CDS implementation of the HEALPix tesselation in Rust and modules to generate libraries in WebAssembly, Python, ...
This library is an implementation in Rust of the HEALPix tesselation. This implementation has been made by the Strasbourg astronomical Data Centre (Centre de Données astronomique de Strasbourg, CDS).
It is used in:
- Aladin Lite V3
- The CDS MOC library in Rust used in:
- The CDS HEALPix Python
- CDS internal developments
- Please help me fill in this list
Initially, it is a port of a part of the CDS Java library available here, but improvement have been added while porting the code and new features are added.
For information on HEALPix in general, see:
- The official web site
- The Wikipedia page
- The two main reference papers: Gorski (2005) and Calabretta (2007)
Official implementations, are available here. It contains GPL v2 codes in Fortran, C++, Java, IDL, Python, ...
Other independent HEALPix implementations:
- Astropy-healpix python wrapper using a C code (C code by Dustin Lang, python wrapper by Thomas Robitaille and others)
- Javascript/Typescript implementation by Koike Michitaro
- Julia implementation by Maurizio Tomasi
- C "official" core functionalities implementation in BSD by Martin Reinecke
- Please Help me adding links to other HEALPix resources and codes
For best performances on your specific hardware, you can compile using:
RUSTFLAGS='-C target-cpu=native' cargo build --release
This uses BMI2 instructions PDEP and PEXT, if supported by your processor, for bit interleaving.
However, the implementaion of those instructions on AMD Ryzen processors are extremely slow (20x slower than a lookup table,
doubling the hash
computation time)!
You can test it using:
RUSTFLAGS='-C target-cpu=native' cargo bench
If the result of ZOrderCurve/BMI
is slower thatn ZOrderCurve/LUPT
, compile without the native
support:
cargo build --release
rustup target install i686-unknown-linux-gnu
sudo apt-get install gcc-multilib
RUSTFLAGS='-C target-cpu=native' cargo build --target=i686-unknown-linux-gnu --release
- Supports the HEALix Nested scheme
- Supports approximated
cone
andelliptical cone
coverage plus exactpolygon
coverage queries - Supports
BMOC
(MOC with a flag telling if a cell is fully or partially covered by a surface) as a result ofcone
,polygon
otelliptical cone
coverage queries - Supports logical operations on
BMOCs
andBMOC
creation from a list of cell number at a given depth - Supports implicit HEALPix density maps (single column so far), with PNG image creation for density maps
- Supports (non standard) HEALPix multi-order maps (MOM, single columns so far), with PNG image creation for density MOMs
- Supports HEALPix external sort
- Supports sorted indexation
- Supports approximated
- Supports the HEALPix Ring scheme with any NSIDE (i.e. not necessarilly powers of 2)
- Not supported
- Polygon and ellipse in the RING scheme
- Spherical Harmonics computations
- Help me fill this
- Not yet implemented
- Exact cone and ellipse solution (but using the
custom
approx methods, one can handle the rate of false positives) - Cone query in the RING scheme
- Exact cone and ellipse solution (but using the
Compute the cell number of a given position on the unit-sphere at a given HEALPix depth.
use cdshealpix::nside;
use cdshealpix::nested::{get, Layer};
let depth = 12_u8;
let lon = 12.5_f64.to_radians();
let lat = 89.99999_f64.to_radians();
let nested_d12 = get(depth);
let nside = nside(depth) as u64;
let expected_cell_number = nside * nside - 1
assert_eq!(expected_cell_number, nested_d12.hash(lon, lat));
Get the spherical coorinates of the 4 vertices of a given cell at a given depth:
use cdshealpix::nested::{get_or_create, Layer};
let depth = 12_u8;
let cell_number= 10_u64;
let nested_d12 = get_or_create(depth);
let [
(lon_south, lat_south),
(lon_east, lat_east),
(lon_north, lat_north),
(lon_west, lat_west)
] = nested_d12.vertices(cell_number);
Get a hierarchical view (a MOC) on the cells overlapped by a given cone:
use cdshealpix::nested::{get, Layer};
let depth = 6_u8;
let nested_d6 = get(depth);
let lon = 13.158329_f64.to_radians();
let lat = -72.80028_f64.to_radians();
let radius = 5.64323_f64.to_radians();
let moc = nested_d6.cone_overlap_approx(lon, lat, radius);
for cell in moc.into_iter() {
println!("cell: {:?}", cell);
}
(Not on crates.io, but on github)
The code source of the very beginning of a standalone exec can be found in cli/src/bin.rs
.
(Not on crates.io, but on github)
To build and use the WebAssembly (and Javascript) files, the libwasmbingen
directory.
We rely on wasm-bingen.
(Not on crates.io, but on github)
See the libpython
directory containing a very first integration in python using CFFI.
For a clean Python wrapper and associated Wheels, see cdshealpix python available on pypi:
pip install cdshealpix
- Modify elliptical cone: compute distance to both foci
- Implement the exact cone solution
If you use this code and work in a scientific public domain (especially astronomy), please acknowledge its usage and the CDS who developed it. It may help us in promoting our work to our financiers.
Like most projects in Rust, this project is licensed under either of
- Apache License, Version 2.0, (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)
at your option.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this project by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.
This code started has my first Rust code.