Skip to main content

FAST-PT is a code to calculate quantities in cosmological perturbation theory at 1-loop (including, e.g., corrections to the matter power spectrum).

Project description

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 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. If you have comments, questions, or feedback, please file an issue.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fast_pt-3.2.tar.gz (37.1 kB view details)

Uploaded Source

Built Distribution

fast_pt-3.2-py3-none-any.whl (49.1 kB view details)

Uploaded Python 3

File details

Details for the file fast_pt-3.2.tar.gz.

File metadata

  • Download URL: fast_pt-3.2.tar.gz
  • Upload date:
  • Size: 37.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for fast_pt-3.2.tar.gz
Algorithm Hash digest
SHA256 ec4cfdb4a352b300ca7ec2f313a73c5676ec61ef665345b0fc37a258f5ecbd5d
MD5 eee87add6493c66c9b19540a0f297f59
BLAKE2b-256 651183df1a1acc4c346f35219481f464f0264932ac3c57f053b1ce68f4d13d02

See more details on using hashes here.

File details

Details for the file fast_pt-3.2-py3-none-any.whl.

File metadata

  • Download URL: fast_pt-3.2-py3-none-any.whl
  • Upload date:
  • Size: 49.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for fast_pt-3.2-py3-none-any.whl
Algorithm Hash digest
SHA256 c988e312bc79df66f1719fcb198ab984fd614a6c942f1e3af6adb07180760387
MD5 a98627c3f0bd732b99f7d1a5dfec508f
BLAKE2b-256 2564db25374b45218b0d305a4378a7fe8399406989e4a26f7cbafc4930200d5b

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page