PyPI 官网下载 | heartandsole-0.0.8.tar.gz

# heartandsole > Python library for analysis of running data files. [](https://www.python.org/downloads/release/python-360/) [](http://badges.mit-license.org) --- ## Table of Contents - [Introduction](#introduction) - [Dependencies and Installation](#dependencies-and-installation) - [Example](#example) - [Project Status](#project-status) - [References](#references) - [Contact](#contact) - [License](#license) --- ## Introduction heartandsole is designed to work with running or walking activity files. It allows for extraction of data from a `.fit` file as well as calculations, such as the following: - elapsed time - moving time - average heart rate - running power (based on Dr. Philip Friere Skiba's GOVSS algorithm) - average running power - normalized running power (based on information publicly available about TrainingPeaks' NP® and NGP®, and Dr. Philip Friere Skiba's GOVSS algorithm) - intensity (based on information publicly available about TrainingPeaks' IF®) - training stress (based on information publicly available about TrainingPeaks' TSS® and Dr. Philip Friere Skiba's GOVSS algorithm) My impetus for this project was to implement a version of Philip Friere Skiba's GOVSS algorithm (with tweaks to better align with the underlying research). The end result will be a free, open-source version of proprietary calculations found in platforms like Strava and Training Peaks. My hope is that other runners will benefit as I have from taking these secret algorithms out of their black box, by understanding the science behind these calculations and training smarter. This package was originally forked from Michael Traver's [fitanalysis package](https://github.com/mtraver/python-fitanalysis), but the two projects diverged significantly enough for me to move my fork to a separate repository. I am indebted to Michael for writing such a clean, useful, easy-to-understand package that served as heartandsole's starting point. --- ## Dependencies and Installation [Pandas](http://pandas.pydata.org/), [NumPy](http://www.numpy.org/), [fitparse](https://github.com/dtcooper/python-fitparse), and [spatialfriend](https://github.com/aaron-schroeder/spatialfriend) are required. `pip install heartandsole` to install. --- ## Example heartandsole provides the `Activity` class. ```python import heartandsole activity = heartandsole.Activity('my_activity.fit') print(activity.elapsed_time) print(activity.moving_time) # Also available for heart rate and cadence. print(activity.mean_power) # Uses power values from .fit file if available, # otherwise calculates running power from speed, # distance, and elevation data. print(activity.norm_power) # Intensity and training stress calculations require # a functional threshold power value (in Watts/kg). print(activity.intensity(17.0)) ``` Construction of an `Activity` parses the `.fit` file and detects periods of inactivity. The decision to remove inactive periods is left to the user. --- ## Project Status ### Complete ### Current Activities ### Future Work --- ## References Coggan, A. (2012, June 20). Re: Calculate Normalised Power for an Interval [Online forum comment]. Retrieved June 14, 2017, from http://www.timetriallingforum.co.uk/index.php?/topic/69738-calculate-normalised-power-for-an-interval/&do=findComment&comment=978386 Coggan, A. (2016, February 10). Normalized Power, Intensity Factor and Training Stress Score. _TrainingPeaks_. Retrieved June 14, 2017, from https://www.trainingpeaks.com/blog/normalized-power-intensity-factor-training-stress/ Coggan, A. (2003, March 13). TSS and IF - at last! [Online forum post]. Retrieved June 14, 2017, from http://lists.topica.com/lists/wattage/read/message.html?mid=907028398&sort=d&start=9353 Di Prampero, P. E., Atchou, G., Brückner, J. C., & Moia, C. (1986). The energetics of endurance running. _European Journal of Applied Physiology and Occupational Physiology, 55_(3), 259-266. Di Prampero, P. E., Capelli, C., Pagliaro, P., Antonutto, G., Girardis, M., Zamparo, P., & Soule, R. G. (1993). Energetics of best performances in middle-distance running. _Journal of Applied Physiology, 74_(5), 2318-2324. Eckner, A. (2017, April 3). Algorithms for Unevenly Spaced Time Series: Moving Averages and Other Rolling Operators. Retrieved June 14, 2017, from http://eckner.com/papers/Algorithms%20for%20Unevenly%20Spaced%20Time%20Series.pdf Friel, J. (2009, September 21). Estimating Training Stress Score (TSS). _TrainingPeaks_. Retrieved June 22, 2017, from https://www.trainingpeaks.com/blog/estimating-training-stress-score-tss/ Minetti, A. E., Moia, C., Roi, G. S., Susta, D., & Ferretti, G. (2002). Energy cost of walking and running at extreme uphill and downhill slopes. _Journal of Applied Physiology, 93_(3), 1039-1046. Pugh, L. G. E. (1971). The influence of wind resistance in running and walking and the mechanical efficiency of work against horizontal or vertical forces. _The Journal of Physiology, 213_(2), 255-276. Skiba, P. F. (2006, September 16). Calculation of Power Output and Quantification of Training Stress in Distance Runners: The Development of the GOVSS Algorithm. _RunScribe_. Retrieved August 20, 2019, from http://runscribe.com/wp-content/uploads/power/GOVSS.pdf --- ## Contact Reach out to me at one of the following places! - Website: <a href="https://trailzealot.com" target="_blank">trailzealot.com</a> - LinkedIn: <a href="https://www.linkedin.com/in/aarondschroeder/" target="_blank">linkedin.com/in/aarondschroeder</a> - Twitter: <a href="https://twitter.com/trailzealot" target="_blank">@trailzealot</a> - Instagram: <a href="https://instagram.com/trailzealot" target="_blank">@trailzealot</a> - GitHub: <a href="https://github.com/aaron-schroeder" target="_blank">github.com/aaron-schroeder</a> --- ## License [](http://badges.mit-license.org) This project is licensed under the MIT License. See [LICENSE](https://github.com/aaron-schroeder/heartandsole/blob/master/LICENSE) file for details.