def visualize_sequence_on_map(self, sequence: list):
"""
Visualizes the resulting sequence of cities on a open source map.
:param sequence: list [int]
:return:
"""
self.sequence = sequence
# Get Marker positions and create map with markers:
markers = self._create_markers(sequence)
m = Map(center=markers[0].location, zoom=7, scroll_wheel_zoom=True)
marker_cluster = MarkerCluster(markers=markers)
m.add_layer(marker_cluster)
# Create line between cities:
line = Polyline(locations=[x.location for x in markers],
color="red",
fill=False)
m.add_layer(line)
m.layout.width = '100vw'
m.layout.height = '100vh'
# Save file and show in webbrowser:
fname = "utils/tmp/map.html"
realpath = os.path.realpath(fname)
m.save(fname)
# webbrowser.open_new_tab(fname)
webbrowser.open_new_tab("file://" + realpath)
print(
"...Opening interactive streetmap in browser. If browser does not show the map correctly, try opening "
"the saved HTML-file ({n}) manually.".format(n=realpath))
reqPassing = urllib2.Request(
"http://api.open-notify.org/iss-pass.json?lat=48.634566&lon=8.09760")
responsePassing = urllib2.urlopen(reqPassing)
fetchPassing = json.loads(responsePassing.read())
passTime = int(fetchPassing['request']['datetime'])
passTimeCounts = fetchPassing['request']['passes']
for i in range(passTimeCounts):
riseTime = int(fetchPassing['response'][i]['risetime'])
print(
"ISS Overflight " + str(i + 1) + ": " +
datetime.utcfromtimestamp(passTime).strftime('%Y-%m-%d %H:%M:%S'))
i = +1
m = Map(basemap=basemaps.Esri.WorldImagery,
center=(lat, long),
zoom=2,
scroll_wheel_zoom=True)
m.add_layer(
Marker(
location=(lat, long),
title="ISS",
icon=Icon(icon_url=
"https://img.icons8.com/fluent/48/000000/gps-device.png",
icon_size=[20, 20])))
m.add_control(FullScreenControl())
m.add_control(ScaleControl(position='bottomleft'))
m.save('current state.html', title="Space Radar")
driver.refresh()
time.sleep(30.0)
def plotmap(self, metric, climatedf, coorddf, filepath, filename='Map'):
sel_cols = ['Location', 'Year', metric]
climatedf = climatedf[sel_cols]
climatedf = climatedf.reindex(columns=climatedf.columns.tolist() +
['color'])
color = []
for (i, j) in climatedf.iterrows():
value = (j[metric] - climatedf[metric].min()) / (
climatedf[metric].max() - climatedf[metric].min())
if (value > 0 and value <= (1 / 6)):
color.append('darkblue')
elif (value > (1 / 6) and value <= (2 / 6)):
color.append('blue')
elif (value > (2 / 6) and value <= (3 / 6)):
color.append('green')
elif (value > (3 / 6) and value <= (4 / 6)):
color.append('orange')
elif (value > (4 / 6) and value <= (5 / 6)):
color.append('red')
else:
color.append('darkred')
climatedf['color'] = color
gps_color = pd.merge(climatedf, coorddf, on=['Location'])
gps_color.head()
newdata = pd.DataFrame([])
for (index, row) in gps_color.iterrows():
row['Latitude'] += random.uniform(0.1, 0.9)
row['Longitude'] += random.uniform(0.1, 0.9)
newdata = newdata.append(row)
center = [39.0119, -98.4842]
zoom = 3
i = 0
m = Map(basemap=basemaps.Esri.WorldImagery, center=center, zoom=zoom)
for (index, row) in newdata.iterrows():
icon = AwesomeIcon(
name='tint',
marker_color=row.loc['color'], #'#583470'
icon_color='black',
spin=False)
loc = [row.loc['Latitude'], row.loc['Longitude']]
marker = Marker(location=loc, draggable=False, icon=icon)
m.add_layer(marker)
i += 1
m.add_control(FullScreenControl())
m.save(filepath + "/" + filename + '.html', title=filename)
mpl.rcParams.update({'font.size': 10})
fig = plt.figure(figsize=(8, 3))
ax = fig.add_subplot(111)
vals = []
for i in range(7):
vals.append(((
(climatedf[metric].max() - climatedf[metric].min()) / 6) * i) +
climatedf[metric].min())
cmap = mpl.colors.ListedColormap([
'darkblue', 'deepskyblue', 'limegreen', 'orange', 'red', 'darkred'
])
norm = mpl.colors.BoundaryNorm(vals, cmap.N)
cb = mpl.colorbar.ColorbarBase(ax,
cmap=cmap,
norm=norm,
spacing='uniform',
orientation='horizontal',
extend='neither',
ticks=vals)
cb.set_label(metric)
ax.set_position((0.1, 0.45, 0.8, 0.1))
plt.savefig(filepath + "/" + 'legend.jpg',
dpi=2000,
bbox_inches="tight")
file = codecs.open(filepath + "/" + filename + '.html', "r", "utf-8")
file_list = file.read().split("\n")
file.close()
print(file_list)
file_list.insert(
-3, "<img src='legend.jpg' alt='Plot Legend' style='width:35%;'>")
file = codecs.open(filepath + "/" + filename + '.html', "w", "utf-8")
file.write("\n".join(file_list))
file.close()
return m, fig
from itertools import cycle, islice
import numpy as np
import folium
cols_list = [
'#e6194b', '#3cb44b', '#ffe119', '#4363d8', '#f58231', '#911eb4',
'#46f0f0', '#f032e6', '#bcf60c', '#fabebe', '#008080', '#e6beff',
'#9a6324', '#fffac8', '#800000', '#aaffc3', '#808000', '#ffd8b1',
'#000075', '#808080'
]
colors = np.array(list(islice(cycle(cols_list), int(max(labels) + 1))))
m = Map(center=[data['Lat'].mean(), data['Long'].mean()],
zoom=5,
basemap=basemaps.OpenStreetMap.Mapnik)
for _, row in data.iterrows():
marker = Marker(
location=[row["Lat"], row['Long']],
draggable=False,
title='Lat:{}, Long:{}, Cluster:{}, ClusterSize:{}, Index:{}'.format(
row["Lat"], row['Long'], labels[row.name], sizes[labels[row.name]],
row.name),
#tooltip = labels[row.name],
#color = colors[labels[row.name]]
)
m.add_layer(marker)
m.save('my.html', title='My Map')
