initial commit

main.py

@@ -0,0 +1,98 @@
+import csv
+import math
+import random
+import matplotlib.pyplot as plt
+class Mensch(object):
+    def __init__(self):
+        #toImplement
+    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]}
+        return [int(bdlDict[bdl][0]) + random.random(), int(bdlDict[bdl][1]) + random.random()]
+    def die(self):
+        #toImplement
+    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]))
+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()
+if __name__ == '__main__':
+    print("Generate Population:")
+    Populationsfaktor = 0.01
+    AnteilFrauen = 0.507
+    Population = []
+    bevAnzahl = 0
+    bevDict = {}
+    gebDict = {}
+    gestDict = {}
+    #read data from Statistik Austria
+    with open('./data/Bevölkerung.csv') as bevoelkerung:
+        csv_reader = csv.reader(bevoelkerung, delimiter = ';')
+        rowcnt = 0
+        for row in csv_reader:
+            rowcnt = rowcnt + 1
+            if rowcnt == 2:
+                bevAnzahl = int(int(row[-1])*Populationsfaktor)
+            if rowcnt > 2:
+                bevDict[row[0]] = row[-1]
+    with open('./data/Geburten2021.csv') as geburten:
+        csv_reader = csv.reader(geburten, delimiter=';')
+        rowcnt = 0
+        for row in csv_reader:
+            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
+        for row in csv_reader:
+            rowcnt = rowcnt + 1
+            if rowcnt > 2:
+                gestDict[row[0]] = [row[-2], row[-1]]
+    print(bevDict)
+    print(gebDict)
+    print(gestDict)
+    print(bevAnzahl)
+    print(random.random())
+    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
+        Population.append(Mensch(age, gender, bdl))
+    Simulation = Simulation(Population)
+    Simulation.simulate()