[WIP] Reimplement ATLAS_Z0_7TEV_46FB_CC

[ecole41]

Added function to filter_utils.py to produce data.yaml.

Issues

There are three tables used in producing the central values, each of these data uses different sig.fig, also the legacy data has a higher sig.fig to the current HEP data available.
I am not sure what the procedure is in this case.

Compatibility Checks:

Covariance Matrices:

from validphys.api import API
import numpy as np
import os

def check_theory_exists(theory_id):
    theory_path = f"/Users/ellacole/miniconda3/envs/nnpdf_dev/share/NNPDF/theories/theory_{theory_id}"
    return os.path.exists(theory_path)

theory_id = 708 


if check_theory_exists(theory_id):
    inp1 = {"dataset_input": {"dataset": "ATLASZRAP11CC"}, "theoryid": theory_id, "use_cuts": "internal"}
    inp2 = {"dataset_input": {"dataset": "ATLASZRAP11CC", "variant": "legacy"}, "theoryid": theory_id, "use_cuts": "internal"}
    covmat1 = API.covmat_from_systematics(**inp1)
    covmat2 = API.covmat_from_systematics(**inp2)
    
    result = np.isclose(covmat1, covmat2)
    print(result)
else:
    print(f"Theory {theory_id} not found. ")
    
 [Out]:
[[ True  True  True  True  True  True  True  True  True  True  True  True
   True  True  True  True  True  True  True  True  True  True  True  True]
 [ True  True  True  True  True  True  True  True  True  True  True  True
   True  True  True  True  True  True  True  True  True  True  True  True]
 [ True  True  True  True  True  True  True  True  True  True  True  True
   True  True  True  True  True  True  True  True  True  True  True  True]
 [ True  True  True  True  True  True  True  True  True  True  True  True
   True  True  True  True  True  True  True  True  True  True  True  True]
 [ True  True  True  True  True  True  True  True  True  True  True  True
   True  True  True  True  True  True  True  True  True  True  True  True]
 [ True  True  True  True  True  True  True  True  True  True  True  True
   True  True  True  True  True  True  True  True  True  True  True  True]
 [ True  True  True  True  True  True  True  True  True  True  True  True
   True  True  True  True  True  True  True  True  True  True  True  True]
 [ True  True  True  True  True  True  True  True  True  True  True  True
   True  True  True  True  True  True  True  True  True  True  True  True]
 [ True  True  True  True  True  True  True  True  True  True  True  True
   True  True  True  True  True  True  True  True  True  True  True  True]
 [ True  True  True  True  True  True  True  True  True  True  True  True
   True  True  True  True  True  True  True  True  True  True  True  True]
 [ True  True  True  True  True  True  True  True  True  True  True  True
   True  True  True  True  True  True  True  True  True  True  True  True]
 [ True  True  True  True  True  True  True  True  True  True  True  True
   True  True  True  True  True  True  True  True  True  True  True  True]
 [ True  True  True  True  True  True  True  True  True  True  True  True
...
 [ True  True  True  True  True  True  True  True  True  True  True  True
   True  True  True  True  True  True  True  True  True  True  True  True]
 [ True  True  True  True  True  True  True  True  True  True  True  True
   True  True  True  True  True  True  True  True  True  True  True  True]]
Output is truncated. View as a [scrollable element](command:cellOutput.enableScrolling?d230cec4-3639-4cac-b0de-d4e2740e1964) or open in a [text editor](command:workbench.action.openLargeOutput?d230cec4-3639-4cac-b0de-d4e2740e1964). Adjust cell output [settings](command:workbench.action.openSettings?%5B%22%40tag%3AnotebookOutputLayout%22%5D)...

t0 Matrix:

from validphys.api import API
import numpy as np
 
inp1 = {"dataset_input": {"dataset": "ATLASZRAP11CC"}, "theoryid": 40_000_000, "use_cuts": "internal", "t0pdfset": "NNPDF40_nnlo_as_01180", "use_t0": True}
inp2 = {"dataset_input": {"dataset": "ATLASZRAP11CC", "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]:covmat True
t0_covmat True

[comane]

this should be [11, 12, 13]. Then you can use it to loop over in eg filter_utils/get_data_values instead of having to write three times

with open(...

[Radonirinaunimi]

Yes, tables should be a Python list specifying the table ID. This will be crucial when we want to remove the rawdata from the remote repository (cc #2199).

[comane]

It could be a good idea to have get_data_values take a tables list that is read from the metadata and passed from filter/filter_ATLAS_Z0_7TEV_46FB_CC_data_kinematics

[comane]

same idea here, I think that the function could be made simpler by adding a tables to the args

[scarlehoff]

Same, should this be closed?