closure test

validphys2/src/validphys/config.py

@@ -1679,15 +1679,15 @@ def produce_filter_data(self, fakedata: bool = False, theorycovmatconfig=None):
         if not fakedata:
             return validphys.filters.filter_real_data
         else:
-            if theorycovmatconfig is not None and theorycovmatconfig.get(
-                "use_thcovmat_in_sampling"
-            ):
-                # NOTE: By the time we run theory covmat closure tests,
-                # hopefully the generation of pseudodata will be done in python.
-                raise ConfigError(
-                    "Generating closure test data which samples from the theory "
-                    "covariance matrix has not been implemented yet."
-                )
+            # if theorycovmatconfig is not None and theorycovmatconfig.get(
+            #     "use_thcovmat_in_sampling"
+            # ):
+            #     # NOTE: By the time we run theory covmat closure tests,
+            #     # hopefully the generation of pseudodata will be done in python.
+            #     raise ConfigError(
+            #         "Generating closure test data which samples from the theory "
+            #         "covariance matrix has not been implemented yet."
+            #     )
             return validphys.filters.filter_closure_data_by_experiment
 
     @configparser.explicit_node

validphys2/src/validphys/theorycovariance/construction.py

@@ -106,7 +106,7 @@ def covmat_alphas(name1, name2, deltas1, deltas2, rescale_alphas_covmat):
     # NOTE: an edit has been made to redefine the covmat to account for
     # second order derivatives of the theory prediction wrt alpha_s. (see
     # section 1.1 of 2105.05114)
-    s = 0.5 * np.outer(deltas1[0] - deltas1[1], deltas2[0] - deltas2[1])
+    s = np.outer(deltas1[0] - deltas1[1], deltas2[0] - deltas2[1])
     return s*rescale_alphas_covmat
 
 def covmat_3fpt(name1, name2, deltas1, deltas2):