loop over point_prescriptions

n3fit/runcards/examples/Fit_with_theory_covmat.yml

@@ -27,7 +27,7 @@ datacuts:
 theory:
   theoryid: 708        # database id
 theorycovmatconfig:
-  point_prescription: "9 point"
+  point_prescriptions: ["9 point", "3 point"]
   # theoryids:
   #   from_: scale_variation_theories
   pdf: NNPDF31_nlo_as_0118

validphys2/src/validphys/config.py

@@ -210,13 +210,16 @@ def produce_replicas(self, nreplica: int):
         """Produce a replicas array"""
         return NSList(range(1, nreplica + 1), nskey="replica")
 
+    def parse_point_prescriptions(self, point_prescriptions):
+        return NSList(point_prescriptions, nskey="point_prescription")
+
     def produce_inclusive_use_scalevar_uncertainties(
-        self, use_scalevar_uncertainties: bool = False, point_prescription: (str, None) = None
+        self, use_scalevar_uncertainties: bool = False, point_prescriptions: (str, None) = None
     ):
         """Whether to use a scale variation uncertainty theory covmat.
         Checks whether a point prescription is included in the runcard and if so
         assumes scale uncertainties are to be used."""
-        if (not use_scalevar_uncertainties) and (point_prescription is not None):
+        if (not use_scalevar_uncertainties) and (point_prescriptions is not None):
             use_scalevar_uncertainties = True
         return use_scalevar_uncertainties
 
@@ -1142,9 +1145,9 @@ def produce_nnfit_theory_covmat(
                 f = total_theory_covmat_fitting
             else:
                 # Only scalevar uncertainties
-                from validphys.theorycovariance.construction import theory_covmat_custom_fitting
+                from validphys.theorycovariance.construction import theory_covmats_fitting
 
-                f = theory_covmat_custom_fitting
+                f = theory_covmats_fitting
         elif use_user_uncertainties:
             # Only user uncertainties
             from validphys.theorycovariance.construction import user_covmat_fitting
@@ -1628,12 +1631,11 @@ def produce_group_dataset_inputs_by_experiment(self, data_input):
     def produce_group_dataset_inputs_by_process(self, data_input):
         return self.produce_group_dataset_inputs_by_metadata(data_input, "nnpdf31_process")
 
-    def produce_theoryids(self, theoryid, point_prescription):
+    def produce_point_prescriptions_theoryids(self, theoryid, point_prescriptions):
         """Produces a list of theoryids given a theoryid at central scales and a point
         prescription. The options for the latter are '3 point', '5 point', '5bar point', '7 point'
         and '9 point'. Note that these are defined in arXiv:1906.10698. This hard codes the
         theories needed for each prescription to avoid user error."""
-        pp = point_prescription
         th = theoryid.id
 
         lsv = yaml.safe_load(read_text(validphys.scalevariations, "scalevariationtheoryids.yaml"))
@@ -1654,44 +1656,50 @@ def produce_theoryids(self, theoryid, point_prescription):
             read_text(validphys.scalevariations, "pointprescriptions.yaml")
         )
 
-        try:
-            scales = pp_scales_dict[pp]
-        except KeyError:
-            valid_pps = ", ".join(pp_scales_dict.keys())
-            raise ConfigError(
-                "Scale variations are not currently defined for this point prescription. This "
-                + "configuration only works when 'point_prescription' is equal to one of the "
-                + f"following: {valid_pps}. Please use one of these instead if you wish to "
-                + "include theory uncertainties here."
-            )
+        pp_thids = {}
+        for pp in point_prescriptions:
+            try:
+                scales = pp_scales_dict[pp]
+            except KeyError:
+                valid_pps = ", ".join(pp_scales_dict.keys())
+                raise ConfigError(
+                    "Scale variations are not currently defined for this point prescription. This "
+                    + "configuration only works when 'point_prescription' is equal to one of the "
+                    + f"following: {valid_pps}. Please use one of these instead if you wish to "
+                    + "include theory uncertainties here."
+                )
 
-        # Get dictionary containing theoryid and variations for central theory from runcard
-        for scalevarsfor_dict in scalevarsfor_list:
-            if scalevarsfor_dict["theoryid"] == int(th):
-                theoryid_variations = scalevarsfor_dict
+            # Get dictionary containing theoryid and variations for central theory from runcard
+            for scalevarsfor_dict in scalevarsfor_list:
+                if scalevarsfor_dict["theoryid"] == int(th):
+                    theoryid_variations = scalevarsfor_dict
 
-        # Find theoryids for given point prescription for given central theoryid
-        try:
-            thids = [theoryid_variations["variations"][scale] for scale in scales]
-        except KeyError:
-            available_scales = list(theoryid_variations["variations"])
-            missing_scales = []
-            for scale in scales:
-                if scale not in available_scales:
-                    missing_scales.append(scale)
-            missing_scales_string = ", ".join(missing_scales)
-            raise ConfigError(
-                "For this central theoryid, the requested point prescription is not currently "
-                + "available. To use this point prescription for this central theoryid, theoryids "
-                + "that correspond to the following scale choices must be created and added to "
-                + "validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml: "
-                + f"(k_F, k_R) = {missing_scales_string}."
-            )
+            # Find theoryids for given point prescription for given central theoryid
+            try:
+                thids = [theoryid_variations["variations"][scale] for scale in scales]
+            except KeyError:
+                available_scales = list(theoryid_variations["variations"])
+                missing_scales = []
+                for scale in scales:
+                    if scale not in available_scales:
+                        missing_scales.append(scale)
+                missing_scales_string = ", ".join(missing_scales)
+                raise ConfigError(
+                    "For this central theoryid, the requested point prescription is not currently "
+                    + "available. To use this point prescription for this central theoryid, theoryids "
+                    + "that correspond to the following scale choices must be created and added to "
+                    + "validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml: "
+                    + f"(k_F, k_R) = {missing_scales_string}."
+                )
+
+            # Check each theory is loaded
+            theoryids = [self.loader.check_theoryID(thid) for thid in thids]
+            pp_thids[pp] = NSList(theoryids, nskey="theoryid")
+
+        return pp_thids
 
-        # Check each theory is loaded
-        theoryids = [self.loader.check_theoryID(thid) for thid in thids]
-        # NSList needs to be used for theoryids to be recognised as a namespace
-        return NSList(theoryids, nskey="theoryid")
+    def produce_theoryids(self, point_prescriptions_theoryids, point_prescription):
+        return point_prescriptions_theoryids[point_prescription]
 
     @configparser.explicit_node
     def produce_filter_data(self, fakedata: bool = False, theorycovmatconfig=None):

validphys2/src/validphys/theorycovariance/construction.py

@@ -53,7 +53,7 @@ def theory_covmat_dataset(
 ProcessInfo = namedtuple("ProcessInfo", ("preds", "namelist", "sizes"))
 
 
-def combine_by_type(each_dataset_results_central_bytheory):
+def combine_by_type(each_dataset_results_central_bytheory, theoryids):
     """Groups the datasets bu process and returns an instance of the ProcessInfo class
 
     Parameters
@@ -523,6 +523,9 @@ def theory_covmat_custom_fitting(theory_covmat_custom, procs_index_matched):
     return df
 
 
+theory_covmats_fitting = collect(theory_covmat_custom_fitting, ("point_prescriptions",))
+
+
 def total_theory_covmat_fitting(total_theory_covmat, procs_index_matched):
     """total_theory_covmat but reindexed so the order of the datasets matches
     those in the experiment covmat so they are aligned when fitting."""

validphys2/src/validphys/theorycovariance/theorycovarianceutils.py

@@ -23,7 +23,6 @@ def check_correct_theory_combination_internal(
         l in {3, 5, 7, 9, 62, 64, 66, 70, 19, 23},
         f"Expecting exactly 3, 5, 7, 9, 62, 64, 66, 23, 19 or 70 theories, but got {l}.",
     )
-    opts = {"bar", "nobar"}
     xifs = [theoryid.get_description()["XIF"] for theoryid in theoryids]
     xirs = [theoryid.get_description()["XIR"] for theoryid in theoryids]
     if l == 3: