def runMutationdevelopment_independentPopulations(self, N, r, d, K, b1, b2, m):
bValues = np.zeros((15000,3))
time = 1
resultPosition = 0
population1 = Population(m, mutationON=False)
population1.addIndividual(r, d, N, b1, K, resident=True)
population2 = Population(m, mutationON=False)
population2.addIndividual(r, d, N, b2, K, resident=True)
while time <= 30000:
population1.updatePopulation(1)
population2.updatePopulation(1)
if time % 100 == 1:
bValues[resultPosition] = [time, population1.getAverageB(), population2.getAverageB()]
resultPosition += 1
time += 1
population1.mutationON = True
population2.mutationON = True
while time <= 150000:
population1.updatePopulation(1)
population2.updatePopulation(1)
if time % 100 == 1:
bValues[resultPosition] = [time, population1.getAverageB(), population2.getAverageB()]
resultPosition += 1
time += 1
return bValues
def runMutationdevelopment_coexistingCommunity(self, N, r, d, K, b1, b2, m):
bValues = np.zeros((15000,3))
time = 1
resultPosition = 0
population = Population(m, mutationON=False)
population.addIndividual(r, d, N, b1, K, resident=True)
population.addIndividual(r, d, N, b2, K, resident=False)
while time <= 30000:
population.updatePopulation(1)
if time % 100 == 1:
bValues[resultPosition]= [time, population.getResidentAverageB(),population.getInvaderAverageB()]
resultPosition += 1
time += 1
population.mutationON = True
while time <= 150000:
population.updatePopulation(1)
if time % 100 == 1:
bValues[resultPosition] = [time, population.getResidentAverageB(),population.getInvaderAverageB()]
resultPosition += 1
time += 1
return bValues
