Rename files

pina/adaptive_function/__init__.py

@@ -14,7 +14,7 @@ __all__ = [
     "AdaptiveExp",
 ]
 
-from .adaptive_func import (
+from .adaptive_function import (
     AdaptiveReLU,
     AdaptiveSigmoid,
     AdaptiveTanh,
@@ -28,4 +28,4 @@ from .adaptive_func import (
     AdaptiveSIREN,
     AdaptiveExp,
 )
-from .adaptive_func_interface import AdaptiveActivationFunctionInterface
+from .adaptive_function_interface import AdaptiveActivationFunctionInterface

pina/adaptive_function/adaptive_function.py

@@ -2,7 +2,7 @@
 
 import torch
 from ..utils import check_consistency
-from .adaptive_func_interface import AdaptiveActivationFunctionInterface
+from .adaptive_function_interface import AdaptiveActivationFunctionInterface
 
 
 class AdaptiveReLU(AdaptiveActivationFunctionInterface):

pina/callback/__init__.py

@@ -6,5 +6,5 @@ __all__ = [
 ]
 
 from .optimizer_callback import SwitchOptimizer
-from .adaptive_refinment_callback import R3Refinement
+from .adaptive_refinement_callback import R3Refinement
 from .processing_callback import MetricTracker, PINAProgressBar

pina/model/__init__.py

@@ -16,9 +16,9 @@ __all__ = [
 from .feed_forward import FeedForward, ResidualFeedForward
 from .multi_feed_forward import MultiFeedForward
 from .deeponet import DeepONet, MIONet
-from .fno import FNO, FourierIntegralKernel
-from .base_no import KernelNeuralOperator
-from .avno import AveragingNeuralOperator
-from .lno import LowRankNeuralOperator
+from .fourier_neural_operator import FNO, FourierIntegralKernel
+from .kernel_neural_operator import KernelNeuralOperator
+from .average_neural_operator import AveragingNeuralOperator
+from .low_rank_neural_operator import LowRankNeuralOperator
 from .spline import Spline
-from .gno import GraphNeuralOperator
+from .graph_neural_operator import GraphNeuralOperator

pina/model/average_neural_operator.py

@@ -3,7 +3,7 @@
 import torch
 from torch import nn, cat
 from .block import AVNOBlock
-from .base_no import KernelNeuralOperator
+from .kernel_neural_operator import KernelNeuralOperator
 from ..utils import check_consistency
 
 

pina/model/block/__init__.py

@@ -25,11 +25,11 @@ from .spectral import (
     SpectralConvBlock2D,
     SpectralConvBlock3D,
 )
-from .fourier import FourierBlock1D, FourierBlock2D, FourierBlock3D
-from .pod import PODBlock
+from .fourier_block import FourierBlock1D, FourierBlock2D, FourierBlock3D
+from .pod_block import PODBlock
 from .orthogonal import OrthogonalBlock
 from .embedding import PeriodicBoundaryEmbedding, FourierFeatureEmbedding
-from .avno_layer import AVNOBlock
-from .lowrank_layer import LowRankBlock
-from .rbf_layer import RBFBlock
+from .average_neural_operator_block import AVNOBlock
+from .lowrank_block import LowRankBlock
+from .rbf_block import RBFBlock
 from .gno_block import GNOBlock

pina/model/block/average_neural_operator_block.py

@@ -1,7 +1,7 @@
 """ Module for Averaging Neural Operator Layer class. """
 
 from torch import nn, mean
-from pina.utils import check_consistency
+from ...utils import check_consistency
 
 
 class AVNOBlock(nn.Module):

pina/model/block/fourier_block.py

@@ -2,7 +2,7 @@ import torch
 import torch.nn as nn
 from ...utils import check_consistency
 
-from pina.model.block import (
+from . import (
     SpectralConvBlock1D,
     SpectralConvBlock2D,
     SpectralConvBlock3D,

pina/model/block/messa_passing.py

@@ -1,11 +0,0 @@
-""" Module for Averaging Neural Operator Layer class. """
-
-from torch import nn, mean
-from torch_geometric.nn import MessagePassing, InstanceNorm, radius_graph
-
-from pina.utils import check_consistency
-
-
-class MessagePassingBlock(nn.Module):
-
-

pina/model/fourier_neural_operator.py

@@ -7,8 +7,8 @@ import torch.nn as nn
 from ..label_tensor import LabelTensor
 import warnings
 from ..utils import check_consistency
-from .block.fourier import FourierBlock1D, FourierBlock2D, FourierBlock3D
-from .base_no import KernelNeuralOperator
+from .block.fourier_block import FourierBlock1D, FourierBlock2D, FourierBlock3D
+from .kernel_neural_operator import KernelNeuralOperator
 
 
 class FourierIntegralKernel(torch.nn.Module):

pina/model/graph_neural_operator.py

@@ -1,7 +1,7 @@
 import torch
 from torch.nn import Tanh
 from .block import GNOBlock
-from .base_no import KernelNeuralOperator
+from .kernel_neural_operator import KernelNeuralOperator
 
 
 class GraphNeuralKernel(torch.nn.Module):

pina/model/low_rank_neural_operator.py

@@ -5,8 +5,8 @@ from torch import nn, cat
 
 from ..utils import check_consistency
 
-from .base_no import KernelNeuralOperator
-from .block.lowrank_layer import LowRankBlock
+from .kernel_neural_operator import KernelNeuralOperator
+from .block.lowrank_block import LowRankBlock
 
 
 class LowRankNeuralOperator(KernelNeuralOperator):

pina/problem/__init__.py

@@ -8,6 +8,6 @@ __all__ = [
 
 from .abstract_problem import AbstractProblem
 from .spatial_problem import SpatialProblem
-from .timedep_problem import TimeDependentProblem
+from .time_dependent_problem import TimeDependentProblem
 from .parametric_problem import ParametricProblem
 from .inverse_problem import InverseProblem

pina/solver/__init__.py

@@ -17,5 +17,5 @@ __all__ = [
 from .solver import SolverInterface, SingleSolverInterface, MultiSolverInterface
 from .physic_informed_solver import *
 from .supervised import SupervisedSolver
-from .rom import ReducedOrderModelSolver
+from .reduced_order_model import ReducedOrderModelSolver
 from .garom import GAROM

pina/solver/reduced_order_model.py

@@ -2,7 +2,7 @@
 
 import torch
 
-from pina.solver import SupervisedSolver
+from . import SupervisedSolver
 
 
 class ReducedOrderModelSolver(SupervisedSolver):

tests/test_blocks/test_pod.py

@@ -1,7 +1,7 @@
 import torch
 import pytest
 
-from pina.model.block.pod import PODBlock
+from pina.model.block.pod_block import PODBlock
 
 x = torch.linspace(-1, 1, 100)
 toy_snapshots = torch.vstack([torch.exp(-x**2)*c for c in torch.linspace(0, 1, 10)])

tests/test_blocks/test_rbf.py

@@ -2,7 +2,7 @@ import torch
 import pytest
 import math
 
-from pina.model.block.rbf_layer import RBFBlock
+from pina.model.block.rbf_block import RBFBlock
 
 x = torch.linspace(-1, 1, 100)
 toy_params = torch.linspace(0, 1, 10).unsqueeze(1)