Running in the Heat good thing I live where it is almost always too cold to breathe

def getHRs(runtimes):
    coldHR=[]
    warmHR=[]
    coldTot=[]
    warmTot=[]

    for t in runtimes:             # go through the elements in the table
        # construct the path from the elements in the table
        path = "hr-heat/"+t[0]+"-"+t[1].replace(":","")+".gpx"

        # open the GPX files and parse the XML
        with open(path) as f:
            tree = ElementTree.parse(f)
        # extract the heart rate values from the XML tree into a list
        a = [int(node.text) for node in
             list( tree.iter("{http://www.garmin.com/xmlschemas/TrackPointExtension/v1}hr") )]

        if t[2] == "AA":   # if we're in Ann Arbor where it's cold
            if not coldHR:
                coldHR = a
                coldTot = [1 for m in coldHR]  # make the count '1' for all of the values
            else:
                for m in range(min(len(coldHR),len(a))):
                    coldHR[m] = (coldHR[m] + a[m])
                    if coldTot[m] == None:
                        coldTot[m] = 1  # extend the array (this might not actually work)
                    else:
                        coldTot[m] += 1 # increment the count for averaging later

        elif t[2] == "SJ":  # if we're in San Juan where it's warm, do all the same stuff
            if not warmHR:
                warmHR = a
                warmTot = [1 for m in warmHR]
            else:
                for m in range(min(len(warmHR),len(a))):
                    warmHR[m] = (warmHR[m] + a[m])
                    if warmTot[m] == None:
                        warmTot[m] = 1
                    else:
                        warmTot[m] += 1

        else:    # we don't know where we are
            pass

    # apply all of our averages
    coldHR = [coldHR[m]/coldTot[m] for m in range(len(coldTot))]
    warmHR = [warmHR[m]/warmTot[m] for m in range(len(warmTot))]

    return (warmHR, coldHR)

def plotHRs(HRs):

    cold=[HRs[x][0] for x in range(len(HRs))]
    warm=[HRs[x][1] for x in range(len(HRs))]
    x = range(len(cold))

    fig = plt.figure()
    fig.suptitle("Heart Rate in Warm and Cold Weather", fontsize=14, fontweight='bold')
    ax = plt.subplot(111)
    ax.set_ylim(0,180)  # don't let autoscaling lie with plots
    # turn off a bunch of chartjunk
    ax.set_xticklabels(''*len(x)) # turn off the xticklabels, since they don't mean anything
    ax.spines['top'].set_visible(False)   # turn off top part of box (top spine)
    ax.spines['right'].set_visible(False) # turn off right part of box (right spine)
    ax.yaxis.set_ticks_position('left')   # turn off tick marks on right
    ax.xaxis.set_ticks_position('none')   # turn off tick marks on top and bottom
    # http://matplotlib.org/examples/ticks_and_spines/spines_demo.html
    # http://matplotlib.org/api/axis_api.html

    startSlopeCalc = 75   # heuristically skip the ramp-up period when calculating slope
    mC, bC = np.polyfit(x[startSlopeCalc:], cold[startSlopeCalc:], 1)
    mW, bW = np.polyfit(x[startSlopeCalc:], warm[startSlopeCalc:], 1)

    # overlay the fit lines
    plt.plot(cold,'b',label="Cold Weather, slope:"+str(round(mC,2)))
    plt.plot(warm,'r',label="Warm Weather, slope:"+str(round(mW,2)))

    plt.legend(loc=3) # 3=lower-left (see pydoc matplotlib.pyplot.legend)
    plt.xlabel('')
    plt.ylabel('heart rate (bpm)')

    # generate and plot y-values for fit lines
    yfitC=[x*mC + bC for x in range(len(cold))]
    yfitW=[x*mW + bW for x in range(len(cold))]
    plt.plot(yfitC,'b')
    plt.plot(yfitW,'r')

    return(fig)

if __name__ == "__main__":

    import numpy as np
    import matplotlib
    import matplotlib.pyplot as plt
    from xml.etree import ElementTree

    (w,c) = getHRs(runtimes)
    HRs = zip(c,w)    # put the cold and hot HR lists together, truncating to the shortest

    fig = plotHRs(HRs)
    filename = "assets/running-hr-warm-cold.png"
    fig.savefig(filename, format='png')
    return(filename)