From dac07c56096e8c94aad65862eb656ae0c77ead69 Mon Sep 17 00:00:00 2001 From: robcaulk Date: Fri, 16 Sep 2022 01:15:19 +0200 Subject: [PATCH] ensure pytest passes --- freqtrade/freqai/spice_rack/test_config.json | 30 +++++ .../strategy/strats/freqai_test_spice_rack.py | 115 ++++++++++++++++++ tests/strategy/test_strategy_loading.py | 6 +- 3 files changed, 148 insertions(+), 3 deletions(-) create mode 100644 freqtrade/freqai/spice_rack/test_config.json create mode 100644 tests/strategy/strats/freqai_test_spice_rack.py diff --git a/freqtrade/freqai/spice_rack/test_config.json b/freqtrade/freqai/spice_rack/test_config.json new file mode 100644 index 000000000..6cf0df2e1 --- /dev/null +++ b/freqtrade/freqai/spice_rack/test_config.json @@ -0,0 +1,30 @@ +{ + + "freqai": { + "enabled": true, + "purge_old_models": true, + "train_period_days": 4, + "backtest_period_days": 2, + "identifier": "spicy-id", + "feature_parameters": { + "include_timeframes": [ + "5m" + ], + "include_corr_pairlist": ["ADA/BTC", "DASH/BTC"], + "label_period_candles": 20, + "include_shifted_candles": 1, + "DI_threshold": 0.9, + "weight_factor": 0.9, + "indicator_periods_candles": [ + 10 + ] + }, + "data_split_parameters": { + "test_size": 0, + "random_state": 1 + }, + "model_training_parameters": { + "n_estimators": 800 + } + } +} diff --git a/tests/strategy/strats/freqai_test_spice_rack.py b/tests/strategy/strats/freqai_test_spice_rack.py new file mode 100644 index 000000000..95105ab8f --- /dev/null +++ b/tests/strategy/strats/freqai_test_spice_rack.py @@ -0,0 +1,115 @@ +import logging +from functools import reduce + +import pandas as pd +import talib.abstract as ta +from pandas import DataFrame + +from freqtrade.strategy import DecimalParameter, IntParameter, IStrategy, merge_informative_pair + + +logger = logging.getLogger(__name__) + + +class freqai_test_spice_rack(IStrategy): + """ + Test strategy - used for testing freqAI functionalities. + DO not use in production. + """ + + minimal_roi = {"0": 0.1, "240": -1} + + plot_config = { + "main_plot": {}, + "subplots": { + "prediction": {"prediction": {"color": "blue"}}, + "target_roi": { + "target_roi": {"color": "brown"}, + }, + "do_predict": { + "do_predict": {"color": "brown"}, + }, + }, + } + + process_only_new_candles = True + stoploss = -0.05 + use_exit_signal = True + startup_candle_count: int = 300 + can_short = False + + linear_roi_offset = DecimalParameter( + 0.00, 0.02, default=0.005, space="sell", optimize=False, load=True + ) + 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_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + + # Example of how to use the freqai.spice_rack. User treats it the same as any + # typical talib indicator. They set a new column in their dataframe + + dataframe['dissimilarity_index'] = self.freqai.spice_rack( + 'DI_values', dataframe, metadata, self) + dataframe['maxima'] = self.freqai.spice_rack( + '&s-maxima', dataframe, metadata, self) + dataframe['minima'] = self.freqai.spice_rack( + '&s-minima', dataframe, metadata, self) + self.freqai.close_spice_rack() # user must close the spicerack + + dataframe['rsi'] = ta.RSI(dataframe) + + return dataframe + + def populate_entry_trend(self, df: DataFrame, metadata: dict) -> DataFrame: + + df.loc[ + ( + (df['tema'] > df['tema'].shift(1)) & # Guard: tema is raising + (df['dissimilarity_index'] < 1) & + (df['maxima'] > 0.1) + ), + 'enter_long'] = 1 + + df.loc[ + ( + (df['tema'] < df['tema'].shift(1)) & # Guard: tema is falling + (df['dissimilarity_index'] < 1) & + (df['minima'] > 0.1) + ), + 'enter_short'] = 1 + + return df + + def populate_exit_trend(self, df: DataFrame, metadata: dict) -> DataFrame: + + df.loc[ + ( + (df['tema'] < df['tema'].shift(1)) & # Guard: tema is falling + (df['dissimilarity_index'] < 1) & + (df['maxima'] > 0.1) + ), + + 'exit_long'] = 1 + + df.loc[ + ( + (df['tema'] > df['tema'].shift(1)) & # Guard: tema is raising + (df['dissimilarity_index'] < 1) & + (df['minima'] > 0.1) + ), + 'exit_short'] = 1 + + return df diff --git a/tests/strategy/test_strategy_loading.py b/tests/strategy/test_strategy_loading.py index bf81cd068..c728a81b0 100644 --- a/tests/strategy/test_strategy_loading.py +++ b/tests/strategy/test_strategy_loading.py @@ -34,7 +34,7 @@ def test_search_all_strategies_no_failed(): directory = Path(__file__).parent / "strats" strategies = StrategyResolver.search_all_objects(directory, enum_failed=False) assert isinstance(strategies, list) - assert len(strategies) == 9 + assert len(strategies) == 10 assert isinstance(strategies[0], dict) @@ -42,10 +42,10 @@ def test_search_all_strategies_with_failed(): directory = Path(__file__).parent / "strats" strategies = StrategyResolver.search_all_objects(directory, enum_failed=True) assert isinstance(strategies, list) - assert len(strategies) == 10 + assert len(strategies) == 11 # with enum_failed=True search_all_objects() shall find 2 good strategies # and 1 which fails to load - assert len([x for x in strategies if x['class'] is not None]) == 9 + assert len([x for x in strategies if x['class'] is not None]) == 10 assert len([x for x in strategies if x['class'] is None]) == 1 directory = Path(__file__).parent / "strats_nonexistingdir"