def __init__(self, *args, **kwargs):
#default data
self.Config = Configuration()
self.frame = 0
# default pop init
self.population_init()
self.pop_tracker = Population_trackers()
#destinations vector init
self.destinations = initialize_destination_matrix(
self.Config.size_pop, 1)
self.figure, self.spec, self.ax1, self.ax2 = build_fig(self.Config)
def run(self):
'''run simulation'''
if self.Config.visualise:
self.fig, self.spec, self.ax1, self.ax2, self.tight_bbox = build_fig(
self.Config)
i = 0
while i < self.Config.simulation_steps:
try:
self.tstep()
except KeyboardInterrupt:
print('\nCTRL-C caught, exiting')
sys.exit(1)
#check whether to end if no infectious persons remain.
#check if self.frame is above some threshold to prevent early breaking when simulation
#starts initially with no infections.
if self.Config.endif_no_infections and self.frame >= 300:
if len(self.population[(self.population[:, 6] == 1) |
(self.population[:, 6] == 4)]) == 0:
i = self.Config.simulation_steps
else:
i += 1
if self.Config.plot_last_tstep:
self.fig_sir, self.spec_sir, self.ax1_sir = build_fig_SIRonly(
self.Config)
draw_SIRonly(self.Config, self.population, self.pop_tracker,
self.frame, self.fig_sir, self.spec_sir, self.ax1_sir)
if self.Config.save_data:
save_data(self.population, self.pop_tracker)
#report outcomes
if self.Config.verbose:
print('\n-----stopping-----\n')
print('total timesteps taken: %i' % self.frame)
print('total dead: %i' %
len(self.population[self.population[:, 6] == 3]))
print('total recovered: %i' %
len(self.population[self.population[:, 6] == 2]))
print('total infected: %i' %
len(self.population[self.population[:, 6] == 1]))
print('total infectious: %i' %
len(self.population[(self.population[:, 6] == 1) |
(self.population[:, 6] == 4)]))
print('total unaffected: %i' %
len(self.population[self.population[:, 6] == 0]))
print('mean distance travelled: %f' %
np.mean(self.pop_tracker.distance_travelled))
def __init__(self, *args, **kwargs):
# load default config data
self.Config = Configuration()
self.frame = 0
# initialize default population
self.population_init()
self.pop_tracker = Population_trackers()
# initalise destinations vector
self.destinations = initialize_destination_matrix(self.Config.pop_size, 1)
self.fig, self.spec, self.ax1, self.ax2 = build_fig(self.Config)
def tstep(self):
'''
takes a time step in the simulation
'''
if self.frame == 0 and self.Config.visualise:
#initialize figure
self.fig, self.spec, self.ax1, self.ax2 , self.ax3 = build_fig(self.Config)
#check destinations if active
#define motion vectors if destinations active and not everybody is at destination
active_dests = len(self.population[self.population[:,11] != 0]) # look op this only once
if active_dests > 0 and len(self.population[self.population[:,12] == 0]) > 0:
self.population = set_destination(self.population, self.destinations)
self.population = check_at_destination(self.population, self.destinations,
wander_factor = self.Config.wander_factor_dest,
speed = self.Config.speed)
if active_dests > 0 and len(self.population[self.population[:,12] == 1]) > 0:
#keep them at destination 到达dest 以一定范围wander
self.population = keep_at_destination(self.population, self.destinations,
self.Config.wander_factor)
#out of bounds 要把wander的方向朝向修改 防止wander超出边界
#define bounds arrays, excluding those who are marked as having a custom destination
if len(self.population[:,11] == 0) > 0:
_xbounds = np.array([[self.Config.xbounds[0] + 0.02, self.Config.xbounds[1] - 0.02]] * len(self.population[self.population[:,11] == 0]))
_ybounds = np.array([[self.Config.ybounds[0] + 0.02, self.Config.ybounds[1] - 0.02]] * len(self.population[self.population[:,11] == 0]))
self.population[self.population[:,11] == 0] = out_of_bounds(self.population[self.population[:,11] == 0],
_xbounds, _ybounds)
#set randoms 最大感染数 只要到达过最大感染数就持续lockdown
if self.Config.lockdown:
if len(self.pop_tracker.infectious) == 0:
mx = 0
else:
mx = np.max(self.pop_tracker.infectious)
if len(self.population[self.population[:,6] == 1]) >= len(self.population) * self.Config.lockdown_percentage or\
mx >= (len(self.population) * self.Config.lockdown_percentage):
#reduce speed of all members of society 使最大速度为0.001
self.population[:,5] = np.clip(self.population[:,5], a_min = None, a_max = 0.001)
#set speeds of complying people to 0 遵循lockdown的速度 为0
self.population[:,5][self.Config.lockdown_vector == 0] = 0
else:
#update randoms
self.population = update_randoms(self.population, self.Config.pop_size, self.Config.speed)
else:
#update randoms
self.population = update_randoms(self.population, self.Config.pop_size, self.Config.speed)
#for dead ones: set speed and heading to 0
self.population[:,3:5][self.population[:,6] == 3] = 0
#update positions
self.population = update_positions(self.population)
#find new infections
self.population, self.destinations = infect(self.population, self.Config, self.frame,
send_to_location = self.Config.self_isolate,
location_bounds = self.Config.isolation_bounds,
destinations = self.destinations,
location_no = 1,
location_odds = self.Config.self_isolate_proportion)
#recover and die
self.population = recover_or_die(self.population, self.frame, self.Config)
#send cured back to population if self isolation active
#perhaps put in recover or die class
#send cured back to population
self.population[:,11][self.population[:,6] == 2] = 0
#compute gdp
peoplegdp, businessgdp, governgdp, totalgdp = economical_change(self.population, self.Config)
#update population statistics
self.pop_tracker.update_counts(self.population, peoplegdp, businessgdp, governgdp, totalgdp)
#visualise
if self.Config.visualise:
draw_tstep(self.Config, self.population, self.pop_tracker, self.frame,
self.fig, self.spec, self.ax1, self.ax2,self.ax3)
#report stuff to console
sys.stdout.write('\r')
sys.stdout.write('%i: healthy: %i, infected: %i, immune: %i, in treatment: %i, \
dead: %i, of total: %i' %(self.frame, self.pop_tracker.susceptible[-1], self.pop_tracker.infectious[-1],
self.pop_tracker.recovered[-1], len(self.population[self.population[:,10] == 1]),
self.pop_tracker.fatalities[-1], self.Config.pop_size))
#save popdata if required
if self.Config.save_pop and (self.frame % self.Config.save_pop_freq) == 0:
save_population(self.population, self.frame, self.Config.save_pop_folder)
#run callback
self.callback()
#update frame
self.frame += 1
def tstep(self):
if self.frame == 0:
self.fig, self.spec, self.ax1, self.ax2 = build_fig(self.Config)
xbounds = np.array(
[[self.Config.xbounds[0] + 0.02, self.Config.xbounds[1] - 0.02]] *
self.Config.pop_size)
ybounds = np.array(
[[self.Config.ybounds[0] + 0.02, self.Config.ybounds[1] - 0.02]] *
self.Config.pop_size)
self.population = out_of_bounds(self.population, xbounds, ybounds)
if self.Config.is_lockdown and self.Config.lockdown == False:
if len(self.population[(self.population[:, 6] == 1)]
) >= self.Config.lockdown_percentage * self.Config.pop_size:
self.Config.lockdown = True
print("\nLockdown Started")
left_range = [
self.Config.xbounds[0] + 0.02, self.Config.xbounds[1] / 3 - 0.02
]
mid_range = [
self.Config.xbounds[1] / 3 + 0.02,
2 * self.Config.xbounds[1] / 3 - 0.02
]
right_range = [
2 * self.Config.xbounds[1] / 3 + 0.02,
self.Config.xbounds[1] - 0.02
]
bottom_range = [
self.Config.ybounds[0] + 0.02, self.Config.ybounds[1] / 2 - 0.02
]
top_range = [
self.Config.ybounds[1] / 2 + 0.02, self.Config.ybounds[1] - 0.02
]
left_condition = (self.population[:, 1] <= self.Config.xbounds[1] / 3)
mid_condition = (
self.population[:, 1] > self.Config.xbounds[1] / 3) & (
self.population[:, 1] <= 2 * self.Config.xbounds[1] / 3)
right_condition = (self.population[:, 1] >
2 * self.Config.xbounds[1] / 3)
bottom_condition = (self.population[:, 2] <=
self.Config.ybounds[1] / 2)
top_condition = (self.population[:, 2] > self.Config.ybounds[1] / 2)
if self.Config.lockdown:
x_left_bottom = np.array(
[left_range] *
len(self.population[left_condition & bottom_condition]))
y_left_bottom = np.array(
[bottom_range] *
len(self.population[left_condition & bottom_condition]))
self.population[left_condition & bottom_condition] = out_of_bounds(
self.population[left_condition & bottom_condition],
x_left_bottom, y_left_bottom)
x_left_top = np.array(
[left_range] *
len(self.population[left_condition & top_condition]))
y_left_top = np.array(
[top_range] *
len(self.population[left_condition & top_condition]))
self.population[left_condition & top_condition] = out_of_bounds(
self.population[left_condition & top_condition], x_left_top,
y_left_top)
x_mid_bottom = np.array(
[mid_range] *
len(self.population[mid_condition & bottom_condition]))
y_mid_bottom = np.array(
[bottom_range] *
len(self.population[mid_condition & bottom_condition]))
self.population[mid_condition & bottom_condition] = out_of_bounds(
self.population[mid_condition & bottom_condition],
x_mid_bottom, y_mid_bottom)
x_mid_top = np.array(
[mid_range] *
len(self.population[mid_condition & top_condition]))
y_mid_top = np.array(
[top_range] *
len(self.population[mid_condition & top_condition]))
self.population[mid_condition & top_condition] = out_of_bounds(
self.population[mid_condition & top_condition], x_mid_top,
y_mid_top)
x_right_bottom = np.array(
[right_range] *
len(self.population[right_condition & bottom_condition]))
y_right_bottom = np.array(
[bottom_range] *
len(self.population[right_condition & bottom_condition]))
self.population[right_condition
& bottom_condition] = out_of_bounds(
self.population[right_condition
& bottom_condition],
x_right_bottom, y_right_bottom)
x_right_top = np.array(
[right_range] *
len(self.population[right_condition & top_condition]))
y_right_top = np.array(
[top_range] *
len(self.population[right_condition & top_condition]))
self.population[right_condition & top_condition] = out_of_bounds(
self.population[right_condition & top_condition], x_right_top,
y_right_top)
self.population = update_randoms(self.population, self.Config.pop_size,
self.Config.speed)
self.population[:, 5][self.population[:, 6] == 3] = 0
self.population = update_positions(self.population)
self.population = infect(self.population, self.Config, self.frame)
self.population = recover_or_die(self.population, self.frame,
self.Config)
self.pop_tracker.update_counts(self.population)
draw_tstep(self.Config, self.population, self.pop_tracker, self.frame,
self.fig, self.spec, self.ax1, self.ax2)
self.peak_infections = max(
self.peak_infections,
len(self.population[self.population[:, 6] == 1]))
if self.frame == 50:
print('\ninfecting patient zero')
self.population[0][6] = 1
self.frame += 1