Automated unit handling in operations

This issue shall describe the problem already noted in the PR #535

The _op_data-function doesn’t handle units automatically. I guess, the corresponding functions add, subtract, multiply, divide and apply only work if the timeseries have the same units, but I didn’t test yet what it does if timeseries have different units.

When doing df.multiply('Emission Factor|Gases', 'Final Energy|Gases', 'Emissions|Gases') I’d expect to have Emissions|Gases the units Mt CO2.

To make _op_data handle units automatically pint might be useful. Pint can do calculations with units, even with numpy-arrays. My first thoughts for it:

import iam_units
# load iam-Units
registry = iam_units.registry
# calculate something with pint - this should be adapted to pyam timeseries and the units stored there
a = registry.Quantity(5, 'TW')
b = registry.Quantity(3, 'Mt')
c = a / b
# store the unit as string 'TW / Mt' - this needs to be passed to the pyam timeseries
unit = '{:~}'.format(c.units)

I think it’s important to handle units when calculating on the variables-axis, e.g. emissions = emission factor * energy. However on other axis like regions or scenarios I’m not sure how much it makes sense and how difficult the implementation would be to handle different units at once.

[znicholls]

how should the binary-ops function work if automated unit handling doesn’t work?

My default here would be to raise an error about the unknown unit or let pint simply raise a dimensionality error or similar… After that, option 2 sounds good with one tweak. If ignore_units is True, I would put ‘unknown’ as the unit (empty string in pyam is treated as nan often so might be dangerous…).

[danielhuppmann]

closed via #541