Installation#

The host app is a small Python package; the two solvers are Tesseract container images you build once.

Prerequisites#

  • Linux or macOS (Windows via WSL2), make

  • Docker (Tesseract builds and runs the solvers as containers)

  • Python ≥ 3.12 in an active virtual environment

  • ~10 GB of disk for the two images

Host app#

git clone https://github.com/benvial/prismo && cd prismo
make install          # pip install -e components/shared_code -e "app[dev]"

git clone https://github.com/benvial/prismo && cd prismo/app
uv sync               # prismo_shared is a path dependency

This installs prismo_shared (the Pydantic schemas both solvers and the app agree on) and the prismo CLI with JAX, NLopt, matplotlib and tesseract-core. No solver runs on the host.

Solver images#

make julia-base chargetransport   # Julia 1.10 + precompiled ChargeTransport.jl (~15 min, once)
make build                        # tesseract build both components (gyptis is a conda image)
make test                         # component regression cases + host unit tests

make images reports whether an image is older than the sources it was built from. The Julia base image only needs rebuilding when components/tesseracts/chargetransport/julia_env/*.toml change.

Without installing anything#

binder opens notebooks/prismo.ipynb on mybinder.org in a JupyterLab where both solvers are installed in-process: gyptis + legacy FEniCS from conda-forge and Julia 1.10 with the ChargeTransport.jl environment pinned to the same Manifest.toml as the container image. Binder has no Docker, so that session uses the make run path (the tesseract apis called in-process, same gyptis-authored mesh, no containers) with about one CPU and 2 GB of RAM: a minute of Julia JIT warm-up on the first evaluation, then a few seconds per evaluation, so the 200-iteration runs in Results take about a quarter of an hour. The FEniCS form cache is compiled into the image, so the eigensolve does not pay form compilation. The image is described by binder/: environment.yml (conda), Project.toml + Manifest.toml (Julia, kept identical to the component’s by a unit test), postBuild (pip-installs the app, warms the FEniCS and Julia caches) and start (points FEniCS at that warmed cache at session start).

Docs#

pip install -e "app[docs]"
make docs                         # docs/_build/html