Problem adding LinearTrend

[AviadAvr]

Hi, and thanks for all your efforts in bringing life into Pastas!

Following the examples provided, I've ran into an issue regarding adding a LinearTrend stressmodel, using the following code:

ml = ps.Model(head)

rch = ps.RechargeModel(meteo.precip, meteo.evap, name='recharge', rfunc=ps.Gamma())
ml.add_stressmodel(rch)

#trend = ps.LinearTrend(start=head.index[0], end=head.index[-1], name='trend')
trend = ps.LinearTrend(start="2020-01-01", end="2021-01-01", name='trend')
ml.add_stressmodel(trend)

ml.solve(solver=ps.LeastSquares(), freq='h', noise=False)

Needless to say, the model works fine without adding the LinearTrend (albeit having a poor fit), but breaks whenever I do add the trend.
I'm a bit confused by the error message, as I'm not using the Hantush function, and I don't have any NoneType objects.

• Not sure if this is related, but printing trend.tmin and trend.tmax shows:
  1677-09-21 00:12:43.145224193 and 2262-04-11 23:47:16.854775807, which don't seem to make much sense, regardless of what I set the 'start' and 'end' parameters to be.

Thanks again,
Avi.

[OnnoEbbens]

This is a bug in pastas that should be solved. I will convert this into an issue. The error occurs when creating the fit report. So a quick fix to avoid this error might be to add report=False to ml.solve.

[AviadAvr]

Yep, that did the trick.
Thanks!

[OnnoEbbens]

The issue is fixed in the dev branch an will be available in a new release of pastas (probably version 1.4).

[dbrakenhoff]

Hi @AviadAvr, thanks for posting your issue. This is a mistake on my part. I'm about to submit a fix. I see Onno provided a workaround for now, so hopefully that allows you to continue for now.

You can still print the rest of the fit_report manually using:

print(ml.fit_report(warnings=False))