def getFig(primaryVary, secondaryVary):
ylists = []
xlist = [x/1000*(xupper[primaryVary]-xlower[primaryVary])+xlower[primaryVary] for x in baseXList]
for mitNum in range(0,5):
iteration = [*varydef]
iteration[secondaryVary] = vary[secondaryVary][mitNum]
ylist = []
for itNum in xlist:
iteration[primaryVary] = itNum
ylist.append(population(*iteration).decay(maxIter))
ylists.append(ylist)
# Change point
# Change line
plt.clf()
plt.plot(xlist, ylists[0], label=vary[secondaryVary][0], mfc='r', marker=',')
plt.plot(xlist, ylists[1], label=vary[secondaryVary][1], mfc='b', marker=',')
plt.plot(xlist, ylists[2], label=vary[secondaryVary][2], mfc='g', marker=',')
plt.plot(xlist, ylists[3], label=vary[secondaryVary][3], mfc='y', marker=',')
plt.plot(xlist, ylists[4], label=vary[secondaryVary][4], mfc='c', marker=',')
plt.xlabel(labelList[primaryVary])
plt.ylabel('Iterations Before Extinction')
plt.title('Iterations vs ' + labelList[primaryVary] + ' with varying ' + labelList[secondaryVary])
plt.axis([xlist[0], xlist[popNum-1],
0, 20])# Change these values to make graph prettier
plt.legend()
return plt
def getPopAttributes(iteration):
#Determine population attributes based on iteration number
# Initial population size
popSize = 10000
# percentage of initial pop. infected
perInfect = .5
# % chance that offspring of an infected male is male
ratio = .5
# Growth of population per generation. 0 means no growth, 1 means double every year, etc.
growth = 6
return (popSize, perInfect, ratio, growth)
start = time.process_time()
# Amount of populations to simulate
popNum = 1000
# Max iteration count
maxIter = 10000
for x in range(1, popNum):
pop = population(*getPopAttributes(x))
print(x, pop.decay(maxIter))
stop = time.process_time()
print("Time Elapsed:", stop - start)
import time
from sim import population, nextGen
#This script simulates a single population slowly decaying due to infection
start = time.process_time()
# Initial population size
popSize = 10000
# percentage of initial pop. infected
perInfect = .5
# % chance that offspring of an infected male is male
ratio = .5
# Growth of population per generation. Zero means no growth, 1 means double every year, etc.
growth = 6
a = population(popSize, perInfect, ratio, growth) # generation 0
gen = a.getInit()
iter = 0
print(iter, gen.population, gen.infected)
while (gen.population > 1 and gen.infected > 1
and iter < 100000): #a.infected > 0
gen = nextGen(gen)
iter += 1
print(iter, gen.population, gen.infected)
stop = time.process_time()
print("Time Elapsed:", stop - start)