2018-07-26 07:53:44 +00:00
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#!/usr/bin/env python
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import argparse
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import datetime
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import sys
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import gpx_parser
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import matplotlib
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matplotlib.use('Agg')
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import matplotlib.pyplot as plt
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import numpy
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import os
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import pandas as pd
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import collections
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def plot_bar_chart(labels, ticklabels, values, title, xlabel, ylabel, filename, xtick_rotation=0):
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fig = plt.figure()
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ax1 = fig.add_subplot(111)
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ax1.grid(zorder=0)
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ax1.spines["top"].set_visible(False)
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ax1.spines["bottom"].set_visible(False)
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ax1.spines["left"].set_visible(False)
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ax1.spines["right"].set_visible(False)
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plt.title(title)
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plt.xlabel(xlabel)
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plt.ylabel(ylabel)
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width = 1.0 / len(values) - 0.03
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x_base = numpy.arange(len(ticklabels))
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x_pos = list()
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for i in range(len(values)):
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x_pos.append([x + (width / 2) + i * width for x in range(len(x_base))])
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plt.bar(x_pos[i], values[i], width=width, label=labels[i], zorder=2)
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plt.xticks(x_base, ticklabels, rotation=xtick_rotation)
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# Tweak spacing to prevent clipping of tick-labels
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plt.subplots_adjust(bottom=0.2)
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plt.legend()
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plt.savefig(filename)
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class Gpx2Html(object):
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MONTH_LABELS = ['jan', 'feb', 'mar', 'apr', 'may', 'jun', 'jul', 'aug', 'sep', 'oct', 'nov', 'dec']
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def __init__(self, infolder, outfolder):
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self.infolder = infolder
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2018-07-26 12:20:15 +00:00
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self.outfolder = os.path.abspath(outfolder)
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self.distance_diag_file = 'distance.png'
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self.distance_diag_abs = os.path.join(self.outfolder, self.distance_diag_file)
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self.avg_spd_diag_file = 'avg_spd.png'
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self.avg_spd_diag_abs = os.path.join(self.outfolder, self.avg_spd_diag_file)
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self.last_n_days_diag_file = None
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self.html_file = os.path.join(self.outfolder, 'index.html')
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self.years_distance = list()
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self.years_avg_spd = list()
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self.years = list()
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def plot_distance_diagram(self):
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plot_bar_chart(self.years, self.MONTH_LABELS, self.years_distance,
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'Distance', 'Month', 'km', self.distance_diag_abs)
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def plot_avg_spd_diagram(self):
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plot_bar_chart(self.years, self.MONTH_LABELS, self.years_avg_spd,
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'Average Speed', 'Month', 'km/h', self.avg_spd_diag_abs)
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def plot_last_n_days(self, day_count):
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plot_bar_chart(["Distance", "Average speed"], self.date_distance.keys(),
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[self.date_distance.values(), self.date_avg_spd.values()],
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'Last {} days'.format(day_count), 'Date', 'km, km/h',
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os.path.join(self.outfolder, self.last_n_days_diag_file), 90)
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def write_html_file(self):
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with open(self.html_file, 'w') as handle:
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handle.write('<!DOCTYPE html>\n')
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handle.write('<html>\n')
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handle.write('<head>\n')
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handle.write('<style>\n')
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handle.write('table {\n')
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handle.write(' border-collapse: separate;\n')
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handle.write(' border-spacing: 20px 0;\n')
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handle.write('}\n')
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handle.write('th {\n')
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handle.write(' text-align: left;\n')
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handle.write('}\n')
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handle.write('</style>\n')
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handle.write('<title> Bicycle </title>\n')
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handle.write('</head>\n')
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handle.write('<body>\n')
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handle.write('<center>\n')
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handle.write('<h1> Bicycle </h1>\n')
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handle.write('<p>\n')
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handle.write('<table>\n')
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handle.write('<tr>\n')
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for year in self.years:
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handle.write('<th>{}</th>\n'.format(year))
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handle.write('</tr>\n')
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handle.write('<tr>\n')
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for i in range(len(self.years_distance)):
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handle.write('<td>{} km</td>\n'.format(round(sum(self.years_distance[i]), 1)))
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handle.write('</tr>\n')
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handle.write('</table>\n')
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handle.write('</p>\n')
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handle.write('<p>\n')
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handle.write('<IMG SRC="{}" ALT="Distance">\n'.format(self.distance_diag_file))
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handle.write('<IMG SRC="{}" ALT="Distance">\n'.format(self.avg_spd_diag_file))
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handle.write('<IMG SRC="{}" ALT="Distance">\n'.format(self.last_n_days_diag_file))
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handle.write('</p>\n')
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handle.write('</body>\n')
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handle.write('<center>\n')
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handle.write('</html>\n')
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2018-07-26 07:53:44 +00:00
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def process(self):
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2018-07-26 12:20:15 +00:00
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self.years[:] = []
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self.years_avg_spd[:] = []
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self.years_distance[:] = []
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2018-07-26 07:53:44 +00:00
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self.tracks = gpx_parser.Tracks(self.infolder)
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for year in range(2017, datetime.datetime.now().year + 1):
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month_avg_spd = {1:0, 2:0, 3:0, 4:0, 5:0, 6:0, 7:0, 8:0, 9:0, 10:0, 11:0, 12:0}
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month_distance = {1:0, 2:0, 3:0, 4:0, 5:0, 6:0, 7:0, 8:0, 9:0, 10:0, 11:0, 12:0}
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month_duration = {1:0, 2:0, 3:0, 4:0, 5:0, 6:0, 7:0, 8:0, 9:0, 10:0, 11:0, 12:0}
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for month in range(1, 13):
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if month == 12:
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max_day = (datetime.date(year + 1, 1, 1) - datetime.timedelta(days=1)).day
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else:
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max_day = (datetime.date(year, month + 1, 1) - datetime.timedelta(days=1)).day
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for day in range(1, max_day + 1):
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date_tracks = self.tracks.get(year, month, day)
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for track in date_tracks:
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month_distance[month] += (track.distance / 1000) # km
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month_duration[month] += track.duration.total_seconds() / 3600 # h
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for i in range(1, 13):
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if month_duration[i] > 0:
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month_avg_spd[i] = month_distance[i] / month_duration[i]
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2018-07-26 12:20:15 +00:00
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self.years_distance.append(month_distance.values())
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self.years_avg_spd.append(month_avg_spd.values())
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self.years.append(str(year))
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2018-07-26 07:53:44 +00:00
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2018-07-26 12:20:15 +00:00
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self.plot_distance_diagram()
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self.plot_avg_spd_diagram()
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2018-07-26 07:53:44 +00:00
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# last n days
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n = 14
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end_date = datetime.date.today()
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start_date = end_date - datetime.timedelta(days=n)
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dates = pd.date_range(start_date, end_date)
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2018-07-26 12:20:15 +00:00
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self.date_distance = dict()
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2018-07-26 07:53:44 +00:00
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date_duration = dict()
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2018-07-26 12:20:15 +00:00
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self.date_avg_spd = dict()
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2018-07-26 07:53:44 +00:00
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for date in dates:
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date_str = "{0:04d}-{1:02d}-{2:02d}".format(date.year, date.month, date.day)
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date_tracks = self.tracks.get(date.year, date.month, date.day)
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for track in date_tracks:
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try:
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2018-07-26 12:20:15 +00:00
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current_dist = self.date_distance[date_str]
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2018-07-26 07:53:44 +00:00
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current_duration = date_duration[date_str]
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except KeyError:
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current_dist = 0
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current_duration = 0
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current_dist += track.distance / 1000
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2018-07-26 12:20:15 +00:00
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self.date_distance.update({date_str:current_dist})
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2018-07-26 07:53:44 +00:00
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current_duration += track.duration.total_seconds() / 3600
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date_duration.update({date_str:current_duration})
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# check for empty dates
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try:
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2018-07-26 12:20:15 +00:00
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current_dist = self.date_distance[date_str]
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2018-07-26 07:53:44 +00:00
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current_duration = date_duration[date_str]
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except KeyError:
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2018-07-26 12:20:15 +00:00
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self.date_distance.update({date_str:0})
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2018-07-26 07:53:44 +00:00
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date_duration.update({date_str:0})
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date_duration = collections.OrderedDict(sorted(date_duration.items()))
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for key, value in date_duration.items():
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if value == 0:
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2018-07-26 12:20:15 +00:00
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self.date_avg_spd.update({key:0})
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2018-07-26 07:53:44 +00:00
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else:
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2018-07-26 12:20:15 +00:00
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avg_spd = self.date_distance[key] / value
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self.date_avg_spd.update({key:avg_spd})
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2018-07-26 07:53:44 +00:00
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2018-07-26 12:20:15 +00:00
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self.date_avg_spd = collections.OrderedDict(sorted(self.date_avg_spd.items()))
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self.date_distance = collections.OrderedDict(sorted(self.date_distance.items()))
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2018-07-26 07:53:44 +00:00
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2018-07-26 12:20:15 +00:00
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self.last_n_days_diag_file = "distance_last_{}_days.png".format(n)
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self.plot_last_n_days(n)
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self.write_html_file()
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