Metadata-Version: 2.1
Name: heartandsole
Version: 0.0.6
Summary: Python library for analysis of ANT/Garmin .fit files
Home-page: https://github.com/aaron-schroeder/heartandsole
Author: Aaron Schroeder
Author-email: aaron@trailzealot.com
License: MIT License
Description: # heartandsole
        
        > Python library for analysis of running data files.
        
        [![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)
        [![License](http://img.shields.io/:license-mit-blue.svg)](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
        
        [![License](http://img.shields.io/:license-mit-blue.svg)](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.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: License :: OSI Approved :: MIT License
Description-Content-Type: text/markdown
