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visualiser.py
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visualiser.py
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'''
contains all methods for visualisation tasks
'''
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
from environment import build_hospital
from utils import check_folder
def set_style(Config):
'''sets the plot style
'''
if Config.plot_style.lower() == 'dark':
mpl.style.use('plot_styles/dark.mplstyle')
def build_fig(Config, figsize=(5,7)):
set_style(Config)
fig = plt.figure(figsize=(5,7))
spec = fig.add_gridspec(ncols=1, nrows=2, height_ratios=[5,2])
ax1 = fig.add_subplot(spec[0,0])
plt.title('infection simulation')
plt.xlim(Config.xbounds[0], Config.xbounds[1])
plt.ylim(Config.ybounds[0], Config.ybounds[1])
ax2 = fig.add_subplot(spec[1,0])
ax2.set_title('number of infected')
#ax2.set_xlim(0, simulation_steps)
ax2.set_ylim(0, Config.pop_size + 100)
#if
return fig, spec, ax1, ax2
def draw_tstep(Config, population, pop_tracker, frame,
fig, spec, ax1, ax2):
#construct plot and visualise
#set plot style
set_style(Config)
#get color palettes
palette = Config.get_palette()
spec = fig.add_gridspec(ncols=1, nrows=2, height_ratios=[5,2])
ax1.clear()
ax2.clear()
ax1.set_xlim(Config.x_plot[0], Config.x_plot[1])
ax1.set_ylim(Config.y_plot[0], Config.y_plot[1])
if Config.self_isolate and Config.isolation_bounds != None:
build_hospital(Config.isolation_bounds[0], Config.isolation_bounds[2],
Config.isolation_bounds[1], Config.isolation_bounds[3], ax1,
addcross = False)
#plot population segments
healthy = population[population[:,6] == 0][:,1:3]
ax1.scatter(healthy[:,0], healthy[:,1], color=palette[0], s = 2, label='healthy')
infected = population[population[:,6] == 1][:,1:3]
ax1.scatter(infected[:,0], infected[:,1], color=palette[1], s = 2, label='infected')
immune = population[population[:,6] == 2][:,1:3]
ax1.scatter(immune[:,0], immune[:,1], color=palette[2], s = 2, label='immune')
fatalities = population[population[:,6] == 3][:,1:3]
ax1.scatter(fatalities[:,0], fatalities[:,1], color=palette[3], s = 2, label='dead')
#add text descriptors
ax1.text(Config.x_plot[0],
Config.y_plot[1] + ((Config.y_plot[1] - Config.y_plot[0]) / 100),
'timestep: %i, total: %i, healthy: %i infected: %i immune: %i fatalities: %i' %(frame,
len(population),
len(healthy),
len(infected),
len(immune),
len(fatalities)),
fontsize=6)
ax2.set_title('number of infected')
ax2.text(0, Config.pop_size * 0.05,
'https://github.com/paulvangentcom/python-corona-simulation',
fontsize=6, alpha=0.5)
#ax2.set_xlim(0, simulation_steps)
ax2.set_ylim(0, Config.pop_size + 200)
if Config.treatment_dependent_risk:
infected_arr = np.asarray(pop_tracker.infectious)
indices = np.argwhere(infected_arr >= Config.healthcare_capacity)
ax2.plot([Config.healthcare_capacity for x in range(len(pop_tracker.infectious))],
'r:', label='healthcare capacity')
if Config.plot_mode.lower() == 'default':
ax2.plot(pop_tracker.infectious, color=palette[1])
ax2.plot(pop_tracker.fatalities, color=palette[3], label='fatalities')
elif Config.plot_mode.lower() == 'sir':
ax2.plot(pop_tracker.susceptible, color=palette[0], label='susceptible')
ax2.plot(pop_tracker.infectious, color=palette[1], label='infectious')
ax2.plot(pop_tracker.recovered, color=palette[2], label='recovered')
ax2.plot(pop_tracker.fatalities, color=palette[3], label='fatalities')
else:
raise ValueError('incorrect plot_style specified, use \'sir\' or \'default\'')
ax2.legend(loc = 'best', fontsize = 6)
plt.draw()
plt.pause(0.0001)
if Config.save_plot:
try:
plt.savefig('%s/%i.png' %(Config.plot_path, frame))
except:
check_folder(Config.plot_path)
plt.savefig('%s/%i.png' %(Config.plot_path, frame))
def plot_sir(Config, pop_tracker, size=(6,3), include_fatalities=False,
title='S-I-R plot of simulation'):
'''plots S-I-R parameters in the population tracker
Keyword arguments
-----------------
Config : class
the configuration class
pop_tracker : ndarray
the population tracker, containing
size : tuple
size at which the plot will be initialised (default: (6,3))
include_fatalities : bool
whether to plot the fatalities as well (default: False)
'''
#set plot style
set_style(Config)
#get color palettes
palette = Config.get_palette()
#plot the thing
plt.figure(figsize=size)
plt.title(title)
plt.plot(pop_tracker.susceptible, color=palette[0], label='susceptible')
plt.plot(pop_tracker.infectious, color=palette[1], label='infectious')
plt.plot(pop_tracker.recovered, color=palette[2], label='recovered')
if include_fatalities:
plt.plot(pop_tracker.fatalities, color=palette[3], label='fatalities')
#add axis labels
plt.xlabel('time in hours')
plt.ylabel('population')
#add legend
plt.legend()
#beautify
plt.tight_layout()
#initialise
plt.show()