import pandas as pd
filename = '../chapter3/data/worldcitiespop.txt'
data = pd.read_csv(filename)

plot(data.Longitude, data.Latitude, ',')

locations = data[['Longitude','Latitude']].as_matrix()

from mpl_toolkits.basemap import Basemap
m = Basemap(projection='mill', llcrnrlat=-65, urcrnrlat=85, llcrnrlon=-180, urcrnrlon=180)

x0, y0 = m(-180, -65)
x1, y1 = m(180, 85)

population = data.Population

x, y = m(locations[:,0], locations[:,1])

weights = population.copy()
weights[isnan(weights)] = 1000

h, _, _ = histogram2d(x, y, bins=(linspace(x0, x1, 500), linspace(y0, y1, 500)), weights=weights)
h[h==0] = 1

import scipy.ndimage.filters
z = scipy.ndimage.filters.gaussian_filter(log(h.T), 1)

figure(figsize=(10,6))
m.drawcoastlines()
m.imshow(z, origin='lower', extent=[x0,x1,y0,y1], cmap=get_cmap('Reds'))