def parse_parameters(sim_pars, epi_pars, int_pars, n_days, location, verbose,
errs, die):
''' Sanitize web parameters into actual simulation ones '''
orig_pars = cv.make_pars()
defaults = get_defaults(merge=True)
web_pars = {}
web_pars['verbose'] = verbose # Control verbosity here
for key, entry in {**sim_pars, **epi_pars}.items():
print(key, entry)
best = defaults[key]['best']
minval = defaults[key]['min']
maxval = defaults[key]['max']
try:
web_pars[key] = np.clip(float(entry['best']), minval, maxval)
except Exception as E:
user_key = entry['name']
user_val = entry['best']
err = f'Could not convert parameter "{user_key}" from value "{user_val}"; using default value instead.'
errs.append(log_err(err, E))
web_pars[key] = best
if die: raise
if key in sim_pars:
sim_pars[key]['best'] = web_pars[key]
else:
epi_pars[key]['best'] = web_pars[key]
# Convert durations
web_pars['dur'] = sc.dcp(
orig_pars['dur']) # This is complicated, so just copy it
web_pars['dur']['exp2inf']['par1'] = web_pars.pop('web_exp2inf')
web_pars['dur']['inf2sym']['par1'] = web_pars.pop('web_inf2sym')
web_pars['dur']['crit2die']['par1'] = web_pars.pop('web_timetodie')
web_dur = web_pars.pop('web_dur')
for key in ['asym2rec', 'mild2rec', 'sev2rec', 'crit2rec']:
web_pars['dur'][key]['par1'] = web_dur
# Add n_days
web_pars['n_days'] = n_days
# Add demographic
web_pars['location'] = location
# Add the intervention
web_pars['interventions'] = parse_interventions(int_pars)
# Handle CFR -- ignore symptoms and set to 1
if web_pars['rand_seed'] == 0:
web_pars['rand_seed'] = None
web_pars['timelimit'] = max_time # Set the time limit
web_pars['pop_size'] = int(web_pars['pop_size']) # Set data type
return web_pars
def set_sim_pars(self, params_dict=None):
"""
Overrides all of the default sim parameters
with the ones in the dictionary
Args:
params_dict: keys are param names, values are expected values to use
Returns:
None, sets self.simulation_params
"""
if not self.sim_pars:
self.sim_pars = cv.make_pars(set_prognoses=True, prog_by_age=True)
if params_dict:
self.sim_pars.update(params_dict)
def test_parameters():
sc.heading('Model parameters')
pars = cv.make_pars()
sc.pp(pars)
return pars
def run_sim(sim_pars=None, epi_pars=None, intervention_pars=None, datafile=None, show_animation=False, n_days=90, verbose=True):
''' Create, run, and plot everything '''
err = ''
try:
# Fix up things that JavaScript mangles
orig_pars = cv.make_pars(set_prognoses=True, prog_by_age=False, use_layers=False)
defaults = get_defaults(merge=True)
web_pars = {}
web_pars['verbose'] = verbose # Control verbosity here
for key,entry in {**sim_pars, **epi_pars}.items():
print(key, entry)
best = defaults[key]['best']
minval = defaults[key]['min']
maxval = defaults[key]['max']
try:
web_pars[key] = np.clip(float(entry['best']), minval, maxval)
except Exception:
user_key = entry['name']
user_val = entry['best']
err1 = f'Could not convert parameter "{user_key}", value "{user_val}"; using default value instead\n'
print(err1)
err += err1
web_pars[key] = best
if die: raise
if key in sim_pars: sim_pars[key]['best'] = web_pars[key]
else: epi_pars[key]['best'] = web_pars[key]
# Convert durations
web_pars['dur'] = sc.dcp(orig_pars['dur']) # This is complicated, so just copy it
web_pars['dur']['exp2inf']['par1'] = web_pars.pop('web_exp2inf')
web_pars['dur']['inf2sym']['par1'] = web_pars.pop('web_inf2sym')
web_pars['dur']['crit2die']['par1'] = web_pars.pop('web_timetodie')
web_dur = web_pars.pop('web_dur')
for key in ['asym2rec', 'mild2rec', 'sev2rec', 'crit2rec']:
web_pars['dur'][key]['par1'] = web_dur
# Add n_days
web_pars['n_days'] = n_days
# Add the intervention
web_pars['interventions'] = []
switcher = {
'social_distance': map_social_distance,
'school_closures': map_school_closures,
'symptomatic_testing': map_symptomatic_testing,
'contact_tracing': map_contact_tracing
}
if intervention_pars is not None:
for key,scenario in intervention_pars.items():
func = switcher.get(key)
func(scenario, web_pars)
# Handle CFR -- ignore symptoms and set to 1
web_pars['prognoses'] = sc.dcp(orig_pars['prognoses'])
web_pars['rel_symp_prob'] = 1e4 # Arbitrarily large
web_pars['rel_severe_prob'] = 1e4
web_pars['rel_crit_prob'] = 1e4
web_pars['prognoses']['death_probs'][0] = web_pars.pop('web_cfr')
if web_pars['rand_seed'] == 0:
web_pars['rand_seed'] = None
web_pars['timelimit'] = max_time # Set the time limit
web_pars['pop_size'] = int(web_pars['pop_size']) # Set data type
web_pars['contacts'] = int(web_pars['contacts']) # Set data type
except Exception as E:
err2 = f'Parameter conversion failed! {str(E)}\n'
print(err2)
err += err2
if die: raise
# Create the sim and update the parameters
try:
sim = cv.Sim(pars=web_pars,datafile=datafile)
except Exception as E:
err3 = f'Sim creation failed! {str(E)}\n'
print(err3)
err += err3
if die: raise
if verbose:
print('Input parameters:')
print(web_pars)
# Core algorithm
try:
sim.run(do_plot=False)
except TimeoutError:
day = sim.t
err4 = f"The simulation stopped on day {day} because run time limit ({sim['timelimit']} seconds) was exceeded. Please reduce the population size and/or number of days simulated."
err += err4
if die: raise
except Exception as E:
err4 = f'Sim run failed! {str(E)}\n'
print(err4)
err += err4
if die: raise
# Core plotting
graphs = []
try:
to_plot = sc.dcp(cv.default_sim_plots)
for p,title,keylabels in to_plot.enumitems():
fig = go.Figure()
for key in keylabels:
label = sim.results[key].name
this_color = sim.results[key].color
y = sim.results[key][:]
fig.add_trace(go.Scatter(x=sim.results['t'][:], y=y, mode='lines', name=label, line_color=this_color))
if sim.data is not None and key in sim.data:
data_t = (sim.data.index-sim['start_day'])/np.timedelta64(1,'D')
print(sim.data.index, sim['start_day'], np.timedelta64(1,'D'), data_t)
ydata = sim.data[key]
fig.add_trace(go.Scatter(x=data_t, y=ydata, mode='markers', name=label + ' (data)', line_color=this_color))
if sim['interventions']:
interv_day = sim['interventions'][0].days[0]
if interv_day > 0 and interv_day < sim['n_days']:
fig.add_shape(dict(type="line", xref="x", yref="paper", x0=interv_day, x1=interv_day, y0=0, y1=1, name='Intervention', line=dict(width=0.5, dash='dash')))
fig.update_layout(annotations=[dict(x=interv_day, y=1.07, xref="x", yref="paper", text="Intervention start", showarrow=False)])
fig.update_layout(title={'text':title}, xaxis_title='Day', yaxis_title='Count', autosize=True)
output = {'json': fig.to_json(), 'id': str(sc.uuid())}
d = json.loads(output['json'])
d['config'] = {'responsive': True}
output['json'] = json.dumps(d)
graphs.append(output)
graphs.append(plot_people(sim))
if show_animation:
graphs.append(animate_people(sim))
except Exception as E:
err5 = f'Plotting failed! {str(E)}\n'
print(err5)
err += err5
if die: raise
# Create and send output files (base64 encoded content)
files = {}
summary = {}
try:
datestamp = sc.getdate(dateformat='%Y-%b-%d_%H.%M.%S')
ss = sim.to_excel()
files['xlsx'] = {
'filename': f'covasim_results_{datestamp}.xlsx',
'content': 'data:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet;base64,' + base64.b64encode(ss.blob).decode("utf-8"),
}
json_string = sim.to_json(verbose=False)
files['json'] = {
'filename': f'covasim_results_{datestamp}.json',
'content': 'data:application/text;base64,' + base64.b64encode(json_string.encode()).decode("utf-8"),
}
# Summary output
summary = {
'days': sim.npts-1,
'cases': round(sim.results['cum_infections'][-1]),
'deaths': round(sim.results['cum_deaths'][-1]),
}
except Exception as E:
err6 = f'File saving failed! {str(E)}\n'
print(err6)
err += err6
if die: raise
output = {}
output['err'] = err
output['sim_pars'] = sim_pars
output['epi_pars'] = epi_pars
output['graphs'] = graphs
output['files'] = files
output['summary'] = summary
return output
import covasim as cv
import matplotlib.pyplot as plt
import numpy as np
dur = cv.make_pars()['dur']
N = 50000
fig = plt.figure(figsize=(16, 16))
for idx, (k, d) in enumerate(dur.items()):
ax = plt.subplot(3, 3, idx + 1)
vals = [cv.utils.sample(**d) for _ in range(N)]
ax.hist(vals,
density=True,
bins=range(int(np.ceil(max(vals) + 1))),
align='left')
mu = np.mean(vals)
ax.plot([mu] * 2, ax.get_ylim(), 'r')
ax.set_title(f'{k}: {d["dist"]}({d["par1"]},{d["par2"]})')
plt.suptitle('Default distributions in Covasim', fontsize=20)
plt.show()
def run_sim(sim_pars=None,
epi_pars=None,
int_pars=None,
datafile=None,
show_animation=False,
n_days=90,
verbose=True,
die=die):
''' Create, run, and plot everything '''
errs = []
try:
# Fix up things that JavaScript mangles
orig_pars = cv.make_pars(set_prognoses=True,
prog_by_age=False,
use_layers=False)
defaults = get_defaults(merge=True)
web_pars = {}
web_pars['verbose'] = verbose # Control verbosity here
for key, entry in {**sim_pars, **epi_pars}.items():
print(key, entry)
best = defaults[key]['best']
minval = defaults[key]['min']
maxval = defaults[key]['max']
try:
web_pars[key] = np.clip(float(entry['best']), minval, maxval)
except Exception as E:
user_key = entry['name']
user_val = entry['best']
err = f'Could not convert parameter "{user_key}" from value "{user_val}"; using default value instead.'
errs.append(log_err(err, E))
web_pars[key] = best
if die: raise
if key in sim_pars:
sim_pars[key]['best'] = web_pars[key]
else:
epi_pars[key]['best'] = web_pars[key]
# Convert durations
web_pars['dur'] = sc.dcp(
orig_pars['dur']) # This is complicated, so just copy it
web_pars['dur']['exp2inf']['par1'] = web_pars.pop('web_exp2inf')
web_pars['dur']['inf2sym']['par1'] = web_pars.pop('web_inf2sym')
web_pars['dur']['crit2die']['par1'] = web_pars.pop('web_timetodie')
web_dur = web_pars.pop('web_dur')
for key in ['asym2rec', 'mild2rec', 'sev2rec', 'crit2rec']:
web_pars['dur'][key]['par1'] = web_dur
# Add n_days
web_pars['n_days'] = n_days
# Add the intervention
web_pars['interventions'] = parse_interventions(int_pars)
# Handle CFR -- ignore symptoms and set to 1
web_pars['prognoses'] = sc.dcp(orig_pars['prognoses'])
web_pars['rel_symp_prob'] = 1e4 # Arbitrarily large
web_pars['rel_severe_prob'] = 1e4
web_pars['rel_crit_prob'] = 1e4
web_pars['prognoses']['death_probs'][0] = web_pars.pop('web_cfr')
if web_pars['rand_seed'] == 0:
web_pars['rand_seed'] = None
web_pars['timelimit'] = max_time # Set the time limit
web_pars['pop_size'] = int(web_pars['pop_size']) # Set data type
web_pars['contacts'] = int(web_pars['contacts']) # Set data type
except Exception as E:
errs.append(log_err('Parameter conversion failed!', E))
if die: raise
# Create the sim and update the parameters
try:
sim = cv.Sim(pars=web_pars, datafile=datafile)
except Exception as E:
errs.append(log_err('Sim creation failed!', E))
if die: raise
if verbose:
print('Input parameters:')
print(web_pars)
# Core algorithm
try:
sim.run(do_plot=False)
except TimeoutError as TE:
err = f"The simulation stopped on day {sim.t} because run time limit ({sim['timelimit']} seconds) was exceeded. Please reduce the population size and/or number of days simulated."
errs.append(log_err(err, TE))
if die: raise
except Exception as E:
errs.append(log_err('Sim run failed!', E))
if die: raise
# Core plotting
graphs = []
try:
graphs += main_plots(sim)
graphs += plot_people(sim)
if show_animation:
graphs += animate_people(sim)
except Exception as E:
errs.append(log_err('Plotting failed!', E))
if die: raise
# Create and send output files (base64 encoded content)
try:
files, summary = get_output_files(sim)
except Exception as E:
files = {}
summary = {}
errs.append(log_err('Unable to save output files!', E))
if die: raise
output = {}
output['errs'] = errs
output['sim_pars'] = sim_pars
output['epi_pars'] = epi_pars
output['int_pars'] = int_pars
output['graphs'] = graphs
output['files'] = files
output['summary'] = summary
return output
def run_sim(sim_pars=None, epi_pars=None, show_animation=False, verbose=True):
''' Create, run, and plot everything '''
err = ''
try:
# Fix up things that JavaScript mangles
orig_pars = cv.make_pars()
defaults = get_defaults(merge=True)
web_pars = {}
web_pars['verbose'] = verbose # Control verbosity here
for key, entry in {**sim_pars, **epi_pars}.items():
print(key, entry)
best = defaults[key]['best']
minval = defaults[key]['min']
maxval = defaults[key]['max']
try:
web_pars[key] = np.clip(float(entry['best']), minval, maxval)
except Exception:
user_key = entry['name']
user_val = entry['best']
err1 = f'Could not convert parameter "{user_key}", value "{user_val}"; using default value instead\n'
print(err1)
err += err1
web_pars[key] = best
if key in sim_pars: sim_pars[key]['best'] = web_pars[key]
else: epi_pars[key]['best'] = web_pars[key]
# Convert durations
web_pars['dur'] = sc.dcp(
orig_pars['dur']) # This is complicated, so just copy it
web_pars['dur']['exp2inf']['par1'] = web_pars.pop('web_exp2inf')
web_pars['dur']['inf2sym']['par1'] = web_pars.pop('web_inf2sym')
web_pars['dur']['crit2die']['par1'] = web_pars.pop('web_timetodie')
web_dur = web_pars.pop('web_dur')
for key in ['asym2rec', 'mild2rec', 'sev2rec', 'crit2rec']:
web_pars['dur'][key]['par1'] = web_dur
# Add the intervention
web_pars['interventions'] = []
if web_pars['web_int_day'] is not None:
web_pars['interventions'] = cv.change_beta(
days=web_pars.pop('web_int_day'),
changes=(1 - web_pars.pop('web_int_eff')))
# Handle CFR -- ignore symptoms and set to 1
prog_pars = cv.get_default_prognoses(by_age=False)
web_pars['rel_symp_prob'] = 1.0 / prog_pars.symp_prob
web_pars['rel_severe_prob'] = 1.0 / prog_pars.severe_prob
web_pars['rel_crit_prob'] = 1.0 / prog_pars.crit_prob
web_pars['rel_death_prob'] = web_pars.pop(
'web_cfr') / prog_pars.death_prob
except Exception as E:
err2 = f'Parameter conversion failed! {str(E)}\n'
print(err2)
err += err2
# Create the sim and update the parameters
try:
sim = cv.Sim()
sim['prog_by_age'] = False # So the user can override this value
sim['timelimit'] = max_time # Set the time limit
if web_pars['seed'] == 0:
web_pars['seed'] = None # Reset
sim.update_pars(web_pars)
except Exception as E:
err3 = f'Sim creation failed! {str(E)}\n'
print(err3)
err += err3
if verbose:
print('Input parameters:')
print(web_pars)
# Core algorithm
try:
sim.run(do_plot=False)
except Exception as E:
err4 = f'Sim run failed! {str(E)}\n'
print(err4)
err += err4
if sim.stopped:
try: # Assume it stopped because of the time, but if not, don't worry
day = sim.stopped['t']
time_exceeded = f"The simulation stopped on day {day} because run time limit ({sim['timelimit']} seconds) was exceeded. Please reduce the population size and/or number of days simulated."
err += time_exceeded
except:
pass
# Core plotting
graphs = []
try:
to_plot = sc.dcp(cv.default_sim_plots)
for p, title, keylabels in to_plot.enumitems():
fig = go.Figure()
for key in keylabels:
label = sim.results[key].name
this_color = sim.results[key].color
y = sim.results[key][:]
fig.add_trace(
go.Scatter(x=sim.results['t'][:],
y=y,
mode='lines',
name=label,
line_color=this_color))
if sim['interventions']:
interv_day = sim['interventions'][0].days[0]
if interv_day > 0 and interv_day < sim['n_days']:
fig.add_shape(
dict(type="line",
xref="x",
yref="paper",
x0=interv_day,
x1=interv_day,
y0=0,
y1=1,
name='Intervention',
line=dict(width=0.5, dash='dash')))
fig.update_layout(annotations=[
dict(x=interv_day,
y=1.07,
xref="x",
yref="paper",
text="Intervention start",
showarrow=False)
])
fig.update_layout(title={'text': title},
xaxis_title='Day',
yaxis_title='Count',
autosize=True)
output = {'json': fig.to_json(), 'id': str(sc.uuid())}
d = json.loads(output['json'])
d['config'] = {'responsive': True}
output['json'] = json.dumps(d)
graphs.append(output)
graphs.append(plot_people(sim))
if show_animation:
graphs.append(animate_people(sim))
except Exception as E:
err5 = f'Plotting failed! {str(E)}\n'
print(err5)
err += err5
# Create and send output files (base64 encoded content)
files = {}
summary = {}
try:
datestamp = sc.getdate(dateformat='%Y-%b-%d_%H.%M.%S')
ss = sim.to_xlsx()
files['xlsx'] = {
'filename':
f'COVASim_results_{datestamp}.xlsx',
'content':
'data:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet;base64,'
+ base64.b64encode(ss.blob).decode("utf-8"),
}
json_string = sim.to_json()
files['json'] = {
'filename':
f'COVASim_results_{datestamp}.txt',
'content':
'data:application/text;base64,' +
base64.b64encode(json_string.encode()).decode("utf-8"),
}
# Summary output
summary = {
'days': sim.npts - 1,
'cases': round(sim.results['cum_infections'][-1]),
'deaths': round(sim.results['cum_deaths'][-1]),
}
except Exception as E:
err6 = f'File saving failed! {str(E)}\n'
print(err6)
err += err6
output = {}
output['err'] = err
output['sim_pars'] = sim_pars
output['epi_pars'] = epi_pars
output['graphs'] = graphs
output['files'] = files
output['summary'] = summary
return output