def evening_callback(self):
""" Called at 6 pm """
self.state['attractors'] = destinations(
status=self.state['status'],
day_fraction=0.75,
home_locations=self.state['home'],
work_locations=self.state['work'])
def simulate(params, plt=None, plot_hourly=None, xlabel=None):
if plot_hourly is None:
plot_hourly = params['geometry']['n'] < 50000 # Hack, remove
# Initialize a city's geography and its denizens
num, num_initially_infected = int(params['geometry']['n']), int(
params['geometry']['i'])
num_times_of_day = int(params['motion']['t'])
precision = int(params['geometry']['p'])
home, work = home_and_work_locations(geometry_params=params['geometry'],
num=num)
positions = nudge(home, w=0.05 * params['motion']['w'])
status = np.random.permutation([INFECTED] * num_initially_infected +
[VULNERABLE] *
(num - num_initially_infected))
day_fraction = 1.0 / num_times_of_day
# Population drifts to work and back, incurring viral load based on proximity to others who are infected
day = 0
while any(s in [INFECTED, POSITIVE, SYMPTOMATIC] for s in status):
day = day + 1
for step_no, time_of_day in enumerate(times_of_day(num_times_of_day)):
stationary = [s in [DECEASED, POSITIVE] for s in status]
attractors = destinations(status, time_of_day, home, work)
positions = evolve_positions(positions=positions,
motion_params=params['motion'],
attractors=attractors,
day_fraction=day_fraction,
stationary=stationary)
exposed = newly_exposed(positions=positions,
status=status,
precision=precision)
status = contact_progression(status=status,
health_params=params['health'],
exposed=exposed)
status = individual_progression(status,
health_params=params['health'],
day_fraction=day_fraction)
if plt and (plot_hourly or step_no % 12 == 0):
plt.clf()
plot_points(plt=plt,
positions=positions,
status=status,
title="Day " + str(day) + ':' +
str(time_of_day * num_times_of_day))
b = params['geometry']['b']
plt.axis([-b, b, -b, b])
if xlabel:
plt.xlabel(xlabel)
plt.show(block=False)
plt.pause(0.01)
pprint(
Counter([list(STATE_DESCRIPTIONS.values())[s]
for s in status]))
def simulate(params, plt=None, hourly=None, xlabel=None, callback=plot_callback, home=None, work=None, positions=None, stopping_i=None, stopping_t=None):
""" OU Pandemic simulation
:param params: dict of dict as per pandemic.conventions
:param plt: Handle to matplotlib plot
:param hourly: Bool Set False to speed up, True to see commuting
:param xlabel: str Label for plot
:param callback: Any function taking home, work, day, params, positions, status (e.g. for plotting, saving etc)
:return: None Use the callback
"""
if stopping_i is None:
import math
stopping_i = int(math.ceil(0.7 * params['geometry']['i']))
if hourly is None:
hourly = params['geometry']['n'] < 50000 # Hack, remove
if stopping_t is None:
stopping_t = 150
# Initialize a city's geography and its denizens
num, num_initially_infected = int(params['geometry']['n']),int(params['geometry']['i'])
num_times_of_day = int(params['motion']['t'])
precision = int(params['geometry']['p'])
if home is None or work is None:
home, work = home_and_work_locations(geometry_params=params['geometry'],num=num)
if positions is None:
positions = nudge(home,w=0.05*params['motion']['w'])
status = np.random.permutation([INFECTED]*num_initially_infected +[VULNERABLE]*(num-num_initially_infected))
time_step = 1.0/num_times_of_day
day = 0
killed = False
while sum( s in [ INFECTED ] for s in status )>=stopping_i and day<stopping_t and not killed:
day = day+1
for step_no, day_fraction in enumerate(times_of_day(num_times_of_day)):
stationary = [ s in [DECEASED, POSITIVE] for s in status ]
attractors = destinations(status, day_fraction, home, work)
positions = evolve_positions(positions=positions, motion_params=params['motion'], attractors=attractors,
time_step=time_step , stationary=stationary )
exposed = newly_exposed(positions=positions, status=status, precision=precision)
status = contact_progression(status=status, health_params=params['health'], exposed=exposed)
status = individual_progression(status, health_params=params['health'], day_fraction=time_step )
if callback:
signal = callback(day=day, day_fraction=day_fraction, home=home, work=work, positions=positions, status=status, params=params, step_no=step_no, hourly=hourly, plt=plt, xlabel=xlabel)
if signal is not None:
if 'kill' in signal:
killed = True
if 'lockdown' in signal:
work = [ h for h in home ]
if 'params' in signal:
params.update(signal['params'])
pprint(Counter([list(STATE_DESCRIPTIONS.values())[s] for s in status]))
def _ensure_state(self):
""" Ensure """
if self.state['home'] is None or self.state['work'] is None:
self.state['home'], self.state['work'] = home_and_work_locations(
geometry_params=self.params['geometry'],
num=self.params['geometry']['n'])
if self.state['positions'] is None:
self.state['positions'] = nudge(self.state['home'],
w=0.05 *
self.params['motion']['w'])
if self.state['attractors'] is None:
self.state['attractors'] = destinations(
status=self.state['status'],
day_fraction=0.75,
home_locations=self.state['home'],
work_locations=self.state['work'])
def simulate(params,
plt=None,
plot_hourly=None,
xlabel=None,
callback=plot_callback):
""" OU Pandemic simulation
:param params: dict of dict as per pandemic.conventions
:param plt: Handle to matplotlib plot
:param plot_hourly: Bool Set False to speed up, True to see commuting
:param xlabel: str Label for plot
:param callback: Any function taking home, work, day, params, positions, status (e.g. for plotting, saving etc)
:return: None Use the callback
"""
if plot_hourly is None:
plot_hourly = params['geometry']['n'] < 50000 # Hack, remove
# Initialize a city's geography and its denizens
num, num_initially_infected = int(params['geometry']['n']), int(
params['geometry']['i'])
num_times_of_day = int(params['motion']['t'])
precision = int(params['geometry']['p'])
home, work = home_and_work_locations(geometry_params=params['geometry'],
num=num)
positions = nudge(home, w=0.05 * params['motion']['w'])
status = np.random.permutation([INFECTED] * num_initially_infected +
[VULNERABLE] *
(num - num_initially_infected))
time_step = 1.0 / num_times_of_day
# Population drifts to work and back, incurring viral load based on proximity to others who are infected
day = 0
while any(s in [INFECTED] for s in status):
day = day + 1
for step_no, day_fraction in enumerate(times_of_day(num_times_of_day)):
stationary = [s in [DECEASED, POSITIVE] for s in status]
attractors = destinations(status, day_fraction, home, work)
positions = evolve_positions(positions=positions,
motion_params=params['motion'],
attractors=attractors,
time_step=time_step,
stationary=stationary)
exposed = newly_exposed(positions=positions,
status=status,
precision=precision)
status = contact_progression(status=status,
health_params=params['health'],
exposed=exposed)
status = individual_progression(status,
health_params=params['health'],
day_fraction=time_step)
if callback:
callback(day=day,
day_fraction=day_fraction,
home=home,
work=work,
positions=positions,
status=status,
params=params,
step_no=step_no,
plot_hourly=plot_hourly,
plt=plt)
pprint(Counter([list(STATE_DESCRIPTIONS.values())[s] for s in status]))
