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User Friendly Magnetic Field Calculations

Project description

Pymagnet

User friendly magnetic field calculations in Python

License: MPL 2.0 License: CC BY-SA 4.0 DOI Anaconda-Server Badge

Getting Started

Installing pymagnet can be done using

python -m pip install pymagnet 

Pymagnet is a collection of routines to calculate and plot the magnetic field due to arbitrary 2D and 3D objects, like cubes or cylinders, as well as complex non-convex structures stored in STL files. The library can also calculate the magnetic forces and torques on one magnet due to all other magnets in the system.

The approach assumes the magnets are uniformly magnetised, and fully transparent to magnetic fields. There are some drawbacks to this compared to Finite Element Methods (FEM), but with the advantage of significantly faster calculations.

The current version is written in Python with some speed up using Numpy and Numba, but the backend is being ported to Rust for improved performance.

Features

This code uses analytical expressions to calculate the magnetic field due to simple magnets:

  • 3D: cubes, prisms (cuboids), cylinders, spheres
  • 2D: rectangles, squares, circles

and complex compound objects:

  • 3D: Polyhedra stored as STL meshes
  • 2D: Polygons constructed from collections of line elements

There are helper functions to plot the data as line, contour, slice, and volume plots, but the underlying data is also accessible.

Documentation

Full documentation can be found here: https://pdunne.github.io/pymagnet/

Examples

Examples can be found in the repository.

Or run on Colab:

2D Examples

Getting Started First Steps

1D Simple Plots Open In Colab

2D Standard Shapes Open In Colab

2D Arbitrary Polygons Open In Colab

Misc. Examples Open In Colab

3D Examples

Analytical Shapes 3D Examples

Spheres Open In Colab

3D STL Meshes Open In Colab

3D Stanford Bunny Open In Colab

Forces and Torques

Cubes Open In Colab

Cylinders Open In Colab

Spheres Open In Colab

Binder

You can test out the libraries on Binder, but performance is not as good:

Binder

Prerequisites

Ensure you have Python version >= 3.6 (to use f-strings), and the following packages:

  • numpy
  • numpy-stl
  • numba
  • matplotlib
  • plotly

Usage

Forms of this library have been used in a number of projects including Liquid flow and control without solid walls, Nature 2020.

Licensing

Source code licensed under the Mozilla Public License Version 2.0

Documentation is licensed under a Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.

This is a human-readable summary of (and not a substitute for) the license, adapted from CS50x. Official translations of this license are available in other languages.

You are free to:

  • Share — copy and redistribute the material in any medium or format.
  • Adapt — remix, transform, and build upon the material.

Under the following terms:

  • Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  • ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original
  • No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you shall be licensed as above, without any additional terms or conditions.

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