Read Garmin GPX with heartrate

In [1]:

    

import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime
import pandas as pd
from lxml import etree

%matplotlib inline


    

In [2]:

    

fn = "activity_721671330.gpx"
tree = etree.parse(fn)


    

In [3]:

    

namespace = {'def': 'http://www.topografix.com/GPX/1/1',
             'gpxtpx': 'http://www.garmin.com/xmlschemas/TrackPointExtension/v1',
             'gpxx': 'http://www.garmin.com/xmlschemas/GpxExtensions/v3',
             'xsi': 'http://www.w3.org/2001/XMLSchema-instance'
             }


    

In [4]:

    

elist = tree.xpath('./def:trk//def:trkpt',namespaces=namespace)
lonlat = [e.values() for e in elist]
lon = np.array([float(i[0]) for i in lonlat])
lat = np.array([float(i[1]) for i in lonlat])
print lon[0],lat[0],np.shape(lon)


    

    




-70.5314680841 41.5790332574 (725L,)

In [5]:

    

elist = tree.xpath('./def:trk//def:time',namespaces=namespace)
fmt = '%Y-%m-%dT%H:%M:%S.%fZ'
time = [datetime.strptime(d.text, fmt) for d in elist]
print time[0], np.shape(time)


    

    




2015-03-16 20:32:31 (725L,)

In [6]:

    

elist = tree.xpath("./def:trk//gpxtpx:hr", namespaces=namespace)
hr = [float(e.text) for e in elist]
print hr[0], np.shape(hr)


    

    




120.0 (725L,)

In [7]:

    

df = pd.DataFrame.from_dict(dict(time=time, lon=lon, lat=lat, hr=hr))
df.set_index('time', drop=True, inplace=True)


    

In [8]:

    

df.head(5)


    

    
Out[8]:






  

    

      

      
hr
      
lat
      
lon
    
    

      
time
      

      

      

    
  
  

    

      
2015-03-16 20:32:31
      
 120
      
 41.579033
      
-70.531468
    
    

      
2015-03-16 20:32:32
      
 120
      
 41.579034
      
-70.531459
    
    

      
2015-03-16 20:32:35
      
 117
      
 41.579035
      
-70.531433
    
    

      
2015-03-16 20:32:42
      
 117
      
 41.579039
      
-70.531378
    
    

      
2015-03-16 20:32:43
      
 128
      
 41.579041
      
-70.531372
    
  

In [9]:

    

df['hr'].plot(figsize=(12,4));


    

In [10]:

    

import cartopy.crs as ccrs
from cartopy.io.img_tiles import MapQuestOpenAerial

geodetic = ccrs.Geodetic(globe=ccrs.Globe(datum='WGS84'))
b=np.array([lon.min(), lat.min(), lon.max(), lat.max()])

plt.figure(figsize=(12,12))
# Open Source Imagery from MapQuest (max zoom = 16?)
tiler = MapQuestOpenAerial()
# Open Street Map (max zoom = 18?)
#tiler = OSM()
ax = plt.axes(projection=tiler.crs)
dx=b[2]-b[0]
dy=b[3]-b[1]
extent = (b[0]-0.1*dx,b[2]+0.1*dx,b[1]-0.1*dy,b[3]+0.1*dy)
ax.set_extent(extent, geodetic)
ax.add_image(tiler, 14)
plt.plot(lon,lat,'m-',transform=ccrs.PlateCarree());
gl=ax.gridlines(draw_labels=True)
gl.xlabels_top = False
gl.ylabels_right = False


    

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