I am working with inference results from Turing.jl. My data is uneven so I’m modeling it in the “long” format while in the Turing model, but after the inference is done, I’d like to reshape the data into a more structured shape (filling in missing values with missing as needed). The Python analogue I’m more familiar with, xarray, has an unstack function that you can use in conjunction with a multi-index. Is there an something like this with InferenceObjects.jl/DimesionalData.jl? I saw DimensionalData.jl has mergedims and the inverse of that operation is exactly what I think I need.
Maybe there is also a more obvious solution I’m missing?