Metadata-Version: 2.2
Name: mortie
Version: 0.3.1
Summary: Morton numbering and indexing for healpix grids
Home-page: https://github.com/espg/mortie
Author: Shane Grigsby (espg)
Author-email: "Shane Grigsby (espg)" <refuge@rocktalus.com>
License: BSD 3-Clause License
        
        Copyright (c) 2022, Shane Grigsby
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Project-URL: Homepage, https://github.com/espg/mortie
Project-URL: Bug Tracker, https://github.com/espg/mortie/issues
Keywords: healpix,geohashing,morton index
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: healpy
Requires-Dist: numba
Requires-Dist: cython
Requires-Dist: llvmlite

mortie
======

![Morty using mortie](./morty.jpg)

Mortie is a library for applying morton indexing to healpix grids. Morton
numbering (also called z-ordering) facilitates several geospatial operators
such as buffering and neighborhood look-ups, and can generally be thought of as
a type of geohashing.

This particular implementation focuses on hierarchical healpix maps, and is
mostly inspired from [this paper](https://doi.org/10.1016/j.heliyon.2017.e00332).

TODO:

- [x] add paper reference
- [x] add funding information
- [ ] add tests
- [x] remove / prune dead code
- [ ] add example(s)
- [x] fix north / south bug
- [ ] remove numba dependency
- [ ] update documentation
- [x] publish to pypi

Dependencies currently are numpy, numba, and healpy. Ideally, this will be
reduced to just healpy and numpy in the near future. Although not a dependency,
there are several functions that have been written to interface with the vaex
project. The environment.yaml file contains a full plotting environment needed
to run the examples; setup.py will only build the minimum requirements for only
the library.

## Funding
Initial funding of this work was supported by the ICESat-2 project science
office, at the Laboratory for Cryospheric Sciences (NASA Goddard, Section 615). 

## References
<a id="1">[1]</a> 
Youngren, Robert W., and Mikel D. Petty. 
"A multi-resolution HEALPix data structure for spherically mapped point data." 
Heliyon 3.6 (2017): e00332. [doi: 10.1016/j.heliyon.2017.e00332](https://doi.org/10.1016/j.heliyon.2017.e00332)
