Running_Wild

所属分类:其他
开发工具:R
文件大小:0KB
下载次数:0
上传日期:2020-10-06 03:23:10
上 传 者sh-1993
说明:  “奔跑野外”虚拟比赛的数据处理和分析,皮埃蒙特野生动物中心的筹款人,
(Data manipulation and analysis for "Running Wild" virtual race, fundraiser for Piedmont Wildlife Center,)

文件列表:
29_not athletic 2.gpx (264631, 2020-10-05)
5kRun.draft1.py (7687, 2020-10-05)
LICENSE (35149, 2020-10-05)
RunScript.ParseMultipleSubmissions.R (4750, 2020-10-05)
RunScript.Sept2020.R (5597, 2020-10-05)
RunScriptWithViz.draft2.R (3727, 2020-10-05)
StravaRegression.png (200361, 2020-10-05)
activities/ (0, 2020-10-05)
activities/1221571927.gpx (122403, 2020-10-05)
activities/2600057939.gpx (78846, 2020-10-05)
activities/2605693556.gpx (336716, 2020-10-05)
activities/2610931686.gpx (131951, 2020-10-05)
activities/2760896729.gpx (64313, 2020-10-05)
activities/2915779083.gpx (116880, 2020-10-05)
activities/2929194330.gpx (53813, 2020-10-05)
activities/2937114499.gpx (108676, 2020-10-05)
activities/2947685040.gpx (137676, 2020-10-05)
activities/2954131832.gpx (253053, 2020-10-05)
activities/2958300786.gpx (159900, 2020-10-05)
activities/2971445305.gpx (146561, 2020-10-05)
activities/2982169417.gpx (407124, 2020-10-05)
activities/2985764592.gpx (261485, 2020-10-05)
activities/2999721589.gpx (116736, 2020-10-05)
activities/3002529466.gpx (496180, 2020-10-05)
activities/3009065976.gpx (34718, 2020-10-05)
activities/3014799232.gpx (159360, 2020-10-05)
activities/3026223663.gpx (190586, 2020-10-05)
activities/3026267603.gpx (104760, 2020-10-05)
activities/3042538227.gpx (137936, 2020-10-05)
activities/3075269901.gpx (386344, 2020-10-05)
activities/3075332811.gpx (212106, 2020-10-05)
activities/3086723013.gpx (179695, 2020-10-05)
activities/3094199197.gpx (3250, 2020-10-05)
activities/3097676991.gpx (144542, 2020-10-05)
activities/3103134461.gpx (2285, 2020-10-05)
activities/3106270347.gpx (186252, 2020-10-05)
activities/3175750344.gpx (101358, 2020-10-05)
activities/3208151184.gpx (245678, 2020-10-05)
activities/3222053585.gpx (191283, 2020-10-05)
... ...

# Running_Wild Data manipulation and analysis for "Running Wild" virtual race, fundraiser for Piedmont Wildlife Center https://run.piedmontwildlifecenter.org/ # The Problem As it is a virtual race, competitors submit individual race routes that are tracked using smartphone apps such as Strava. However, we needed a way to compare the different race routes which inevitably had differences in steepness (gradient). The code shows calculation of a Grade Adjusted Pace (GAP) - that is the speed adjusted to account for the different gradients in each individual race, in order to make the race as fair as possible given the differences in routes. The graph below shows the function used to adjust the pace given the gradient which was calculated from lat/long coordinates and elevation over each time point recorded by the app. ![StravaPolynomial](https://github.com/ElsitaK/Running_Wild/blob/master/StravaRegression.png) More information on GAP here: https://medium.com/strava-engineering/an-improved-gap-model-8b07ae8886c3 # Files Files include several scripts and and sample gpx files. - "RunScript.Sept2020.R": script for use within the webpage, uses the trackeR package to process gpx/ tcx files - input is a user-submitted gpx or tcx file and a specified run distance (5K, 10K, or 15K) - outputs a grade adjusted pace (m/s), the actual pace (m/s), the absolute elevational change in meters, the grade adjusted race time (minutes), the actual race time (minutes), as well as latitude coordinates, longitude coordinates, and the date/time from the start point for future viz - "RunScriptWithViz.draft2.R": includes the above, and also includes a visualization of the polynomial formula used to relate gradient to adjusted pace and additional race graphs (eg distance versus altitude) created using ggplot2 - "5kRun.draft1.py": similar to above but in python, uses the geopy package to calculate geodesic distance from lat/long coordinates and also includes additional race graphs (eg map of the race route created from lat/long coordinates) created using matplotlib - "RunScript.ParseMultipleSubmissions.R": extracts longitude, latitude and datetime from the 'activities' folder containing sample gpx files for further visualization and map creation # Map Visualization The folder "map_of_users" includes html, css and javascript code (using D3.js) to map the locations of each user submitted route. It runs a timer to add a point on the map for each route based on the time the race was run. # Required Packages R packages: - trackeR - zoo - hms - lubridate - ggplot2 Python packages: - os - gpxpy - pandas - matplotlib - geopy # Contact Author: elsita.k@gmail.com

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