Remove bugged raise Error when using multiple covmats

n3fit/src/n3fit/backends/keras_backend/operations.py

@@ -154,7 +154,7 @@ def op_multiply_dim(o_list, **kwargs):
     """
     if len(o_list) != 2:
         raise ValueError(
-            "The number of observables is incorrect, operations.py:op_multiply_dim, expected 2, received {0}".format(
+            "The number of observables is incorrect, operations.py:op_multiply_dim, expected 2, received {}".format(
                 len(o_list)
             )
         )
@@ -309,7 +309,7 @@ def pow(tensor, power):
     return tf.pow(tensor, power)
 
 
-@tf.function(experimental_relax_shapes=True)
+@tf.function(reduce_retracing=True)
 def op_log(o_tensor, **kwargs):
     """
     Computes the logarithm of the input

validphys2/src/validphys/config.py

@@ -1,9 +1,3 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Wed Mar  9 15:43:10 2016
-
-@author: Zahari Kassabov
-"""
 from collections import ChainMap, defaultdict
 from collections.abc import Mapping, Sequence
 import copy
@@ -15,6 +9,7 @@
 import numbers
 import pathlib
 
+from frozendict import frozendict
 import pandas as pd
 
 from reportengine import configparser, report
@@ -45,13 +40,12 @@
 )
 from validphys.paramfits.config import ParamfitsConfig
 from validphys.plotoptions import get_info
-from validphys.utils import freeze_args
-from frozendict import frozendict
 import validphys.scalevariations
-
+from validphys.utils import freeze_args
 
 log = logging.getLogger(__name__)
 
+
 class Environment(Environment):
     """Container for information to be filled at run time"""
 
@@ -717,10 +711,11 @@ def produce_loaded_theory_covmat(
             str(output_path / "tables/datacuts_theory_theorycovmatconfig_user_covmat.csv"),
         ]
         paths.remove(str(output_path / "tables" / generic_path))
-        for f in files:
-            for path in paths:
-                if f == path:
-                    raise ValueError("More than one theory_covmat file in folder tables")
+        if not (use_user_uncertainties and use_scalevar_uncertainties):
+            for f in files:
+                for path in paths:
+                    if f == path:
+                        raise ValueError("More than one theory_covmat file in folder tables")
         theorypath = output_path / "tables" / generic_path
         theory_covmat = pd.read_csv(
             theorypath, index_col=[0, 1, 2], header=[0, 1, 2], sep="\t|,", engine="python"
@@ -919,9 +914,7 @@ def produce_combined_shift_and_theory_dataspecs(self, dataspecs):
         len_th = len(dataspecs)
         for s in matched_datasets:
             new_dataspecs.append(ChainMap({"dataspecs": s["dataspecs"][len_th:]}, s))
-        return {
-            "dataspecs": {"dataspecs": new_dataspecs, "original": dataspecs },
-        }
+        return {"dataspecs": {"dataspecs": new_dataspecs, "original": dataspecs}}
 
     # TODO: Worth it to do some black magic to not pass params explicitly?
     # Note that `parse_experiments` doesn't exist yet.