mortie 0.6.1

Morton numbering and indexing for healpix grids

mortie

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.

Performance

Mortie uses Rust-accelerated morton indexing functions for high performance, with an automatic fallback to pure Python if Rust is unavailable. The Rust implementation provides dramatic speedups:

Dataset Size	Rust	Pure Python	Speedup
1,000 values	1.93 ms	4.14 ms	2.1x
100,000 values	1.85 ms	410.59 ms	222x
1.2M coordinates	102.51 ms	5.1 sec	50x

Pre-built wheels are available for Linux, macOS, and Windows. If a wheel is unavailable for your platform, mortie will automatically use the pure Python fallback.

Installation

# With healpy (default HEALPix backend)
pip install mortie[healpy]

# With cdshealpix (Rust-backed, better ARM64 support)
pip install mortie[cdshealpix]

# Both backends
pip install mortie[all]

For development builds with Rust, see BUILDING.md.

HEALPix Backend

Mortie supports two HEALPix backends — healpy (C/Fortran) and cdshealpix (Rust). By default, mortie auto-detects whichever is installed (preferring cdshealpix). You can force a specific backend:

export MORTIE_HEALPIX_BACKEND=healpy      # or cdshealpix

Spatial Buffer

Mortie provides a morton_buffer function for expanding a set of morton cells by a configurable border ring. This is useful for capturing edge cells missed by sparse vertex sampling (e.g., near HEALPix pole holes).

import numpy as np
import mortie

# Convert coordinates to morton cells at order 6
cells = np.unique(mortie.geo2mort(lats, lons, order=6))

# Expand by 1-cell ring (8-connected neighbors)
border = mortie.morton_buffer(cells, k=1)
expanded = np.union1d(cells, border)

All input indices must be at the same order. The function returns only the new border cells, not the input cells themselves.

Dependencies

numpy and one of healpy or cdshealpix. The Rust-accelerated morton functions are optional — if unavailable, mortie will automatically fall back to a pure Python implementation.

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

[1] 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