Pace Check

#import packages I will be using
import geopandas as gpd
import pandas as pd
import numpy as np
import fiona
import folium
from folium.plugins import * 
import matplotlib.pyplot as plt
import datetime

path = '/Users/Jackson/Downloads/export_53889752/activities/3282057413.gpx'

fiona.listlayers(path)

run = gpd.read_file(path, layer='tracks'
                   ).dropna(how='all', axis=1)

pings = gpd.read_file(path, layer='track_points'
                     ).dropna(how='all', axis=1)

run

pings

pings.ele.plot(figsize=(15,5), c='g');
plt.ylabel('Elevation (ft)');
plt.xlabel('Ping');

pings['hear_rate'] = pings.gpxtpx_TrackPointExtension.str.extract("<gpxtpx:hr>(\d{3})</gpxtpx:hr>").astype(int)

pings.hear_rate.plot(figsize=(15,5), c = 'm');
plt.ylabel('Heart Rate (bpm)');
plt.xlabel('Ping');

run.plot(figsize=(30,30));
plt.axis('off');

pings.plot(markersize=.2, figsize=(30,30), c='red');
plt.axis('off');

pings.crs #current projection

#switch projections to get euclidean distance
pings_in_meters = pings.to_crs({'init':'epsg:3857'})

# Get distance between consecutive points
pings['distance_meters'] = pings_in_meters.distance(pings_in_meters.shift(1))

pings.distance_meters.describe()

# make sure the time stamp is properly reckognized
pings.time = pd.to_datetime(pings.time)

#get time in seconds between consecutive pings
pings['seconds_past'] = pings.time.diff().dt.total_seconds()

pings.seconds_past.describe()

# calc running pace in minutes per mile
pings['pace'] = pings.seconds_past / pings.distance_meters * 26.8223333

# take the rolling average between every 3 pings to smooth measurement error
pings.pace = pings.pace.rolling(3, min_periods=1, center=True).mean()

pings.pace.plot(figsize=(15,5));

plt.ylabel('Pace (Minutes per Mile)');
plt.xlabel('Ping');

pings[pings.pace>20]

#init fig and ax object
fig, ax = plt.subplots(figsize=(30,30))

#plot the pings in red
pings.plot(markersize=.2, c='r', ax=ax);

#get outlier pings, shown above
outlier_pings = pings[pings.pace>20]

#plot the outlier pings in green
outlier_pings.plot(markersize=5, c='g', ax=ax); 

#plot a circle around the green outlier pings to highlight them
ax.scatter(x = outlier_pings.geometry.x.mean(),
           y = outlier_pings.geometry.y.mean(),
           marker='o',
           s=2000,
           facecolors='none',
           edgecolors='b'
          );

plt.axis('off');

from branca import colormap

pace_cm = colormap.LinearColormap(['lightblue', 'lightgreen','yellow','orange', 'red'][::-1],
                                  vmin=pings.pace.quantile(.1).round(1),
                                  vmax=pings.pace.quantile(.9).round(1),
                                  caption='Pace Legend (Minutes per Mile)'
                                 )

pace_cm

def strformatpace(pace_in_min_decimals):
    
    #get the exact time diff
    delta_microsec_res = datetime.timedelta(minutes=pace_in_min_decimals) 
    
    #round time diff to nearest second
    delta_second_res = datetime.timedelta(seconds = delta_microsec_res.seconds + (delta_microsec_res.microseconds > 5e5)) 

    #format as string, remove leading zeros
    out_str = str(delta_second_res)[2:]
    
    if out_str[0]=='0':
        out_str=out_str[1:]
        
    return out_str

# get starting map location
start = [run.centroid.y, run.centroid.x]

# init folium map
m = folium.Map(location=start, zoom_start=15, tiles='Carto db Positron')

# init a folium feature group to put line segments in
segments_between_pings = folium.FeatureGroup().add_to(m)

# iterate over rows of pings
for index, row in pings.iterrows():
    
    if index==0: continue #first row has not line segments
    
    #the coords of the polyline are the pings 
    coords = [[pings.loc[index-1, 'geometry'].y, pings.loc[index-1, 'geometry'].x],
              [pings.loc[index, 'geometry'].y, pings.loc[index, 'geometry'].x]] 
    
    
    folium.PolyLine(locations = coords,
                        weight = max(3, row.ele/2), # line thickness is elevation, min is 3 though
                        color=pace_cm(row.pace), # color map gradient for pace
                        tooltip=(f'<strong>Pace</strong>: {strformatpace(row.pace)}/mile<br>' #make tooltip to show info
                                 f'<strong>Elevation</strong>: {round(row.ele)} feet<br>'
                                 f'<strong>Heart Rate</strong>: {row.hear_rate} bpm'),
                        ).add_to(segments_between_pings) #add to feature group

    
pace_cm.add_to(m) # add the pace colormap as a legend

m # show map