Correct bug in linear function

Author: achiefa

validphys2/src/validphys/theorycovariance/higher_twist_functions.py

@@ -113,18 +113,17 @@ def linear_bin_function(
     a: npt.ArrayLike, y_shift: npt.ArrayLike, bin_edges: npt.ArrayLike
 ) -> np.ndarray:
     """
-    This function defines the linear bin function used to construct the prior. The bins of the
-    function are constructed using pairs of consecutive points. For instance, given the set of
-    points [0.0, 0.1, 0.3, 0.5], there will be three bins with edges [[0.0, 0.1], [0.1, 0.3],
-    0.3, 0.5]]. Each bin is coupled with a shift, which correspond to the y-value of the bin.
+    This function defines the linear bin function used to construct the prior. Specifically,
+    the prior is constructed using a triangular function whose value at the peak of the node
+    is linked to the right and left nodes using a straight line.
 
     Parameters
     ----------
     a:  ArrayLike of float
       A one-dimensional array of points at which the function is evaluated.
     y_shift:  ArrayLike of float
       A one-dimensional array whose elements represent the y-value of each bin
-    bin_edges: ArrayLike of float
+    bin_nodes: ArrayLike of float
       A one-dimensional array containing the edges of the bins. The bins are
       constructed using pairs of consecutive points.
 
@@ -153,7 +152,9 @@ def linear_bin_function(
             bin_high = bin_mid
             m1 = shift / (bin_mid - bin_low)
             m2 = 0.0
-        cond_low = np.multiply(a >= bin_low, a < bin_mid)
+        cond_low = np.multiply(
+            a >= bin_low, a < bin_mid if shift_pos != len(y_shift) - 1 else a <= bin_mid
+        )
         cond_high = np.multiply(
             a >= bin_mid, a < bin_high if shift_pos != len(y_shift) - 1 else a <= bin_high
         )
@@ -1052,7 +1053,6 @@ def average(y_values_pc2_p, y_values_pcL_p, y_values_pc3_p):
         # When this happens, this part must be updated.
         eta = cd_table['kin1'].to_numpy()
         pT = cd_table['kin2'].to_numpy()
-        q2 = pT * pT
 
         pc_func = JET_pc(pc_jet_nodes, pT, eta, pc_func_type)
         for pars_pc in pars_combs: