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