def OA1(agent):
"""
This rule activates the agents in an random order at every cycle.
"""
pop = get_pop(agent)
if agent == p.get_agents(pop)[0]: #IF IT IS THE FIRST AGENT
shuffle(p.get_agents(pop))
def OA2(agent):
"""
This rule activates the agents in an order which makes the agent
who has the lowest sugar level move first. This order changes at
every cycle.
"""
pop = get_pop(agent)
if agent == p.get_agents(pop)[0]: #IF IT IS THE FIRST AGENT
l_res = []
for elem in p.get_agents(pop):
l_res.append(get_sugar_level(elem))
u.sort_on_second_list(p.get_agents(pop), l_res, u_mod.order_scalar_asc)
def __draw_pop(canvas, pop, cell_size):
# Draw the population on the canvas
env = p.get_env(pop)
env_size = e.size(env)
for agent in p.get_agents(pop):
if a.get_is_living(agent):
cell_ref = __swap_y(env_size, a.get_pos(agent))
canvas.create_oval(__bbox_for_cell_ref(cell_ref, cell_size, 0.6), fill='red', width=0)
def kill_agent(pop, agent):
"""
Kills the agent.
"""
env = p.get_env(pop)
cell = e.get_cell(env, get_pos(agent))
p.end_agent(agent, p.get_agents(pop))
c.set_present_agent(cell, None)
def add_baby_agent_if_possible(env, pop, env_size, agent, l_pos):
"""
Makes a female agent give birth to a new agent if there is a free
position around her. If there is no free position, the baby won't
born. This strategy limmits the overpopulation.
"""
if len(l_pos) != 0:
baby = new_instance(pop)
mother_dead_age = get_dead_age(agent)
mother_metabolism = get_metabolism(agent)
father_dead_age = get_partner_spec(agent)[0]
father_metabolism = get_partner_spec(agent)[1]
set_dead_age(baby, int((mother_dead_age + father_dead_age) / 2))
set_metabolism(baby, (mother_metabolism + father_metabolism) / 2)
p.get_agents(pop).append(baby)
set_pos(baby, l_pos[0])
c.set_present_agent(e.get_cell(env, l_pos[0]), baby)
def __draw_pop(canvas, pop, cell_size):
# Draw the population on the canvas
env = p.get_env(pop)
env_size = e.size(env)
for agent in p.get_agents(pop):
if a.get_is_living(agent):
cell_ref = __swap_y(env_size, a.get_pos(agent))
canvas.create_oval(__bbox_for_cell_ref(cell_ref, cell_size, 0.6), fill='red', width=0)
def pop_plot(pop):
"""
Add a plot of the each agent to the current pylab plot.
To actually show the plot, the pylab.show() method
still has to be invoked.
"""
agents_list = p.get_agents(pop)
for agent in agents_list:
agent_plot(agent)
def kill(agent):
"""
Fonction qui tue un agent
"""
pop = get_population(agent)
agents = p.get_agents(pop)
cell = get_cell(agent)
p.increment_dead_agents(pop)
if agent in agents:
del agents[agents.index(agent)]
c.set_present_agent(cell, None)
def kill(agent): """ Fonction qui tue un agent """ pop = get_population(agent) agents = p.get_agents(pop) cell = get_cell(agent) p.increment_dead_agents(pop) if agent in agents: del agents[agents.index(agent)] c.set_present_agent(cell,None)
def __draw_pop(canvas, pop, cell_size):
# Draw the population on the canvas
# WE ADD THE color_agent FUNCTION IN PLACE OF "red"
# AND THE THICKNESS EVOLVES THANKS THE thk FUNCTION
env = p.get_env(pop)
env_size = e.size(env)
for agent in p.get_agents(pop):
if a.get_is_living(agent):
cell_ref = v.__swap_y(env_size, a.get_pos(agent))
canvas.create_oval(v.__bbox_for_cell_ref(cell_ref, cell_size,
thk(agent)),
fill=color_agent(agent),
width=0)
def is_an_agent_can_be_there_faster(agent,target): """ si un autre agent peut atteindre avant la cellule visée """ pop = get_population(agent) agents = p.get_agents(pop) i=0 already_found = False while i < len(agents) and not already_found: if agents[i] != agent and target in accecible_positions(agents[i]): already_found = (u.eucl_dist(get_pos(agents[i]),target) < u.eucl_dist(get_pos(agent),target)) i+=1 return already_found
def is_an_agent_can_be_there_faster(agent, target):
"""
si un autre agent peut atteindre avant la cellule visée
"""
pop = get_population(agent)
agents = p.get_agents(pop)
i = 0
already_found = False
while i < len(agents) and not already_found:
if agents[i] != agent and target in accecible_positions(agents[i]):
already_found = (u.eucl_dist(get_pos(agents[i]), target) <
u.eucl_dist(get_pos(agent), target))
i += 1
return already_found
def reproduction(agent):
"""
Choose the best male around the female agent in order the make her
enter in a gestation period which will allow to give birth to a new
agent 9 cycles after the reproduction.
"""
pop = get_pop(agent)
env = p.get_env(pop)
env_size = e.size(env)
first_pop_size = len(p.get_agents(pop))
l, l_pos = potential_partners(pop, agent, env, env_size, 1, l=[], l_pos=[])
l_partners = partners_list_under_conditions(env, agent, l_pos)
if len(l_partners) != 0:
best_age = get_dead_age(best_partner_from_list(l_partners))
metabolism = get_metabolism(best_partner_from_list(l_partners))
if get_gestation(agent) == -1:
set_gestation(agent, 9)
set_partner_spec(agent, (best_age, metabolism))
def make_a_child(agent):
"""
règle permettant la reproduction asexuée selon une certaine probablité
les agents doivent être dans un intervalle d'âge précis
"""
pop = get_population(agent)
env = get_env(agent)
min_age = p.get_pop_property(pop, "MIN_AGE_TO_MAKE_CHILDS")
max_age = p.get_pop_property(pop, "MAX_AGE_TO_MAKE_CHILDS")
max_pop = p.get_pop_property(pop, "MAX_POP")
min_prob, max_prob = p.get_pop_property(pop, "PROB_TO_HAVE_SEX")
if (min_age <= get_age(agent) <= max_age and theres_is_an_other_sex_around(agent) \
and randint(min_prob,max_prob) == 1 and p.size(pop) < max_pop ):
new_child = new_instance(pop)
set_age(new_child, 0)
set_sugar_level(agent, 0)
#le nouveau-née hérite du métabolisme et de la vision de capacité de son géniteur
set_metabolism(new_child, get_metabolism(agent))
set_vision_capacity(new_child, get_vision_capacity(agent))
agents_list = p.get_agents(pop)
agents_list.append(new_child)
def make_a_child(agent): """ règle permettant la reproduction asexuée selon une certaine probablité les agents doivent être dans un intervalle d'âge précis """ pop = get_population(agent) env = get_env(agent) min_age = p.get_pop_property(pop,"MIN_AGE_TO_MAKE_CHILDS") max_age = p.get_pop_property(pop,"MAX_AGE_TO_MAKE_CHILDS") max_pop = p.get_pop_property(pop,"MAX_POP") min_prob,max_prob = p.get_pop_property(pop,"PROB_TO_HAVE_SEX") if (min_age <= get_age(agent) <= max_age and theres_is_an_other_sex_around(agent) \ and randint(min_prob,max_prob) == 1 and p.size(pop) < max_pop ): new_child = new_instance(pop) set_age(new_child,0) set_sugar_level(agent,0) #le nouveau-née hérite du métabolisme et de la vision de capacité de son géniteur set_metabolism(new_child,get_metabolism(agent)) set_vision_capacity(new_child,get_vision_capacity(agent)) agents_list = p.get_agents(pop) agents_list.append(new_child)
