
"nil_g4": Condition(domain="g4", equation=FixedValue(0.0)),
"laplace_D": Condition(domain="D", equation=Equation(laplace_equation)),
"data": Condition(
input_points=data_input.extract(["x", "y"]),
output_points=data_output,
),
}