def testDieStarveSync(self):
env = environment.environment(10,'sync')
# Create a starving fox
rabbit= agents.rabbit(age=2,food=-1,pos=[5.5,5.5],speed=2,last_breed=7)
# Ensure that it knows that its time to die
rabbit.die(env)
self.failUnless(rabbit.messages.dead,'Starved rabbit did not die')
def testDieOldSync(self):
env = environment.environment(10,'sync')
# Create an old rabbit
rabbit= agents.rabbit(age=1000,food=10,pos=[5.5,5.5],speed=2,last_breed=7)
# Ensure that it knows that its time to die
rabbit.die(env)
self.failUnless(rabbit.messages.dead,'Ancient rabbit did not die')
def testDefault(self):
self.rabbit = agents.rabbit()
self.assertEqual(self.rabbit.age,[])
self.assertEqual(self.rabbit.food,[])
self.assertEqual(self.rabbit.pos,[])
self.assertEqual(self.rabbit.speed,[])
self.assertEqual(self.rabbit.last_breed,[])
def testBreed1(self):
#Esnure that a rabbit that can breed, does breed
env = environment.environment(5)
#Create a rabbit that's ready to breed
rabbit = agents.rabbit(age=30,food=100,pos=[5.5,5.5],speed=2,last_breed=21)
new_rabbit = rabbit.breed(env)
self.failUnless(isinstance(new_rabbit,agents.rabbit))
def create_agents(self, nr, nf, list_type='joined'):
"""
environment.create_agents(nr, nf) - Creates a list of agents
within the environment
Input Parameters
----------------
nr : integer
Number of rabbits
nf : integer
Number of foxes
list_type : string (default='joined')
Determines how the agents are stored.
'joined' - maintains a single list containing both
rabbits and foxes.
'seprate' - maintains separate lists of rabbits and foxes
(THIS WONT WORK WITH THE REST OF ECOLAB YET)
Output:
-------
agent_list : list
List(s) of generated agents
"""
# We create the transpose here in order to generate matrices
# that are identical to MATLAB's
# generate random initial positions for rabbits and foxes
rloc = np.transpose((self.bm_size-1)*rand(2, nr))+1
floc = np.transpose((self.bm_size-1)*rand(2, nf))+1
rabbits = []
foxes = []
for r in range(nr):
pos = rloc[r, :]
age = np.ceil(rand()*10)
food = np.ceil(rand()*20)+20
lbreed = np.round(rand()*rabbit.brdfq)
rabbits.append(rabbit(age, food, pos, rabbit.speed, lbreed))
for f in range(nf):
pos = floc[f, :]
age = np.ceil(rand()*10)
food = np.ceil(rand()*20)+20
lbreed = np.round(rand()*fox.brdfq)
foxes.append(fox(age, food, pos, fox.speed, lbreed))
if list_type == 'separate':
self.foxes = foxes
self.rabbits = rabbits
elif list_type == 'joined':
self.agents = rabbits
self.agents.extend(foxes)
def testMigrateWhenFoodAvailable(self):
#Does a rabbit at (5.5,5.5) migrate to the same position as the MATLAB version given that food is available
self.env= environment.environment(10,mode='sync')
numpy.random.seed(1) #MMigrate uses random numbers so need to seed to get reproducable results
rabbit= agents.rabbit(age=2,food=10,pos=[5.5,5.5],speed=2,last_breed=7)
rabbit.migrate(self.env)
self.failUnlessAlmostEqual(rabbit.pos[0],4.917022,places=4,msg='Migrating rabbit has given different results from MATLAB')
self.failUnlessAlmostEqual(rabbit.pos[1],5.22032449,places=4,msg='Migrating rabbit has given different results from MATLAB')
def testExtractLocalFoodTopLeftCorner(self):
self.env = environment.environment(10)
rabbit = agents.rabbit(age=2,food=10,pos=[1.1,1.1],speed=2,last_breed=7) #Rabbit in corner of simulation
(local_food,xmin,ymin) = rabbit.extract_local_food(self.env)
self.failUnlessEqual(numpy.shape(local_food),(3,3),'Incorrect local food size for rabbit in top left corner')
self.failUnless(numpy.all(local_food==50),'Incorrect local food values for rabbit in top left')
def testEatInDesert(self):
self.env = environment.environment(10)
self.rabbit = agents.rabbit(age=2,food=10,pos=[5.5,5.5],speed=2,last_breed=7) #In a food desert
#The rabbit is in a food desert. Does it eat correctly?
starting_food = self.env.food[self.rabbit.cpos[0],self.rabbit.cpos[1]]
self.failUnlessEqual(starting_food,0,'This rabbit was supposed to be in a desert')
eaten = self.rabbit.eat(self.env)
self.failUnlessEqual(self.env.food[self.rabbit.cpos[0],self.rabbit.cpos[1]],0,'Starting food was 0. Rabbit incorrectly changed that!')
self.failIfEqual(eaten,1,'Rabbit reports that it has eaten when it can''t have')
def testExtractLocalFoodBottomRightCorner(self):
self.env = environment.environment(10)
rabbit = agents.rabbit(age=2,food=10,pos=[9.5,9.5],speed=2,last_breed=7) #Rabbit in corner of simulation
(local_food,xmin,ymin) = rabbit.extract_local_food(self.env)
self.failUnlessEqual(numpy.shape(local_food),(3,3),'Incorrect local food size for rabbit in bottom right corner')
correct = numpy.array([[0,50,50],[50,50,50],[50,50,50]])
self.failUnless(numpy.array_equal(local_food,correct),'Incorrect local food values for rabbit in bottom right corner')
def testMigrateWhenFoodNotAvailable(self):
#Does a rabbit at (9.8,9.8) migrate to the same posiiton as the MATLAV version given that no food is available
numpy.random.seed(1) #MMigrate uses random numbers so need to seed to get reproducable results
self.env= environment.environment(10,mode='sync')
self.env.food= numpy.zeros((10,10)) #Eat all the food
rabbit= agents.rabbit(age=2,food=10,pos=[9.8,9.8],speed=2,last_breed=7)
rabbit.migrate(self.env)
self.failUnlessAlmostEqual(rabbit.pos[0],7.86930887,places=4,msg='Migrating rabbit has given different results from MATLAB')
self.failUnlessAlmostEqual(rabbit.pos[1],9.27805005,places=4,msg='Migrating rabbit has given different results from MATLAB')
def testExtractLocalFoodCentral(self):
correct = [[50,50,50,50,50], \
[50,50,50,50,50], \
[50,50,50,50,50], \
[50,50,50,0,0], \
[50,50,50,0,0]]
self.env = environment.environment(10)
rabbit = agents.rabbit(age=2,food=10,pos=[5,5],speed=2,last_breed=7)
(local_food,xmin,ymin) = rabbit.extract_local_food(self.env)
self.failUnless(numpy.array_equal(local_food,correct),'Incorrect local food values for rabbit in center')
def testEat1Async(self):
env = environment.environment(5,'async')
# Create a very fast fox
fox = agents.fox(age=2, food=10, pos=[1.5,1.5], speed=10, last_breed=7)
# create a rabbit very close to it
env.agents = [agents.rabbit(age=2, food=10, pos=[1.52,1.52], speed=10, last_breed=7)]
#Set the previous position of rabbit to be [1.52,1.52]
env.agents[0].messages.pos = [1.52, 1.52]
# Its almost certain that this fox ate this rabbit
fox.eat(env)
# Doex rabbit know that its been eaten?
self.failUnless(env.agents[0].has_been_eaten)
def testEatWhenHasFood(self):
#The rabbit has some food. Does it eat correctly?
self.env = environment.environment(10)
self.rabbit = agents.rabbit(age=2,food=10,pos=[1.2,1.2],speed=2,last_breed=7) #Food initially=50
starting_food = self.env.food[(self.rabbit.cpos[0],self.rabbit.cpos[1])]
self.failIfEqual(starting_food,0,'This rabbit was supposed to have access to food')
eaten = self.rabbit.eat(self.env)
self.failUnlessEqual(self.env.food[self.rabbit.cpos[0],self.rabbit.cpos[1]],starting_food-1,'Rabbit has incorrectly changed food quanity after eating.')
self.failIfEqual(eaten,0,'Rabbit reports that it hasn''t eaten when it has')
def testBreed2(self):
#Ensure that an eaten rabbit doesn't breed in async mode
env = environment.environment(5,mode='async')
env.agents = []
# Put a hungry fox next to a rabbit
env.agents.append(agents.fox(20,30,[1.5,1.5],5,10))
env.agents.append(agents.rabbit(20,30,[1.5,1.25],2,10))
eaten = env.agents[0].eat(env)
self.failUnless(eaten,'Fox should have eaten rabbit')
new = env.agents[1].breed(env)
self.failUnless(new is None,'Dead rabbit bred')
def testDieDoubleCount(self):
# Ensure that we don't decrement rabbit counter twice
# If an eaten rabbit was also ready to die
env = environment.environment(10,'async')
env.agents = []
# Put an old rabbit next to a hungry fox
env.agents.append(agents.rabbit(1000,30,[1.5,1.5],2,1))
env.agents.append(agents.fox(20,30,[1.5,1.25],10,10))
# Fox eats rabbit
eaten = env.agents[1].eat(env)
self.failUnless(eaten,'Fox didn''t eat rabbit')
# Apply die rule to the dead rabbit
env.agents[0].die(env)
self.failUnlessEqual(agents.rabbit.num_rabbits,0,'Should be 0 rabbits')
def testEat2(self):
# Ensure that the same rabbit doesn't get eaten multiple times in async mode
env = environment.environment(5,mode='async')
env.agents = []
# Surround a rabbit by 4 foxes in eating range
env.agents.append(agents.rabbit(20 ,30, [1.5, 1.5], 2, 1))
env.agents.append(agents.fox(20 ,30, [1.5, 1.25], 10, 10))
env.agents.append(agents.fox(20 ,30, [1.25, 1.5], 10, 10))
env.agents.append(agents.fox(20 ,30, [1.25, 1.25], 10, 10))
env.agents.append(agents.fox(20 ,30, [1.3, 1.25], 10, 10))
eaten1 = env.agents[1].eat(env)
eaten2 = env.agents[2].eat(env)
eaten3 = env.agents[3].eat(env)
eaten4 = env.agents[4].eat(env)
self.failUnless(eaten1, 'Fox 1 should have eaten but didn''t')
self.failUnless(not eaten2, 'Fox 2 should not have eaten but did')
self.failUnless(not eaten3, 'Fox 3 should not have eaten but did')
self.failUnless(not eaten4, 'Fox 4 should not have eaten but did')
self.failUnlessEqual(agents.rabbit.num_rabbits,0)
def testCpos(self):
# Ensures cpos is calculated correctly
self.rabbit1 = agents.rabbit(age=2,food=10,pos=[5.5,5.5],speed=2,last_breed=7) #In a food desert
self.failUnless(all(self.rabbit1.cpos==5))