From 8910d9f4c7c7486848aa4881b0714e4ee36e3570 Mon Sep 17 00:00:00 2001
From: Aitor Bengoetxea <aitorabf@gmail.com>
Date: Mon, 27 Jun 2022 11:56:32 +0200
Subject: [PATCH] Update doctring and reconstruction

---
 sandy/core/lpc.py |  9 ++-------
 sandy/core/xs.py  |  4 ----
 sandy/pert.py     |  9 ++++++---
 sandy/pfns.py     | 26 ++++++++++++++------------
 sandy/shared.py   |  6 ++++++
 5 files changed, 28 insertions(+), 26 deletions(-)

diff --git a/sandy/core/lpc.py b/sandy/core/lpc.py
index 756e2e17..8b7d294e 100644
--- a/sandy/core/lpc.py
+++ b/sandy/core/lpc.py
@@ -188,14 +188,8 @@ def custom_perturbation(self, pert):
 
         Parameters
         ----------
-        pert : `sandy.Pert`
+        pert : `sandy.Pert` or pd.Dataframe
             tabulated perturbations
-        mat : `int`, optional
-            MAT material number. The default is None.
-        mt : `int`, optional
-            MT reaction number. The default is None.
-        p : `int`, optional
-            order of the Legendre polynomial coefficient. The default is None.
 
         Returns
         -------
@@ -224,6 +218,7 @@ def custom_perturbation(self, pert):
         Name: 1, dtype: float64
         """
         pert_ = sandy.Pert(pert) if not isinstance(pert, sandy.Pert) else pert
+        # Endf6 mf=34 incosistency solver:
         if 'L' in pert_.data.columns.names:
             pert_.data.columns = pert_.data.columns.set_names('P', level='L')
 
diff --git a/sandy/core/xs.py b/sandy/core/xs.py
index 9da849d3..b236990f 100644
--- a/sandy/core/xs.py
+++ b/sandy/core/xs.py
@@ -165,10 +165,6 @@ def custom_perturbation(self, pert, **kwargs):
         pert : `sandy.Pert` or `pd.Dataframe`
             tabulated perturbations with the index representing the energy grid
             and the columns representing MT.
-        mat : `int`, optional
-            MAT number. The default is None.
-        mt : `int`, optional
-            MT number. The default is None.
         **kwargs : `dict`
             keyword argument to pass to `sandy.Xs._recontruct_sums`.
 
diff --git a/sandy/pert.py b/sandy/pert.py
index 049029b0..8f3dd9b5 100644
--- a/sandy/pert.py
+++ b/sandy/pert.py
@@ -29,8 +29,8 @@ class Pert():
 
     Attributes
     ----------
-    data : `pandas.Series`
-        series of groupwise perturbation coefficients
+    data : `pandas.DataFrame`
+        DataFrame of groupwise perturbation coefficients
     left : `pandas.Series`
         perturbation coefficients with left-bounds of the energy intervals as
         index
@@ -114,7 +114,7 @@ def right(self):
 
         Returns
         -------
-        `pandas.Series`
+        `pandas.DataFrame`
             perturbations
 
         Examples
@@ -240,6 +240,9 @@ def reshape(self, eg, inplace=False, right_values=1):
             monotonic energy grid with non-negative values
         inplace : `bool`, optional, default is `False`
             apply changes **inplace** and return `None`
+        right_values: `float`, optional, default is 1
+            This value will be used to fill in for requested points outside of
+            the data range at the upper limit.
 
         Returns
         -------
diff --git a/sandy/pfns.py b/sandy/pfns.py
index 280b47b8..5ba84066 100644
--- a/sandy/pfns.py
+++ b/sandy/pfns.py
@@ -423,17 +423,17 @@ def normalize(self):
         1  9437  18  0 2.00000e+00 1.00000e+00
         """
         integrals = self.get_integrals()
-        data = self.data.copy()
-        keys = ["MAT", "MT", "K", "EIN"]
-        out = []
-        for (mat, mt, k, ein), chi in data.groupby(keys):
-            mask = (integrals.MAT == mat) & \
-                   (integrals.MT == mt) & \
-                   (integrals.K == k) & \
-                   (integrals.EIN == ein)
-            chi.loc[:, "VALUE"] /= integrals[mask].INTEGRAL.squeeze()
-            out.append(chi)
-        df = pd.concat(out)
+
+        def foo(df, integrals):
+            data = df.iloc[0]
+            mask = (integrals.MAT == data.MAT) & \
+                   (integrals.MT == data.MT) & \
+                   (integrals.K == data.K) & \
+                   (integrals.EIN == data.EIN)
+            df.loc[:, "VALUE"] /= integrals[mask].INTEGRAL.squeeze()
+            return df
+
+        df = self.data.groupby(["MAT", "MT", "K", "EIN"]).apply(foo, integrals)
         return self.__class__(df)
 
     def custom_perturbation(self, pert):
@@ -445,7 +445,7 @@ def custom_perturbation(self, pert):
 
         Parameters
         ----------
-        pert : `sandy.Pert` or `pd.Series`
+        pert : `sandy.Pert` or `pd.DataFrame`
             perturbation object.
 
         Returns
@@ -504,8 +504,10 @@ def foo(df, pert):
                              .values.flatten()
                 df["VALUE"] = df['VALUE'].values + pert_
             return df
+
         pert_edistr = self.data.groupby(['MAT', 'MT', 'K', 'EIN'])\
                           .apply(foo, u_pert)
+
         return self.__class__(pert_edistr).normalize()
 
     def _perturb(self, pert, method=2, normalize=True, **kwargs):
diff --git a/sandy/shared.py b/sandy/shared.py
index 4d005e9a..c95754ee 100644
--- a/sandy/shared.py
+++ b/sandy/shared.py
@@ -306,6 +306,12 @@ def reshape_bfill(x, y, xnew, left_values="first", right_values=0):
         new energy grid
     y : `numpy.ndarray` with at least two entries and same length as `x`
         array to interpolate
+    left_values:`str` or `float`
+        This value will be used to fill in for requested points outside of the
+        data range at the lower limit.ç
+    right_values:`str` or `float`
+        This value will be used to fill in for requested points outside of the
+        data range at the upper limit.
 
     Returns
     -------