import math
import random

def get_nothing():
    return None

MAX_FOOD = 700
MAX_WATER = 166400
MIN_FOOD = 450
MIN_WATER = 365 * 100

class Zone:
    name = ''

    CLIMATE    = 1
    CROPS      = get_nothing()
    POPULATION = get_nothing()
    LIVESTOCK  = get_nothing()
    WATER_CONSUMPTION = get_nothing()
    INCOME     = 0
    MORTALITY  = get_nothing()
    QUALITY_OF_LIFE = get_nothing()
    AIR_POLLUTION = 0
    WATER = get_nothing()
    TECH_PROGRESS = 1
    AIR_PURIFICATION = 0
    INVESTIOTION_IN = 0
    INVESTIOTION_OUT = 0
    FERTILITY = get_nothing()
    MORTALITY = get_nothing()
    MORTALITY_0 = get_nothing()
    MORTALITY_1 = get_nothing()
    SOIL_DEGRADATION = 0
    F = get_nothing()

    AIR_POLLUTION0 = get_nothing()
    SOIL_DEGRADATION0 = get_nothing()

    MINERALS = get_nothing()
    EDUCATION = get_nothing()

    def __init__(self, name):
        self.name = name.replace(' ', '-')

        self.csv = open(self.name + '.csv', 'w')
        self.csv.write('Time,Population,Income,TechProgress,Education,Climate,F,Crops\n')

    def post_init(self):
        self.CROPS0 = self.CROPS
        self.POPULATION0 = self.POPULATION
        self.WATER_CONSUMPTION0 = self.WATER_CONSUMPTION
        self.MORTALITY0 = self.MORTALITY
        self.old_derivF = 0

    def upd(self, dt):
        if self.name == 'South America' or self.name == 'South America':
            self.CROPS = self.POPULATION * self.CROPS0 / self.POPULATION0
            tmp1 = (self.WATER - self.POPULATION * self.WATER_CONSUMPTION) * self.CLIMATE * self.TECH_PROGRESS
            tmp2 = (self.WATER0 - self.POPULATION0 * self.WATER_CONSUMPTION0) * (1 + 7.5 * self.LIVESTOCK)
            self.CROPS = min(self.CROPS, self.CROPS0 * tmp1 / tmp2)
            tmp1 = self.CROPS0 * (1.0 - self.SOIL_DEGRADATION) * self.CLIMATE * self.TECH_PROGRESS
            tmp2 = 1 + 10 * self.LIVESTOCK
            self.CROPS = min(self.CROPS, tmp1 / tmp2)
        else:
            self.CROPS = self.POPULATION * self.CROPS0 / self.POPULATION0
            tmp1 = self.CROPS0 * (1 - self.SOIL_DEGRADATION) * self.CLIMATE * self.TECH_PROGRESS
            tmp2 = 1 + 10 * self.LIVESTOCK

            self.CROPS = min(self.CROPS, tmp1 / tmp2)

        self.SOIL_DEGRADATION += self.SOIL_DEGRADATION0 / self.TECH_PROGRESS * dt
        self.AIR_POLLUTION += (self.AIR_POLLUTION0 * (0.855 * self.MINERALS + 0.145 * self.LIVESTOCK * self.CROPS) / self.TECH_PROGRESS - self.AIR_PURIFICATION) * dt
        self.CLIMATE += -1e-18 * self.AIR_POLLUTION * dt

        temp = (-5e2 * self.AIR_PURIFICATION / self.TECH_PROGRESS + 6e11 * self.MINERALS * self.TECH_PROGRESS + self.INVESTIOTION_IN - self.INVESTIOTION_OUT + self.F)
        self.INCOME = temp / self.POPULATION

        old_EDU = self.EDUCATION
        self.EDUCATION = min(3e-13 * math.pow(self.INCOME, 8.5026), 100)
        deriv_EDU = self.EDUCATION - old_EDU

        oldF = self.F
        self.F += (0.35 * deriv_EDU / self.EDUCATION * self.F + self.old_derivF) * dt
        self.old_derivF = (self.F - oldF) / dt

        old_techp = self.TECH_PROGRESS
        self.TECH_PROGRESS += (0.00000001399211484 * self.INCOME * self.EDUCATION) / self.TECH_PROGRESS * dt
        deriv_TECHP = self.TECH_PROGRESS - old_techp

        self.POPULATION += (self.POPULATION / 1e3) * (self.FERTILITY - self.MORTALITY) * dt

        self.MORTALITY_0 = self.MORTALITY0 * deriv_TECHP * dt
        self.MORTALITY_1 = 0

        if self.WATER_CONSUMPTION < MIN_WATER:
            self.MORTALITY_1 = max(self.MORTALITY_1, 1000 * (1 - self.WATER_CONSUMPTION / MIN_WATER))

        xx = (self.CROPS * (1 + self.LIVESTOCK)) / self.POPULATION

        if xx < MIN_FOOD:
            self.MORTALITY_1 = max(self.MORTALITY_1, 1000 * (1 - xx / MIN_FOOD))

        self.MORTALITY = self.MORTALITY_0 + self.MORTALITY_1

        self.QUALITY_OF_LIFE = 20 * xx / MAX_FOOD
        self.QUALITY_OF_LIFE += 10 * self.LIVESTOCK
        self.QUALITY_OF_LIFE += 20 * (self.WATER_CONSUMPTION / MAX_WATER)
        self.QUALITY_OF_LIFE += 30 * (1 - self.MORTALITY / self.POPULATION)
        self.QUALITY_OF_LIFE += 15 * (1 - 1 / (self.INCOME + 1))
        self.QUALITY_OF_LIFE += 5 * (1 - 1 / (self.CLIMATE + 1))


    def write_down(self, time):
        # TODO: write all variables
        line = str(time) + ',' + str(self.POPULATION)
        line = line + ',' + str(self.INCOME)
        line = line + ',' + str(self.TECH_PROGRESS)
        line = line + ',' + str(self.EDUCATION)
        line = line + ',' + str(self.CLIMATE)
        line = line + ',' + str(self.F)
        line = line + ',' + str(self.CROPS)

        if self.name == 'North America':
            print(line)

        self.csv.write(line + '\n')

# Gr. Middle East == North Africa + Near East

africa = Zone('Africa')
africa.CROPS = 10552996000
africa.MINERALS = 25.3567
africa.WATER = 121248399900
africa.WATER_CONSUMPTION = 17.155
africa.LIVESTOCK = 0.09933179102
africa.SOIL_DEGRADATION0 = 0.014 * 1e-7
africa.AIR_POLLUTION0 = 8.98
africa.CLIMATE = 1e-18
africa.FERTILITY = 49
africa.MORTALITY = 14
africa.POPULATION = 987240925
africa.TECH_PROGRESS = 0.00000001399211484
africa.F = 0.7 * 390.7 * 1e6
africa.EDUCATION = 61

europe = Zone('Europe')
europe.CROPS = 238395160000
europe.MINERALS = 44325.28774
europe.WATER = 180458288600
europe.WATER_CONSUMPTION = 54.75
europe.LIVESTOCK = 0.08819771984
europe.SOIL_DEGRADATION0 = 0.001 * 1e-7
europe.AIR_POLLUTION0 = 6.475
europe.CLIMATE = 1e-18
europe.FERTILITY = 13
europe.MORTALITY = 7
europe.POPULATION = 446377929
europe.TECH_PROGRESS = 0.00000001399211484
europe.F = 0.95 * 9028.2 * 1e6
europe.EDUCATION = 98

east_europe = Zone('East Europe')
east_europe.CROPS = 134040732000
east_europe.MINERALS = 305893
east_europe.WATER = 6570724502084
east_europe.WATER_CONSUMPTION = 90.52
east_europe.LIVESTOCK = 0.05960922493
east_europe.SOIL_DEGRADATION0 = 0.033 * 1e-7
east_europe.AIR_POLLUTION0 = 11.858
east_europe.CLIMATE = 1e-18
east_europe.FERTILITY = 15
east_europe.MORTALITY = 9
east_europe.POPULATION = 292897892
east_europe.TECH_PROGRESS = 0.00000001399211484
east_europe.F = 0.95 * 656.1 * 1e6
east_europe.EDUCATION = 98

near_east = Zone('Greater Middle East')
near_east.CROPS = 508607093000
near_east.MINERALS = 10184.11
near_east.WATER = 109235162200
near_east.WATER_CONSUMPTION = 87.6
near_east.LIVESTOCK = 0.207629848
near_east.SOIL_DEGRADATION0 = 0.0033 * 1e-7
near_east.AIR_POLLUTION0 = 6.159
near_east.CLIMATE = 1e-18
near_east.FERTILITY = 17
near_east.MORTALITY = 7
near_east.POPULATION = 436738031
near_east.TECH_PROGRESS = 0.00000001399211484
near_east.F = 0.25 * 967.037 * 1e6
near_east.EDUCATION = 74

asia = Zone('Asia')
asia.CROPS = 1137577423000
asia.MINERALS = 202824
asia.WATER = 1345012376629
asia.WATER_CONSUMPTION = 34.675
asia.LIVESTOCK = 0.08473485815
asia.SOIL_DEGRADATION0 = 0.0033 * 1e-7
asia.AIR_POLLUTION0 = 16.093
asia.CLIMATE = 1e-18
asia.FERTILITY = 10
asia.MORTALITY = 7
asia.POPULATION = 4461876215
asia.TECH_PROGRESS = 0.00000001399211484
asia.F = 0.1 * 9447.3 * 1e6
asia.EDUCATION = 85

australia = Zone('Australia')
australia.CROPS = 52845564000
australia.MINERALS = 421.764
australia.WATER = 685357950250
australia.WATER_CONSUMPTION = 310
australia.LIVESTOCK = 0.102410541
australia.SOIL_DEGRADATION0 = 0.0034 * 1e-7
australia.AIR_POLLUTION0 = 15.37
australia.CLIMATE = 1e-18
australia.FERTILITY = 15
australia.MORTALITY = 7
australia.POPULATION = 24309329
australia.TECH_PROGRESS = 0.00000001399211484
australia.F = 0.82 * 479.6 * 1e6
australia.EDUCATION = 99

north_america = Zone('North America')
north_america.CROPS = 508607093000
north_america.MINERALS = 312840.2
north_america.WATER = 426211950320
north_america.WATER_CONSUMPTION = 210.97
north_america.LIVESTOCK = 0.09882738604
north_america.SOIL_DEGRADATION0 = 0.0042 * 1e-7
north_america.AIR_POLLUTION0 = 16.351
north_america.CLIMATE = 1e-18
north_america.FERTILITY = 15
north_america.MORTALITY = 8
north_america.POPULATION = 359735880
north_america.TECH_PROGRESS = 0.00000001399211484
north_america.F = 0.8 * 11.031 * 1e6
north_america.EDUCATION = 97

south_america = Zone('South America')
south_america.CROPS = 186238366000
south_america.MINERALS = 144553
south_america.WATER = 1252548288000
south_america.WATER_CONSUMPTION = 87.6
south_america.LIVESTOCK = 0.2910487881
south_america.SOIL_DEGRADATION0 = 0.0017 * 1e-7
south_america.AIR_POLLUTION0 = 9.247
south_america.CLIMATE = 1e-18
south_america.FERTILITY = 14
south_america.MORTALITY = 8
south_america.POPULATION = 422534692
south_america.TECH_PROGRESS = 0.00000001399211484
south_america.F = 0.8 * 1366.6 * 1e6
south_america.EDUCATION = 89

zones = [africa, europe, east_europe, near_east, asia, australia, north_america, south_america]

T = 20
STEP = 1 # one year

start_time = 2000
cur_time = start_time

for zone in zones:
    zone.post_init()
    zone.write_down(cur_time)

while cur_time < start_time + T:

    for zone in zones:
        try:
            zone.upd(STEP)
        except:
            print('error in zone:', zone.name)
            break

    cur_time += STEP

    for zone in zones:
        zone.write_down(math.floor(cur_time))