Merge branch 'boschresearch:main' into main

.github/workflows/docs-gh-pages.yml

@@ -0,0 +1,53 @@
+name: documentation
+
+on:
+  workflow_dispatch:
+  push:
+    branches: [ main ]
+  pull_request:
+    branches: [ main ]
+
+# Sets permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages
+permissions:
+  contents: read
+  pages: write
+  id-token: write
+
+# Allow only one concurrent deployment, skipping runs queued between the run in-progress and latest queued.
+# However, do NOT cancel in-progress runs as we want to allow these production deployments to complete.
+concurrency:
+  group: "pages"
+  cancel-in-progress: false
+
+
+jobs:
+  build-docs:
+    runs-on: [ubuntu-latest]
+    container: python:3.10-bookworm
+    steps:
+      - uses: actions/checkout@v3
+      - name: Install dependencies
+        run: |
+          apt-get update
+          apt-get -y install xvfb pandoc
+          python -m pip install --upgrade pip setuptools setuptools_scm wheel
+          pip install -e .[docs]
+          pip install -r docs/requirements.txt
+      - name: Build documentation
+        run: |
+          sphinx-build -b html docs/ _site
+      - name: Upload artifact
+        uses: actions/upload-pages-artifact@v3
+
+  # Deployment job
+  deploy-docs:
+    environment:
+      name: github-pages
+      url: ${{ steps.deployment.outputs.page_url }}
+    runs-on: ubuntu-latest
+    if: github.ref_name == 'main'
+    needs: build-docs
+    steps:
+      - name: Deploy to GitHub Pages
+        id: deployment
+        uses: actions/deploy-pages@v4

.github/workflows/pypi-deploy.yml

@@ -0,0 +1,80 @@
+name: Build and upload to PyPI
+
+on:
+  release:
+    type: [published]
+
+env:
+  CIBW_BUILD: cp37-* cp38-* cp39-* cp310-*
+  CIBW_BEFORE_BUILD: pip install cython
+  CIBW_MANYLINUX_X86_64_IMAGE: manylinux2014
+  CIBW_MANYLINUX_I686_IMAGE: manylinux2014
+
+jobs:
+  build_wheels:
+    name: Build wheels on [ ubuntu-latest ]
+    runs-on: [ ubuntu-latest ]
+    strategy:
+      matrix:
+        os: [ubuntu-latest] #, windows-latest]
+    steps:
+      - uses: actions/checkout@v2
+        with:
+          fetch-depth: 0
+
+      - uses: actions/setup-python@v2
+        name: Install Python
+        with:
+          python-version: '3.10'
+
+      - name: Install cibuildwheel
+        run: |
+          # python -m pip install cibuildwheel
+          pip install -U setuptools setuptools_scm wheel
+      - name: Build wheels
+        run: |
+          # python -m cibuildwheel --output-dir wheelhouse
+          python setup.py bdist_wheel
+      - uses: actions/upload-artifact@v2
+        with:
+          path: ./dist/*.whl
+
+
+  build_sdist:
+    name: Build source distribution
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+        with:
+          fetch-depth: 0
+
+      - uses: actions/setup-python@v2
+        name: Install Python
+        with:
+          python-version: '3.10'
+
+      - name: Install setuptools
+        run: |
+          pip install -U setuptools setuptools_scm wheel
+
+      - name: Build sdist
+        run: python setup.py sdist
+
+      - uses: actions/upload-artifact@v2
+        with:
+          path: dist/*.tar.gz
+
+  upload_pypi:
+    needs: [build_wheels, build_sdist]
+    runs-on: ubuntu-latest
+    if: github.event_name == 'release' && github.event.action == 'published'
+    steps:
+      - uses: actions/download-artifact@v2
+        with:
+          name: artifact
+          path: dist
+
+      - uses: pypa/gh-action-pypi-publish@master
+        with:
+          user: __token__
+          password: ${{ secrets.upload_pypi }}

.github/workflows/python-package.yml → .github/workflows/pytest.yml

@@ -1,11 +1,11 @@
 # This workflow will install Python dependencies, run tests and lint with a variety of Python versions
 # For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
 
-name: Python package
+name: Unit tests
 
 on:
   push:
-    branches: '**'
+    branches: [ main ]
   pull_request:
     branches: [ main ]
 
@@ -16,17 +16,18 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.7, 3.8, 3.9]
+        python-version: ["3.7", "3.8", "3.9", "3.10"]
 
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v4
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
+        pip install -U setuptools setuptools_scm wheel
         python -m pip install flake8 pytest pytest-cov
         python -m pip install -e .
         if [ -f requirements.txt ]; then pip install -r requirements.txt; fi

CHANGELOG.rst

@@ -12,4 +12,8 @@ Version 1.0.1
 =============
     - Updated documentation and error messages
     - Simplyfied creation/definition of DeepONets
-    - Add more evalution types for the DeepONet
+    - Add more evalution types for the DeepONet
+
+Version 1.0.2
+=============
+    - Test for python versions up to 3.10

docs/conf.py

@@ -78,6 +78,8 @@
     "sphinx.ext.ifconfig",
     "sphinx.ext.mathjax",
     "sphinx.ext.napoleon",
+    "nbsphinx",
+    "nbsphinx_link",
 ]
 
 # Add any paths that contain templates here, relative to this directory.

docs/requirements.txt

@@ -13,4 +13,11 @@ trimesh>=3.9.19
 shapely>=1.7.1
 rtree>=0.9.7
 scipy>=1.6.3
-networkx>=2.5.1 
+networkx>=2.5.1
+jupyter
+nbsphinx
+nbsphinx-link
+sphinx_rtd_theme>=1.0
+ipywidgets
+ipython<8.17.0 # https://github.com/ipython/ipython/issues/14235
+ipykernel

docs/tutorial/Introduction_Tutorial_PINNs.nblink

@@ -0,0 +1,3 @@
+{
+    "path": "../../examples/tutorial/Introduction_Tutorial_PINNs.ipynb"
+}

docs/tutorial/main_page.rst

@@ -1,48 +1,43 @@
 =========================
 The TorchPhysics Tutorial
 =========================
-Here one can find all important information and knowledge to get started with the 
+Here one can find all important information and knowledge to get started with the
 software library TorchPhysics.
 
-In order to make it as easy and user-friendly as possible for all users, 
+In order to make it as easy and user-friendly as possible for all users,
 both complete novices and professionals in Machine Learning and PDEs, to get started, the tutorial
 starts with some basics regarding differential equations and neural networks. For more
 experienced users, these points can be skipped.
 
-Afterward, we give a rough overview of different Deep Learning approaches for solving 
+Afterward, we give a rough overview of different Deep Learning approaches for solving
 differential equations, with a focus on PINNs and DeepONet.
 
 The main and final topic is the use of TorchPhysics. Here we split the tutorial into two parts.
-The first part, guides you along some implementations of different small examples, while showing 
+The first part, guides you along some implementations of different small examples, while showing
 all the important aspects and steps to solve a differential equation in TorchPhysics. This tutorial
-series is aimed at an audience which is more interested on the direct utilization of the library 
+series is aimed at an audience which is more interested on the direct utilization of the library
 and for getting a fast and small overview of the possibilities.
 
-To get a deeper understanding of the library, we show in the second part how the library is 
+To get a deeper understanding of the library, we show in the second part how the library is
 internally structured. This series is more aimed for users who plan to add or change functionalities.
 
 
-Basics of Deep Learning and Differential Equations
-=====================================================
-Will be added in the future.
+.. toctree::
+   :maxdepth: 1
+   :caption: Basics tutorial
 
+   Introduction_Tutorial_PINNs
 
-Overview of Deep Learning Methods for Differential Equations
-============================================================
-Will be added in the future.
 
+.. toctree::
+   :maxdepth: 1
+   :caption: Applied tutorial
 
-Usage of TorchPhysics
-=====================
-Like mentioned at the beginning, here we explain the aspects of TorchPhysics in more 
-detail. We split the tutorial into two categories:
+   applied_tutorial_start
 
-1) A more applied tutorial to learn TorchPhysics by implementing some examples.
-   All basics features will be explained. The start can be found here_.
 
-2) A more in depth tutorial that focuses more on the library architecture. This 
-   tutorial begins on this page_.
+.. toctree::
+   :maxdepth: 1
+   :caption: In depth tutorial
 
-
-.. _here : applied_tutorial_start.html
-.. _page : tutorial_start.html
+   tutorial_start

examples/tutorial/Introduction_Tutorial_PINNs.ipynb

@@ -65,7 +65,7 @@
    "id": "8da6279e-83c2-41ed-a56b-453b21f05d11",
    "metadata": {},
    "source": [
-    "# Recall PINNs\n",
+    "## Recall PINNs\n",
     "The goal is to find a neural network $u_\\theta: \\overline{\\Omega\\times I} \\to \\mathbb{R}$, which approximately satisfies all four conditions of the PDE problem above, where $\\theta$ are the trainable parameters of the neural network.\n",
     "Let us shortly recall the main idea behind PINNs.\n",
     "\n",
@@ -105,7 +105,7 @@
    "id": "8f0db4a0-cace-4d21-845f-f34680880d7d",
    "metadata": {},
    "source": [
-    "# Translating the PDE Problem into the Language of TorchPhysics\n",
+    "## Translating the PDE Problem into the Language of TorchPhysics\n",
     "Translating the PDE problem into the framework of TorchPhysics works in a convenient and intuitive way, as the notation is close to the mathematical formulation. The general procedure can be devided into five steps. Also when solving other problems with TorchPhysics, such as parameter identification or variational problems, the same steps can be applied, see also the further [tutorials](https://torchphysics.readthedocs.io/en/latest/tutorial/tutorial_start.html) or [examples](https://torchphysics.readthedocs.io/en/latest/examples.html)."
    ]
   },
@@ -529,7 +529,7 @@
    "id": "31d80c43-5879-401c-8212-0e4a5fd6514c",
    "metadata": {},
    "source": [
-    "# Training based on Pytorch Lightning \n",
+    "## Training based on Pytorch Lightning \n",
     "In order to train a model, TorchPhysics makes use of the Pytorch Lightning library, which hence must be imported. Further, we import \"os\" so that GPUs can be used for the calculations."
    ]
   },
@@ -622,11 +622,13 @@
    "outputs": [],
    "source": [
     "# Start the training\n",
-    "trainer = pl.Trainer(gpus=device, # or None if CPU is used\n",
-    "                     max_steps=5000, # number of training steps\n",
-    "                     logger=False,\n",
-    "                     benchmark=True,\n",
-    "                     checkpoint_callback=False)\n",
+    "trainer = pl.Trainer(\n",
+    "    gpus=device, # or None if CPU is used\n",
+    "    max_steps=5000, # number of training steps\n",
+    "    logger=False,\n",
+    "    benchmark=True,\n",
+    "    # checkpoint_callback=False  # Uncomment this for more verbose\n",
+    ")\n",
     "\n",
     "trainer.fit(solver) # start training"
    ]
@@ -648,7 +650,7 @@
    "id": "bac7c186-2be3-4ce0-a252-527ae5083019",
    "metadata": {},
    "source": [
-    "# Visualization\n",
+    "## Visualization\n",
     "Torchphysics provides built-in functionalities for visualizing the outcome of the neural network.\n",
     "As a first step, for the 2D heat equation example one might be interested in creating a contour plot for the heat distribution inside of the room at some fixed time.\n",
     "\n",
@@ -862,7 +864,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -876,7 +878,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.4"
+   "version": "3.10.13"
   }
  },
  "nbformat": 4,

pyproject.toml

@@ -3,6 +3,6 @@
 requires = ["setuptools>=46.1.0", "setuptools_scm[toml]>=5", "wheel"]
 build-backend = "setuptools.build_meta"
 
-#[tool.setuptools_scm]
+[tool.setuptools_scm]
 # See configuration details in https://github.com/pypa/setuptools_scm
-#version_scheme = "no-guess-dev"
+version_scheme = "no-guess-dev"

setup.cfg

@@ -6,7 +6,6 @@
 name = torchphysics
 description = PyTorch implementation of Deep Learning methods to solve differential equations
 author = Nick Heilenkötter, Tom Freudenberg
-version = 1.0.1
 author_email = [email protected], [email protected]
 license = Apache-2.0
 long_description = file: README.rst
@@ -65,11 +64,11 @@ exclude =
 [options.extras_require]
 # Add here additional requirements for extra features, to install with:
 # `pip install torchphysics[all]` like:
-all = 
+all =
     trimesh>=3.9.19
     shapely>=1.7.1
     rtree>=0.9.7
-    networkx>=2.5.1 
+    networkx>=2.5.1
 
 # Add here test requirements (semicolon/line-separated)
 testing =
@@ -135,4 +134,4 @@ exclude =
 # This will be used when updating. Do not change!
 version = 4.0.1
 package = torchphysics
-extensions = 
+extensions =

setup.py

@@ -10,7 +10,7 @@
 
 if __name__ == "__main__":
     try:
-        setup(use_scm_version=False) #use_scm_version={"version_scheme": "no-guess-dev"}
+        setup(use_scm_version={"version_scheme": "no-guess-dev"})
     except:  # noqa
         print(
             "\n\nAn error occurred while building the project, "