Skip to main content

ARL Python Tools

Project description

Packages such as numpy and scipy provide excellent mathematical tools for scientists and engineers using Python. However, these packages are still young and evolving, and understandably have some gaps, especially when it comes to domain-specific requirements. The arlpy package aims to fill in some of the gaps in the areas of underwater acoustics, signal processing, and communication. Additionally, arlpy also includes some commonly needed utilities and plotting routines based on bokeh.

General modules

The following modules are general and are likely to be of interest to researchers and developers working on signal processing, communication and underwater acoustics:

  • Signal processing (arlpy.signal)

  • Communications (arlpy.comms)

  • Beamforming and array processing (arlpy.bf)

  • Stable distributions (arlpy.stable)

  • Geographical coordinates (arlpy.geo)

  • Underwater acoustics (arlpy.uwa)

  • Underwater acoustic propagation modeling (arlpy.uwapm)

  • Plotting utilities (arlpy.plot)

  • Common utilities (arlpy.utils)

Special-purpose modules

The following modules are specific to tools available at the ARL and may not be of general interest to others:

  • Digital Towed Array (arlpy.dtla)

  • ROMANIS (arlpy.romanis)

  • HiDAQ (arlpy.hidaq)

  • UNET (arlpy.unet)

Usage

Installation:

pip install arlpy

To import all general modules:

import arlpy

Notes

Png export of bokeh plots requires selenium, pillow and phantomjs. These are not installed as automatic depdendencies, since they are optional and only required for png export. These should be installed manually, if desired.

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

arlpy-1.8.4.tar.gz (44.2 kB view details)

Uploaded Source

File details

Details for the file arlpy-1.8.4.tar.gz.

File metadata

  • Download URL: arlpy-1.8.4.tar.gz
  • Upload date:
  • Size: 44.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.7

File hashes

Hashes for arlpy-1.8.4.tar.gz
Algorithm Hash digest
SHA256 87dc3d450cf545f2cecbc8b73c2475f872fcf4b38c267f56e1d51b96005367e9
MD5 d89bdc777dc77d6b1022a75d87d83ab3
BLAKE2b-256 bab8cd2856796a7fd5c83c8c9ae73a0a49105e31251b0da7ba693ac85aacc197

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