Error running f.robyn() about robyn

[gufengzhou]

hey, we're looking into this case now. it does not always occur and thus bit difficult to debug for us. we'll report back asap. also, please make sure the set_hyperBoundLocal is set correctly (right names using local_name, right bounds according to guide) and set_mediaVarName and set_mediaSpendName are set correctly

[LeoUbbiali]

Thanks @gufengzhou .

Further context if it can help:

• I have a 1to1 mapping between set_mediaVarName and set_mediaSpendName (aspend metric for each pressure metric)
• adstock = 'geometric'
  

[gufengzhou]

I think we found the root cause. What train/test split are you using/ what value do you put in set_modTrainSize? One extreme example, you have 2 years data and one media channel didnt have any spend until 2 recent months. When you set set_modTrainSize = 0.8, that media channel will only contain 0 in the training set and that causes problem in the transformation. What you can already do is set appropriate training split by looking at the plot f.plotTrainSize(T), the higher the bhatta coef the better. Basically you should avoid any channel only containing 0 in the train set. I'll push a fix to warn this condition

[LeoUbbiali]

Yep. That's likely to be the issue. I have channel that were switched on only recently.
I'll play around with f.plotTrainSize(T) to find the best bhatta coef and comeback to you

Current train-test split
set_modTrainSize <- 0.74

[LeoUbbiali]

I got this output with `f.plotTrainSize(T)'

I have channels with data only for the last couple of months so I'll work backwords by trying a model with data for most of the weeks (rows)

[LeoUbbiali]

Issue resolved by aggregating/remove channels containing 0 in the training set.
Thank you very much

[gufengzhou]

FYI, I've pushed an update to deal with/better warn about situation where some media has many 0. Please use the new version. thanks again for the great use case.

[LeoUbbiali]

thanks. Updated and run successfully locally 🙌