from folium.plugins import BeautifyIcon
from gpxplotter import (
create_folium_map,
read_gpx_file,
add_segment_to_map,
)
from gpxplotter.common import cluster_velocities
line_options1 = {'weight': 13, 'color': '#006d2c'}
line_options2 = {
'weight': 8,
}
the_map = create_folium_map(tiles='kartverket_topo4')
for track in read_gpx_file('example3.gpx'):
for i, segment in enumerate(track['segments']):
segment['velocity-level'] = cluster_velocities(
segment['velocity'],
n_clusters=9,
)
add_segment_to_map(the_map,
segment,
line_options=line_options1,
add_start_end=False)
add_segment_to_map(the_map,
segment,
color_by='velocity-level',
cmap='RdYlGn_09',
line_options=line_options2,
add_start_end=False)
from gpxplotter import read_gpx_file
from gpxplotter.mplplotting import plot_elevation_hr_multi_dist, save_fig
from matplotlib import pyplot as plt
plt.style.use('seaborn-poster')
for track in read_gpx_file('09_27_20.gpxtest.gpx'):
for i, segment in enumerate(track['segments']):
fig = plot_elevation_hr_multi_dist(track, segment)
save_fig(fig, 'test-{}.png'.format(i))
# from gpxplotter import read_gpx_file
# from gpxplotter.mplplotting import plot_map, save_map
# for track in read_gpx_file('test.gpx'):
# for i, segment in enumerate(track['segments']):
# fig = plot_map(track, segment, zcolor='pulse')
# save_map(fig, 'test-{}.html'.format(i))
from matplotlib import pyplot as plt
from gpxplotter import read_gpx_file
from gpxplotter.mplplotting import plot_map, save_map, plot_map2
fig = plt.figure()
count = 0
for track in read_gpx_file('test.gpx', maxpulse=187):
for i, segment in enumerate(track['segments']):
count += 1
if (count == 1):
fig = plot_map(track, segment, zcolor='ele')
save_map(fig, 'map.html'.format(i))
else:
fig = plot_map2(track, segment, fig, zcolor='pulse')
save_map(fig, 'map.html'.format(i))
print(count)
# for track in read_gpx_file('test.gpx', maxpulse=187):
# for i, segment in enumerate(track['segments']):
# fig = plot_map(track, segment, zcolor='pulse')
# save_map(fig, 'map-{}.html'.format(i))
=============================
This example will use the calculated heart rate zones from
gpxplotter to show the fraction of time spent in the different
zones.
"""
from matplotlib import pyplot as plt
from matplotlib.cm import get_cmap
from gpxplotter import read_gpx_file
from gpxplotter.common import format_time_delta
import numpy as np
plt.style.use('seaborn-talk')
MAX_HEART_RATE = 189
for track in read_gpx_file('example4.gpx', max_heart_rate=MAX_HEART_RATE):
for i, segment in enumerate(track['segments']):
time = segment['time']
time_in_zones = {}
for start, stop, value in segment['hr-regions']:
seconds = (time[stop] - time[start]).seconds
if value not in time_in_zones:
time_in_zones[value] = 0
time_in_zones[value] += seconds
sum_time = sum([val for _, val in time_in_zones.items()])
# Check consistency:
print('Times are equal?', sum_time == (time[-1] - time[0]).seconds)
zones = sorted(list(time_in_zones.keys()))
zone_txt = segment['zone_txt']
from gpxplotter import read_gpx_file
from gpxplotter.mplplotting import plot_elevation_hr_multi_dist, save_fig
from matplotlib import pyplot as plt
plt.style.use('seaborn-poster')
for track in read_gpx_file('test.gpx'):
for i, segment in enumerate(track['segments']):
fig = plot_elevation_hr_multi_dist(track, segment)
save_fig(fig, 'test-{}.png'.format(i))