1.6.7 • Published 5 months ago

@trainerday/cycling-metrics v1.6.7

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License
ISC
Repository
github
Last release
5 months ago

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

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Deployment

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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
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