Jets with single parameters

Author: achiefa

validphys2/src/validphys/theorycovariance/higher_twist_functions.py

@@ -246,6 +246,11 @@ def jets_pc_func(
     return PC
 
 
+def jet_single_par(delta_h: float, pT: npt.ArrayLike, rap: npt.ArrayLike) -> npt.ArrayLike:
+    ret = [delta_h for _ in range(rap.size)]
+    return np.array(ret) / pT
+
+
 def JET_pc(dataset_sp, pdf, pc_nodes, pT, rap, pc_func_type: str = "step"):
     """
     Returns the function that computes the shift for the ratio for single
@@ -271,6 +276,26 @@ def func(y_values):
     return func
 
 
+def JET_pc_single_par(dataset_sp, pdf, pc_nodes, pT, rap, pc_func_type: str = "step"):
+    """
+    As JET_pc, but with one single shift for all rapidity bins.
+
+    This function is meant to be for development purposes only. It will either substitute
+    JET_pc or be deleted in the future."""
+    cuts = dataset_sp.cuts
+    (fkspec,) = dataset_sp.fkspecs
+    fk = fkspec.load_with_cuts(cuts)
+    xsec = central_fk_predictions(fk, pdf)
+
+    def func(y_values):
+        assert y_values.size == 1
+        ret = [y_values[0] for _ in range(rap.size)]
+        ret = np.array(ret) / pT
+        return np.multiply(ret, xsec.to_numpy()[:, 0])
+
+    return func
+
+
 # TODO Maybe we want to treat the function that parametrizes the PC
 # as argument?
 def DIS_F2_pc(pc2_nodes, x, q2, pc_func_type: str = "step"):
@@ -1046,7 +1071,7 @@ def average(y_values_pc2_p, y_values_pcL_p, y_values_pc3_p):
         eta = dataset_sp.commondata.metadata.load_kinematics()['y'].to_numpy().reshape(-1)[cuts]
         pT = dataset_sp.commondata.metadata.load_kinematics()['pT'].to_numpy().reshape(-1)[cuts]
 
-        pc_func = JET_pc(dataset_sp, pdf, pc_jet_nodes, pT, eta, pc_func_type)
+        pc_func = JET_pc_single_par(dataset_sp, pdf, pc_jet_nodes, pT, eta, pc_func_type)
         for pars_pc in pars_combs:
             deltas[pars_pc['label']] = pc_func(pars_pc['comb']['Hj'])
 
@@ -1064,7 +1089,7 @@ def average(y_values_pc2_p, y_values_pcL_p, y_values_pc3_p):
                 .to_numpy()
                 .reshape(-1)[cuts]
             )
-            pc_func = JET_pc(dataset_sp, pdf, pc_jet_nodes, m_jj, eta_star, pc_func_type)
+            pc_func = JET_pc_single_par(dataset_sp, pdf, pc_jet_nodes, m_jj, eta_star, pc_func_type)
             for pars_pc in pars_combs:
                 deltas[pars_pc['label']] = pc_func(pars_pc['comb']['H2j_ATLAS'])
 
@@ -1080,7 +1105,7 @@ def average(y_values_pc2_p, y_values_pcL_p, y_values_pc3_p):
                 .to_numpy()
                 .reshape(-1)[cuts]
             )
-            pc_func = JET_pc(dataset_sp, pdf, pc_jet_nodes, m_jj, eta_diff, pc_func_type)
+            pc_func = JET_pc_single_par(dataset_sp, pdf, pc_jet_nodes, m_jj, eta_diff, pc_func_type)
             for pars_pc in pars_combs:
                 deltas[pars_pc['label']] = pc_func(pars_pc['comb']['H2j_CMS'])