Esempio n. 1
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def get_fake_points(origin, destination):
    all_points.append(origin)
    params = {  'origin': "%s,%s" % (origin[LAT], origin[LON]),
                'destination': "%s,%s" % (destination[LAT], destination[LON]),
                'mode': "driving",
                # 'avoid': "highways",
                'sensor': "false"
                }
    params = net.urlencode(params)
    url = "http://maps.googleapis.com/maps/api/directions/json?" + params
    response = net.read(url)
    directions = json.loads(response)
    try:
        steps = directions['routes'][0]['legs'][0]['steps']  
    except Exception as e:
        print(response)
        exit()    
    points = []
    for i, step in enumerate(steps):
        instruction = step['html_instructions']
        instructions.append(instruction)
        if i != 0:
            point = [step['start_location']['lng'], step['start_location']['lat'], None, None, None]
            points.append(point)
        if i != len(steps) - 1:    
            point = [step['end_location']['lng'], step['end_location']['lat'], None, None, None]
            points.append(point)
    for point in points:
        point[X] = util.scale(point[LON], min_lon, max_lon)
        point[Y] = util.scale(point[LAT], min_lat, max_lat) 
        all_points.append(point)
    all_points.append(destination)               
    return points
Esempio n. 2
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    def get(self, page):
        if page == "stations":
            stations = model.fetch_stations()
            s = {}
            for station_id, station in stations.items():
                s[station_id] = geo.project((station['lon'], station['lat']))
            max_x = s[max(s, key=lambda d: s[d][0])][0]
            min_x = s[min(s, key=lambda d: s[d][0])][0]
            max_y = s[max(s, key=lambda d: s[d][1])][1]
            min_y = s[min(s, key=lambda d: s[d][1])][1]
            for station_id, value in s.items():
                x, y = value
                s[station_id] = util.scale(x, min_x, max_x), util.scale(y, min_y, max_y)
            return self.json(s)
            

        return self.render("home.html")
Esempio n. 3
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max_x = np.max(all_points[:,X])
min_x = np.min(all_points[:,X])
max_y = np.max(all_points[:,Y])
min_y = np.min(all_points[:,Y])

width = float(abs(max_x - min_x))
height = float(abs(max_y - min_y))
ratio = width / height

print(ratio)
    
points = list(points)
for walk in walks:
    for point in walk['points']:
        point[X] = util.scale(point[X], min_x, max_x)
        point[Y] = util.scale(point[Y], min_y, max_y)



ctx = drawing.Context(1000, int(1000.0/ratio), relative=True, flip=True, hsv=True, margin=20, background=(252/256, 245/256, 216/256))

for w, walk in enumerate(walks):
    c = float(w) / len(walks)
    points = [(point[X], point[Y]) for point in walk['points']]
    # ctx.line(points, thickness=3.0, stroke=(0.55, 1.0, c))
    # ctx.line(points, thickness=3.0, stroke=(0.55, 0.0, c))    
    # ctx.line(points, thickness=5.0, stroke=(0.55, 1.0, 0.7, 0.4))
    ctx.line(points, thickness=5.0, stroke=(0.55, 0.0, 0.0, 0.4))
      
ctx.output("charts/geo_%s.png" % int(time.time()))
Esempio n. 4
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points = json.loads(open("thief_points.json").read())
points = np.array([(float(point['lon']), float(point['lat']), time.mktime(util.parse_date(point['time']).timetuple()), None, None) for point in points])

median_lon = np.median(points[:,0])
median_lat = np.median(points[:,1])
points = np.array([point for point in points if abs(point[0] - median_lon) < ZOOM and abs(point[1] - median_lat) < ZOOM])    
max_lon = np.max(points[:,0])
min_lon = np.min(points[:,0])
max_lat = np.max(points[:,1])
min_lat = np.min(points[:,1])
points = list(points)

for point in points:
    point[X] = util.scale(point[LON], min_lon, max_lon)
    point[Y] = util.scale(point[LAT], min_lat, max_lat)

all_points = []

# should also print out the directions
instructions = []

def get_fake_points(origin, destination):
    all_points.append(origin)
    params = {  'origin': "%s,%s" % (origin[LAT], origin[LON]),
                'destination': "%s,%s" % (destination[LAT], destination[LON]),
                'mode': "driving",
                # 'avoid': "highways",
                'sensor': "false"
                }