def test_progress_bar():
sc.heading('Progress bar')
n = 50
for i in range(n):
sc.progressbar(i + 1, n)
sc.timedsleep(1.0 / n, verbose=False)
return i
def run(self,
do_plot=False,
until=None,
restore_pars=True,
reset_seed=True,
verbose=None,
**kwargs):
'''
Run the simulation.
Args:
do_plot (bool): whether to plot
until (int): day to run until
restore_pars (bool): whether to make a copy of the parameters before the run and restore it after, so runs are repeatable
reset_seed (bool): whether to reset the random number stream immediately before run
verbose (float): level of detail to print, e.g. 0 = no output, 0.2 = print every 5th day, 1 = print every day
kwargs (dict): passed to sim.plot()
Returns:
results (dict): the results object (also modifies in-place)
'''
# Initialize
T = sc.tic()
if not self.initialized:
self.initialize()
else:
self.validate_pars(
) # We always want to validate the parameters before running
self.init_interventions() # And interventions
if reset_seed:
self.set_seed(
) # Ensure the random number generator is freshly initialized
if restore_pars:
orig_pars = sc.dcp(
self.pars
) # Create a copy of the parameters, to restore after the run, in case they are dynamically modified
if verbose is None:
verbose = self['verbose']
if until:
until = self.day(until)
# Main simulation loop
for t in self.tvec:
# Print progress
if verbose:
elapsed = sc.toc(output=True)
simlabel = f'"{self.label}": ' if self.label else ''
string = f' Running {simlabel}{self.datevec[t]} ({t:2.0f}/{self.pars["n_days"]}) ({elapsed:0.2f} s) '
if verbose >= 2:
sc.heading(string)
else:
if not (t % int(1.0 / verbose)):
sc.progressbar(t + 1,
self.npts,
label=string,
length=20,
newline=True)
# Do the heavy lifting -- actually run the model!
self.step()
# Check if we were asked to stop
elapsed = sc.toc(T, output=True)
if self['timelimit'] and elapsed > self['timelimit']:
sc.printv(f"Time limit ({self['timelimit']} s) exceeded", 1,
verbose)
break
elif self['stopping_func'] and self['stopping_func'](self):
sc.printv("Stopping function terminated the simulation", 1,
verbose)
break
if self.t == until: # If until is specified, just stop here
return
# End of time loop; compute cumulative results outside of the time loop
self.finalize(verbose=verbose) # Finalize the results
sc.printv(f'Run finished after {elapsed:0.2f} s.\n', 1, verbose)
if restore_pars:
self.restore_pars(orig_pars)
if do_plot: # Optionally plot
self.plot(**kwargs)
return self.results
def run(self, do_plot=False, until=None, restore_pars=True, reset_seed=True, verbose=None, **kwargs):
'''
Run the simulation.
Args:
do_plot (bool): whether to plot
until (int/str): day or date to run until
restore_pars (bool): whether to make a copy of the parameters before the run and restore it after, so runs are repeatable
reset_seed (bool): whether to reset the random number stream immediately before run
verbose (float): level of detail to print, e.g. 0 = no output, 0.2 = print every 5th day, 1 = print every day
kwargs (dict): passed to sim.plot()
Returns:
results (dict): the results object (also modifies in-place)
'''
# Initialization steps -- start the timer, initialize the sim and the seed, and check that the sim hasn't been run
T = sc.tic()
if verbose is None:
verbose = self['verbose']
if not self.initialized:
self.initialize()
self._orig_pars = sc.dcp(self.pars) # Create a copy of the parameters, to restore after the run, in case they are dynamically modified
if reset_seed:
# Reset the RNG. If the simulation is newly created, then the RNG will be reset by sim.initialize() so the use case
# for resetting the seed here is if the simulation has been partially run, and changing the seed is required
self.set_seed()
until = self.npts if until is None else self.day(until)
if until > self.npts:
raise AlreadyRunError(f'Requested to run until t={until} but the simulation end is t={self.npts}')
if self.complete:
raise AlreadyRunError('Simulation is already complete (call sim.initialize() to re-run)')
if self.t >= until: # NB. At the start, self.t is None so this check must occur after initialization
raise AlreadyRunError(f'Simulation is currently at t={self.t}, requested to run until t={until} which has already been reached')
# Main simulation loop
while self.t < until:
# Check if we were asked to stop
elapsed = sc.toc(T, output=True)
if self['timelimit'] and elapsed > self['timelimit']:
sc.printv(f"Time limit ({self['timelimit']} s) exceeded; call sim.finalize() to compute results if desired", 1, verbose)
return
elif self['stopping_func'] and self['stopping_func'](self):
sc.printv("Stopping function terminated the simulation; call sim.finalize() to compute results if desired", 1, verbose)
return
# Print progress
if verbose:
simlabel = f'"{self.label}": ' if self.label else ''
string = f' Running {simlabel}{self.datevec[self.t]} ({self.t:2.0f}/{self.pars["n_days"]}) ({elapsed:0.2f} s) '
if verbose >= 2:
sc.heading(string)
else:
if not (self.t % int(1.0/verbose)):
sc.progressbar(self.t+1, self.npts, label=string, length=20, newline=True)
# Do the heavy lifting -- actually run the model!
self.step()
# If simulation reached the end, finalize the results
if self.complete:
self.finalize(verbose=verbose, restore_pars=restore_pars)
sc.printv(f'Run finished after {elapsed:0.2f} s.\n', 1, verbose)
if do_plot: # Optionally plot
self.plot(**kwargs)
return self.results
else:
return # If not complete, return nothing
def run(self, do_plot=False, until=None, verbose=None, **kwargs):
'''
Run the simulation.
Args:
do_plot (bool): whether to plot
until (int): day to run until
verbose (int): level of detail to print
kwargs (dict): passed to self.plot()
Returns:
results: the results object (also modifies in-place)
'''
# Initialize
T = sc.tic()
if not self.initialized:
self.initialize()
else:
self.validate_pars(
) # We always want to validate the parameters before running
self.init_interventions() # And interventions
if verbose is None:
verbose = self['verbose']
if until:
until = self.day(until)
# Main simulation loop
for t in self.tvec:
# Print progress
if verbose >= 1:
elapsed = sc.toc(output=True)
simlabel = f'"{self.label}": ' if self.label else ''
string = f' Running {simlabel}{self.datevec[t]} ({t:2.0f}/{self.pars["n_days"]}) ({elapsed:0.2f} s) '
if verbose >= 2:
sc.heading(string)
elif verbose == 1:
sc.progressbar(t + 1,
self.npts,
label=string,
length=20,
newline=True)
# Do the heavy lifting -- actually run the model!
self.step()
# Check if we were asked to stop
elapsed = sc.toc(T, output=True)
if self['timelimit'] and elapsed > self['timelimit']:
sc.printv(f"Time limit ({self['timelimit']} s) exceeded", 1,
verbose)
break
elif self['stopping_func'] and self['stopping_func'](self):
sc.printv("Stopping function terminated the simulation", 1,
verbose)
break
if self.t == until: # If until is specified, just stop here
return
# End of time loop; compute cumulative results outside of the time loop
self.finalize(verbose=verbose) # Finalize the results
sc.printv(f'Run finished after {elapsed:0.2f} s.\n', 1, verbose)
if do_plot: # Optionally plot
self.plot(**kwargs)
return self.results