In [1]:

    

%matplotlib inline
import matplotlib.pyplot as plt
import io as fio

fname = 'C:/Users/styler/workspace/illah/20100227.gpx'

ft = fio.open(fname)

ft.close()


    

    




---------------------------------------------------------------------------
IOError                                   Traceback (most recent call last)
<ipython-input-1-18f0e6896eac> in <module>()
      5 fname = 'C:/Users/styler/workspace/illah/20100227.gpx'
      6 
----> 7 ft = fio.open(fname)
      8 
      9 ft.close()

IOError: [Errno 2] No such file or directory: 'C:/Users/styler/workspace/illah/20100227.gpx'

In [16]:

    

import xml.etree.ElementTree as ET 
tree = ET.parse(fname) 
root = tree.getroot()


    

In [17]:

    

print root.keys


    

    




<bound method Element.keys of <Element '{http://www.topografix.com/GPX/1/1}gpx' at 0xeac81d0>>

In [18]:

    

root.attrib


    

    
Out[18]:





{'creator': '',
 'version': '1.1',
 '{http://www.w3.org/2001/XMLSchema-instance}schemaLocation': 'http://www.topografix.com/GPX/1/1 http://www.topografix.com/GPX/1/1/gpx.xsd'}

In [19]:

    

def get_element_by_tag(element, tag):
    if element.tag.endswith(tag):
        yield element
    for child in element:
        for g in get_element_by_tag(child, tag):
            yield g


    

In [20]:

    

def stripnamespace(xmltree):
    for node in xmltree.getiterator():
        if '}' in node.tag:
            node.tag = node.tag.split('}', 1)[1]


    

In [21]:

    

stripnamespace(root)
root.getchildren()


    

    
Out[21]:





[<Element 'trk' at 0xeac8f60>,
 <Element 'trk' at 0xec37c88>,
 <Element 'trk' at 0xec414a8>,
 <Element 'trk' at 0xed773c8>,
 <Element 'trk' at 0xed83668>]

In [22]:

    

root.getchildren()[1].getchildren()[1].getchildren()[0].getchildren()[1].text


    

    
Out[22]:





'2010-02-27T22:36:44Z'

In [23]:

    

vals = list()
for node in root.iter('trkpt'):
    vals.append(dict(node.items()+[('ele',node.getchildren()[0].text),('time',node.getchildren()[1].text)]))


    

In [24]:

    

lats = [val['lat'] for val in vals]
lons = [val['lon'] for val in vals]


    

In [25]:

    

plt.plot(lons,lats)


    

    
Out[25]:





[<matplotlib.lines.Line2D at 0x108bb748>]






    

In [2]:

    

import pandas
fname2 = '/Users/astyler/projects/ChargeCarData/csv/illah20100227_1.csv'
df = pandas.read_csv(fname2)
df.dtypes
#convert_numeric=True)


    

    
Out[2]:





Latitude           float64
Longitude          float64
Elevation          float64
Bearing            float64
PlanarDistance     float64
Speed              float64
Acceleration       float64
Power              float64
TotalEnergyUsed    float64
PeriodMS             int64
Time                 int64
dtype: object

In [3]:

    

df.head()


    

    
Out[3]:






  

    

      

      
Latitude
      
Longitude
      
Elevation
      
Bearing
      
PlanarDistance
      
Speed
      
Acceleration
      
Power
      
TotalEnergyUsed
      
PeriodMS
      
Time
    
  
  

    

      
0
      
40.429277
      
-79.915235
      
414.87
      
-0.73
      
7.47
      
7.474
      
0.000
      
5044.7621
      
0.0000
      
1000
      
1267328212000
    
    

      
1
      
40.429232
      
-79.915169
      
415.15
      
-0.73
      
7.47
      
7.474
      
0.000
      
5044.7826
      
1.4013
      
1000
      
1267328213000
    
    

      
2
      
40.429187
      
-79.915104
      
415.44
      
-0.76
      
5.49
      
5.508
      
-1.965
      
-7649.4367
      
2.8027
      
1000
      
1267328214000
    
    

      
3
      
40.429153
      
-79.915057
      
414.96
      
-0.64
      
3.17
      
3.187
      
-2.322
      
-1559.9135
      
0.6778
      
1000
      
1267328215000
    
    

      
4
      
40.429136
      
-79.915027
      
415.33
      
-0.64
      
3.17
      
3.187
      
0.000
      
5118.6085
      
0.2445
      
1000
      
1267328216000
    
  

In [4]:

    

#%pylab inline
#df.plot(x='Longitude',y='Latitude',c='Power')
%matplotlib notebook
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

p = plt.figure().gca(projection='3d')
p.plot(df.Longitude, df.Latitude, df.Power)
p.set_xlabel('Lon')
p.set_ylabel('Lat')
p.set_zlabel('Power')
plt.show()


    

In [9]:

    

p2 = plt.figure()

p.plot(df.Longitude, df.Latitude)
plt.show()


    

In [38]:

    

bp.show(p2)


    

In [35]:

    

import plotly.plotly as py
from plotly.graph_objs import *
data = [Scatter3d(x=df.Longitude, y=df.Latitude, z=df.Power,mode='lines')]
py.iplot(data, filename = 'basic-line')


    

    
Out[35]:

In [ ]: