Clean up no longer needed informative sample code

docs/freqai.md

@@ -190,19 +190,6 @@ The FreqAI strategy requires the user to include the following lines of code in
     # passed to any single indicator)
     startup_candle_count: int = 20
 
-    def informative_pairs(self):
-        whitelist_pairs = self.dp.current_whitelist()
-        corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"]
-        informative_pairs = []
-        for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]:
-            for pair in whitelist_pairs:
-                informative_pairs.append((pair, tf))
-            for pair in corr_pairs:
-                if pair in whitelist_pairs:
-                    continue  # avoid duplication
-                informative_pairs.append((pair, tf))
-        return informative_pairs
-
     def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
 
         # the model will return all labels created by user in `populate_any_indicators`

freqtrade/templates/FreqaiExampleStrategy.py

@@ -47,19 +47,6 @@ class FreqaiExampleStrategy(IStrategy):
     std_dev_multiplier_sell = CategoricalParameter(
         [0.1, 0.25, 0.4], space="sell", default=0.2, optimize=True)
 
-    def informative_pairs(self):
-        whitelist_pairs = self.dp.current_whitelist()
-        corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"]
-        informative_pairs = []
-        for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]:
-            for pair in whitelist_pairs:
-                informative_pairs.append((pair, tf))
-            for pair in corr_pairs:
-                if pair in whitelist_pairs:
-                    continue  # avoid duplication
-                informative_pairs.append((pair, tf))
-        return informative_pairs
-
     def populate_any_indicators(
         self, pair, df, tf, informative=None, set_generalized_indicators=False
     ):

freqtrade/templates/FreqaiHybridExampleStrategy.py

@@ -95,20 +95,6 @@ class FreqaiExampleHybridStrategy(IStrategy):
     short_rsi = IntParameter(low=51, high=100, default=70, space='sell', optimize=True, load=True)
     exit_short_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True)
 
-    # FreqAI required function, leave as is or add additional informatives to existing structure.
-    def informative_pairs(self):
-        whitelist_pairs = self.dp.current_whitelist()
-        corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"]
-        informative_pairs = []
-        for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]:
-            for pair in whitelist_pairs:
-                informative_pairs.append((pair, tf))
-            for pair in corr_pairs:
-                if pair in whitelist_pairs:
-                    continue  # avoid duplication
-                informative_pairs.append((pair, tf))
-        return informative_pairs
-
     # FreqAI required function, user can add or remove indicators, but general structure
     # must stay the same.
     def populate_any_indicators(

tests/strategy/strats/freqai_test_multimodel_strat.py

@@ -43,19 +43,6 @@ class freqai_test_multimodel_strat(IStrategy):
     )
     max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True)
 
-    def informative_pairs(self):
-        whitelist_pairs = self.dp.current_whitelist()
-        corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"]
-        informative_pairs = []
-        for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]:
-            for pair in whitelist_pairs:
-                informative_pairs.append((pair, tf))
-            for pair in corr_pairs:
-                if pair in whitelist_pairs:
-                    continue  # avoid duplication
-                informative_pairs.append((pair, tf))
-        return informative_pairs
-
     def populate_any_indicators(
         self, pair, df, tf, informative=None, set_generalized_indicators=False
     ):