Countries distributed with random.choice() - more comprehensible code style

main.py

@@ -2,54 +2,151 @@ import csv
 import math
 import random
 import matplotlib.pyplot as plt
+
 class Mensch(object):
-    def __init__(self):
-        #toImplement
+
+    def __init__(self, alter, geschlecht, bdl):
+        self.Alter = alter
+        self.Geschlecht = geschlecht #0 Mann, 1 Frau
+        self.Bundesland = bdl
+        self.Koordinaten = self.getCoordinates(bdl)
+        self.Infiziert = False
+        self.Stichtag = None
+
+
+    def __del__(self):
+        self.Alter = None
+        self.Geschlecht = None
+        self.Bundesland = None
+        self.Koordinaten = None
+
     def getCoordinates(self, bdl):
-        bdlDict = {'Vorarlberg': [0, 0], 'Tirol': [1, 0], 'Kärnten': [2, 0], 'Salzburg': [0, 1],
-                   'Steiermark': [1, 1], 'Burgenland': [2, 1], 'Oberösterreich': [0, 2],
-                   'Niederösterreich': [1, 2], 'Wien': [2, 2]}
+        bdlDict = {'Vorarlberg':[0,0], 'Tirol':[1,0], 'Kärnten':[2,0], 'Salzburg':[0,1], 'Steiermark':[1,1], 'Burgenland':[2,1], 'Oberösterreich':[0,2] ,'Niederösterreich':[1,2], 'Wien':[2,2]}
+
         return [int(bdlDict[bdl][0]) + random.random(), int(bdlDict[bdl][1]) + random.random()]
+
     def die(self):
-        #toImplement
+        randDie = random.random()
+        infectFaktor = 1
+        genderFaktor = 0.493
+        if self.Geschlecht == 1:
+            genderFaktor = 0.507
+        if self.Infiziert:
+            infectFaktor = 5
+        if (randDie < (int(gestDict[self.Bundesland][int(self.Geschlecht)])*infectFaktor/(int(bevDict[self.Bundesland])*365*genderFaktor))):
+            return True
+        else:
+            return False
+
     def infect(self, day):
-        #toImplement
-        #Distanz = math.sqrt((self.Koordinaten[0] - Population[randIndex].Koordinaten[0]) * (self.Koordinaten[0] - Population[randIndex].Koordinaten[0]) + (self.Koordinaten[1] - Population[randIndex].Koordinaten[1]) * (self.Koordinaten[1] - Population[randIndex].Koordinaten[1]))
+        if (int(day) - int(self.Stichtag)) > 10:
+            self.Infiziert = False
+        else:
+            for i in range(20):
+                randIndex = random.randint(0, len(Population)-1)
+                randInfect = random.random()
+                if(self.Bundesland == Population[randIndex].Bundesland):
+                    Distanz = math.sqrt((self.Koordinaten[0] - Population[randIndex].Koordinaten[0]) * (
+                                self.Koordinaten[0] - Population[randIndex].Koordinaten[0]) + (
+                                                    self.Koordinaten[1] - Population[randIndex].Koordinaten[1]) * (
+                                                    self.Koordinaten[1] - Population[randIndex].Koordinaten[1]))
+                    InfectProb = 0.3 * (1 - Distanz)
+                else:
+                    InfectProb = 0.0015
+                if(randInfect< InfectProb):
+                    Population[randIndex].Infiziert = True
+                    Population[randIndex].Stichtag = day
+
 class Simulation(object):
+
     def __init__(self, population):
         self.Population = population
+
     def simulate(self):
-        #toImplement
-        # Visualisierung
-        # Scatter Plot
-        x_inf = []
-        y_inf = []
-        x_fit = []
-        y_fit = []
-        for human in Population:
-            if (human.Infiziert):
-                x_inf.append(human.Koordinaten[0])
-                y_inf.append(human.Koordinaten[1])
-            else:
-                x_fit.append(human.Koordinaten[0])
-                y_fit.append(human.Koordinaten[1])
-        plt.title("Population")
-        plt.scatter(x_inf, y_inf, c="red", s=5)
-        plt.scatter(x_fit, y_fit, c="blue", s=2)
-        plt.draw()
-        if (i % 5 == 0):
-            plt.savefig('result/populationOnDay' + str(i) + '.png')
-        plt.pause(0.0001)
-        plt.clf()
+
+        print(len(Population))
+
+        RandomStartInfekt = random.randint(0, len(Population)-1)
+        Population[RandomStartInfekt].Infiziert = True
+        Population[RandomStartInfekt].Stichtag = 0
+        RandomStartInfekt = random.randint(0, len(Population)-1)
+        Population[RandomStartInfekt].Infiziert = True
+        Population[RandomStartInfekt].Stichtag = 0
+        RandomStartInfekt = random.randint(0, len(Population)-1)
+        Population[RandomStartInfekt].Infiziert = True
+        Population[RandomStartInfekt].Stichtag = 0
+
+        plt.ion()
+
+        for i in range(365):
+            print("Today is day number "+ str(i))
+            for key in gebDict.keys():
+                for j in range(int(abs(random.gauss((int(gebDict[key][0])*Populationsfaktor/(365)), 1)))):
+                     self.Population.append(Mensch(0, 0, key))
+                for j in range(int(abs(random.gauss((int(gebDict[key][1])*Populationsfaktor / (365)), 1)))):
+                    self.Population.append(Mensch(0, 1, key))
+
+            print(len(Population))
+
+            deathlist = []
+            for human in Population:
+                if(human.die()):
+                    deathlist.append(Population.index(human))
+                if(human.Infiziert):
+                    human.infect(i)
+
+            deathlist.sort(reverse=True)
+            for index in deathlist:
+                Population.remove(Population[index])
+
+
+
+            #Visualisierung
+            #Scatter Plot
+            x_inf = []
+            y_inf = []
+            x_fit = []
+            y_fit = []
+
+            for human in Population:
+                if(human.Infiziert):
+                    #plt.plot(human.Koordinaten[0], human.Koordinaten[1], "o", color="red",  markersize=2)
+                    x_inf.append(human.Koordinaten[0])
+                    y_inf.append(human.Koordinaten[1])
+                else:
+                    #plt.plot(human.Koordinaten[0], human.Koordinaten[1], "o", color="blue", markersize=1)
+                    x_fit.append(human.Koordinaten[0])
+                    y_fit.append(human.Koordinaten[1])
+
+            plt.title("Population")
+            plt.scatter(x_inf, y_inf, c="red", s=5)
+            plt.scatter(x_fit, y_fit, c="blue", s=2)
+
+            plt.draw()
+            if(i % 5 == 0):
+                plt.savefig('result/populationOnDay' + str(i) + '.png')
+            plt.pause(0.0001)
+            plt.clf()
+
+
+
+        print(len(Population))
+
+
+
 if __name__ == '__main__':
+
+
     print("Generate Population:")
     Populationsfaktor = 0.01
-    AnteilFrauen = 0.507
     Population = []
     bevAnzahl = 0
     bevDict = {}
     gebDict = {}
     gestDict = {}
+    AnteilFrauen = 0.507
+
+
     #read data from Statistik Austria
     with open('./data/Bevölkerung.csv') as bevoelkerung:
         csv_reader = csv.reader(bevoelkerung, delimiter = ';')
@@ -67,6 +164,7 @@ if __name__ == '__main__':
             rowcnt = rowcnt + 1
             if rowcnt > 2:
                 gebDict[row[0]] = [row[-2], row[-1]]
+
     with open('./data/Gestorbene2021.csv') as gestorbene:
         csv_reader = csv.reader(gestorbene, delimiter=';')
         rowcnt = 0
@@ -74,25 +172,29 @@ if __name__ == '__main__':
             rowcnt = rowcnt + 1
             if rowcnt > 2:
                 gestDict[row[0]] = [row[-2], row[-1]]
+
     print(bevDict)
     print(gebDict)
     print(gestDict)
     print(bevAnzahl)
-    print(random.random())
+
+    bdls = []
+    weights = []
+    for key in bevDict.keys():
+        bdls.append(str(key))
+        weights.append(int(bevDict[key]) * Populationsfaktor / int(bevAnzahl))
+
+
     for i in range(int(bevAnzahl)):
         gender = 1
         if(random.random()>0.507):
             gender = 0
         age = random.randint(0, 101)
-        bdl = ""
-        randBdl = random.random()
-        BdlCount = 0
-        for key in bevDict.keys():
-            BdlCount += int(bevDict[key])
-            checkWlsk = (BdlCount*Populationsfaktor)/int(bevAnzahl)
-            if(randBdl < checkWlsk):
-                bdl = str(key)
-                break
+
+        bdl = random.choices(bdls, weights)[0]
+
         Population.append(Mensch(age, gender, bdl))
+
     Simulation = Simulation(Population)
     Simulation.simulate()
+