Skip to main content

Tools for interacting with GT's LF AWESOME Receiver data

Project description

LF Logo

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 lf

Example Usage

import lf

# Load an entire .mat file
data = lf.data.rx.load_rx_data("path_to_mat_file")

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

# Create an LFData object from two mat files or dictionaries
mat_files = ["amplitudeNS.mat", "phaseNS.mat", "amplitudeEW.mat", "phaseEW.mat"]
data = lf.data.rx.LFData(mat_files)

# Evaluate the quality of your data with the EvalLF object
data_eval = lf.data.rxquality.EvalLF(data)

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

lf-0.1.7.tar.gz (29.9 kB view details)

Uploaded Source

File details

Details for the file lf-0.1.7.tar.gz.

File metadata

  • Download URL: lf-0.1.7.tar.gz
  • Upload date:
  • Size: 29.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.7.7

File hashes

Hashes for lf-0.1.7.tar.gz
Algorithm Hash digest
SHA256 e23e459629ba49879ddbd04b66bf9aecad2847c97b03bf1507798145dbf1e1bb
MD5 c643558221c9f983e2e71793e12e3d14
BLAKE2b-256 98e0764265750f34350c6c7246746a7b660c194465fc735d8846ea9d1f7045b2

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