SWIFTsim (swiftsim.com) i/o routines for python.
Project description
SWIFTsimIO
The SWIFT astrophysical simulation code (http://swift.dur.ac.uk) is used
widely. There exists many ways of reading the data from SWIFT, which outputs
HDF5 files. These range from reading directly using h5py
to using a complex
system such as yt
; however these either are unsatisfactory (e.g. a lack of
unit information in reading HDF5), or too complex for most use-cases.
swiftsimio
provides an object-oriented API to read (dynamically) data
from SWIFT.
Full documentation is available at ReadTheDocs.
Getting set up with swiftsimio
is easy; it (by design) has very few
requirements. There are a number of optional packages that you can install
to make the experience better and these are recommended.
Requirements
This requires python
v3.8.0
or higher. Unfortunately it is not
possible to support swiftsimio
on versions of python lower than this.
It is important that you upgrade if you are still a python2
user.
Python packages
numpy
, required for the core numerical routines.h5py
, required to read data from the SWIFT HDF5 output files.unyt
, required for symbolic unit calculations (depends on sympy`).
Optional packages
numba
, highly recommended should you wish to use the in-built visualisation tools.scipy
, required if you wish to generate smoothing lengths for particle types that do not store this variable in the snapshots (e.g. dark matter)tqdm
, required for progress bars for some long-running tasks. If not installed no progress bar will be shown.py-sphviewer
, if you wish to use our integration with this visualisation code.
Installing
swiftsimio
can be installed using the python packaging manager, pip
,
or any other packaging manager that you wish to use:
pip install swiftsimio
Citing
Please cite swiftsimio
using the JOSS paper:
@article{Borrow2020,
doi = {10.21105/joss.02430},
url = {https://doi.org/10.21105/joss.02430},
year = {2020},
publisher = {The Open Journal},
volume = {5},
number = {52},
pages = {2430},
author = {Josh Borrow and Alexei Borrisov},
title = {swiftsimio: A Python library for reading SWIFT data},
journal = {Journal of Open Source Software}
}
If you use any of the subsampled projection backends, we ask that you cite our relevant SPHERIC paper. Note that citing the arXiv version here is recommended as the ADS cannot track conference proceedings well.
@article{Borrow2021
title={Projecting SPH Particles in Adaptive Environments},
author={Josh Borrow and Ashley J. Kelly},
year={2021},
eprint={2106.05281},
archivePrefix={arXiv},
primaryClass={astro-ph.GA}
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for swiftsimio-9.0.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 06e5511f9cc547e09085c816ab80bb50f23280c900135ae3ea4fdc894834a54d |
|
MD5 | 2848512e22f3ed2bf863c3890d649e0f |
|
BLAKE2b-256 | 3fb3041d2761b3eaf8f3f87c44a68651ac9f8a1e26d87de3f8211110db84db5f |