I'm finding that when I use the MISTEvolutionTrackGrid or MISTIsochroneGrid, two of the columns in the dataframe are all NaNs. These are the dt_deep and dm_deep columns. I don't actually plan on using the data contained in these columns, but they appear to be causing problems in the model fitting. When I run the fitting example, I find that the log prior is giving NaNs for any input parameters, while the log likelihood appears to be working properly. Is this due to the fact that there are Nans in the dt_deep column? Is there a way to not consider these columns when fitting a model?
Hello,
I'm finding that when I use the MISTEvolutionTrackGrid or MISTIsochroneGrid, two of the columns in the dataframe are all NaNs. These are the dt_deep and dm_deep columns. I don't actually plan on using the data contained in these columns, but they appear to be causing problems in the model fitting. When I run the fitting example, I find that the log prior is giving NaNs for any input parameters, while the log likelihood appears to be working properly. Is this due to the fact that there are Nans in the dt_deep column? Is there a way to not consider these columns when fitting a model?
Thanks, Noah Tuchow