some trivial stuff to plot jcdecaux data

jcdecaux.py

import math, json, glob, time

from numpy import *
from matplotlib.pyplot import *
from matplotlib import animation

# http://wiki.openstreetmap.org/wiki/Slippy_map_tilenames#Python
def deg2num(lat_deg, lon_deg):
    lat_rad = math.radians(lat_deg)
    x = (lon_deg + 180.0) / 360.0
    y = (1.0 - math.log(math.tan(lat_rad) + (1 / math.cos(lat_rad))) / math.pi) / 2.0
    return (x, y)


# http://docs.python.org/2/library/json.html
def parse_city(filename):

    with open(filename) as f:
        city = json.load(f)

    n = len(city)-1

    coords_x = zeros(n)
    coords_y = zeros(n)
    bikes    = zeros(n)
    stands   = zeros(n)
    update   = zeros(n)

    i = 0
    for station in city:
        gps = station['position']
        cartesian = deg2num(gps['lat'], gps['lng'])
        if cartesian[1] < .4:   # Paris
            (coords_x[i], coords_y[i]) = cartesian
            bikes[i]  = station['available_bikes']
            stands[i] = station['bike_stands']
            update[i] = station['last_update']
            i += 1

    return (coords_x, -coords_y, bikes, stands)


# http://matplotlib.org/examples/pylab_examples/polar_scatter.html
def city_scatter(filename, surface='bikes', scale=lambda x:5*x):


    (x, y, bikes, stands) = parse_city(filename)

    data = { 'bikes': bikes,
             'stands': stands,
             'empty': stands - bikes }

    c = scatter(x, y, s=scale(data[surface]))
    c.set_alpha(0.5)
    gca().set_aspect('equal')
    tight_layout()
    xlim(x.min(), x.max())
    ylim(y.min(), y.max())

def make_anim():
    fig  = figure(figsize=(16,12))
    files = glob.glob('Paris/*')
    files.sort()
    files = files[:146]
    scale = lambda x:5*x+1

    title(time.strftime('%c', time.localtime(float(files[0].split('/')[1]))))
    (x, y, bikes, stands) = parse_city(files[0])
    scat = scatter(x, y, s=scale(bikes))
    xlim(x.min(), x.max())
    ylim(y.min(), y.max())

    def update_plot(i):
        (x, y, bikes, stands) = parse_city(files[i])
        title(time.strftime('%c', time.localtime(float(files[i].split('/')[1]))))
        scat._sizes = scale(bikes)
        return scat,

    ani = animation.FuncAnimation(fig, update_plot, frames=len(files)-1)
    ani.save('pop.mp4', fps=20)

#make_anim()
files = glob.glob('Paris/*')
files.sort()
figure()
city_scatter(files[0], surface='stands')
figure()
city_scatter(files[0], surface='bikes')
show()