import numpy as np
from efficientroutes.model import Bicyclist, Route, Trip
bicyclist = Bicyclist()
flatNoStopData = np.recfromcsv('../data/flat_no_stops.csv')
stopLocations = []
for i, device in enumerate(flatNoStopData['traffic_control']):
if device != '' and device != False:
stopLocations.append(flatNoStopData['distance'][i])
flatNoStopRoute = Route(flatNoStopData['distance'],
flatNoStopData['elevation'], flatNoStopData['speed_limit'],
stopLocations=np.array(stopLocations))
flatNoStopTrip = Trip(bicyclist, flatNoStopRoute)
flatNoStopTrip.solve()
print "==============================="
print "Flat with no stops route stats:"
print "==============================="
flatNoStopTrip.stats()
flatNoStopFig = flatNoStopTrip.plot()
flatNoStopFig.suptitle('Flat, No Stops')
flatNoStopFig.set_figheight(8.0)
flatNoStopFig.savefig('../data/flat-no-stops.png', dpi=200)
flatNoStopFig.show()
flatWithStopData = np.recfromcsv('../data/flat_with_stops.csv')
stopLocations = []
for i, device in enumerate(flatWithStopData['traffic_control']):
if device != '' and device != False:
bicyclist = Bicyclist()
routes = {}
for way in ['third', 'fifth', 'eighth']:
routeData = np.recfromcsv('../data/fifth_to_hutchinson_via_' + way + '.csv')
stopLocations = []
for i, device in enumerate(routeData['traffic_control']):
if device != '':
stopLocations.append(routeData['distance'][i])
routes[way] = Route(routeData['distance'],
routeData['elevation'], routeData['speed_limit'],
stopLocations=np.array(stopLocations))
for k, v in routes.items():
trip = Trip(bicyclist, v)
trip.solve()
string = '{} route stats:'.format(k.capitalize())
print "=" * len(string)
print string
print "=" * len(string)
trip.stats()
fig = trip.plot()
fig.suptitle('Via {}'.format(k.capitalize()))
fig.set_figheight(8.0)
fig.savefig('../data/fith-to-hutchinson-via-' + k + '.png', dpi=200)
fig.show()
bicyclist = Bicyclist()
# Load in the the planned bicycle route data and process the traffic controls
# column.
bicycleRouteData = np.recfromcsv('../data/columbia_river_crossing_bicycle.csv')
stopLocations = []
for i, device in enumerate(bicycleRouteData['traffic_control']):
if device != '':
stopLocations.append(bicycleRouteData['distance'][i])
bicycleRoute = Route(bicycleRouteData['distance'],
bicycleRouteData['elevation'], bicycleRouteData['speed_limit'],
stopLocations=np.array(stopLocations))
# Setup and compute the results for the trip across the planned bicycle route.
bicycleTrip = Trip(bicyclist, bicycleRoute)
bicycleTrip.solve()
print "===================="
print "Bicycle route stats:"
print "===================="
bicycleTrip.stats()
bicycleFig = bicycleTrip.plot()
bicycleFig.suptitle('Bicycle Route')
bicycleFig.set_figheight(8.0)
bicycleFig.savefig('../data/columbia_river_crossing_bicycle.png', dpi=200)
bicycleFig.show()
# Load in the data for the automobile path.
autoRouteData = np.recfromcsv('../data/columbia_river_crossing_auto.csv')
autoRoute = Route(autoRouteData['distance'],
autoRouteData['elevation'], autoRouteData['speed_limit'] - 17.88)