npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

@trainerday/cycling-metrics

v1.6.7

Published

BETA - BETA This is still in the testing and refactoring phases. We plan to have it ready for general consumption in Oct 2019

Downloads

135

Readme

Cycling Metrics

BETA - BETA This is still in the testing and refactoring phases. We plan to have it ready for general consumption in Oct 2019

Cycling power data analysis. Includes both single workout analysis as well as multiple workout analysis. Takes data directly from Strava API Stream array format. Created in Type Script. Al

Getting Started

npm install @trainerday/cycling-metrics --save

var cm = require('@trainerday/cycling-metrics')

const power = [102, 106, 110, 114, 118, 120, 116, 112, 108, 104, 100]
const mmp = cm.getMeanMaxPowerCurve(power)
console.log(mmp)
//120,119,118,117,116,115,114,113,112,111,110

//we support power ramps, start at one percent and end at another 

const intervals = [[30,100,100],[30,100,100]] // minutes, wattsStart, wattsEnd
const trainingStress = cm.getTrainingStress(100, intervals) //ftp watts + intervals
console.log(trainingStress)
//100  60 minutes @100w with 100w ftp by definition is ts = 100


If you look at the tests there are many other methods.  We will add more examples here.
getIntensityFactor
getPowerDurationCurve
getMergedPDCurve - Will show a 7 day power curve best overlaying a 90 day power curve for example
getCTL - Chronic Training Load
getTSB - New and not finished yet

Running the tests

Explain how to run the automated tests for this system

Break down into end to end tests

Explain what these tests test and why

Give an example

And coding style tests

Explain what these tests test and why

Give an example

Deployment

Add additional notes about how to deploy this on a live system

Built With

  • Type Script
  • Jest (Testing framework)
  • ESlint

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

Versioning

We use SemVer for versioning. For the versions available, see the tags on this repository.

Authors

  • TrainerDay - Sponsor
  • Artur Tadrala - Initial work
  • Alex VanLaningham - Initial work

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

  • Special thanks to
    • Mark from GoldenCheetah
    • TrainingPeaks and Coggan for their leadership in volume based research
  • Hat tip to anyone whose code was used
  • Inspiration
  • etc