Generate vp reports

[alecandido]

Since we have no comparable fit data (wrt n3fit ones) there are a few things we can't reproduce from a full comparison report. But most things only rely on an LHAPDF grid, so we just need to generate that one.

• evolve a fit (essentially the resulting NumPy array) with evolven3fit
• First generate a brief one
  • this is already based just on an LHAPDF grid, so once we have one, we can make it
• Then try to get as many elements from the complete one as possible, purging the template
  • essentially the only things to suppressed are those related to training lengths

Thanks @RoyStegeman for all the explanations and the references.

[RoyStegeman]

Just as a reminder: the basic difference is that if you only provide an lhapdf grid, you have pdfs/pdf as opposed to fits/fit in terms of what validphys interprets. So any vp function that requires a fit you will not be able to use.

For you, maybe an important difference is that PDFs don't contain the runcard and all the information that is in there. For example, if you look for examples of validphys runcards, you will find that we often extract information (such as what dataset was used during the fit) from the runcard to then calculate the chi2 to those datasets, if you use a pdf as input you would have to write all datasets explicitly in the runcard (or come up with some other trick).

[alecandido]

In the first place I will reproduce the thing you did, and that does not involve datasets.

When it comes to them, most likely the easiest thing to do is to generate the runcard from what we'll have. Actually the datasets are stemming from 4.0 runcard in the first place...

I guess there is a lot of room to improve, and we'll do it, after we'll have at least a prototype :)

[RoyStegeman]

Sure you could even do something a bit hacky like

fit: NNPDF40
pdf: mcpdf

datasets_inputs:
  from_: fit

Mainly I just wanted to point out the difference between fits and pdfs.