def __init__(self,
t=TimeInt(0, 23),
p_think=0.5,
p_eat=0.5,
is_verbose=False,
memo=None):
super().__init__('think-and-eat', t, memo)
self.p_think = p_think
self.p_eat = p_eat
self.is_verbose = is_verbose
0). # confirm that only one pruned group exists
run() # confirm that the simulation runs
)
print()
# ----------------------------------------------------------------------------------------------------------------------
# (3) Improper simulations (that will not run):
# (3.1) Problem: Attempting to add a rule after having added a group:
print('(3.1)')
try:
(Simulation(TimeHour(6), 16).add_rule(
ProgressFluRule()).add_probe(probe_grp_size_flu).new_group(
'0',
1000).set_attr('flu-stage', AttrFluStage.NO).commit().add_rule(
GoToRule(TimeInt(10, 16), 0.4, 'home', 'work')))
except SimulationConstructionError as e:
print(e)
print()
# (3.2) Problem: Attempting to add a group with no rules present:
print('(3.2)')
try:
(Simulation(TimeHour(6), 16).new_group('0', 1000).set_attr(
'flu-stage', AttrFluStage.NO).commit().add_rule(
ProgressFluRule()).add_probe(probe_grp_size_flu))
except SimulationConstructionError as e:
print(e)
print()
# (3.3) Problem: A group has superfluous attributes and relations:
def __init__(self, t=TimeInt(8,20), p_infection_min=0.01, p_infection_max=0.95, memo=None): # 8am - 8pm
super().__init__('progress-flu', t, memo)
self.p_infection_min = p_infection_min
self.p_infection_max = p_infection_max
def __init__(self, t=TimeInt(8,20), memo=None):
super().__init__('progress-flu', t, memo)
(Simulation(6,1,24, rand_seed=rand_seed).
new_group('g0', 1000).
set_rel(Site.AT, sites['home']).
set_rel('home', sites['home']).
set_rel('work', sites['work-a']).
set_rel('store', sites['store-a']).
commit().
new_group('g1', 1000).
set_rel(Site.AT, sites['home']).
set_rel('home', sites['home']).
set_rel('work', sites['work-b']).
set_rel('store', sites['store-b']).
commit().
new_group('g2', 100).
set_rel(Site.AT, sites['home']).
set_rel('home', sites['home']).
set_rel('work', sites['work-c']).
commit().
add_rule(GotoRule(TimeInt( 8,12), 0.4, 'home', 'work', 'Some agents leave home to go to work')).
add_rule(GotoRule(TimeInt(16,20), 0.4, 'work', 'home', 'Some agents return home from work')).
add_rule(GotoRule(TimeInt(16,21), 0.2, 'home', 'store', 'Some agents go to a store after getting back home')).
add_rule(GotoRule(TimeInt(17,23), 0.3, 'store', 'home', 'Some shopping agents return home from a store')).
add_rule(GotoRule(TimePoint(24), 1.0, 'store', 'home', 'All shopping agents return home after stores close')).
add_rule(GotoRule(TimePoint( 2), 1.0, None, 'home', 'All still-working agents return home')).
add_probe(probe_grp_size_site).
summary((True, True, True, True, True), (0,1)).
run().
summary((False, True, False, False, False), (1,1)).
run(4)
)
def __init__(self, t=TimeInt(8, 16), memo=None):
super().__init__('attend-school', t, memo)
print(self._dump(tree))
@staticmethod
def get_str(node):
return list(ast.iter_fields(node))[0][1]
from pram.rule import GotoRule, TimeInt
from sim.rules import AttendSchoolRule, ProgressFluRule, ProgressAndTransmitFluRule
ra = RuleAnalyzer()
# ra.analyze(ProgressFluRule())
# ra.analyze(R())
ra.analyze(GotoRule(TimeInt(8, 12), 0.4, 'home', 'work'))
# ra.analyze(ProcessRule(AttendSchoolRule())
# ra.analyze(ProcessRule(ProgressFluRule())
# ra.analyze(ProcessRule(ProgressAndTransmitFluRule())
# ra.dump(ProgressFluRule())
# ra.dump(R())
print('----')
print(f'attr : {ra.attr}')
print(f'rel : {ra.rel}')
print(f'known : {ra.cnt_known}')
print(f'unknown : {ra.cnt_unknown}')
# ----
def __init__(self, t=TimeInt(0, 12), memo=None):
super().__init__('snake-eats-mice', t, memo)
self.T_UNIT_MS = Time.MS.M
def __init__(self, t=TimeInt(0, 12), memo=None):
super().__init__('mice-birth', t, memo)
self.T_UNIT_MS = Time.MS.M
def __init__(self, t=TimeInt(0, 12), memo=None):
super().__init__('hunter-kills-snakes', t, memo)
self.T_UNIT_MS = Time.MS.M
s: Site(s)
for s in ['home', 'work-a', 'work-b', 'work-c', 'store-a', 'store-b']
}
probe_grp_size_site = GroupSizeProbe.by_rel(
'site',
Site.AT,
sites.values(),
msg_mode=ProbeMsgMode.DISP,
memo='Mass distribution across sites')
(Simulation().add().rule(
GoToRule(0.4,
'home',
'work',
TimeInt(8, 12),
memo='Some agents leave home to go to work')).rule(
GoToRule(0.4,
'work',
'home',
TimeInt(16, 20),
memo='Some agents return home from work')).
rule(
GoToRule(0.2,
'home',
'store',
TimeInt(16, 21),
memo='Some agents go to a store after getting back home')).rule(
GoToRule(
0.3,
'store',