2019-11-24 22:46:36 -08:00
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# meanas
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2016-04-13 04:05:08 -07:00
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2019-08-04 13:48:41 -07:00
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**meanas** is a python package for electromagnetic simulations
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2019-10-08 23:56:33 -07:00
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** UNSTABLE / WORK IN PROGRESS **
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Formerly known as [fdfd_tools](https://mpxd.net/code/jan/fdfd_tools).
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2019-08-04 13:48:41 -07:00
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This package is intended for building simulation inputs, analyzing
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simulation outputs, and running short simulations on unspecialized hardware.
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It is designed to provide tooling and a baseline for other, high-performance
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purpose- and hardware-specific solvers.
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2016-05-30 22:30:45 -07:00
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**Contents**
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2019-08-04 13:48:41 -07:00
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- Finite difference frequency domain (FDFD)
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* Library of sparse matrices for representing the electromagnetic wave
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equation in 3D, as well as auxiliary matrices for conversion between fields
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* Waveguide mode operators
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* Waveguide mode eigensolver
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* Stretched-coordinate PML boundaries (SCPML)
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* Functional versions of most operators
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* Anisotropic media (limited to diagonal elements eps_xx, eps_yy, eps_zz, mu_xx, ...)
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* Arbitrary distributions of perfect electric and magnetic conductors (PEC / PMC)
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- Finite difference time domain (FDTD)
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* Basic Maxwell time-steps
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* Poynting vector and energy calculation
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* Convolutional PMLs
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2016-05-30 22:30:45 -07:00
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2016-08-04 22:55:24 -07:00
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This package does *not* provide a fast matrix solver, though by default
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`meanas.fdfd.solvers.generic(...)` will call
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`scipy.sparse.linalg.qmr(...)` to perform a solve.
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For 2D FDFD problems this should be fine; likewise, the waveguide mode
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solver uses scipy's eigenvalue solver, with reasonable results.
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For solving large (or 3D) FDFD problems, I recommend a GPU-based iterative
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solver, such as [opencl_fdfd](https://mpxd.net/code/jan/opencl_fdfd) or
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2019-10-08 23:56:33 -07:00
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those included in [MAGMA](http://icl.cs.utk.edu/magma/index.html). Your
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solver will need the ability to solve complex symmetric (non-Hermitian)
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linear systems, ideally with double precision.
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2020-02-19 18:56:56 -08:00
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- [Source repository](https://mpxd.net/code/jan/meanas)
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2024-03-30 18:06:41 -07:00
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- [PyPI](https://pypi.org/project/meanas)
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- [Github mirror](https://github.com/anewusername/meanas)
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2019-08-04 13:48:41 -07:00
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2016-05-30 22:30:45 -07:00
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## Installation
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**Requirements:**
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2024-03-30 18:06:31 -07:00
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* python >=3.11
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* numpy
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* scipy
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2019-10-08 23:56:33 -07:00
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Install from PyPI with pip:
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```bash
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pip3 install meanas
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```
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Optional extras:
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- `meanas[test]`: pytest and coverage
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- `meanas[docs]`: MkDocs-based documentation toolchain
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- `meanas[examples]`: optional runtime dependencies used by the tracked examples
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- `meanas[dev]`: the union of `test`, `docs`, and `examples`, plus local lint/docs-publish helpers
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Examples:
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```bash
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pip3 install 'meanas[test]'
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pip3 install 'meanas[docs]'
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pip3 install 'meanas[examples]'
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pip3 install 'meanas[dev]'
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```
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2019-10-08 23:56:33 -07:00
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### Development install
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Install python3 and git:
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```bash
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# This is for Debian/Ubuntu/other-apt-based systems; you may need an alternative command
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sudo apt install python3 build-essential python3-dev git
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```
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In-place development install:
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```bash
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# Download using git
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git clone https://mpxd.net/code/jan/meanas.git
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# If you'd like to create a virtualenv, do so:
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python3 -m venv my_venv
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# If you are using a virtualenv, activate it
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source my_venv/bin/activate
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# Install in-place (-e, editable) from ./meanas, including development dependencies ([dev])
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pip3 install --user -e './meanas[dev]'
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# Run tests
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2019-11-05 19:02:40 -08:00
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cd meanas
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python3 -m pytest -rsxX | tee test_results.txt
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```
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2019-10-09 00:11:27 -07:00
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#### See also:
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- [git book](https://git-scm.com/book/en/v2)
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- [venv documentation](https://docs.python.org/3/tutorial/venv.html)
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- [python language reference](https://docs.python.org/3/reference/index.html)
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- [python standard library](https://docs.python.org/3/library/index.html)
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2019-10-08 23:56:33 -07:00
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2016-08-04 22:55:24 -07:00
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## Use
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2026-04-19 00:50:22 -07:00
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`meanas` is a collection of finite-difference electromagnetics tools:
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2026-04-18 14:24:18 -07:00
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- `meanas.fdfd`: frequency-domain wave equations, sparse operators, SCPML, and
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iterative solves for driven problems.
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- `meanas.fdfd.waveguide_2d` / `meanas.fdfd.waveguide_3d`: waveguide mode
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solvers, mode-source construction, and overlap windows for port-based
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excitation and analysis.
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- `meanas.fdtd`: Yee-step updates, CPML boundaries, flux/energy accounting, and
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on-the-fly phasor extraction for comparing time-domain runs against FDFD.
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- `meanas.fdmath`: low-level finite-difference operators, vectorization helpers,
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and derivations shared by the FDTD and FDFD layers.
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2026-04-19 00:50:22 -07:00
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For most users, the tracked examples under `examples/` are the right entry
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point. The library API is primarily a toolbox; the module docstrings and API
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pages are there to document the mathematical conventions and derivations behind
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those tools.
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2026-04-18 14:24:18 -07:00
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2026-04-18 15:05:35 -07:00
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## Documentation
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API and workflow docs are generated from the package docstrings with
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[MkDocs](https://www.mkdocs.org/), [Material for MkDocs](https://squidfunk.github.io/mkdocs-material/),
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and [mkdocstrings](https://mkdocstrings.github.io/).
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Install the docs toolchain with:
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```bash
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pip3 install -e './meanas[docs]'
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```
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Then build the docs site with:
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```bash
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./make_docs.sh
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```
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This produces:
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- a normal multi-page site under `site/`
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- a combined printable single-page HTML site under `site/print_page/`
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- an optional fully inlined `site/standalone.html` when `htmlark` is available
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The docs build uses a local MathJax bundle vendored under `docs/assets/`, so
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the rendered HTML does not rely on external services for equation rendering.
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2026-04-19 00:50:22 -07:00
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The tracked examples under `examples/` are the intended entry points for users:
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- `examples/fdtd.py`: broadband FDTD pulse excitation, phasor extraction, and a
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residual check against the matching FDFD operator.
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- `examples/waveguide.py`: waveguide mode solving, unidirectional mode-source
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construction, overlap readout, and FDTD/FDFD comparison on a guided structure.
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- `examples/fdfd.py`: direct frequency-domain waveguide excitation and overlap /
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Poynting analysis without a time-domain run.
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Several examples rely on optional packages such as
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[gridlock](https://mpxd.net/code/jan/gridlock).
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### Frequency-domain waveguide workflow
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For a structure with a constant cross-section in one direction:
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1. Build `dxes` and the diagonal `epsilon` / `mu` distributions on the Yee grid.
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2. Solve the port mode with `meanas.fdfd.waveguide_3d.solve_mode(...)`.
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3. Build a unidirectional source with `compute_source(...)`.
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4. Build a matching overlap window with `compute_overlap_e(...)`.
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5. Solve the full FDFD problem and project the result onto the overlap window or
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evaluate plane flux with `meanas.fdfd.functional.poynting_e_cross_h(...)`.
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### Time-domain phasor workflow
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For a broadband or continuous-wave FDTD run:
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1. Advance the fields with `meanas.fdtd.maxwell_e/maxwell_h` or
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`updates_with_cpml(...)`.
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2. Inject electric current using the same sign convention used throughout the
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examples and library: `E -= dt * J / epsilon`.
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3. Accumulate the desired phasor with `accumulate_phasor(...)` or the Yee-aware
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wrappers `accumulate_phasor_e/h/j(...)`.
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4. Build the matching FDFD operator on the stretched `dxes` if CPML/SCPML is
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part of the simulation, and compare the extracted phasor to the FDFD field or
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residual.
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