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Right now we make an error, when we add recharge from the KNMI-server to a model dataset. The recharge from the next stress period is assigned to the current stress period. See the code in read\knmi.py:
model_recharge = pd.Series(index=ds.time.data, dtype=float)
for j, ts in enumerate(model_recharge.index):
if j < (len(model_recharge) - 1):
model_recharge.loc[ts] = (
timeseries.loc[ts : model_recharge.index[j + 1]].iloc[:-1].mean()
)
else:
model_recharge.loc[ts] = timeseries.loc[ts:end].iloc[:-1].mean()
The index of the pandas Series timeseries is equal to the end of the period that the data describes. Therefore I will change this into the following code:
* Fix issue #129 and some improvements
make sure time dimension is always first
no separate code for steady-state models anymore
* Fix assignment of values
* Fix assignment of values some more
Right now we make an error, when we add recharge from the KNMI-server to a model dataset. The recharge from the next stress period is assigned to the current stress period. See the code in read\knmi.py:
The index of the pandas Series
timeseries
is equal to the end of the period that the data describes. Therefore I will change this into the following code:Keep in mind this will change model output in the next version.
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