| Name | fast-pt JSON |
| Version |
3.2
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 | 2024-11-01 00:45:36 |
| maintainer | None |
| docs_url | None |
| author | Joseph E. McEwen, Xiao Fang, Jonathan Blazek |
| requires_python | >=3.5 |
| 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 |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# FAST-PT
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 example: `cd examples && python fastpt_example.py`
* hopefully you get a plot!
See the [user manual](docs/usr_manual.pdf) for more details.
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 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/JoeMcEwen/FAST-PT/issues).
Raw data
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"description": "# FAST-PT\n\nFAST-PT is a code to calculate quantities in cosmological perturbation theory\nat 1-loop (including, e.g., corrections to the matter power spectrum). The code\nutilizes Fourier methods combined with analytic expressions to reduce the\ncomputation time to scale as N log N, where N is the number of grid points in\nthe input linear power spectrum.\n\nNOTE: 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.\n\nEasy installation with pip:\n\n* `pip install fast-pt`\n* Note: use `--no-deps` if you use a conda python distribution, or just use conda installation\n\nEasy installation with conda:\n\n* `conda install fast-pt`\n\nFull installation with examples:\n\n* Make sure you have current version of numpy, scipy, and matplotlib\n* download the latest FAST-PT release (or clone the repo)\n* install the repo: `python -m pip install .`\n* run the example: `cd examples && python fastpt_example.py`\n* hopefully you get a plot!\n\nSee the [user manual](docs/usr_manual.pdf) for more details.\n\nOur papers (JCAP 2016, 9, 15; arXiv:1603.04826) and (JCAP 2017, 2, 30; arXiv:1609.05978)\ndescribe the FAST-PT algorithm and implementation. Please cite these papers\nwhen using FAST-PT in your research. For the intrinsic alignment\nimplementation, cite arXiv:1708.09247.\n\nFAST-PT is under continued development and should be considered research in\nprogress. FAST-PT is open source and distributed with the\n[MIT license](https://opensource.org/licenses/mit). If you have comments,\nquestions, or feedback, please file an [issue](https://github.com/JoeMcEwen/FAST-PT/issues).\n",
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