is mean_skill working correctly with more than one model? #161
Replies: 5 comments 6 replies
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Furthermore, when I have a single comparer and look at a single observation (either comparer of run 00 or run 23) I get ~3000 points but when I do the same for the comparer with both runs, it all goes crazy and it creates ~114,000 points. |
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@jsmariegaard
If I remove the |
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I will have a look at your notebook today. And if I am getting you right, this is only a problem in the https://github.com/DHI/fmskill/tree/max_gap_interp branch and associated #148 ? |
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The issue seems to be related to |
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@ecomodeller Can we tag this as a bug?? |
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Hi all, I got a question because I am not sure I am getting sensible results when using
mean_skill
with more than one model.To summarize:
I have two runs (of slighlty different lengths) , Run 000 with ~203,000 points and Run 023 with ~197,000 points
if I have a single comparer object (
cc_aux
) and get themean_skill
I get what I am supposed to get (I checked against the dataframe with all my PointObservations)but If I add the
comparer object
of run 23 to thecomparer
of run 00 (withcc.add_comparer(cc_aux)
) and then get themean_skill
my values change completelySomehow the number of paired model-observations increases to ~8 million points
@ecomodeller : Is this a bug or am I not understanding how the
mean_skill
works?Beta Was this translation helpful? Give feedback.
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