MillerIndices

Documentation for MillerIndices.

MillerIndices.jl is a Julia package that provides a convenient way to handle Miller indices and Miller–Bravais indices in crystallography.

See the Index for the complete list of documented functions and types.

The code, which is hosted on GitHub, is tested using various continuous integration services for its validity.

This repository is created and maintained by @singularitti, and contributions are highly welcome.

Package features

1. Representation of indices:

   • Miller: Represents the Miller indices in real space (crystal directions).
   • ReciprocalMiller: Represents the Miller indices in reciprocal space (planes).
   • MillerBravais: Represents the Miller–Bravais indices in real space (crystal directions).
   • ReciprocalMillerBravais: Represents the Miller–Bravais indices in reciprocal space (planes).

2. Macro for easy generation:

   m"[-1, 0, 1]"        # Miller
   m"<2, -1, -1, 3>"    # MillerBravais
   m"(-1, 0, 1)"        # ReciprocalMiller
   m"(1, 0, -1, 0)"     # ReciprocalMillerBravais

3. List equivalent directions/planes

4. Conversion between Miller and Miller-Bravais representations

5. Calculate angles between indices

6. Interplanar spacing calculation

Installation

The package can be installed with the Julia package manager. From the Julia REPL, type ] to enter the Pkg mode and run:

pkg> add MillerIndices

Or, equivalently, via Pkg.jl:

julia> import Pkg; Pkg.add("MillerIndices")   Resolving package versions...
    Updating `~/.julia/packages/MillerIndices/uC856/docs/Project.toml`
  [f41335bc] ~ MillerIndices v0.2.0 `~/.julia/dev/MillerIndices` ⇒ v0.2.0
    Updating `~/.julia/packages/MillerIndices/uC856/docs/Manifest.toml`
  [f41335bc] ~ MillerIndices v0.2.0 `~/.julia/dev/MillerIndices` ⇒ v0.2.0

Documentation

• STABLE — documentation of the most recently tagged version.
• DEV — documentation of the in-development version.

Project status

The package is developed for and tested against Julia v1.6 and above on Linux, macOS, and Windows.

Questions and contributions

You can post usage questions on our discussion page.

We welcome contributions, feature requests, and suggestions. If you encounter any problems, please open an issue. The Contributing page has a few guidelines that should be followed when opening pull requests and contributing code.

Manual outline

• Installation Guide
• • Install Julia
  • • Which version should I pick?
  • Install the package
  • Update the package
  • Uninstall and then reinstall the package
• Examples
• • Representing Miller and Miller–Bravais indices
  • Generating indices from strings
  • Converting between Miller and Miller–Bravais indices
  • Finding equivalent directions/planes
  • Angle calculation
• Troubleshooting
• • Cannot find the Julia executable
  • Julia starts slow
• Contributing
• • Code of conduct
  • Join the community forum
  • Improve the documentation
  • File a bug report
  • Contribute code to MillerIndices
  • • Step 1: decide what to work on
    • Step 2: fork MillerIndices
    • Step 3: install MillerIndices locally
    • Step 4: checkout a new branch
    • Step 5: make changes
    • Step 6a: test your code changes
    • Step 6b: test your documentation changes
    • Step 7: make a pull request
    • Step 8: respond to comments
    • Step 9: cleaning up
• Style Guide
• • Formatting
  • • Run JuliaFormatter
    • Use the Julia extension for Visual Studio Code
• Design Principles
• • Consistency vs adherence
  • Community contribution guidelines
  • Open source contributions are allowed to start small and grow over time
  • Generic code is preferred unless code is known to be specific
  • Internal types should match the types used by users when possible
  • Trait definition and adherence to generic interface is preferred when possible
  • Macros should be limited and only be used for syntactic sugar
  • Errors should be caught as early as possible, and error messages should be made contextually clear for newcomers
  • Subpackaging and interface packages is preferred over conditional modules via Requires.jl
  • Functions should either attempt to be non-allocating and reuse caches, or treat inputs as immutable
  • Out-of-place and immutability is preferred when sufficient performant
  • Tests should attempt to cover a wide gamut of input types
  • When in doubt, a submodule should become a subpackage or separate package
  • Globals should be avoided whenever possible
  • Type-stable and type-grounded code is preferred wherever possible
  • Closures should be avoided whenever possible
  • Numerical functionality should use the appropriate generic numerical interfaces
  • Functions should capture one underlying principle
  • Internal choices should be exposed as options whenever possible
  • Prefer code reuse over rewrites whenever possible
  • Prefer to not shadow functions

Library outline

• Public API
• • Contents
  • Index
  • Public interface
• Abstract types

Index