keesvanginkel / urban-setp Goto Github PK

Make sure that in all variants of calling the tipping point identification algorithms, we use the same window length (=4 years)

Check if the difference between the thresholds in actions for economicus and setniment are large enough. Maybe better a factor 10 than a factor 2.

I have done this, but it makes the differences between the mayors less distinct.

See specification in the SI of the paper.

Remove the flood proofing from the model for Mayor economicus. Do a seperate run with the old mayor.

D:\Python\Urban-SETP\tipping.py:210: RuntimeWarning: divide by zero encountered in double_scalars perc_diff = 100 * abs(difference / mean_state_before)