Skip to main content

Tools for interacting with GT's LF AWESOME Receiver data

Project description

LF Data

This project provides a set of useful tools for interacting with data taken from the LF AWESOME receivers maintained by the LF Radio Lab at Georgia Tech. This data is available publicly at Waldo World.

Installation

Run the following to install:

pip install lfdata

Example Usage

from lfdata import data_loader

# Load an entire .mat file
data = data_loader("path_to_mat_file")

# Load a specific variable or set of variables
variables = ["station_name", "call_sign", "data"]
data = data_loader("path_to_mat_file", variables)

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

lf-0.0.1-py3-none-any.whl (21.1 kB view details)

Uploaded Python 3

File details

Details for the file lf-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: lf-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 21.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.3

File hashes

Hashes for lf-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 99c7cce2f44b9ad8ef4bcfed51a09876d17529d9d17a88ef39ec276c4eda4c27
MD5 eade2d9c166c7c9931a1966750023d9b
BLAKE2b-256 110fa102b3113fda75866eb408d20f88750bfe66fdd74b66df02fbd126602759

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