Action to compute a chi2 taking into account pdf errors and plot the chi2 per-replica

Created by: scarlehoff

Chi2 with pdf errors.

I started working on the history-test project for n3fit I talked about in Varenna. In order to have this I want to have something able to compute \chi^{2} adding a covariance matrix which gives information about the PDF error. i.e.,

Where C is the normal covariance matrix and P is the one due to the PDF errors.

This is the quickest solution I could think of to get the table I wanted, i.e., the result is final, the code will not be (I just saw I left some debug code in in the commit)

Plot chi2 per replica.

There is currently an action to compute the chi2 per replica per experiment, but not a corresponding action to plot it. I will also commit an action to plot this as I am interested in having this in the reports.

Example:

This is an example runcard that will produce a

fit: 181101-001-sc
pdf: 181101-001-sc

use_cuts: internal
q2min: 3.49
w2min: 12.5
theoryid: 53

actions_:
    - perexperiment_pdferr_chi2_table

theory:
    from_: fit

experiments:
  - experiment: NMCPD
    datasets:
      - { dataset: NMCPD, frac: 0.5 }

Note: i could not find this done anywhere in vp, if it has been done let me know¡!

validphys2/src/validphys/results.py

@@ -541,10 +541,10 @@ def pdferr_plus_data_covmat(dataset, pdf, data_covmat):
 
     >>> from validphys.api import API
     >>> inp = {
-            'dataset_input': {'ATLASTTBARTOT'},
-            'theoryid': 52,
+            'dataset_input': {'dataset' : 'ATLASTTBARTOT'},
+            'theoryid': 53,
             'pdf': 'NNPDF31_nlo_as_0118',
-            'use_cuts': 'no_cuts'
+            'use_cuts': 'nocuts'
         }
     >>> a = API.covariance_matrix(**inp, use_pdferr=True)
     >>> b = API.pdferr_plus_data_covmat(**inp)