Skip to main content

Tool for measuring 3/4 PCFs on discrete periodic data.

Project description

A useful python package to measure the 3/4 PCFs of discrete periodic data in $\mathcal{O}(N_g \log N_g)$ time. This is done using Fast Fourier Transforms.

Basic Usage:

import sarabande

NPCF_obj = sarabande.measure(**kwargs)
sarabande.calc_zeta(NPCF_obj)
zeta = NPCF_obj.zeta

Where **kwargs can be any of the arguments to the measure constructor function. The possible arguments are:

Args:

  • nPCF ([int]): Must be either 3 or 4. Determines how many points we use in our nPCF.

  • projected ([bool]): Flag to determine whether the user wants a projected 3/4 PCF or the Full. Defaults to False.

    • if projected:
      • m_max ([int]): If user chooses projected, we set an m_max (similar to the ell_max in 3D)
    • if not projected:
      • ell_max ([int]): If user choosees not projected (full nPCF) then ell_max is the highest order for calculation.
  • density_field_data ([ndarray]): A square ndarray of data that is periodic. Must be 2D for projected and 3D for full.

  • save_dir ([string]): A string to tell the algorithm where to save and store files. All temporary files will be stored here.

  • save_name ([string]): A string to tell the algorithm what to name the files.

  • nbins ([int]): Number of bins to be used in nPCF calculation.

  • bin_spacing ([string]): A string to determine the spacing of bins. Options are 'LIN', 'INV', or 'LOG'

  • bin_min ([int]): The lower bound of the inner most bin. Default is 1. Optional.

  • physical_boxsize ([float]): An optional parameter if using a physical scale. The length of one side of the data.

  • rmin ([float]): minimum calculation distance (determins bin_min)

  • rmax ([float]): maximum calculation distance (determins bin_max)

Workflow:

The map of SARABANDE is as follows:

For more information about each algorithm, please read (Sunseri et al. 2022)

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

sarabande-0.0.4.tar.gz (12.1 kB view details)

Uploaded Source

Built Distribution

sarabande-0.0.4-py3-none-any.whl (16.9 kB view details)

Uploaded Python 3

File details

Details for the file sarabande-0.0.4.tar.gz.

File metadata

  • Download URL: sarabande-0.0.4.tar.gz
  • Upload date:
  • Size: 12.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.9

File hashes

Hashes for sarabande-0.0.4.tar.gz
Algorithm Hash digest
SHA256 e644c0769d36e59e1a967bc1c983ad75f1208c46886e6e5fe73fdbc3787e6436
MD5 7df460f2fbcf28a88b322d2a5eccd93e
BLAKE2b-256 5e5810c12fd8f85014c05f9b7bd04fac20ec40505a232eaad14d2fd0a1fcf884

See more details on using hashes here.

Provenance

File details

Details for the file sarabande-0.0.4-py3-none-any.whl.

File metadata

  • Download URL: sarabande-0.0.4-py3-none-any.whl
  • Upload date:
  • Size: 16.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.9

File hashes

Hashes for sarabande-0.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 36da96c2b050f371c0fd8b355d6ff36a4571da42fc21ed813867df387c34fe6c
MD5 02fd8d34e1f7fd7f2cebd882bc0b6796
BLAKE2b-256 f910f5c384d052de7645605a7867fb466367831eca6004e9a41d5746be1a678e

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