From 778833f90e0bc8ec04a030b6c93982d15e49c8f2 Mon Sep 17 00:00:00 2001 From: Matthias Date: Thu, 4 Aug 2022 07:17:26 +0200 Subject: [PATCH] Modify comment in new test-strategies to point out their purpose --- .../strats/freqai_test_multimodel_strat.py | 28 ++----------------- tests/strategy/strats/freqai_test_strat.py | 28 ++----------------- 2 files changed, 4 insertions(+), 52 deletions(-) diff --git a/tests/strategy/strats/freqai_test_multimodel_strat.py b/tests/strategy/strats/freqai_test_multimodel_strat.py index e58086757..4f8877f14 100644 --- a/tests/strategy/strats/freqai_test_multimodel_strat.py +++ b/tests/strategy/strats/freqai_test_multimodel_strat.py @@ -13,13 +13,8 @@ logger = logging.getLogger(__name__) class freqai_test_multimodel_strat(IStrategy): """ - Example strategy showing how the user connects their own - IFreqaiModel to the strategy. Namely, the user uses: - self.freqai.start(dataframe, metadata) - - to make predictions on their data. populate_any_indicators() automatically - generates the variety of features indicated by the user in the - canonical freqtrade configuration file under config['freqai']. + Test strategy - used for testing freqAI multimodel functionalities. + DO not use in production. """ minimal_roi = {"0": 0.1, "240": -1} @@ -64,20 +59,6 @@ class freqai_test_multimodel_strat(IStrategy): def populate_any_indicators( self, pair, df, tf, informative=None, set_generalized_indicators=False ): - """ - Function designed to automatically generate, name and merge features - from user indicated timeframes in the configuration file. User controls the indicators - passed to the training/prediction by prepending indicators with `'%-' + coin ` - (see convention below). I.e. user should not prepend any supporting metrics - (e.g. bb_lowerband below) with % unless they explicitly want to pass that metric to the - model. - :params: - :pair: pair to be used as informative - :df: strategy dataframe which will receive merges from informatives - :tf: timeframe of the dataframe which will modify the feature names - :informative: the dataframe associated with the informative pair - :coin: the name of the coin which will modify the feature names. - """ coin = pair.split('/')[0] @@ -149,11 +130,6 @@ class freqai_test_multimodel_strat(IStrategy): self.freqai_info = self.config["freqai"] - # All indicators must be populated by populate_any_indicators() for live functionality - # to work correctly. - # the model will return 4 values, its prediction, an indication of whether or not the - # prediction should be accepted, the target mean/std values from the labels used during - # each training period. dataframe = self.freqai.start(dataframe, metadata, self) dataframe["target_roi"] = dataframe["&-s_close_mean"] + dataframe["&-s_close_std"] * 1.25 diff --git a/tests/strategy/strats/freqai_test_strat.py b/tests/strategy/strats/freqai_test_strat.py index 8288228d1..e239a30b0 100644 --- a/tests/strategy/strats/freqai_test_strat.py +++ b/tests/strategy/strats/freqai_test_strat.py @@ -13,13 +13,8 @@ logger = logging.getLogger(__name__) class freqai_test_strat(IStrategy): """ - Example strategy showing how the user connects their own - IFreqaiModel to the strategy. Namely, the user uses: - self.freqai.start(dataframe, metadata) - - to make predictions on their data. populate_any_indicators() automatically - generates the variety of features indicated by the user in the - canonical freqtrade configuration file under config['freqai']. + Test strategy - used for testing freqAI functionalities. + DO not use in production. """ minimal_roi = {"0": 0.1, "240": -1} @@ -64,20 +59,6 @@ class freqai_test_strat(IStrategy): def populate_any_indicators( self, pair, df, tf, informative=None, set_generalized_indicators=False ): - """ - Function designed to automatically generate, name and merge features - from user indicated timeframes in the configuration file. User controls the indicators - passed to the training/prediction by prepending indicators with `'%-' + coin ` - (see convention below). I.e. user should not prepend any supporting metrics - (e.g. bb_lowerband below) with % unless they explicitly want to pass that metric to the - model. - :params: - :pair: pair to be used as informative - :df: strategy dataframe which will receive merges from informatives - :tf: timeframe of the dataframe which will modify the feature names - :informative: the dataframe associated with the informative pair - :coin: the name of the coin which will modify the feature names. - """ coin = pair.split('/')[0] @@ -137,11 +118,6 @@ class freqai_test_strat(IStrategy): self.freqai_info = self.config["freqai"] - # All indicators must be populated by populate_any_indicators() for live functionality - # to work correctly. - # the model will return 4 values, its prediction, an indication of whether or not the - # prediction should be accepted, the target mean/std values from the labels used during - # each training period. dataframe = self.freqai.start(dataframe, metadata, self) dataframe["target_roi"] = dataframe["&-s_close_mean"] + dataframe["&-s_close_std"] * 1.25