Skip to main content

Three-point clustering measurements in large-scale structure analyses.

Project description

https://github.com/MikeSWang/Triumvirate/raw/main/docs/source/_static/Triumvirate.png

Three-Point Clustering Measurements in LSS

CI Docs Release

Triumvirate is a Python/C++ software package for measuring three-point (and two-point) clustering statistics in large-scale structure (LSS) cosmological analyses.

Documentation

Comprehensive documentation including the scientific background, installation instructions, tutorials and API reference can be found at triumvirate.readthedocs.io.

Installation

Python package

PyPI conda

Triumvirate as a Python package is distributed through PyPI and conda. Instructions for installation can be found on the Installation page in the documentation.

C++ library & program

Triumvirate as either a C++ library or a ‘black-box’ C++ program can be built using make. Instructions for compilation can be found on the Installation page in the documentation.

Development mode

Both the Python package and the C++ library/program can be set up in development mode with make. First check the required dependencies, namely the GSL and FFTW3 libraries, are installed. Then git clone the GitHub repository and git checkout the branch/release to be edited:

$ git clone git@github.com:MikeSWang/Triumvirate.git --branch <branch-or-release>
$ cd Triumvirate

Then at the repository directory root, run

$ make clean
$ make [py|cpp]install [useomp=(true|1)]

where install builds both and pyinstall/cppinstall is for Python/C++ build only; you may also replace this with cpplibinstall or cppappbuild above to compile the C++ static library or binary executable only. To enable OpenMP parallelisation, append useomp=true or useomp=1 to the end of the second line as shown above.

The latest release is on the main branch. The default Makefile (located at the repository directory root) suits most use cases, but you may modify it as appropriate for your need.

Attribution

JOSS arXiv MNRAS MNRAS

To acknowledge the use of Triumvirate in your published research, please cite the publications linked above which contain the relevant information in the BibTeX format.

Acknowledgement

ERC

This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 853291).

Key underlying numerical algorithms were originally developed by Naonori S Sugiyama, and are available in the GitHub repository hitomi.

Contributing

User feedback and contributions are very welcome. Please refer to the contribution guidelines.

Releases

Changes in current and past releases are listed in the change log.

Licence

GPL-3.0 Licence

Triumvirate is made freely available under the GPL-3.0 licence. Please see Licence (located at the repository directory root) for full terms and conditions.

&copy; 2023 Mike S Wang & Naonori S Sugiyama

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

Triumvirate-0.1.0.tar.gz (1.2 MB view details)

Uploaded Source

Built Distributions

Triumvirate-0.1.0-cp311-cp311-manylinux_2_24_x86_64.whl (4.5 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.24+ x86-64

Triumvirate-0.1.0-cp311-cp311-macosx_10_9_x86_64.whl (4.0 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

Triumvirate-0.1.0-cp310-cp310-manylinux_2_24_x86_64.whl (4.5 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.24+ x86-64

Triumvirate-0.1.0-cp310-cp310-macosx_10_9_x86_64.whl (4.0 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

Triumvirate-0.1.0-cp39-cp39-manylinux_2_24_x86_64.whl (4.5 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.24+ x86-64

Triumvirate-0.1.0-cp39-cp39-macosx_10_9_x86_64.whl (4.0 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

Triumvirate-0.1.0-cp38-cp38-manylinux_2_24_x86_64.whl (4.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.24+ x86-64

Triumvirate-0.1.0-cp38-cp38-macosx_10_9_x86_64.whl (4.0 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

File details

Details for the file Triumvirate-0.1.0.tar.gz.

File metadata

  • Download URL: Triumvirate-0.1.0.tar.gz
  • Upload date:
  • Size: 1.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.8

File hashes

Hashes for Triumvirate-0.1.0.tar.gz
Algorithm Hash digest
SHA256 a32eb5a0e6716be3075788064fbf71d26c487794e5cddb8449011a3cb5cd883a
MD5 238401a5155a82b54cec305ae48479c7
BLAKE2b-256 32ad9507d43e80622d64a2313a68078044f0c711652995a6a4cf010bee0ea982

See more details on using hashes here.

Provenance

File details

Details for the file Triumvirate-0.1.0-cp311-cp311-manylinux_2_24_x86_64.whl.

File metadata

File hashes

Hashes for Triumvirate-0.1.0-cp311-cp311-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 be36bf8347772530340ef3f766554a93eb20f1fcccdce9c4d130eb7d102b2b4e
MD5 87961294f009a637dc6f9f3d76e5504f
BLAKE2b-256 f212c0678c08e565ee04560f151136c0605e77501cf05a4871efdf65fa81f5c1

See more details on using hashes here.

Provenance

File details

Details for the file Triumvirate-0.1.0-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for Triumvirate-0.1.0-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 31a6750991f371e733b827320c37b4b8f26bd166a9b3c4d6387990cd678b5de3
MD5 aab9798370dd51015c17d28328bb24aa
BLAKE2b-256 3b2475ac15c3f16abd0397f63f1d24cc8976a8c5a1b78a10a32f8cffd4ccb5e1

See more details on using hashes here.

Provenance

File details

Details for the file Triumvirate-0.1.0-cp310-cp310-manylinux_2_24_x86_64.whl.

File metadata

File hashes

Hashes for Triumvirate-0.1.0-cp310-cp310-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 45d315a248092900dea0e068e33ae2ee4b635a68cd51fa0910dac9439bc70d1d
MD5 b35eea3546ba3115fb8488ed72a92894
BLAKE2b-256 3624b4cc186b3a5c7f168c0eafdd8e7ac9d82115c7d7197132377f629215eaec

See more details on using hashes here.

Provenance

File details

Details for the file Triumvirate-0.1.0-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for Triumvirate-0.1.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 8160afe389821edb89175a36774c8827920bc1adb25b8dffbf41e0d11bd00079
MD5 64c90a6b4fb8fd7b5ffd6e87b93b7b45
BLAKE2b-256 e91855de2a306c1cc6c4ecad16de7e16aa3261844d9ba4389b33459af41fb1ae

See more details on using hashes here.

Provenance

File details

Details for the file Triumvirate-0.1.0-cp39-cp39-manylinux_2_24_x86_64.whl.

File metadata

File hashes

Hashes for Triumvirate-0.1.0-cp39-cp39-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 908c02fefa9fe216b845653040cfc6a64ee718a42b1359935d9499000077fe74
MD5 2406a690849043e06bc8047993476f11
BLAKE2b-256 02d741c83a719fbe98269bdaf5d78f4117d3b3feb83427f824cb3de990a42f8d

See more details on using hashes here.

Provenance

File details

Details for the file Triumvirate-0.1.0-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for Triumvirate-0.1.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 987b54984c5fb9ba38ac744fa1f194d72bceb3e5f24eb9668380574b5f010a0c
MD5 7a59993cacf6b77296658bdbe86b27c1
BLAKE2b-256 ec0c9f018cd8721a497df8976de72db554a2b22d820c0d09767f76622a8387b0

See more details on using hashes here.

Provenance

File details

Details for the file Triumvirate-0.1.0-cp38-cp38-manylinux_2_24_x86_64.whl.

File metadata

File hashes

Hashes for Triumvirate-0.1.0-cp38-cp38-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 65adc88f868b34a22950472219c0f99d1b9bdaf8cbbde15f90902654f7ae6574
MD5 98ddd3e97469e7a37c51222d6c43dfdb
BLAKE2b-256 2a01d43469938f6426c35f50d05bb2bd8dec1d96ce89cd92b498ed9de1d1b08c

See more details on using hashes here.

Provenance

File details

Details for the file Triumvirate-0.1.0-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for Triumvirate-0.1.0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 217083c8601dfc60b5f0bdb6715273e20f9e29384ff017cbd8c0ddc7873d7871
MD5 c163a41b7f8312808f20c44ed0758ab9
BLAKE2b-256 b963e3d70be22bd3925d676512ab6debe1455a398eb59763533ac7c88242037a

See more details on using hashes here.

Provenance

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