Load the data



In [1]:

    
import tcxparser
import pandas as pd
from datetime import datetime
from os import listdir
from os.path import join



In [2]:

    
def get_hr_data(tcx_path):
    tcx = tcxparser.TCXParser(tcx_path)
    hr_values = tcx.hr_values()
    time_values = [datetime.strptime(t, '%Y-%m-%dT%H:%M:%S.000Z') for t in tcx.time_values()]
    elapsed = [(tv - time_values[0]).seconds for tv in time_values]
    return pd.DataFrame(data={'elapsed': elapsed, 'hr': hr_values})

def load_data(dir_path):
    tcx_filenames = [f for f in listdir(dir_path) if f.endswith('.tcx')]
    data = [get_hr_data(join(dir_path, f)) for f in tcx_filenames]
    dates = [datetime.strptime(f.split('_')[1], '%Y%m%d') for f in tcx_filenames]
    return data, dates



In [3]:

    
activities, activity_dates = load_data('data')

What does the data look like?



In [4]:

    
first_activity = activities[0]
first_activity.head()



In [5]:

    
first_activity.tail()

...and visualise the data with Bokeh



In [6]:

    
import bokeh
from bokeh.io import output_notebook
from bokeh.plotting import figure, show
from bokeh.palettes import Blues9, Spectral9, RdYlGn5
from bokeh.models import BoxAnnotation
from bokeh.models import Range1d



In [7]:

    
output_notebook()









    





    
        
        Loading BokehJS ...

What does the first activity look like?



In [8]:

    
p = figure(plot_width=800, tools='box_zoom,resize,reset,hover')

p.line(first_activity.elapsed, first_activity.hr, line_width=2)

show(p)









    






    







    Out[8]:




<Bokeh Notebook handle for In[8]>



In [9]:

    
WALKING = Spectral9[0]
JOGGING = Spectral9[1]
RUNNING = Spectral9[6]

p = figure(plot_width=800, tools='box_zoom,resize,reset,hover')

p.line(first_activity.elapsed, first_activity.hr, line_width=2)

p.add_layout(BoxAnnotation(left=0, right=300, fill_alpha=0.1, line_color=WALKING, fill_color=WALKING))
p.add_layout(BoxAnnotation(left=300, right=600, fill_alpha=0.1, line_color=JOGGING, fill_color=JOGGING))
p.add_layout(BoxAnnotation(left=600, right=3000, fill_alpha=0.1, line_color=RUNNING, fill_color=RUNNING))
p.add_layout(BoxAnnotation(left=3000, right=3300, fill_alpha=0.1, line_color=JOGGING, fill_color=JOGGING))
p.add_layout(BoxAnnotation(left=3300, right=3600, fill_alpha=0.1, line_color=WALKING, fill_color=WALKING))

show(p)









    






    







    Out[9]:




<Bokeh Notebook handle for In[9]>



In [10]:

    
TOOLS = 'box_zoom,resize,reset,hover'
WIDTH=800
BAND_OPACITY=0.1

WALKING = Spectral9[0]
JOGGING = Spectral9[1]
RUNNING = Spectral9[6]

def plot_activity(activity):
    p = figure(plot_width=WIDTH, tools=TOOLS)
    p.line(activity.elapsed, activity.hr, line_width=2)
    return p

def add_intensity_band(p, left, right, colour):
    band = BoxAnnotation(left=left, right=right, fill_alpha=BAND_OPACITY, line_color=colour, fill_color=colour)
    p.add_layout(band)

def add_intensity_bands(p):
    add_intensity_band(p, 0, 300, WALKING)
    add_intensity_band(p, 300, 600, JOGGING)
    add_intensity_band(p, 600, 3000, RUNNING)
    add_intensity_band(p, 3000, 3300, JOGGING)
    add_intensity_band(p, 3300, 3600, WALKING)

Now all activities



In [11]:

    
p = figure(plot_width=WIDTH, tools=TOOLS)

for activity in activities:
    p.line(activity.elapsed, activity.hr, line_width=2)

show(p)









    






    







    Out[11]:




<Bokeh Notebook handle for In[11]>

What's going on? How do they vary over time?



In [12]:

    
p = figure(plot_width=WIDTH, tools=TOOLS)

colours = list(Blues9); colours.reverse()

for activity in activities:
    line_colour = colours.pop()
    p.line(activity.elapsed, activity.hr, line_width=2, line_color=line_colour)

show(p)









    






    







    Out[12]:




<Bokeh Notebook handle for In[12]>



In [13]:

    
X_LABEL = 'Elapsed Time (s)'
Y_LABEL = 'Heart Rate (BPM)'

def plot_activities_colourful(activities):
    p = figure(plot_width=WIDTH, tools=TOOLS, x_axis_label=X_LABEL, y_axis_label=Y_LABEL)
    colours = list(Blues9); colours.reverse()
    for activity in activities:
        line_colour = colours.pop()
        p.line(activity.elapsed, activity.hr, line_width=2, line_color=line_colour)
    return p

def focus(p, start, end, hr_min, hr_max):
    p.x_range = Range1d(start, end)
    p.y_range = Range1d(hr_min, hr_max)

All together now!



In [14]:

    
p = plot_activities_colourful(activities)
add_intensity_bands(p)
focus(p, 0, 3600, 70, 170)
show(p)









    






    







    Out[14]:




<Bokeh Notebook handle for In[14]>

Zooming in on the first transition



In [15]:

    
p = plot_activities_colourful(activities)
add_intensity_bands(p)

p.title = 'Walking to Jogging'
focus(p, 240, 600, 80, 140)

show(p)









    






    







    Out[15]:




<Bokeh Notebook handle for In[15]>



In [16]:

    
p = plot_activities_colourful(activities)
add_intensity_bands(p)

p.title = 'Jogging to Running'
focus(p, 540, 900, 115, 155)

show(p)









    






    







    Out[16]:




<Bokeh Notebook handle for In[16]>



In [17]:

    
p = plot_activities_colourful(activities)
add_intensity_bands(p)

p.title = 'Running to Jogging'
focus(p, 2940, 3300, 135, 165)

show(p)

	elapsed	hr
0	0	95
1	1	94
2	7	91
3	9	88
4	21	91

	elapsed	hr
482	3587	121
483	3589	121
484	3590	122
485	3591	122
486	3598	120