# dates for the calibration
start = datetime.datetime(y, 1, 1)
end = datetime.datetime(y + 2, 1, 1)
ds = start, end
# use the postprocessor to get the time series
postprocessor = Postprocessor(hspfmodel, ds, comid=comid)
# get the flows and other timeseries from the two-year calibration
stimes, sflow = postprocessor.get_sim_flow(comid)
otimes, oflow = postprocessor.get_obs_flow()
ptimes, precip = postprocessor.get_precipitation(comid)
etimes, evap = postprocessor.get_evaporation(comid)
times, pet = postprocessor.get_pet(comid=comid)
# close this postprocessor
postprocessor.close()
# get the flows for the thirty-year model
i = ttimes.index(start)
if end in ttimes:
j = ttimes.index(end)
thirty = tflow[i:j]
else:
# get the NSE during the calibration period
d = datetime.datetime(y, 1, 1), datetime.datetime(y + 2 , 1, 1)
stimes, sflow = postprocessor.get_sim_flow(comid, tstep = 'daily',
dates = d)
otimes, oflow = postprocessor.get_obs_flow(tstep = 'daily',
dates = d)
NSEcalibration = (1 - sum((numpy.array(sflow)-numpy.array(oflow))**2) /
sum((numpy.array(oflow) - numpy.mean(oflow))**2))
# get the total precipitation during the calibration period
ptimes, precip = postprocessor.get_precipitation(comid, dates = d)
precipitation = sum(precip) / (d[1] - d[0]).days * 365.25
# get the validation NSE
stimes, sflow = postprocessor.get_sim_flow(comid, tstep = 'daily')
otimes, oflow = postprocessor.get_obs_flow(tstep = 'daily')
NSEvalidation = (1 - sum((numpy.array(sflow) - numpy.array(oflow))**2) /
sum((numpy.array(oflow) - numpy.mean(oflow))**2))
# percent error in runoff
error = (sum(sflow) - sum(oflow)) / sum(oflow)
