Automatic scale variations#75
Conversation
Yes I know :) This is really only a draft. I just want to write a proof of concept example as soon as possible and I will improve docs and readability later. The main point is that I want to know if doing this is possible with what we already have or not. Anyway thanks for the comments :) Not strictly related to this comment but I take the opportunity to tag @cschwan which may want to have a look. |
I could see that it was a draft (apart from the draft mode, there were some missing implementations), but you wrote:
so I acted consequently :D |
Co-authored-by: Alessandro Candido <candido.ale@gmail.com>
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@andreab1997 whenever you actually need another review, either remove draft mode or tag me again :) |
Co-authored-by: Alessandro Candido <candido.ale@gmail.com>
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Given that this PR is becoming very big and given that the tests are passing I would say that this is a good moment to merge it. I know that @alecandido, together with @cschwan, is making an effort to make the code here simpler but since we are all very busy I believe we can merge this as it is and we will open another PR once the necessary improvements in |
We want a new module called
scale_variationsthat should be able to generate automatically renormalization and factorization scale variations starting from a pre-existing grid. It should also be able to generate a new grid filling the scale variations orders. The roadmap of this PR should be approximately the followingpineappl_pyis able to extract a subgrid, rescale it and construct a new grid (Note that for factorization scale variations we will also need convolutions)cli(maybe taking advantage of thetheorycommand) that can upgrade all the necessary grids for a dataset@felixhekhorn @cschwan @alecandido This is just a draft, suggestions are welcomed :)