Dev updates

.github/workflows/monthly-tagger.yml

@@ -11,7 +11,7 @@ jobs:
     strategy:
       matrix:
         os: [windows-latest, macos-latest, ubuntu-latest]
-        python-version: [3.9, '3.10', '3.11', '3.12', '3.13'] 
+        python-version: ['3.10', '3.11', '3.12', '3.13', '3.14'] 
     steps:
     - uses: actions/checkout@v2
     - name: Set up Python

.github/workflows/tester.yml

@@ -1,7 +1,7 @@
 name: "Testing Pull Request"
 
 on:
-  pull_request:
+  pull_request_target:
     branches:
       - "master"
       - "dev"
@@ -13,7 +13,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [windows-latest, macos-latest, ubuntu-latest]
-        python-version: [3.9, '3.10', '3.11', '3.12', '3.13']
+        python-version: ['3.10', '3.11', '3.12', '3.13', '3.14']
 
     steps:
     - uses: actions/checkout@v4

.github/workflows/tutorial_exporter.yml

@@ -23,7 +23,7 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v5
       with:
-        python-version: 3.9
+        python-version: 3.10
 
     - name: Install dependencies
       run: |
@@ -91,7 +91,7 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v5
       with:
-        python-version: 3.9
+        python-version: 3.10
 
     - name: Install dependencies
       run: |

docs/source/_rst/_code.rst

@@ -95,6 +95,7 @@ Models
     MultiFeedForward <model/multi_feed_forward.rst>
     ResidualFeedForward <model/residual_feed_forward.rst>
     Spline <model/spline.rst>
+    SplineSurface <model/spline_surface.rst>
     DeepONet <model/deeponet.rst>
     MIONet <model/mionet.rst>
     KernelNeuralOperator <model/kernel_neural_operator.rst>
@@ -105,6 +106,8 @@ Models
     GraphNeuralOperator <model/graph_neural_operator.rst>
     GraphNeuralKernel <model/graph_neural_operator_integral_kernel.rst>
     PirateNet <model/pirate_network.rst>
+    EquivariantGraphNeuralOperator <model/equivariant_graph_neural_operator.rst>
+    SINDy <model/sindy.rst>
 
 Blocks
 -------------
@@ -134,6 +137,7 @@ Message Passing
     E(n) Equivariant Network Block <model/block/message_passing/en_equivariant_network_block.rst>
     Interaction Network Block <model/block/message_passing/interaction_network_block.rst>
     Radial Field Network Block <model/block/message_passing/radial_field_network_block.rst>
+    EquivariantGraphNeuralOperatorBlock <model/block/message_passing/equivariant_graph_neural_operator_block.rst>
 
 
 Reduction and Embeddings

docs/source/_rst/model/block/message_passing/equivariant_graph_neural_operator_block.rst

@@ -0,0 +1,7 @@
+EquivariantGraphNeuralOperatorBlock
+=====================================
+.. currentmodule:: pina.model.block.message_passing.equivariant_graph_neural_operator_block
+
+.. autoclass:: EquivariantGraphNeuralOperatorBlock
+   :members:
+   :show-inheritance:

docs/source/_rst/model/equivariant_graph_neural_operator.rst

@@ -0,0 +1,7 @@
+EquivariantGraphNeuralOperator
+=================================
+.. currentmodule:: pina.model.equivariant_graph_neural_operator
+
+.. autoclass:: EquivariantGraphNeuralOperator
+   :members:
+   :show-inheritance:

docs/source/_rst/model/sindy.rst

@@ -0,0 +1,7 @@
+SINDy
+=======================
+.. currentmodule:: pina.model.sindy
+
+.. autoclass:: SINDy
+   :members:
+   :show-inheritance:

docs/source/_rst/model/spline_surface.rst

@@ -0,0 +1,7 @@
+Spline Surface
+================
+.. currentmodule:: pina.model.spline_surface
+
+.. autoclass:: SplineSurface
+    :members:
+    :show-inheritance:

docs/source/_tutorial.rst

@@ -40,5 +40,6 @@ Supervised Learning
 - `Introductory Tutorial: Supervised Learning with PINA  <tutorial20/tutorial.html>`_
 - `Chemical Properties Prediction with Graph Neural Networks <tutorial15/tutorial.html>`_
 - `Reduced Order Model with Graph Neural Networks for Unstructured Domains <tutorial22/tutorial.html>`_
+- `Data-driven System Identification with SINDy <tutorial23/tutorial.html>`_
 - `Unstructured Convolutional Autoencoders with Continuous Convolution <tutorial4/tutorial.html>`_
 - `Reduced Order Modeling with POD-RBF and POD-NN Approaches for Fluid Dynamics <tutorial8/tutorial.html>`_