def sim_flu_init(session, do_force=False):
if 'sim-flu' in session and not do_force:
return
if 'sim-flu' in session:
session.pop('sim-flu')
sites = { s:Site(s) for s in ['home', 'school-a', 'school-b']}
probe_grp_size_site = GroupSizeProbe.by_rel('site', Site.AT, sites.values(), msg_mode=ProbeMsgMode.CUMUL)
session['sim-flu'] = (
Simulation().
set().
pragma_live_info(False).
pragma_live_info_ts(False).
done().
add().
rule(ResetSchoolDayRule(TimePoint(7))).
rule(GoToAndBackTimeAtRule(t_at_attr='t@school')).
probe(probe_grp_size_site).
done().
new_group(500).
set_rel(Site.AT, sites['home']).
set_rel('home', sites['home']).
set_rel('school', sites['school-a']).
done().
new_group(500).
set_rel(Site.AT, sites['home']).
set_rel('home', sites['home']).
set_rel('school', sites['school-b']).
done()
)
def run_the_app():
# Draw the UI elements to search for objects (pedestrians, cars, etc.)
gsize, s1, s2, s3, i1, i2, i3, r1, r2, r3, run = frame_selector_ui()
progress_flu_rule = DiscreteInvMarkovChain('flu-status',
{ 's': [s1, s2, s3], 'i': [i1, i2, i3], 'r': [r1, r2, r3] })
# s - susceptible
# i - infectious
# r - recovered
sites = { 'home': Site('h'), 'work': Site('w') }
probe_grp_size_flu = GroupSizeProbe.by_attr('flu', 'flu-status', progress_flu_rule.get_states(), msg_mode=ProbeMsgMode.DISP, memo='Mass distribution across flu status')
probe_grp_size_site = GroupSizeProbe.by_rel('site', Site.AT, sites.values(), msg_mode=ProbeMsgMode.DISP, memo='Mass distribution across sites')
data = ""
s = Simulation()
s.add_rule(progress_flu_rule)
s.add_probe(probe_grp_size_flu)
s.add_group(Group('g0', gsize, { 'flu-status': 's' }))
sys.stdout = open('out.dat', 'w')
s.run(int(run))
sys.stdout.close()
with open('out.dat') as file:
data = file.readlines()
for line in data:
st.write(line)
def simple(self):
progress_flu_rule = DiscreteInvMarkovChain('flu-status', { 's': [0.95, 0.05, 0.00], 'i': [0.00, 0.50, 0.50], 'r': [0.10, 0.00, 0.90] })
# s - susceptible
# i - infectious
# r - recovered
sites = { 'home': Site('h'), 'work': Site('w') }
probe_grp_size_flu = GroupSizeProbe.by_attr('flu', 'flu-status', progress_flu_rule.get_states(), msg_mode=ProbeMsgMode.DISP, memo='Mass distribution across flu status')
probe_grp_size_site = GroupSizeProbe.by_rel('site', Site.AT, sites.values(), msg_mode=ProbeMsgMode.DISP, memo='Mass distribution across sites')
# ----------------------------------------------------------------------------------------------------------------------
# (1) Simulations testing the basic operations on groups and rules:
# (1.1) A single-group, single-rule (1g.1r) simulation:
s = Simulation()
s.add_rule(progress_flu_rule)
s.add_probe(probe_grp_size_flu)
s.add_group(Group('g0', 1000, { 'flu-status': 's' }))
sys.stdout = open('out.dat', 'w')
s.run(24)
sys.stdout.close()
with open('out.dat') as file:
self.data = file.readlines()
self.data = str(self.data)
apple = self.data.replace('\\n', '<br>')
# print(apple)
return apple
def add_initial_rules(time_offset):
"Imports rules built into pram and inserts them into the rules dictionary"
global sites
sites = {
s: Site(s)
for s in ['home', 'work-a', 'work-b', 'work-c', 'store-a', 'store-b']
}
mall_sites_names = [
"big_theater", "down_store1", "down_store2", "down_store3",
"down_store4", "down_store5", "down_store6", "down_store7",
"down_store8", "down_store9", "big_down_store10", "big_down_store11",
"big_down_store12", "up_store1", "up_store2", "up_store3", "up_store4",
"up_store5", "up_store6", "up_store7", "up_store8", "up_store9",
"big_down_courtyard_1", "big_down_courtyard_2", "big_down_courtyard_3",
"big_down_courtyard_4"
]
mall_sites = [Site(s) for s in mall_sites_names]
for i in range(len(mall_sites)):
sites[mall_sites_names[i]] = mall_sites[i]
#rules["Mall Movement"] = [MallMovement(0.2, mall_sites)]
rules["Mall Flu"] = [MallFlu(1, 0.2, mall_sites)]
rules["Simple Flu Progress Rule"] = [
SimpleFluProgress(
'flu-status', {
's': [0.95, 0.05, 0.00],
'i': [0.00, 0.50, 0.50],
'r': [0.10, 0.00, 0.90]
}, sites['home'])
]
# rules["Home-Work-School Rules"] = [SimpleGoTo(TimeInt( (8 - time_offset)%24,(12 - time_offset)%24), 0.4, 'home', 'work', 'Some agents leave home to go to work'),
# SimpleGoTo(TimeInt((16- time_offset)%24,(20- time_offset)%24), 0.4, 'work', 'home', 'Some agents return home from work'),
# SimpleGoTo(TimeInt((16- time_offset)%24,(21- time_offset)%24), 0.2, 'home', 'store', 'Some agents go to a store after getting back home'),
# SimpleGoTo(TimeInt((17- time_offset)%24,(23- time_offset)%24), 0.3, 'store', 'home', 'Some shopping agents return home from a store'),
# SimpleGoTo(TimePoint((24- time_offset)%25), 1.0, 'store', 'home', 'All shopping agents return home after stores close'),
# SimpleGoTo(TimePoint( (2- time_offset)%25), 1.0, None, 'home', 'All still-working agents return home')]
global probe_grp_size_site
probe_grp_size_site = GroupSizeProbe.by_rel(
'site',
Site.AT,
sites.values(),
msg_mode=ProbeMsgMode.DISP,
memo='Mass distribution across sites')
return
def sim01():
from pram.data import GroupSizeProbe, ProbeMsgMode
from pram.entity import Site
from pram.rule import GoToAndBackTimeAtRule, ResetSchoolDayRule, TimePoint
from pram.sim import Simulation
sites = {s: Site(s) for s in ['home', 'school-a', 'school-b']}
probe_grp_size_site = GroupSizeProbe.by_rel('site',
Site.AT,
sites.values(),
msg_mode=ProbeMsgMode.CUMUL)
(Simulation().add().rule(ResetSchoolDayRule(TimePoint(7))).rule(
GoToAndBackTimeAtRule(t_at_attr='t@school')).probe(
probe_grp_size_site).commit().new_group(500).set_rel(
Site.AT, sites['home']).set_rel('home', sites['home']).set_rel(
'school',
sites['school-a']).commit().new_group(500).set_rel(
Site.AT,
sites['home']).set_rel('home', sites['home']).set_rel(
'school', sites['school-b']).commit().run(18))
return probe_grp_size_site.get_msg()
})
# s - susceptible
# i - infectious
# r - recovered
sites = {'home': Site('h'), 'work': Site('w')}
probe_grp_size_flu = GroupSizeProbe.by_attr(
'flu',
'flu-status',
progress_flu_rule.get_states(),
msg_mode=ProbeMsgMode.DISP,
memo='Mass distribution across flu status')
probe_grp_size_site = GroupSizeProbe.by_rel(
'site',
Site.AT,
sites.values(),
msg_mode=ProbeMsgMode.DISP,
memo='Mass distribution across sites')
# ----------------------------------------------------------------------------------------------------------------------
# (1) Simulations testing the basic operations on groups and rules:
# (1.1) A single-group, single-rule (1g.1r) simulation:
s = Simulation()
s.add_rule(progress_flu_rule)
s.add_probe(probe_grp_size_flu)
s.add_group(Group('g0', 1000, {'flu-status': 's'}))
s.run(24)
# (1.2) A single-group, two-rule (1g.2r) simulation:
# s = Simulation()
import random
from scipy.stats import poisson
from pram.data import GroupSizeProbe, ProbeMsgMode
from pram.entity import Group, GroupDBRelSpec, GroupQry, GroupSplitSpec, Site
from pram.rule import SegregationModel
from pram.sim import Simulation
# ----------------------------------------------------------------------------------------------------------------------
# (1) Simulation (two locations)
loc = [Site('a'), Site('b')]
probe_loc = GroupSizeProbe.by_rel('loc',
Site.AT,
loc,
msg_mode=ProbeMsgMode.DISP)
probe_sim = GroupSizeProbe(name='sim',
queries=[
GroupQry(attr={'team': 'blue'},
rel={Site.AT: loc[0]}),
GroupQry(attr={'team': 'red'},
rel={Site.AT: loc[0]}),
GroupQry(attr={'team': 'blue'},
rel={Site.AT: loc[1]}),
GroupQry(attr={'team': 'red'},
rel={Site.AT: loc[1]})
],
qry_tot=None,
msg_mode=ProbeMsgMode.DISP)
def main():
# SAMPLE SIMULATION FROM 09-segregation
import os
from pram.data import GroupSizeProbe, ProbeMsgMode, ProbePersistenceDB
from pram.entity import Group, GroupQry, Site, GroupSplitSpec
from pram.rule import SegregationModel
from pram.sim import Simulation
# -----------------------------------------------------------------------------------------------------------------
# (1) Simulation (two locations)
loc = [Site('a'), Site('b')]
def gs(pop, group):
return [
GroupSplitSpec(p=0.7, attr_set={'foobar': 'foo'}),
GroupSplitSpec(p=0.3, attr_set={'foobar': 'bar'})
]
probe_loc = GroupSizeProbe.by_rel('loc',
Site.AT,
loc,
msg_mode=ProbeMsgMode.DISP)
probe_sim = GroupSizeProbe(name='sim',
queries=[
GroupQry(attr={'team': 'blue'},
rel={Site.AT: loc[0]}),
GroupQry(attr={'team': 'red'},
rel={Site.AT: loc[0]}),
GroupQry(attr={'team': 'blue'},
rel={Site.AT: loc[1]}),
GroupQry(attr={'team': 'red'},
rel={Site.AT: loc[1]})
],
qry_tot=None,
persistence=ProbePersistenceDB(),
msg_mode=ProbeMsgMode.DISP)
s = (
Simulation().set().pragma_autocompact(True).pragma_live_info(False).
fn_group_setup(gs).done().add([
SegregationModel('team', len(loc)),
# TranslateEverything(),
# LambdasAndArguments(),
Group(m=200,
attr={'team': 'blue'},
rel={
Site.AT: loc[0],
'origin': loc[0]
}),
Group(m=300,
attr={'team': 'blue'},
rel={
Site.AT: loc[1],
'origin': loc[1]
}),
Group(m=100,
attr={'team': 'red'},
rel={
Site.AT: loc[0],
'origin': loc[0]
}),
Group(m=400,
attr={'team': 'red'},
rel={
Site.AT: loc[1],
'origin': loc[1]
}),
probe_loc, # the distribution should tend to 50%-50%
probe_sim # mass should tend to move towards two of the four sites
# fixed naming issue in pram/sim.py line 815
]))
pram2mesa(s, 'TestSimultaneousGrammar')
