In [1]:
from lxml import etree
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime
import cartopy.crs as ccrs
from cartopy.io.img_tiles import MapQuestOpenAerial, MapQuestOSM, OSM
%matplotlib inline
In [ ]:
In [2]:
fn = r"activity_721671330.gpx"
tree = etree.parse(fn)
root = tree.getroot()
Find all the trkpt elements
In [3]:
string = ".//{http://www.topografix.com/GPX/1/1}"
lon, lat, time = [], [], []
for point in tree.findall(string + "trkpt"):
lon.append(point.attrib.get("lon"))
lat.append(point.attrib.get("lat"))
time.append(point.find(string + "time").text)
In [4]:
lon=np.array(lon).astype('float')
lat=np.array(lat).astype('float')
In [5]:
fmt = '%Y-%m-%dT%H:%M:%S.%fZ'
time = [datetime.strptime(d, fmt) for d in time]
Find all the hr elements in the gpstpx namespace
In [6]:
namespace = {'gpxtpx': 'http://www.garmin.com/xmlschemas/TrackPointExtension/v1',
'gpxx': 'http://www.garmin.com/xmlschemas/GpxExtensions/v3',
'xsi': 'http://www.w3.org/2001/XMLSchema-instance'
}
elist = tree.xpath(".//gpxtpx:hr", namespaces=namespace)
hr = [float(e.text) for e in elist]
Make the dataframe
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]:
Plot the heartrate
In [9]:
df['hr'].plot(figsize=(12,4));
Plot lon/lat with Cartopy
In [10]:
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
In [ ]: