| Name | fast-pt JSON |
| Version |
4.0.0
JSON |
| download |
| home_page | None |
| Summary | FAST-PT is a code to calculate quantities in cosmological perturbation theory at 1-loop (including, e.g., corrections to the matter power spectrum). |
| upload_time | 2025-07-10 18:44:29 |
| maintainer | None |
| docs_url | None |
| author | Joseph E. McEwen, Xiao Fang, Jonathan Blazek, Vincent Schacknies |
| requires_python | >=3.7 |
| license | MIT License
Copyright (c) 2018, the FAST-PT developers (https://github.com/JoeMcEwen/FAST-PT/graphs/contributors).
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE. |
| keywords |
fastpt
fast-pt
perturbation-theory
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
numpy
scipy
matplotlib
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# FAST-PT
[](https://fast-pt.readthedocs.io/en/latest/?badge=latest)
[](https://arxiv.org/abs/1603.04826)
[](https://arxiv.org/abs/1609.05978)
[](https://arxiv.org/abs/1708.09247)
[](https://opensource.org/licenses/MIT)
FAST-PT is a code to calculate quantities in cosmological perturbation theory
at 1-loop (including, e.g., corrections to the matter power spectrum). The code
utilizes Fourier methods combined with analytic expressions to reduce the
computation time to scale as N log N, where N is the number of grid points in
the input linear power spectrum.
NOTE: v3.1.0 and earlier require numpy version < 1.24. This is fixed in v3.1.1 and later, which is available on pip and conda.
Easy installation with pip:
* `pip install fast-pt`
* Note: use `--no-deps` if you use a conda python distribution, or just use conda installation
Easy installation with conda:
* `conda install fast-pt`
Full installation with examples:
* Make sure you have current version of numpy, scipy, and matplotlib
* download the latest FAST-PT release (or clone the repo)
* install the repo: `python -m pip install .`
* run the most recent example: `cd examples && python3 hello_fastpt.py`
* hopefully you get a plot!
* for a more in-depth example of new features: `cd examples && python3 v4_example.py`
* for older examples see the 'examples' folder
Our papers (JCAP 2016, 9, 15; arXiv:1603.04826) and (JCAP 2017, 2, 30; arXiv:1609.05978)
describe the FAST-PT algorithm and implementation. Please cite these papers
when using FAST-PT in your research. For the intrinsic alignment
implementation, cite PRD 100, 103506 (arXiv:1708.09247).
FAST-PT is under continued development and should be considered research in
progress. FAST-PT is open source and distributed with the
[MIT license](https://opensource.org/licenses/mit). If you have comments,
questions, or feedback, please file an [issue](https://github.com/jablazek/FAST-PT/issues).
Raw data
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