[WIP] Reimplement ATLAS WPWM 7TeV 36PB

[ecole41]

Functions haves been added to produce the data central, kinematic and uncertainties yaml files for this dataset.

Old vs New Data Report

https://vp.nnpdf.science/6-mHiiJJTcC5Mf86u4NJ2g==/

Compatabiliy Check

[In]:from validphys.api import API
import numpy as np
 
inp1 = {"dataset_input": {"dataset": "ATLASWRAP36PB"}, "theoryid": 40_000_000, "use_cuts": "internal", "t0pdfset": "NNPDF40_nnlo_as_01180", "use_t0": True}
inp2 = {"dataset_input": {"dataset": "ATLASWRAP36PB", "variant": "legacy"}, "theoryid": 40_000_000, "use_cuts": "internal", "t0pdfset": "NNPDF40_nnlo_as_01180", "use_t0": True}

covmat1 = API.covmat_from_systematics(**inp1)
covmat2 = API.covmat_from_systematics(**inp2)
 
t0_covmat1 = API.t0_covmat_from_systematics(**inp1)
t0_covmat2 = API.t0_covmat_from_systematics(**inp2)
 
result = np.all(np.isclose(covmat1, covmat2))
result_2 = np.all(np.isclose(t0_covmat1, t0_covmat2))

print('covmat', result)
print('t0_covmat', result_2)

[Out]:LHAPDF 6.5.4 loading [/Users/ellacole/miniconda3/envs/nnpdf_dev/share/LHAPDF/NNPDF40_nnlo_as_01180/NNPDF40_nnlo_as_01180_0000.dat](https://file+.vscode-resource.vscode-cdn.net/Users/ellacole/miniconda3/envs/nnpdf_dev/share/LHAPDF/NNPDF40_nnlo_as_01180/NNPDF40_nnlo_as_01180_0000.dat)
NNPDF40_nnlo_as_01180 PDF set, member #0, version 1; LHAPDF ID = 331100
covmat True
t0_covmat True

[scarlehoff]

I think it is better to finish the ones that are already started and then move to the more weird datasets ^^U

When the data don't match, try to take the ratio and check whether the difference is just normalization. Some of the old datasets were normalized for bin size / total cross section / other stuff.

[scarlehoff]

Hi @ecole41 I've had a look and the tables from https://www.hepdata.net/record/ins928289 match the data up to a factor of 1.0187 for all bins.

I have checked only Table 1 (which is the Z) against https://github.com/NNPDF/nnpdf/blob/master/nnpdf_data/nnpdf_data/commondata/ATLAS_Z0_7TEV_36PB/data_legacy_ETA.yaml
(there's also a factor 1000 of fb vs pb)

In cases like this, when there's one single factor for all bins, your best bet is to look at the old buildmaster and... indeed...

nnpdf/buildmaster/filters/ATLASZRAP36PB.cc

Line 24 in 843a03d

const double lcorr = 1.0187; // correction factor due to luminosity upgrade

[ecole41]

I am not sure if I should include this conversion factor here

[jacoterh]

looking at commondataparser.py this is valid input! So I would keep it.

[jacoterh]

@ecole41 if you could please redo the report including conversion_factor = 1.0187 it's easier to compare theory and data. Thanks.

[ecole41]

@ecole41 if you could please redo the report including conversion_factor = 1.0187 it's easier to compare theory and data. Thanks.

The report was made with the conversion factor in the metadata already, so it the old and new should hopefully match. I will remove the comment now

[jacoterh]

please add the inspire link too

[jacoterh]

Version can be set to 1

[jacoterh]

@ecole41 if you could please redo the report including conversion_factor = 1.0187 it's easier to compare theory and data. Thanks.

The report was made with the conversion factor in the metadata already, so it the old and new should hopefully match. I will remove the comment now

Ah interesting, is there a reason why the theory is consistently higher than the data then? I see it's the same in the old implementation, so it's technically not part of this PR, but I got curious.

[ecole41]

@ecole41 if you could please redo the report including conversion_factor = 1.0187 it's easier to compare theory and data. Thanks.

The report was made with the conversion factor in the metadata already, so it the old and new should hopefully match. I will remove the comment now

Ah interesting, is there a reason why the theory is consistently higher than the data then? I see it's the same in the old implementation, so it's technically not part of this PR, but I got curious.

Are we sure that the conversion factor should be included in the metadata? I have already included it when producing the data.yaml file so maybe it isn't needed in the metadata also? Then maybe the theory would be more consistent with the data

[jacoterh]

onversion factor should be included in the metadata? I have already included it when producing the data.yaml file so maybe it isn't needed in the metadat

Maybe, the best way here is to simply try what the theory vs data comparison looks like without including this factor, i.e. setting it to one.

[ecole41]

onversion factor should be included in the metadata? I have already included it when producing the data.yaml file so maybe it isn't needed in the metadat

Maybe, the best way here is to simply try what the theory vs data comparison looks like without including this factor, i.e. setting it to one.

Here is with conversion_factor: 1.0187: https://vp.nnpdf.science/6-mHiiJJTcC5Mf86u4NJ2g==/

Here is with conversion_factor: 1.0: https://vp.nnpdf.science/4JZ3wcPYTDOGHtDyu70pjg==/

There is a difference but I am not sure which one is correct. I would guess to keep the conversion factor equal to 1 as this has already been included in the data.yaml? But that might be wrong