Fix codacy warnings

pina/model/block/message_passing/en_equivariant_network_block.py

@@ -41,7 +41,7 @@ class EnEquivariantNetworkBlock(MessagePassing):
         DOI: `<https://doi.org/10.48550/arXiv.2102.09844>`_.
     """
 
-    def __init__(
+    def __init__(  # pylint: disable=R0913, R0917
         self,
         node_feature_dim,
         edge_feature_dim,
@@ -143,7 +143,9 @@ def __init__(
                 func=activation,
             )
 
-    def forward(self, x, pos, edge_index, edge_attr=None, vel=None):
+    def forward(
+        self, x, pos, edge_index, edge_attr=None, vel=None
+    ):  # pylint: disable=R0917
         """
         Forward pass of the block, triggering the message-passing routine.
 
@@ -169,7 +171,9 @@ def forward(self, x, pos, edge_index, edge_attr=None, vel=None):
             edge_index=edge_index, x=x, pos=pos, edge_attr=edge_attr, vel=vel
         )
 
-    def message(self, x_i, x_j, pos_i, pos_j, edge_attr):
+    def message(
+        self, x_i, x_j, pos_i, pos_j, edge_attr
+    ):  # pylint: disable=R0917
         """
         Compute the message to be passed between nodes and edges.
 
@@ -234,7 +238,9 @@ def aggregate(self, inputs, index, ptr=None, dim_size=None):
 
         return agg_message, agg_m_ij
 
-    def update(self, aggregated_inputs, x, pos, edge_index, vel):
+    def update(
+        self, aggregated_inputs, x, pos, edge_index, vel
+    ):  # pylint: disable=R0917
         """
         Update node features, positions, and optionally velocities.
 

pina/model/block/message_passing/equivariant_graph_neural_operator_block.py

@@ -23,7 +23,7 @@ class EquivariantGraphNeuralOperatorBlock(torch.nn.Module):
         <https://arxiv.org/abs/2401.11037>`_
     """
 
-    def __init__(
+    def __init__(  # pylint: disable=R0913, R0917
         self,
         node_feature_dim,
         edge_feature_dim,
@@ -101,7 +101,9 @@ def __init__(
             flow=flow,
         )
 
-    def forward(self, x, pos, vel, edge_index, edge_attr=None):
+    def forward(  # pylint: disable=R0917
+        self, x, pos, vel, edge_index, edge_attr=None
+    ):
         """
         Forward pass of the Equivariant Graph Neural Operator block.
 
@@ -182,7 +184,11 @@ def _convolution(self, x, einsum_idx, real, img):
         weights = torch.complex(real[..., :modes], img[..., :modes])
 
         # Convolution in Fourier space
-        fourier = torch.fft.rfftn(x, dim=[0])[:modes]
+        # torch.fft.rfftn and irfftn are callable functions, but pylint
+        # incorrectly flags them as E1102 (not callable).
+        fourier = torch.fft.rfftn(x, dim=[0])[:modes]  # pylint: disable=E1102
         out = torch.einsum(einsum_idx, fourier, weights)
 
-        return torch.fft.irfftn(out, s=x.shape[0], dim=0)
+        return torch.fft.irfftn(  # pylint: disable=E1102
+            out, s=x.shape[0], dim=0
+        )

pina/model/equivariant_graph_neural_operator.py

@@ -5,7 +5,9 @@
 from .block.message_passing import EquivariantGraphNeuralOperatorBlock
 
 
-class EquivariantGraphNeuralOperator(torch.nn.Module):
+# Disable pylint warnings for too few public methods (since this is a simple
+# model class in a standard PyTorch style)
+class EquivariantGraphNeuralOperator(torch.nn.Module):  # pylint: disable=R0903
     """
     Equivariant Graph Neural Operator (EGNO) for modeling 3D dynamics.
 
@@ -32,7 +34,9 @@ class EquivariantGraphNeuralOperator(torch.nn.Module):
         <https://arxiv.org/abs/2401.11037>`_
     """
 
-    def __init__(
+    # Disable pylint warnings for too many arguments in init (since this is a
+    # model class with many configurable parameters)
+    def __init__(  # pylint: disable=R0913, R0917, R0914
         self,
         n_egno_layers,
         node_feature_dim,