Mercurial Hosting > traffic-intelligence
view scripts/visualize-monresovelo.py @ 763:277e9cdcedce dev
added demo script for monresovelo
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Sun, 29 Nov 2015 00:22:58 -0500 |
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# -*- coding: utf-8 -*- import simplejson, sys, datetime import moving, utils from pyproj import Proj import matplotlib.pyplot as plt import matplotlib.mlab as pylab import numpy as np import pandas as pd #notes = [f['properties']['notes'] for f in data['features'] if len(f['properties']['notes']) > 0] english2French = {'Commute': 'Domicile-travail', 'Errand': 'Courses', 'Exercise': 'Sport', 'Leisure': 'Loisirs', 'Other': 'Autre', 'Autres': 'Autre', 'Autres motifs': 'Autre', 'School': u'École', 'Shopping': 'Magasinage', 'Work-Related': 'Travail', 'Work-related': 'Travail', 'Other': 'Autre', 'other': 'Autre'} odMotifs = ['Magasinage', 'Retour au domicile', "Chercher quelqu'un", 'Travail ', '\xc9tude / \xc9cole', 'Autre', 'Loisir', "Visites d'ami(e)s et/ou de la parent\xe9", "Reconduire quelqu'un", "Rendez-vous d'affaires", 'Sant\xe9', 'Ind\xe9termin\xe9 / refus / NSP'] def convertJsonToMTM(data = None, filename = None): 'Converts the in put json data to MTM and optionally saves to file' proj = Proj(init="epsg:2950") if data is None: data = simplejson.load(open(filename)) for i in xrange(len(data['features'])): latlon = data['features'][i]['geometry']['coordinates'] mtm = [proj(p[0], p[1]) for p in latlon] data['features'][i]['geometry']['coordinates'] = mtm if filename is not None: simplejson.dump(data, open(utils.removeExtension(filename)+'-mtm.json', 'w')) return data def convertToObjects(data, timeStep = 1, project = True, minLength = 10): 'Converts the trips to the moving.MovingObject class from Traffic Intelligence' if project: proj = Proj(init="epsg:2950") objects = [] nTrips = len(data['features']) for i in xrange(nTrips): latlon = data['features'][i]['geometry']['coordinates'] if project: projectedX = [proj(p[0], p[1]) for p in latlon[::timeStep]] else: projectedX = latlon[::timeStep] o = moving.MovingObject(num = i, positions = moving.Trajectory(np.array(projectedX).T.tolist())) o.properties = data['features'][i]['properties'] o.motif = english2French.get(o.properties['purpose'], o.properties['purpose']) try: o.start = datetime.datetime.strptime(o.properties['start'], '%Y-%m-%d %H:%M:%S') o.stop = datetime.datetime.strptime(o.properties['stop'], '%Y-%m-%d %H:%M:%S') if o.positions.length() > minLength: objects.append(o) except TypeError: print('{} {}'.format(o.properties['start'], o.properties['stop'])) print('issue with {}'.format(o.properties)) #o.start = datetime.datetime(1979, 7, 21) #o.stop = o.start #print(e) return objects filename = './trip5000.json' data = simplejson.load(open(filename)) # od = pd.read_csv('/home/nicolas/tmp/defivelomtl/velo-od-2013/od13niv2 - Résident MTL avec vélo.csv', delimiter = ';') #convertJsonToMTM(data) #objects = convertToObjects(data, project = False, minLength = 10) objects = convertToObjects(data, minLength = 10) colors = utils.PlottingPropertyValues('rk') def printMRV(objects, motifs, color, linewidth, alpha, blackBG = False): fig = plt.figure() for o in objects: if o.motif in motifs: o.plot(color, linewidth = linewidth, alpha = alpha) plt.axis('equal') plt.axis('off') plt.tight_layout() if blackBG: fig.patch.set_facecolor('black') plt.savefig(u'mrv-'+u'-'.join(motifs).replace(' ', '-')+'-'+color+'-blackbg.png', dpi = 300, facecolor=fig.get_facecolor(), edgecolor='none') else: plt.savefig(u'mrv-'+u'-'.join(motifs).replace(' ', '-')+'-'+color+u'.png', dpi = 300) for i, m in enumerate(allmotifs): printMRV(objects, [m], colors[i], 0.5, 0.1) printMRV(objects, ['Aller au travail', 'Domicile-travail'], 'k', 0.5, 0.1) printMRV(objects, ['Travail', u'D\xe9placement professionnel'], 'k', 0.5, 0.1) printMRV(objects, ['Aller au travail', 'Domicile-travail', 'Travail', u'D\xe9placement professionnel'], 'k', 0.5, 0.1) # generate an enriched json with added data generateJSON = False if generateJSON: for o in objects: o.positions.computeCumulativeDistances() #properties = {'length': [], # 'wiggliness': []} removeBothEnds = 2 # export mean speed, nseconds, wiggliness, speeds, accel for o in objects: #print o.positions.length(), (o.stop-o.start).seconds, (o.stop-o.start).seconds/float(o.positions.length()), o.positions.wiggliness() #print o.positions.length(), o.properties['n_coord'], len(o.positions.differentiateSG(5,2,2)), len(o.positions.differentiateSG(5,2,1)) speeds = o.positions.differentiateSG(5,2,1, removeBothEnds = removeBothEnds).norm().tolist() accel = o.positions.differentiateSG(5,2,2, removeBothEnds = removeBothEnds).norm().tolist() data['features'][o.getNum()]['properties']['speeds'] = [speeds[0]]*removeBothEnds+speeds+[speeds[-1]]*removeBothEnds data['features'][o.getNum()]['properties']['accelerations'] = [accel[0]]*removeBothEnds+accel+[accel[-1]]*removeBothEnds data['features'][o.getNum()]['properties']['n_points'] = o.positions.length() data['features'][o.getNum()]['properties']['n_seconds'] = (o.stop-o.start).seconds data['features'][o.getNum()]['properties']['mean_speed'] = o.positions.cumulativeDistances[-1]/data['features'][o.getNum()]['properties']['n_seconds'] data['features'][o.getNum()]['properties']['wiggliness'] = o.positions.wiggliness() nums = [o.getNum() for o in objects] data['features'] = [d for i, d in enumerate(data['features']) if i in nums] simplejson.dump(data, open(utils.removeExtension(filename)+'-enriched.json', 'w'))