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from lxml import etree

# This string will contain the models.py file
modelsContents = "from neo4django.db import models\n\n"

# Enter the name of the OWL file to parse
# The relationships in the file should always start with has...
owlFile = "ontology.owl"

# Gives the ontology URI. Only needed for documentation purposes

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	# Loops through all zoom levels
	for zoom_level in range(4,13):

		#Loops through all cities
		for city in cities:

			#Finds out which tile the city is in
			X_city, Y_city = deg2num(city_lat, city_lng, zoom_level)
			
			# Computes the 16 tiles around the city

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	# Loops through all zoom levels
	for zoom_level in range(4,13):

		# Computes all tiles for the whole world
		for X in range (0, int(math.pow(2, zoom_level))):
			for Y in range (0, int(math.pow(2, zoom_level))):
				
				# Finds the bounds of each tile
				N_tile, W_tile = num2deg(X, Y, zoom_level)
				S_tile, E_tile = num2deg(X + 1, Y + 1, zoom_level)

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#!/usr/bin/env python
# -*- coding: utf-8 -*-

import csv
import urllib2
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as image
import pylab
from PIL import Image

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{
  "log": {
    "comment": "",
    "creator": {
      "comment": "",
      "name": "BrowserMob Proxy",
      "version": "2.1.4"
    },
    "entries": [
      {

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from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.common.by import By
import csv, time
import os.path

browser = webdriver.Chrome()

for year in range(2013, 2020):
    for month in range(1,13):