Mercurial > hg > nsaunier > traffic-intelligence

comparison scripts/visualize-monresovelo.py @ 763:277e9cdcedce dev

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added demo script for monresovelo
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Sun, 29 Nov 2015 00:22:58 -0500
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762:d6f0e0cab07d 763:277e9cdcedce
1 # -*- coding: utf-8 -*-
2 import simplejson, sys, datetime
3 import moving, utils
4 from pyproj import Proj
5
6 import matplotlib.pyplot as plt
7 import matplotlib.mlab as pylab
8 import numpy as np
9 import pandas as pd
10
11 #notes = [f['properties']['notes'] for f in data['features'] if len(f['properties']['notes']) > 0]
12
13 english2French = {'Commute': 'Domicile-travail',
14 'Errand': 'Courses',
15 'Exercise': 'Sport',
16 'Leisure': 'Loisirs',
17 'Other': 'Autre',
18 'Autres': 'Autre',
19 'Autres motifs': 'Autre',
20 'School': u'École',
21 'Shopping': 'Magasinage',
22 'Work-Related': 'Travail',
23 'Work-related': 'Travail',
24 'Other': 'Autre',
25 'other': 'Autre'}
26
27 odMotifs = ['Magasinage', 'Retour au domicile', "Chercher quelqu'un",
28 'Travail ', '\xc9tude / \xc9cole', 'Autre', 'Loisir',
29 "Visites d'ami(e)s et/ou de la parent\xe9", "Reconduire quelqu'un",
30 "Rendez-vous d'affaires", 'Sant\xe9',
31 'Ind\xe9termin\xe9 / refus / NSP']
32
33 def convertJsonToMTM(data = None, filename = None):
34 'Converts the in put json data to MTM and optionally saves to file'
35 proj = Proj(init="epsg:2950")
36 if data is None:
37 data = simplejson.load(open(filename))
38 for i in xrange(len(data['features'])):
39 latlon = data['features'][i]['geometry']['coordinates']
40 mtm = [proj(p[0], p[1]) for p in latlon]
41 data['features'][i]['geometry']['coordinates'] = mtm
42 if filename is not None:
43 simplejson.dump(data, open(utils.removeExtension(filename)+'-mtm.json', 'w'))
44 return data
45
46 def convertToObjects(data, timeStep = 1, project = True, minLength = 10):
47 'Converts the trips to the moving.MovingObject class from Traffic Intelligence'
48 if project:
49 proj = Proj(init="epsg:2950")
50 objects = []
51 nTrips = len(data['features'])
52 for i in xrange(nTrips):
53 latlon = data['features'][i]['geometry']['coordinates']
54 if project:
55 projectedX = [proj(p[0], p[1]) for p in latlon[::timeStep]]
56 else:
57 projectedX = latlon[::timeStep]
58 o = moving.MovingObject(num = i, positions = moving.Trajectory(np.array(projectedX).T.tolist()))
59 o.properties = data['features'][i]['properties']
60 o.motif = english2French.get(o.properties['purpose'], o.properties['purpose'])
61 try:
62 o.start = datetime.datetime.strptime(o.properties['start'], '%Y-%m-%d %H:%M:%S')
63 o.stop = datetime.datetime.strptime(o.properties['stop'], '%Y-%m-%d %H:%M:%S')
64 if o.positions.length() > minLength:
65 objects.append(o)
66 except TypeError:
67 print('{} {}'.format(o.properties['start'], o.properties['stop']))
68 print('issue with {}'.format(o.properties))
69 #o.start = datetime.datetime(1979, 7, 21)
70 #o.stop = o.start
71 #print(e)
72 return objects
73
74 filename = './trip5000.json'
75 data = simplejson.load(open(filename))
76 # od = pd.read_csv('/home/nicolas/tmp/defivelomtl/velo-od-2013/od13niv2 - Résident MTL avec vélo.csv', delimiter = ';')
77
78 #convertJsonToMTM(data)
79 #objects = convertToObjects(data, project = False, minLength = 10)
80 objects = convertToObjects(data, minLength = 10)
81 colors = utils.PlottingPropertyValues('rk')
82
83 def printMRV(objects, motifs, color, linewidth, alpha, blackBG = False):
84 fig = plt.figure()
85 for o in objects:
86 if o.motif in motifs:
87 o.plot(color, linewidth = linewidth, alpha = alpha)
88 plt.axis('equal')
89 plt.axis('off')
90 plt.tight_layout()
91 if blackBG:
92 fig.patch.set_facecolor('black')
93 plt.savefig(u'mrv-'+u'-'.join(motifs).replace(' ', '-')+'-'+color+'-blackbg.png', dpi = 300, facecolor=fig.get_facecolor(), edgecolor='none')
94 else:
95 plt.savefig(u'mrv-'+u'-'.join(motifs).replace(' ', '-')+'-'+color+u'.png', dpi = 300)
96
97 for i, m in enumerate(allmotifs):
98 printMRV(objects, [m], colors[i], 0.5, 0.1)
99
100 printMRV(objects, ['Aller au travail', 'Domicile-travail'], 'k', 0.5, 0.1)
101 printMRV(objects, ['Travail', u'D\xe9placement professionnel'], 'k', 0.5, 0.1)
102 printMRV(objects, ['Aller au travail', 'Domicile-travail', 'Travail', u'D\xe9placement professionnel'], 'k', 0.5, 0.1)
103
104 # generate an enriched json with added data
105 generateJSON = False
106 if generateJSON:
107 for o in objects:
108 o.positions.computeCumulativeDistances()
109
110 #properties = {'length': [],
111 # 'wiggliness': []}
112
113 removeBothEnds = 2
114 # export mean speed, nseconds, wiggliness, speeds, accel
115 for o in objects:
116 #print o.positions.length(), (o.stop-o.start).seconds, (o.stop-o.start).seconds/float(o.positions.length()), o.positions.wiggliness()
117 #print o.positions.length(), o.properties['n_coord'], len(o.positions.differentiateSG(5,2,2)), len(o.positions.differentiateSG(5,2,1))
118 speeds = o.positions.differentiateSG(5,2,1, removeBothEnds = removeBothEnds).norm().tolist()
119 accel = o.positions.differentiateSG(5,2,2, removeBothEnds = removeBothEnds).norm().tolist()
120 data['features'][o.getNum()]['properties']['speeds'] = [speeds[0]]*removeBothEnds+speeds+[speeds[-1]]*removeBothEnds
121 data['features'][o.getNum()]['properties']['accelerations'] = [accel[0]]*removeBothEnds+accel+[accel[-1]]*removeBothEnds
122 data['features'][o.getNum()]['properties']['n_points'] = o.positions.length()
123 data['features'][o.getNum()]['properties']['n_seconds'] = (o.stop-o.start).seconds
124 data['features'][o.getNum()]['properties']['mean_speed'] = o.positions.cumulativeDistances[-1]/data['features'][o.getNum()]['properties']['n_seconds']
125 data['features'][o.getNum()]['properties']['wiggliness'] = o.positions.wiggliness()
126
127 nums = [o.getNum() for o in objects]
128 data['features'] = [d for i, d in enumerate(data['features']) if i in nums]
129 simplejson.dump(data, open(utils.removeExtension(filename)+'-enriched.json', 'w'))