From 006b11e5d5d7c8ca388dd9dd7ad765cd22da1ea6 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Sun, 14 Aug 2022 21:42:55 +0200
Subject: [PATCH] fix leftover bug in indicator population

---
 freqtrade/freqai/data_kitchen.py | 34 ++++++++++++++++----------------
 1 file changed, 17 insertions(+), 17 deletions(-)

diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index cf0af6c08..35f51baed 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -965,23 +965,23 @@ class FreqaiDataKitchen:
         for tf in tfs:
             if tf == tfs[-1]:
                 sgi = True  # doing this last allows user to use all tf raw prices in labels
-                dataframe = strategy.populate_any_indicators(
-                    pair,
-                    dataframe.copy(),
-                    tf,
-                    informative=base_dataframes[tf],
-                    set_generalized_indicators=sgi
-                )
-                if pairs:
-                    for i in pairs:
-                        if pair in i:
-                            continue  # dont repeat anything from whitelist
-                        dataframe = strategy.populate_any_indicators(
-                            i,
-                            dataframe.copy(),
-                            tf,
-                            informative=corr_dataframes[i][tf]
-                        )
+            dataframe = strategy.populate_any_indicators(
+                pair,
+                dataframe.copy(),
+                tf,
+                informative=base_dataframes[tf],
+                set_generalized_indicators=sgi
+            )
+            if pairs:
+                for i in pairs:
+                    if pair in i:
+                        continue  # dont repeat anything from whitelist
+                    dataframe = strategy.populate_any_indicators(
+                        i,
+                        dataframe.copy(),
+                        tf,
+                        informative=corr_dataframes[i][tf]
+                    )
 
         self.get_unique_classes_from_labels(dataframe)