Restore needed thcovmat functions by andreab1997 · Pull Request #1901 · NNPDF/nnpdf

andreab1997 · 2023-12-21T11:40:34Z

It seems that #1899 removed some functions that are needed for some of the reports we usually do (cc @giacomomagni). For example for shift_diag_cov_comparison. I am trying to restore and eventually fix this here. @RoyStegeman @scarlehoff

scarlehoff

I guess the important question is, do we need this for the papers and do we need this quick?

I might be able to work tomorrow on changing the functions that use arrays to use dataframes instead (if you point me to them).

As I said in the comments, I'm not convinced covmap is correct unless the order in the runcard is the "right one".

edit: note that the need for all this trickery was probably due to the mix of C++ and python. Now that in vp we can have dataframes all way through you should not need any mappings because the dataframe contains the mapping.

giacomomagni · 2023-12-21T13:42:50Z

I guess the important question is, do we need this for the papers and do we need this quick?

Unfortunately I think we need this plot (ie the red and black shift plot) for the papers. 😭
But at this point, fits are delayed after Christmas, so we have a bit of time.

Thanks you all for the help.

scarlehoff · 2023-12-21T13:44:55Z

Only shift_diag_cov_comparison is needed? (and currently broken)

giacomomagni · 2023-12-21T13:52:32Z

Only shift_diag_cov_comparison is needed? (and currently broken)

I think so, running the previous vp-runcard I'm getting:

A parameter is required: theory_covmat_custom_dataspecs.
This is needed to process:
 - report
through:
 - template_text
through:
 - shift_diag_cov_comparison
through:
 - thx_covmat

RoyStegeman · 2023-12-21T14:07:15Z

Can you share your runcard?

giacomomagni · 2023-12-21T14:10:21Z

template_shifts_n3lo.md

here you go:

meta:
   author: Giacomo Magni
   keywords: [theory uncertainties, 7-point, N3LO]
   title: validation shifts NNLO vs N3LO for DIS and DY 

datasets_inputs_nnlo: &datasets_list_nnlo
  - {dataset: NMCPD_dw_ite}
  - {dataset: NMC}
  - {dataset: SLACP_dwsh}
  - {dataset: SLACD_dw_ite}
  - {dataset: BCDMSP_dwsh}
  - {dataset: BCDMSD_dw_ite}
  - {dataset: CHORUSNUPb_dw_ite}
  - {dataset: CHORUSNBPb_dw_ite}
  - {dataset: NTVNUDMNFe_dw_ite, cfac: [MAS]}
  - {dataset: NTVNBDMNFe_dw_ite, cfac: [MAS]}
  - {dataset: HERACOMBNCEM}
  - {dataset: HERACOMBNCEP460}
  - {dataset: HERACOMBNCEP575}
  - {dataset: HERACOMBNCEP820}
  - {dataset: HERACOMBNCEP920}
  - {dataset: HERACOMBCCEM}
  - {dataset: HERACOMBCCEP}
  - {dataset: HERACOMB_SIGMARED_C}
  - {dataset: HERACOMB_SIGMARED_B}
  # - {dataset: DYE886R_dw_ite}
  # - {dataset: DYE886P, cfac: []}
  #- {dataset: DYE605_dw_ite, cfac: []}
  #- {dataset: DYE906R_dw_ite, cfac: [ACC]}
  - {dataset: CDFZRAP_NEW}
  - {dataset: D0ZRAP_40, cfac: []}
  - {dataset: D0WMASY}
  - {dataset: ATLASWRAP36PB}
  - {dataset: ATLASZRAP36PB}
  - {dataset: ATLASZHIGHMASS49FB}
  - {dataset: ATLASLOMASSDY11EXT}
  - {dataset: ATLASWRAP11CC}
  - {dataset: ATLASZRAP11CC}
  - {dataset: ATLASWZRAP11CF}
  - {dataset: ATLASDY2D8TEV, cfac: []}
  - {dataset: ATLAS_DY_2D_8TEV_LOWMASS, cfac: []}
  - {dataset: ATLAS_Z_TOT_13TEV, cfac: [NRM]}
  - {dataset: ATLAS_W_TOT_13TEV, cfac: [NRM]}
  # - {dataset: ATLAS_WP_JET_8TEV_PT, cfac: []}
  # - {dataset: ATLAS_WM_JET_8TEV_PT, cfac: []}
  # #- {dataset: ATLAS_WCHARM_WP_DIFF_7TEV, cfac: []}
  # #- {dataset: ATLAS_WCHARM_WM_DIFF_7TEV, cfac: []}
  - {dataset: ATLASZPT8TEVMDIST, cfac: []}
  - {dataset: ATLASZPT8TEVYDIST, cfac: []}
  # - {dataset: ATLASTTBARTOT7TEV, cfac: []}
  # - {dataset: ATLASTTBARTOT8TEV, cfac: []}
  # - {dataset: ATLAS_TTBARTOT_13TEV_FULLLUMI, cfac: []}
  # - {dataset: ATLAS_TTB_DIFF_8TEV_LJ_TRAPNORM, cfac: []}
  # - {dataset: ATLAS_TTB_DIFF_8TEV_LJ_TTRAPNORM, cfac: []}
  # - {dataset: ATLAS_TOPDIFF_DILEPT_8TEV_TTRAPNORM, cfac: []}
  # - {dataset: ATLAS_1JET_8TEV_R06_DEC, cfac: []}
  # - {dataset: ATLAS_2JET_7TEV_R06, cfac: []}
  # - {dataset: ATLASPHT15_SF, cfac: [EWK]}
  # - {dataset: ATLAS_SINGLETOP_TCH_R_7TEV, cfac: []}
  # - {dataset: ATLAS_SINGLETOP_TCH_R_13TEV, cfac: []}
  # - {dataset: ATLAS_SINGLETOP_TCH_DIFF_7TEV_T_RAP_NORM, cfac: []}
  # - {dataset: ATLAS_SINGLETOP_TCH_DIFF_7TEV_TBAR_RAP_NORM, cfac: []}
  # - {dataset: ATLAS_SINGLETOP_TCH_DIFF_8TEV_T_RAP_NORM, cfac: []}
  # - {dataset: ATLAS_SINGLETOP_TCH_DIFF_8TEV_TBAR_RAP_NORM, cfac: []}
  - {dataset: CMSWEASY840PB}
  - {dataset: CMSWMASY47FB}
  - {dataset: CMSDY2D11, cfac: []}
  - {dataset: CMSWMU8TEV}
  - {dataset: CMSZDIFF12, cfac: [NRM]}
  # - {dataset: CMS_2JET_7TEV, cfac: []}
  # - {dataset: CMS_1JET_8TEV, cfac: []}
  # - {dataset: CMSTTBARTOT7TEV, cfac: []}
  # - {dataset: CMSTTBARTOT8TEV, cfac: []}
  # - {dataset: CMSTTBARTOT13TEV, cfac: []}
  # - {dataset: CMSTOPDIFF8TEVTTRAPNORM, cfac: []}
  # - {dataset: CMSTTBARTOT5TEV, cfac: []}
  # - {dataset: CMS_TTBAR_2D_DIFF_MTT_TRAP_NORM, cfac: []}
  # - {dataset: CMS_TTB_DIFF_13TEV_2016_2L_TRAP, cfac: []}
  # - {dataset: CMS_TTB_DIFF_13TEV_2016_LJ_TRAP, cfac: []}
  # - {dataset: CMS_SINGLETOP_TCH_TOT_7TEV, cfac: []}
  # - {dataset: CMS_SINGLETOP_TCH_R_8TEV, cfac: []}
  # - {dataset: CMS_SINGLETOP_TCH_R_13TEV, cfac: []}
  #- {dataset: CMSWCHARMTOT}
  #- {dataset: CMSWCHARMRAT}
  #- {dataset: CMS_WCHARM_DIFF_UNNORM_13TEV}
  - {dataset: LHCBZ940PB}
  - {dataset: LHCBZEE2FB_40}
  - {dataset: LHCBWMU7TEV, cfac: [NRM]}
  - {dataset: LHCBZMU7TEV, cfac: [NRM]}
  - {dataset: LHCBWMU8TEV, cfac: [NRM]}
  - {dataset: LHCBZMU8TEV, cfac: [NRM]}
  - {dataset: LHCB_Z_13TEV_DIMUON}
  - {dataset: LHCB_Z_13TEV_DIELECTRON}

datasets_inputs_n3lo: &datasets_list_n3lo
  - {dataset: NMCPD_dw_ite}
  - {dataset: NMC}
  - {dataset: SLACP_dwsh}
  - {dataset: SLACD_dw_ite}
  - {dataset: BCDMSP_dwsh}
  - {dataset: BCDMSD_dw_ite}
  - {dataset: CHORUSNUPb_dw_ite}
  - {dataset: CHORUSNBPb_dw_ite}
  - {dataset: NTVNUDMNFe_dw_ite, cfac: [MAS]}
  - {dataset: NTVNBDMNFe_dw_ite, cfac: [MAS]}
  - {dataset: HERACOMBNCEM}
  - {dataset: HERACOMBNCEP460}
  - {dataset: HERACOMBNCEP575}
  - {dataset: HERACOMBNCEP820}
  - {dataset: HERACOMBNCEP920}
  - {dataset: HERACOMBCCEM}
  - {dataset: HERACOMBCCEP}
  - {dataset: HERACOMB_SIGMARED_C}
  - {dataset: HERACOMB_SIGMARED_B}
  # - {dataset: DYE886R_dw_ite}
  # - {dataset: DYE886P, cfac: []}
  #- {dataset: DYE605_dw_ite, cfac: []}
  #- {dataset: DYE906R_dw_ite, cfac: [ACC]}
  - {dataset: CDFZRAP_NEW, cfac: []}
  - {dataset: D0ZRAP_40, cfac: []}
  - {dataset: D0WMASY, cfac: []}
  - {dataset: ATLASWRAP36PB, cfac: []}
  - {dataset: ATLASZRAP36PB, cfac: []}
  - {dataset: ATLASZHIGHMASS49FB, cfac: []}
  - {dataset: ATLASLOMASSDY11EXT, cfac: []}
  - {dataset: ATLASWRAP11CC, cfac: []}
  - {dataset: ATLASZRAP11CC, cfac: []}
  - {dataset: ATLASWZRAP11CF, cfac: []}
  - {dataset: ATLASDY2D8TEV, cfac: []}
  - {dataset: ATLAS_DY_2D_8TEV_LOWMASS, cfac: []}
  - {dataset: ATLAS_Z_TOT_13TEV, cfac: [NRM,]}
  - {dataset: ATLAS_W_TOT_13TEV, cfac: [NRM,]}
  # - {dataset: ATLAS_WP_JET_8TEV_PT, cfac: []}
  # - {dataset: ATLAS_WM_JET_8TEV_PT, cfac: []}
  # #- {dataset: ATLAS_WCHARM_WP_DIFF_7TEV, cfac: []}
  # #- {dataset: ATLAS_WCHARM_WM_DIFF_7TEV, cfac: []}
  - {dataset: ATLASZPT8TEVMDIST, cfac: []}
  - {dataset: ATLASZPT8TEVYDIST, cfac: []}
  # - {dataset: ATLASTTBARTOT7TEV, cfac: []}
  # - {dataset: ATLASTTBARTOT8TEV, cfac: []}
  # - {dataset: ATLAS_TTBARTOT_13TEV_FULLLUMI, cfac: []}
  # - {dataset: ATLAS_TTB_DIFF_8TEV_LJ_TRAPNORM, cfac: []}
  # - {dataset: ATLAS_TTB_DIFF_8TEV_LJ_TTRAPNORM, cfac: []}
  # - {dataset: ATLAS_TOPDIFF_DILEPT_8TEV_TTRAPNORM, cfac: []}
  # - {dataset: ATLAS_1JET_8TEV_R06_DEC, cfac: []}
  # - {dataset: ATLAS_2JET_7TEV_R06, cfac: []}
  # - {dataset: ATLASPHT15_SF, cfac: [EWK]}
  # - {dataset: ATLAS_SINGLETOP_TCH_R_7TEV, cfac: []}
  # - {dataset: ATLAS_SINGLETOP_TCH_R_13TEV, cfac: []}
  # - {dataset: ATLAS_SINGLETOP_TCH_DIFF_7TEV_T_RAP_NORM, cfac: []}
  # - {dataset: ATLAS_SINGLETOP_TCH_DIFF_7TEV_TBAR_RAP_NORM, cfac: []}
  # - {dataset: ATLAS_SINGLETOP_TCH_DIFF_8TEV_T_RAP_NORM, cfac: []}
  # - {dataset: ATLAS_SINGLETOP_TCH_DIFF_8TEV_TBAR_RAP_NORM, cfac: []}
  - {dataset: CMSWEASY840PB, cfac: []}
  - {dataset: CMSWMASY47FB, cfac: []}
  - {dataset: CMSDY2D11, cfac: []}
  - {dataset: CMSWMU8TEV, cfac: []}
  - {dataset: CMSZDIFF12, cfac: [NRM]}
  # - {dataset: CMS_2JET_7TEV, cfac: []}
  # - {dataset: CMS_1JET_8TEV, cfac: []}
  # - {dataset: CMSTTBARTOT7TEV, cfac: []}
  # - {dataset: CMSTTBARTOT8TEV, cfac: []}
  # - {dataset: CMSTTBARTOT13TEV, cfac: []}
  # - {dataset: CMSTOPDIFF8TEVTTRAPNORM, cfac: []}
  # - {dataset: CMSTTBARTOT5TEV, cfac: []}
  # - {dataset: CMS_TTBAR_2D_DIFF_MTT_TRAP_NORM, cfac: []}
  # - {dataset: CMS_TTB_DIFF_13TEV_2016_2L_TRAP, cfac: []}
  # - {dataset: CMS_TTB_DIFF_13TEV_2016_LJ_TRAP, cfac: []}
  # - {dataset: CMS_SINGLETOP_TCH_TOT_7TEV, cfac: []}
  # - {dataset: CMS_SINGLETOP_TCH_R_8TEV, cfac: []}
  # - {dataset: CMS_SINGLETOP_TCH_R_13TEV, cfac: []}
  #- {dataset: CMSWCHARMTOT}
  #- {dataset: CMSWCHARMRAT}
  #- {dataset: CMS_WCHARM_DIFF_UNNORM_13TEV}
  - {dataset: LHCBZ940PB, cfac: []}
  - {dataset: LHCBZEE2FB_40, cfac: []}
  - {dataset: LHCBWMU7TEV, cfac: [NRM,]}
  - {dataset: LHCBZMU7TEV, cfac: [NRM]}
  - {dataset: LHCBWMU8TEV, cfac: [NRM,]}
  - {dataset: LHCBZMU8TEV, cfac: [NRM,]}
  - {dataset: LHCB_Z_13TEV_DIMUON, cfac: []}
  - {dataset: LHCB_Z_13TEV_DIELECTRON, cfac: []}


orthonormalisation: qr # Choice of orthonormalisation scheme
                             # for finding th covmat basis. Default is qr.
theoryid: 708
      
pdf: "NNPDF40_nnlo_as_01180"
use_cuts: internal
q2min: 3.49                       # Q2 minimum
w2min: 12.5                       # W2 minimum


shiftconfig:     # For calculating NNLO-NLO shift

  use_cuts: internal
  q2min: 3.49                      # Q2 minimum
  w2min: 12.5                       # W2 minimum


  theoryid: 708
      
  dataspecs:
    - theoryid: 708
      pdf: "NNPDF40_nnlo_as_01180"
      speclabel: "NNLO"
      dataset_inputs: *datasets_list_nnlo
                          
    - theoryid: 722
      pdf: "NNPDF40_nnlo_as_01180"
      speclabel: "N3LO"
      dataset_inputs: *datasets_list_n3lo

theoryconfig:

  theoryid: 708

  theoryids:
    from_: scale_variation_theories

  point_prescription: '7 point'
  use_cuts: internal
  q2min: 3.49                      # Q2 minimum
  w2min: 12.5                       # W2 minimum
  pdf: "NNPDF40_nnlo_as_01180"     

  dataspecs:
    - theoryid: 708
      speclabel: $(\xi_F,\xi_R)=(1,1)$
      dataset_inputs: *datasets_list_nnlo
    - theoryid: 711
      speclabel: $(\xi_F,\xi_R)=(2,1)$
      dataset_inputs: *datasets_list_nnlo
    - theoryid: 705
      speclabel: $(\xi_F,\xi_R)=(0.5,1)$
      dataset_inputs: *datasets_list_nnlo
    - theoryid: 709
      speclabel: $(\xi_F,\xi_R)=(1,2)$
      dataset_inputs: *datasets_list_nnlo
    - theoryid: 707
      speclabel: $(\xi_F,\xi_R)=(1,0.5)$
      dataset_inputs: *datasets_list_nnlo
    - theoryid: 712
      speclabel: $(\xi_F,\xi_R)=(2,2)$
      dataset_inputs: *datasets_list_nnlo
    - theoryid: 704
      speclabel: $(\xi_F,\xi_R)=(0.5,0.5)$
      dataset_inputs: *datasets_list_nnlo

template: template_shifts_n3lo.md

dataset_report:
   meta: Null
   template_text: |
      ## Testing 7pt NNLO global covariance matrix against N3LO-NNLO shift
actions_:
  - report(main=true, mathjax=True)

RoyStegeman · 2023-12-21T14:15:55Z

Do we know why is the theorycovmat shift calculated using the diagonal elements of the theory covmat instead of e.g. the values on the diagonal of the covmat with all variations considered? I know both neglect part of the picture and I'm not sure which is the better choice for interpretation/presentation, but do you know the motivation for this chioce?

giacomomagni · 2023-12-21T14:52:16Z

Do we know why is the theorycovmat shift calculated using the diagonal elements of the theory covmat instead of e.g. the values on the diagonal of the covmat with all variations considered?

Personally I don't, this looks more something that happens when you start with a basic setup and then you add features but you forgot to update everything.

I know both neglect part of the picture and I'm not sure which is the better choice for interpretation/presentation, but do you know the motivation for this chioce?

I'd say we can fix this behaviour and always compute the full covmat. If only the diagonal is needed you extract them from the full matrix. Maybe @andreab1997 or someone else have better ideas.

RoyStegeman · 2023-12-21T14:53:46Z

I'd say we can fix this behaviour and always compute the full covmat. If only the diagonal is needed you extract them from the full matrix. Maybe @andreab1997 or someone else have better ideas.

I was indeed thinking along those lines

andreab1997 · 2024-01-03T13:19:58Z

Only shift_diag_cov_comparison is needed? (and currently broken)

No we need all the functions in tests.py (at least I need all of them).

andreab1997 · 2024-01-08T13:37:02Z

Just to keep track of this: Now the function shift_diag_cov_comparison_test works and does what expected. However while in some cases the results are very similar to the old ones (as expected), for example in the DIS NC case, in other cases the results are pretty weird, for instance in the DY CC case. Given that now the dataset order is enforced trought the DataFrames, I fear there might be a problem with the order of the datapoints in the datasets and/or with the labels of the theory_covmat. @RoyStegeman and @scarlehoff when you can, please have a look.

I leave here a couple of runcard that you can use (given that I simplified their structure a bit):
DIS NC: 231116-valplot-DISNC.txt
DY CC: 231116-valplot-DYCC.txt
template: template_test.md

andreab1997 · 2024-01-08T13:57:38Z

Ok maybe the problem was just the one corrected in 52f3262 but if you can please have a look anyway

RoyStegeman · 2024-01-08T14:02:33Z

Given that now the dataset order is enforced trought the DataFrames, I fear there might be a problem with the order of the datapoints in the datasets and/or with the labels of the theory_covmat

Do you mean the problem is with the labels of the stored covmat from vp-setupfit or only in these plotting function? I'm not so sure what you'd like us to check, could you share the plot/table you're worried about?

andreab1997 · 2024-01-08T14:45:28Z

Given that now the dataset order is enforced trought the DataFrames, I fear there might be a problem with the order of the datapoints in the datasets and/or with the labels of the theory_covmat

Do you mean the problem is with the labels of the stored covmat from vp-setupfit or only in these plotting function? I'm not so sure what you'd like us to check, could you share the plot/table you're worried about?

No, after 52f3262 maybe there is no problem. For example this is the new report for DYCC to be compared with the old one DYCC. Of course they are not the same and they should not given that the old one was affected by all the ordering problems, but now they look reasonably similar. Anyway, I will ask you for a review but if you want to have a look at the code even now, please do it even if for the moment it is just a draft.

giacomomagni

LGTM and it's working!

andreab1997 · 2024-01-09T12:27:26Z

@scarlehoff I resolved all your conversations because they refer to functions that I now removed (5db9ae0), together with all the others that are not used anymore in the theorycovariance module. Please check if in 5db9ae0 I removed something that you use or that I should not have removed.

scarlehoff

I'm completely happy with anything that implies removing code from this module :P

andreab1997 · 2024-01-09T12:37:59Z

This is the complete test report that we need for the papers as obtained with the current status of this branch: https://vp.nnpdf.science/MLy8yUWdRyOqJpEYERiEmg== . Results are very similar to old ones but of course not completely identical given that we solved the ordering issue. I am now about to check and improve everything again in tests.py so comments and suggestions are welcomed (note however that at the moment this is really a draft).

CC: @giacomomagni (I don't know to be honest if you need all the tests but in case here it is)

scarlehoff · 2024-01-09T12:41:44Z

comments and suggestions are welcomed

Regression tests. Once you have a result which you know for sure that it is correct, add a regression test. You can use the theories from here https://docs.nnpdf.science/vp/examples.html?highlight=resources#recommended-resources
That way future changes that change the order in magical ways will make the tests fail.

andreab1997 · 2024-01-10T10:40:15Z

Given that from my side everything is ready here (excluding regression tests), I would say that this is ready to be reviewed.

@scarlehoff about regression tests I was thinking about comparing reports (given that the tests pourpose is exactly producing a validation report). How do you suggest to do?

RoyStegeman · 2024-01-10T11:01:53Z

@scarlehoff about regression tests I was thinking about comparing reports (given that the tests pourpose is exactly producing a validation report). How do you suggest to do?

Instead of comparing reports you could compare plots (or tables with info used to construct the plots)

scarlehoff · 2024-01-10T11:11:00Z

Yes. I'd suggest comparing dataframes (there's a few examples in the tests). You can compare for instance theory covmat with a few edge cases that you know would fail for a problematic ordering.

RoyStegeman

Please make sure to not leave any dead code after removing functions. I only pointed out two of them, but I didn't check all functions so there may be more.

RoyStegeman

Okay I didn't look at it super close but given the results I'll trust that it works. We don't want to wait a long time with merging this either.

andreab1997 · 2024-01-12T11:32:17Z

Okay I didn't look at it super close but given the results I'll trust that it works. We don't want to wait a long time with merging this either.

Ok then I would say that if @giacomomagni can try again now his usual plots just to be sure, then we can merge. Note that I am about to do just another commit for cosmetic changes so wait for that.

outdated review

giacomomagni · 2024-01-15T09:33:18Z

I'm happy with this PR, but unfortunately some changes are still required (at least for the N3LO):

In particular:

- Different marker style for each category
- Avoid yellow as color

shall I give a try to implement them here?

andreab1997 · 2024-01-15T13:22:27Z

I'm happy with this PR, but unfortunately some changes are still required (at least for the N3LO):

In particular:
- Different marker style for each category
- Avoid yellow as color
shall I give a try to implement them here?

I would say, let's merge this now in such a way we can tag the code and then let's open another PR for these changes you are asking for. Do you agree?

Readd needed functions

33cc091

andreab1997 marked this pull request as draft December 21, 2023 11:40

scarlehoff previously requested changes Dec 21, 2023

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First draft

e5f177f

RoyStegeman mentioned this pull request Jan 8, 2024

Nn layers refactor #1888

Merged

5 tasks

Second draft

273e487

Correct wrong sqrt

52f3262

giacomomagni reviewed Jan 8, 2024

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Comment thread validphys2/src/validphys/theorycovariance/tests.py Outdated

Comment thread validphys2/src/validphys/theorycovariance/tests.py Outdated

andreab1997 added 4 commits January 8, 2024 18:33

Start fixing the other tests functions

c5c4d75

Fixing eigenvector plot and deltamiss

ac2401d

Use speclabels to write NNLO-NLO shift

6491368

Polish the thcovariance module

5db9ae0

scarlehoff reviewed Jan 9, 2024

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Comment thread validphys2/src/validphys/theorycovariance/tests.py Outdated

Comment thread validphys2/src/validphys/theorycovariance/tests.py Outdated

Comment thread validphys2/src/validphys/theorycovariance/tests.py Outdated

andreab1997 added 2 commits January 9, 2024 13:38

Run black

e0952bc

Address comments

3802078

Remove index on id

17777e4

andreab1997 marked this pull request as ready for review January 10, 2024 10:40

andreab1997 requested review from RoyStegeman, giacomomagni and scarlehoff January 10, 2024 10:40

RoyStegeman requested changes Jan 11, 2024

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Comment thread validphys2/src/validphys/theorycovariance/construction.py

Comment thread validphys2/src/validphys/theorycovariance/construction.py

RoyStegeman reviewed Jan 11, 2024

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Comment thread validphys2/src/validphys/theorycovariance/tests.py Outdated

andreab1997 added 3 commits January 11, 2024 16:40

Remove dead code

392f176

Keep removing dead code

a6d1a09

Cosmetic changes

3a428bf

RoyStegeman approved these changes Jan 12, 2024

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Comment thread validphys2/src/validphys/theorycovariance/construction.py Outdated

Address comment

f6263c2

andreab1997 added 2 commits January 12, 2024 14:14

Cosmetic changes to covmat plots

34cfa62

Correct linscale

8c71585

andreab1997 merged commit 59d3ef9 into master Jan 15, 2024

andreab1997 deleted the restore_thcovmat_funcs branch January 15, 2024 14:12

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