linopy: multiply array of variables by a scalar array

[barry.m...@dcu.ie]

Hi Folks -

I'm just experimenting with the use of linopy for custom constraints in pypsa (but from a position with little/no prior xarray understanding...). So I have a set of linopy variables, indexed by snapshot, extracted like this:

    lpmodel = network.optimize.create_model()

    charge_vars = lpmodel.variables['StorageUnit-p_store']

and I now want to set up a set of constant scalar multipliers for each of these variables, but the specific constant value varies by snapshot. I already have this set of multipliers in a pd.Series, indexed by snapshot (call it "factors"). I somewhat naively hoped I might be able to so something like:

    lhs = factors * charge_vars

but that throws:

      ValueError: different number of dimensions on data and dims: 1 vs 2

So I'm guessing/hoping that there might be some concise (?) xarray syntax that will be able to do what I want here?

Any pointers appreciated.

Kind regards - Barry

[barry.m...@dcu.ie]

So, just to say that I have resolved this problem (I think!).  The more substantive problem (that led to the error I reported) seems to be just that linopy expression arithmetic (multiplication in this case) can be sensitive to the operand order. Simply reversing the order to:

    lhs = charge_vars * factors

fixed this, and the resulting expression read as I intended (and indeed, the custom constraint I derived from the expression worked as I intended when I ran the optimisation). 

It's a little bit counter-intuitive (one tends to expect "arithmetic" operations to be commutative), but I'm happy that it is now working.

(There was also a subsidiary issue, that was not apparent in my previous message, in that I had initially derived the 'factors' pd. Series in such a way that the index label was not 'snapshot'; but that was fixed by taking the index from network.snapshots instead - as I should have done in the first place anyway...)

Regards - Barry

[Fabian Hofmann]

Hey Barry,

just for some background:

It is indeed the order of the objects which make things safer here. In Python the first object in a multiplication is the "dominant" one which determines the resulting type of the multiplication (except for multiplication with inherited classes with the use of __rmul__ as well as multiplication with numpy objects and the use of __array_priority__). For multiplication with xarray objects (with xarray on the first place), we prioritize linopy object through some sly monkey patch (https://github.com/PyPSA/linopy/blob/master/linopy/monkey_patch_xarray.py), but we did not implement it for pandas for reasons of code security.

Best wishes

Fabian Hofmann

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Fabian Hofmann 

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[Barry McMullin]

Hi Fabian -

Thanks for that - very useful to have this confirmation and clarification (even if the "sly monkey patch" is well beyond my own technical grasp!).

Kind regards - Barry

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Barry McMullin

Ollamh | Scoil na hInnealtóireachta Leictreonaí | Ollscoil Chathair Bhaile Átha Cliath 

Professor | School of Electronic Engineering | Dublin City University 

barry.m...@dcu.ie |  + 353 1 700 5432|  www.eeng.dcu.ie/~mcmullin/

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