def simulate(years, iterations):
forecast_id = dbutil.get_forecast_id()
original_physicians = dbutil.load_workforce()
forecast = {}
for iteration in range(iterations):
# list() creates a copy of the original list
physicians = list(original_physicians)
for year in range(2011, years+2012):
if year > 2011:
r = retire.RetireEvent()
r.process(physicians)
c = census.CensusEvent(forecast_buckets)
c.process(physicians)
rows = []
for key, value in c.counts.iteritems():
# HeadcountSigma, HeadcountSigma^2, FTESigma, FTESigma^2
stats = [value, value*value, value, value*value, iteration];
rows.append([forecast_id, year] + list(key) + stats)
dbutil.write_forecast(rows)
dbutil.merge_forecast(forecast_id, iterations)
return dbutil.get_forecast(forecast_id)
def get(self):
fid = int(self.get_argument('fid', 1))
rows = dbutil.get_forecast(fid)
self.render('templates/simulation.html', rows=rows, forecast_id=fid,
years='?', iterations='?')