Rlamboll

OK, I think the simple solution is to always ensure "model" and "scenario" are strings (I can't think of cases where that is problematic, even if ints/floats are fed in)

It would mimic/generalise these two functions, extracting emissions data from the IIASA database unless it had already been downloaded previously: `def download_or_load_sr15(filename, valid_model_ids="*"): """ Load SR1.5 data, if it isn't...

it can go somewhere on my to-do list!

I've been assuming model / scenario / region /variable / time is a unique key, and throwing errors if I see multiple units for a variable, so everything would need...

The main use of the factors is to do subtraction with -1, e.g. `aggregate = "Emissions|CO2|Other"` `other_CO2 = mi.infill_composite_values( sr15_data, { aggregate: { "Emissions|CO2": 1, "Emissions|CO2|Energy and Industrial Processes": -1,...

Yeah, I don't know that there's a pressing need for it other than to infill values defined by consistency conditions, which is very much something you'd download silicone to do....