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Fixes to enable daily calibration frequency #4

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Fixes to enable daily calibration frequency #4

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7 changes: 6 additions & 1 deletion liscal/hydro_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -236,7 +236,12 @@ def generate_benchmark(cfg, subcatch, lis_template, param_target, outfile, start
simulated_streamflow = utils.read_tss(Qsim_tss)
simulated_streamflow[1][simulated_streamflow[1] == 1e31] = np.nan
Qsim = simulated_streamflow[1].values
index = pd.to_datetime(pd.date_range(start, end, freq='6H'), format='%d/%m/%Y %H:%M', errors='raise')
if cfg.calibration_freq == r"6-hourly":
index = pd.to_datetime(pd.date_range(start, end, freq='6H'), format='%d/%m/%Y %H:%M', errors='raise')
elif cfg.calibration_freq == r'daily':
index = pd.to_datetime(pd.date_range(start, end, freq='24H'), format='%d/%m/%Y %H:%M', errors='raise')
else:
raise Exception('Calibration freq {} not supported'.format(cfg.calibration_freq))
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@doc78 , I'm wondering if it wouldn't be cleaner to put the if statement for the calibration_freq in the config and then use the value to derive directly the step when constructing the time series:
it would give something like:
index = pd.to_datetime(pd.date_range(start, end, freq='{}H'.format(cfg.freq_hours)), format='%d/%m/%Y %H:%M', errors='raise')

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We could even put a value in minutes to be more future proof.

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I agree

Qsim = pd.DataFrame(data=Qsim, index=index)
Qsim.columns = [str(subcatch.obsid)]
Qsim.index.name = 'Timestamp'
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12 changes: 9 additions & 3 deletions liscal/objective.py
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Expand Up @@ -70,8 +70,13 @@ def read_simulated_streamflow(self, run_id, start, end):

simulated_streamflow = utils.read_tss(Qsim_tss)[1] # need to take [1] or we get 2d array
simulated_streamflow[simulated_streamflow==1e31] = np.nan # PCRaster will put 1e31 instead of NaN, set to NaN to catch errors
simulated_streamflow.index = [(datetime.strptime(start, "%d/%m/%Y %H:%M") + timedelta(hours=6*i)).strftime('%d/%m/%Y %H:%M') for i in range(len(simulated_streamflow.index))]

if self.cfg.calibration_freq == r"6-hourly":
simulated_streamflow.index = [(datetime.strptime(start, "%d/%m/%Y %H:%M") + timedelta(hours=6*i)).strftime('%d/%m/%Y %H:%M') for i in range(len(simulated_streamflow.index))]
elif self.cfg.calibration_freq == r'daily':
simulated_streamflow.index = [(datetime.strptime(start, "%d/%m/%Y %H:%M") + timedelta(hours=24*i)).strftime('%d/%m/%Y %H:%M') for i in range(len(simulated_streamflow.index))]
else:
raise Exception('Calibration freq {} not supported'.format(self.cfg.calibration_freq))

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Same here, it would give:
simulated_streamflow.index = [(datetime.strptime(start, "%d/%m/%Y %H:%M") + timedelta(hours=cfg.freq_hours*i)).strftime('%d/%m/%Y %H:%M') for i in range(len(simulated_streamflow.index))]

if simulated_streamflow.index[-1] != end:
raise ValueError('Simulated streamflow with run_id {} not consistent: end date is {} and should be {}'.format(run_id, simulated_streamflow.index[-1], end))

Expand All @@ -85,8 +90,8 @@ def resample_streamflows(self, start, end, simulated_streamflow, observed_stream
# Finally, extract equal-length arrays from it
Qobs = observed_streamflow[start:end]
Qsim = simulated_streamflow[start:end]
date_range = pd.date_range(start_pd, end_pd, freq="360min")
if cfg.calibration_freq == r"6-hourly":
date_range = pd.date_range(start_pd, end_pd, freq="360min")
# DD: Check if daily or 6-hourly observed streamflow is available
# DD: Aggregate 6-hourly simulated streamflow to daily ones
if self.subcatch.data["CAL_TYPE"].find("_24h") > -1:
Expand All @@ -101,6 +106,7 @@ def resample_streamflows(self, start, end, simulated_streamflow, observed_stream
date_range = Qobs.index

elif cfg.calibration_freq == r"daily":
date_range = pd.date_range(start_pd, end_pd, freq="24H")
# DD Untested code! DEBUG TODO
Qobs.index = date_range
Qobs = Qobs.resample('24H', label="right", closed="right").mean()
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