import operator
import pandas as pd
import math
import numpy as np
import matplotlib.pyplot as plt
import random

# the first two lines do the same thing as read.csv
routes = []
with open('routes.csv', 'r') as file:
	# apre il file e riempie 'routes' con le righe del file
	routes = file.read().splitlines()
# for each element in 'routes', divide the string around the ';'
routes = [route.split(';') for route in routes]


aircodes = []
with open('airport-codes.csv', 'r') as file:
	aircodes = file.read().splitlines()
aircodes = [code.split(';') for code in aircodes]


data = pd.read_csv('countries of the world.csv', decimal=',')

#Transform aircodes in dictionary + association of airport and nation

airport_nation = {}

for r in aircodes:
	airport_code = r[1]
	country = r[3]
	if not airport_code in airport_nation:
		airport_nation[airport_code] = country

print(airport_code, country) #example of how this cell works
print(airport_nation['GZA']) #example of how I get the country from the abbreviate form of the airport

#Dictionary to make list with the abbreviations of the airports of departure (first 3 letters) and of arrival (second 3 letters), frequency

coppie = {}

for r in routes:
	source_airport = r[2]
	destination_airport = r[4]
	aircoppia = ''.join(sorted([source_airport, destination_airport]))
	if aircoppia in coppie:
		coppie[aircoppia] += 1
	else:
		coppie[aircoppia] = 1

coppie = sorted(coppie.items(), key=operator.itemgetter(1))

print(coppie[1]) #example of how it works, it works in reverse order (the one with less frequency first)
print(coppie[-1]) #most busy
print(len(coppie)) #test for know number of routes
print(len(routes)) #tests to find out about total journeys

#Starting from trying to make a map, the frequency of flights was found to be irregular, so using pyplot we printed a graph that reveals that return flights are much more popular than one-way flights

collegamenti = [] #collegamenti means: number of times that route appears (not considering the order)
freq_collegamento = [] #summ of sections that have n connections
dist = [x[1] for x in coppie]
for y in set([x[1] for x in coppie]):
	if not y > 25: #Elimination of outliers
		print(y, dist.count(y))
		collegamenti += [y]
		freq_collegamento += [dist.count(y)]

plt.yscale('log')#log to detect distribution that is exponential
plt.plot(collegamenti,freq_collegamento)
plt.plot(collegamenti[1::2],freq_collegamento[1::2])#take peers (round trip)
plt.plot(collegamenti[::2],freq_collegamento[::2])#takes the odd (one way or only return)
plt.show()

# We divide the number of pairs of airports that have an even number of connections for one that has an odd connection number and we see that the even ones are 11.39 times the odd number so there are more round trips than one way

float(sum(freq_collegamento[1::2])) / sum(freq_collegamento[::2])

errors = 0
nations = {}

for x in coppie:
	a1, a2, conteggio = x[0][:3], x[0][-3:], x[1]
	try:
		if not airport_nation[a1].lower() in nations:
			nations[airport_nation[a1].lower().strip()] = conteggio
		else:
			nations[airport_nation[a1].lower().strip()] += conteggio

		if not airport_nation[a2].lower() in nations:
			nations[airport_nation[a2].lower().strip()] = conteggio
		else:
			nations[airport_nation[a2].lower().strip()] += conteggio
	except:
		errors += 1

print(airport_nation[a2].lower().strip(), nations[airport_nation[
	a2].lower().strip()])  # Number of times the united states have been 'visited' (departure or arrival) on various trips
print('The number of errors in percentage is: ', errors / float(len(coppie)) * 100)

sorted_nations = sorted(nations.items(), key=operator.itemgetter(1)) #To print in an orderly way the naz. in which he found no errors
print(sorted_nations[-10:], len(sorted_nations) )

#Count of the various data we need (gdp, number of flights) to make the graph with pyplot.

err = 0
popgdp =[]
n_voli = []
for x in range(len(data)):
	try:
		country = data['Country'][x].lower().strip()
		gdp_capita = data['GDP ($ per capita)'][x]
		pop = data['Population'][x]
		service = data['Service'][x]
		#print country, pop*gdp_capita, pop, gdp_capita, nazioni[country]

		n_voli += [nazioni[country]] #it must be put before n_voli of popgdp because if there is an error here it exits from the loop before putting in popgdp the value
		popgdp += [pop*gdp_capita]

	except Exception as e:
		err += 1


print(float(err)/len(data)) #print errors

#DISTRIBUTION OF DOUBLE LOG(popgdp, n_voli)

x = list(map(math.log, popgdp))  #comment if you whant to see the bug bug
y = list(map(math.log, n_voli)) #comment if you whant to see the bug bug
#x=popgdp                      #discomfort if you whant to see the bug bug
#y=n_voli                     #discomfort if you whant to see the bug bug
(m, b) = np.polyfit(x, y, 1)

yp = np.polyval([m, b], x)
plt.plot(x, yp)
plt.grid(True)
plt.scatter(x,y)
plt.xlabel('GDP',fontsize=10)
plt.ylabel('Flights',fontsize=10)

#plt.xscale('log') #bug because it makes the wrong fit
#plt.yscale('log') #bug because it makes the wrong fit

plt.show()
print(m, b)

#Associazione di nome nazione e codice aeroportuale

nations_codes = open('nations_codes', 'r').read().split('\n')
nations_codes_d = {}
for x in nations_codes:
	# print x[5:].lower(), x.split(' ')[0]
	nations_codes_d[x[5:].lower()] = x.split(' ')[0]


print(x[5:].lower() , nations_codes_d[x[5:].lower()])
#print nations_codes_d    # ---->discomfort if I want to see all the nation codes

#mappe html fatte in D3js---->JavaScript library for producing dynamic, interactive data visualizations in web browsers
#Map source --https://bl.ocks.org/ChumaA/385a269db46ae56444772b62f1ae82bf --

json_voli = open('json_start', 'r').read()
err = 0
for x in range(len(data)):
	try:
		country = data['Country'][x].lower().strip()
		country_code = nations_codes_d[country]
		service = data['Service'][x]
		gdp_capita = data['GDP ($ per capita)'][x]
		pop = data['Population'][x]

		json_voli += ''' {"key": "''' + country_code + '''", "doc_count": ''' + str(
			pop * gdp_capita / 1000000000000) + ''' },'''  # ho cambiato i nomi e ho generato 3 pagine html con servizi gdp e voli
	# json_voli += ''' {"key": "'''+country_code+'''", "doc_count": '''+str(service*1000)+''' },'''
	# json_voli += ''' {"key": "'''+country_code+'''", "doc_count": '''+str(nations[country])+''' },'''
	except Exception as e:
		# print 'Error', e , country
		err += 1

json_voli = json_voli[:-1]
json_voli += "]}}}"
# print json_voli

# Print errors
print(float(err) / len(data))

#Class that starting it tells me given an airport of departure an airport of arrival based on the probability of the airports

routes = open('routes.csv', 'r').read().split('\n')
routes = map(lambda x: x.split(';'), routes)



coppie = {}

for r in routes:
	source_airport = r[2]
	destination_airport = r[4]
	aircoppia = ''.join(sorted([source_airport, destination_airport]))
	if aircoppia in coppie:
		coppie[aircoppia] += 1
	else:
		coppie[aircoppia] = 1


class Passeggero_girovago:
	'''
	This passenger chooses a possible destination at random from those of the initial airport,
    assigning the frequency of the journey to the destination airport
	'''

	def __init__(self, start):
		self.start = start
		self.steps = 0

	def __repr__(self):
		return "ciccio si trova in: " + self.start + " dopo " + str(self.steps) + " viaggi"

	@staticmethod
	def find_airports(aircode):
		cc = []
		for c in coppie.keys():
			airport1 = c[:3]
			airport2 = c[3:]
			freq_coll = coppie[c]
			if aircode == airport1:
				cc += [[airport2, freq_coll]]
			if aircode == airport2:
				cc += [[airport1, freq_coll]]
		return cc

	@staticmethod
	def choose_airport(airports):
		max_number = sum([x[1] for x in airports])
		choosen = random.choice(range(max_number))
		y = 0
		number = 0
		while number <= choosen and y < len(airports):
			number = sum([x[1] for x in airports[:y]])
			y += 1
		return airports[y - 1][0]

	def update(self):
		# print find_airports(self.start)
		arrival = self.choose_airport(self.find_airports(self.start))
		self.start = arrival
		self.steps += 1


start = 'ORD'
arrivo = 'sdohuedwihu'  # We fix here a random name in order to make our class work
ciccio = Passeggero_girovago(start)
while start != arrivo:
	ciccio.update()
	print(ciccio)
	arrivo = ciccio.start