Update readme and add some more configs

.dockerignore

@@ -1 +1 @@
-.github
+.github

.github/workflows/build_docs.yml

@@ -26,17 +26,19 @@ jobs:
 
       - name: Install graphviz
         run: apt update && apt install -y graphviz-dev
-        
+
       - name: Install mesa-utils
-        run: apt-get update && apt-get install -y mesa-utils 
-       
+        run: apt-get update && apt-get install -y mesa-utils
+
       - name: Install dependencies
-        run: python3 -m pip install ".[docs]"
+        run: |
+          python3 -m pip install git+https://github.com/funsim/moola.git
+          python3 -m pip install ".[docs]"
 
       - name: Build docs
         run: jupyter book build -W .
 
-      - name: Upload artifact 
+      - name: Upload artifact
         uses: actions/upload-artifact@v7
         # always upload artifact, which can include error messages
         if: always()

.github/workflows/check_formatting.yml

@@ -32,6 +32,6 @@ jobs:
         run: |
           ruff check .
           ruff format --check .
-      
+
       - name: Mypy check
         run: python3 -m mypy .

.github/workflows/deploy.yml

@@ -15,7 +15,7 @@ concurrency:
   group: "pages"
   cancel-in-progress: true
 
-jobs:  
+jobs:
 
   check-formatting:
     uses: ./.github/workflows/check_formatting.yml
@@ -48,7 +48,7 @@ jobs:
     #     with:
     #       name: code-coverage-report
     #       path: "./public/code-coverage-report"
-  
+
       - name: Upload artifact
         uses: actions/upload-pages-artifact@v5
         with:

.github/workflows/pypi.yml

@@ -0,0 +1,44 @@
+name: PyPI
+
+on:
+  push:
+    branches:
+      - "main"
+    tags:
+      - "v*"
+  pull_request:
+    branches:
+      - "main"
+
+
+jobs:
+  dist:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v6
+
+    - name: Build SDist and wheel
+      run: pipx run build
+
+    - uses: actions/upload-artifact@v7
+      with:
+        path: dist/*
+
+    - name: Check metadata
+      run: pipx run twine check dist/*
+
+  publish:
+    needs: [dist]
+    runs-on: ubuntu-latest
+    if: startsWith(github.ref, 'refs/tags')
+    environment: pypi
+    permissions:
+      id-token: write
+
+    steps:
+    - uses: actions/download-artifact@v8
+      with:
+        name: artifact
+        path: dist
+
+    - uses: pypa/gh-action-pypi-publish@release/v1

.github/workflows/test_package.yml

@@ -4,11 +4,11 @@ on:
   push:
     branches:
       - main
-  
+
   pull_request:
     branches:
       - main
-    
+
   workflow_dispatch:
   workflow_call:
 
@@ -28,4 +28,4 @@ jobs:
 
 
       - name: Run tests parallel
-        run: mpirun -n 2 python3 -m pytest -vs tests/
+        run: mpirun -n 2 python3 -m pytest -vs tests/

.gitignore

@@ -131,4 +131,4 @@ dmypy.json
 _build/
 
 *.dot
-*.bp
+*.bp

.pre-commit-config.yaml

@@ -0,0 +1,31 @@
+# See https://pre-commit.com for more information
+# See https://pre-commit.com/hooks.html for more hooks
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v6.0.0
+    hooks:
+      - id: trailing-whitespace
+      - id: end-of-file-fixer
+      - id: check-yaml
+      - id: check-added-large-files
+        args: ['--maxkb=3000']
+      - id: check-docstring-first
+      - id: debug-statements
+      - id: check-toml
+
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    # Ruff version.
+    rev: 'v0.15.14'
+    hooks:
+       # Run the linter.
+      - id: ruff
+        args: [ --fix ]
+      # Run the formatter.
+      - id: ruff-format
+
+  - repo: https://github.com/pre-commit/mirrors-mypy
+    rev: v2.1.0
+    hooks:
+      - id: mypy
+        files: ^src/|^tests/
+        args: ["--config-file", "pyproject.toml"]

CITATION.cff

@@ -10,8 +10,8 @@ authors:
     email: dokken@simula.no
     affiliation: Simula Research Laboratory
     orcid: 'https://orcid.org/0000-0001-6489-8858'
-repository-code: 'https://github.com/jorgensd/dxa'
-url: 'https://jsdokken.com/dxa'
+repository-code: 'https://github.com/scientificcomputing/dolfinx-adjoint'
+url: 'https://github.com/scientificcomputing/dolfinx-adjoint'
 abstract: >-
   Adjoint framework for DOLFINx
 keywords:
@@ -21,4 +21,4 @@ keywords:
   - Optimization
 license: MIT
 version: v0.1.0
-date-released: '2023-04-04'
+date-released: '2023-04-04'

Dockerfile

@@ -1,5 +1,5 @@
 # Use github pages for docker image
-FROM ghcr.io/jorgensd/dxa:v0.1.0
+FROM ghcr.io/scientificcomputing/dolfinx-adjoint:v0.2.0
 
 # Create user with a home directory
 ARG NB_USER

README.md

@@ -1,6 +1,120 @@
-# dxa
-_________________
+# DOLFINx-Adjoint
 
-[![MIT](https://img.shields.io/github/license/jorgensd/dxa)](LICENSE)
-[Read Latest Documentation](https://jorgensd.github.io/dxa/)
-_________________
+**DOLFINx-Adjoint** is an algorithmic differentiation (AD) framework for [DOLFINx](https://github.com/FEniCS/dolfinx). It allows you to automatically compute the gradients and Hessians of PDE-constrained optimization problems and track your computational graphs through the `pyadjoint` backend.
+
+Read the [Latest Documentation here](https://scientificcomputing.github.io/dolfinx-adjoint).
+
+> **Note for Legacy FEnICS Users:** If you are using the legacy FEnICS (`dolfin`) library, please refer to the original [dolfin-adjoint repository](https://github.com/dolfin-adjoint/dolfin-adjoint). This repository (DOLFINx-Adjoint) is built specifically for the modern DOLFINx environment and is currently under active development. It is intended to eventually support the same comprehensive feature set and capabilities as the legacy version.
+
+## Features
+
+* **Automated Adjoints:** Seamlessly derive discrete adjoint models from DOLFINx forward models.
+
+* **Overloaded API:** Swap out standard `dolfinx` calls with their `dolfinx_adjoint` equivalents (e.g., `Function`, `Constant`, `LinearProblem`, `NonlinearProblem`, `assemble_scalar`) to automatically record the computational tape.
+
+* **Optimization:** Seamless integration with PDE-constrained optimization frameworks like [Moola](https://github.com/funsim/moola) or SciPy via `pyadjoint.ReducedFunctional`.
+
+## Installation
+
+### Dependencies
+
+DOLFINx-Adjoint requires **DOLFINx** (>=0.10.0) and **pyadjoint-ad**.
+
+### via pip
+
+The main way to install the package is via pip:
+
+```bash
+python3 -m pip install dolfinx-adjoint
+```
+
+### Development Install
+
+To install the latest development version directly from the repository, use:
+
+```bash
+python3 -m pip install git+[https://github.com/scientificcomputing/dolfinx-adjoint.git](https://github.com/scientificcomputing/dolfinx-adjoint.git)
+```
+
+If you plan to actively modify the code, clone the repository and install the optional dependencies for testing, development, and documentation generation:
+
+```bash
+git clone [https://github.com/scientificcomputing/dolfinx-adjoint.git](https://github.com/scientificcomputing/dolfinx-adjoint.git)
+cd dolfinx-adjoint
+python3 -m pip install -e ".[all]"
+```
+
+### Docker
+
+A pre-built Docker image is automatically published by the CI. You can pull the nightly build which comes with DOLFINx and DOLFINx-Adjoint pre-installed:
+
+```bash
+docker run -ti ghcr.io/scientificcomputing/dolfinx-adjoint:v0.2.0
+```
+
+*(Note: Adjust the tag to the latest release or build).*
+
+## Quick Start
+
+Using `dolfinx_adjoint` is designed to be as close to standard `dolfinx` syntax as possible. Here is a brief overview of how to track a parameter and assemble an objective functional:
+<!-- #endregion -->
+
+```python
+import dolfinx
+from mpi4py import MPI
+import pyadjoint
+import dolfinx_adjoint
+
+# Create mesh and function space
+mesh = dolfinx.mesh.create_unit_square(MPI.COMM_WORLD, 10, 10)
+V = dolfinx.fem.functionspace(mesh, ("Lagrange", 1))
+
+# Use dolfinx_adjoint overloaded types
+# This ensures operations are tracked on the pyadjoint tape!
+f = dolfinx_adjoint.Function(V, name="Control")
+uh = dolfinx_adjoint.Function(V, name="State")
+
+# ... Define your UFL forms ...
+
+# Use overloaded solvers
+problem = dolfinx_adjoint.LinearProblem(a, L, u=uh, bcs=[bc])
+problem.solve()
+
+# Assemble the objective scalar using the overloaded assembly
+J_symbolic = 0.5 * ufl.inner(uh - d, uh - d) * ufl.dx
+J = dolfinx_adjoint.assemble_scalar(J_symbolic)
+
+# Create a ReducedFunctional for optimization
+control = pyadjoint.Control(f)
+Jhat = pyadjoint.ReducedFunctional(J, control)
+
+# Evaluate gradient
+gradient = Jhat.derivative()
+```
+
+<!-- #region -->
+For more comprehensive examples, such as solving the optimal control of the Poisson equation or time-distributed control problems, check out the `demos/` directory or the [online documentation](https://scientificcomputing.github.io/dolfinx-adjoint).
+
+## Development and Testing
+
+Code formatting is enforced via `ruff` and type-checking via `mypy`. To set up your local development environment:
+
+```bash
+# Install development dependencies
+python3 -m pip install -e ".[dev,test]"
+
+# Run formatting checks
+ruff check .
+ruff format --check .
+
+# Run type checking
+python3 -m mypy .
+
+# Run tests
+python3 -m pytest -vs tests/
+```
+
+## License
+
+MIT License. See [LICENSE](LICENSE) for more details.
+<!-- #endregion -->

_config.yml

@@ -24,7 +24,7 @@ html:
 
 
 bibtex_bibfiles:
-  - bibliography.bib
+  - docs/bibliography.bib
 
 
 parse:
@@ -46,4 +46,4 @@ sphinx:
   - 'sphinx.ext.autodoc'
   - 'sphinx.ext.napoleon'
   - 'sphinx.ext.viewcode'
-exclude_patterns: ["README.md",".pytest_cache/*"]
+exclude_patterns: [".pytest_cache/*"]

_toc.yml

@@ -1,5 +1,5 @@
 format: jb-book
-root: index
+root: README.md
 
 parts:
   - caption: Examples
@@ -9,4 +9,4 @@ parts:
   - caption: Python API
     chapters:
     - file: "docs/api"
-    - file: "docs/api_blocks"
+    - file: "docs/api_blocks"

docker/Dockerfile

@@ -4,8 +4,8 @@ ENV DEB_PYTHON_INSTALL_LAYOUT=deb_system
 
 WORKDIR /tmp/
 
-COPY . ./dxa
-RUN python3 -m pip install ./dxa[all]
+COPY . ./dolfinx-adjoint
+RUN python3 -m pip install ./dolfinx-adjoint[all]
 
 
 RUN rm -rf /tmp

docs/api.rst

@@ -5,4 +5,3 @@ The following is the API of the functions and classes provided by the `dolfinx_a
 
 .. automodule:: dolfinx_adjoint
     :members:
-

docs/api_blocks.rst

@@ -4,4 +4,4 @@ DOLFINx-adjoint Blocks API
 The following is the API of the blocks implemented in the DOLFINx-adjoint package, which is used within the `pyadjoint` framework.
 
 .. automodule:: dolfinx_adjoint.blocks
-    :members:
+    :members: