remove use_theorycovmat key

This key was only used in a check, where it is forced to be set to true, though an error is raised if this is not the case, so it serves little purpose. Probably a remnant of a time where it could be used to toggle the use of the theory covmat.

validphys2/src/validphys/checks.py

@@ -1,9 +1,9 @@
-# -*- coding: utf-8 -*-
 """
 Created on Thu Jun  2 19:35:40 2016
 
 @author: Zahari Kassabov
 """
+
 from collections import Counter
 import logging
 import platform
@@ -51,12 +51,6 @@ def check_pdf_is_hessian(pdf, **kwargs):
     )
 
 
-@make_argcheck
-def check_using_theory_covmat(use_theorycovmat):
-    """Check that the `use_theorycovmat` is set to True"""
-    check(use_theorycovmat, "Expecting `use_theorycovmat: true`")
-
-
 @make_argcheck
 def check_not_using_pdferr(use_pdferr=False, **kwargs):
     check(

validphys2/src/validphys/results.py

@@ -538,14 +538,11 @@ def procs_corrmat(procs_covmat):
 def results(dataset: DataSetSpec, pdf: PDF, covariance_matrix, sqrt_covmat):
     """Tuple of data and theory results for a single pdf. The data will have an associated
     covariance matrix, which can include a contribution from the theory covariance matrix which
-    is constructed from scale variation. The inclusion of this covariance matrix by default is used
-    where available, however this behaviour can be modified with the flag `use_theorycovmat`.
+    is constructed from scale variation.
 
     The theory is specified as part of the dataset (a remnant of the old C++ layout)
     A group of datasets is also allowed.
     """
-    # TODO: is the message about the usage of the theory covariance matrix here true?
-    # probably not in most cases...
     return (
         DataResult(dataset, covariance_matrix, sqrt_covmat),
         ThPredictionsResult.from_convolution(pdf, dataset),
@@ -580,9 +577,10 @@ def results_with_theory_covmat(dataset, results, theory_covmat_dataset):
     Most notably, this can be used to compute the chi2 including theory errors while plotting
     data theory covariance in which the experimental uncertainties are not stained by the thcovmat
     """
-    # TODO: in principle this function could be removed, and `results` could automagically
-    # include the theory covmat when `use_theorycovmat: true` by changing the nodes in `config.py`
-    # however at the moment config.py _loads_ theory covmats and we need to compute it on the fly
+    # TODO: in principle this function could be removed, and `results` could automagically include
+    # the theory covmat when a key, let's call it `use_theorycovmat: true`, by changing the nodes in
+    # `config.py` however at the moment config.py _loads_ theory covmats and we need to compute it
+    # on the fly
     from .covmats import sqrt_covmat
 
     data_result, central_th_result = results

validphys2/src/validphys/tests/conftest.py

@@ -91,7 +91,6 @@ def data_config():
 def thcovmat_config(data_config):
     """Same as data_config but with additional info for the thcovmat production."""
     new_config = dict(data_config)
-    new_config["use_theorycovmat"] = "true"
     new_config["use_cuts"] = "internal"
     new_config.update(theoryid=708)
     new_config.update(dataset_inputs=DATA_THCOVMAT)

validphys2/src/validphys/theorycovariance/construction.py

@@ -11,7 +11,8 @@
 
 from reportengine import collect
 from reportengine.table import table
-from validphys.checks import check_using_theory_covmat
+
+pass
 from validphys.results import results, results_central
 from validphys.theorycovariance.theorycovarianceutils import (
     check_correct_theory_combination,
@@ -25,10 +26,7 @@
 each_dataset_results_central_bytheory = collect("results_central_bytheoryids", ("data",))
 
 
-@check_using_theory_covmat
-def theory_covmat_dataset(
-    results, results_central_bytheoryids, point_prescription, use_theorycovmat  # for the check
-):
+def theory_covmat_dataset(results, results_central_bytheoryids, point_prescription):
     """
     Compute the theory covmat for a collection of theoryids for a single dataset.