From 0d4a2c6c3af13d614cca871661fd2a4daeab4f64 Mon Sep 17 00:00:00 2001 From: hroff-1902 Date: Thu, 8 Aug 2019 22:45:37 +0300 Subject: [PATCH] advanced sample hyperopt added; changes to helpstrings --- freqtrade/optimize/default_hyperopt.py | 3 +- user_data/hyperopts/sample_hyperopt.py | 16 +- .../hyperopts/sample_hyperopt_advanced.py | 261 ++++++++++++++++++ 3 files changed, 271 insertions(+), 9 deletions(-) create mode 100644 user_data/hyperopts/sample_hyperopt_advanced.py diff --git a/freqtrade/optimize/default_hyperopt.py b/freqtrade/optimize/default_hyperopt.py index 1d4c40916..e05dfc95c 100644 --- a/freqtrade/optimize/default_hyperopt.py +++ b/freqtrade/optimize/default_hyperopt.py @@ -13,10 +13,9 @@ from freqtrade.optimize.hyperopt_interface import IHyperOpt class DefaultHyperOpts(IHyperOpt): """ - Default hyperopt provided by freqtrade bot. + Default hyperopt provided by the Freqtrade bot. You can override it with your own hyperopt """ - @staticmethod def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe['adx'] = ta.ADX(dataframe) diff --git a/user_data/hyperopts/sample_hyperopt.py b/user_data/hyperopts/sample_hyperopt.py index 9a755e52e..1a3823afa 100644 --- a/user_data/hyperopts/sample_hyperopt.py +++ b/user_data/hyperopts/sample_hyperopt.py @@ -14,25 +14,27 @@ import freqtrade.vendor.qtpylib.indicators as qtpylib from freqtrade.optimize.hyperopt_interface import IHyperOpt -# This class is a sample. Feel free to customize it. class SampleHyperOpts(IHyperOpt): """ - This is a test hyperopt to inspire you. + This is a sample hyperopt to inspire you. + Feel free to customize it. More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md - You can: - - Rename the class name. + You should: + - Rename the class name to some unique name. - Add any methods you want to build your hyperopt. - Add any lib you need to build your hyperopt. You must keep: - The prototypes for the methods: populate_indicators, indicator_space, buy_strategy_generator. - The roi_space, generate_roi_table, stoploss_space methods were moved to the parent class, you may - override them here if you need it. + The roi_space, generate_roi_table, stoploss_space methods are no longer required to be + copied in every custom hyperopt. However, you may override them if you need the + 'roi' and the 'stoploss' spaces that differ from the defaults offered by Freqtrade. + Sample implementation of these methods can be found in + https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt_advanced.py """ - @staticmethod def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe['adx'] = ta.ADX(dataframe) diff --git a/user_data/hyperopts/sample_hyperopt_advanced.py b/user_data/hyperopts/sample_hyperopt_advanced.py new file mode 100644 index 000000000..00062a58d --- /dev/null +++ b/user_data/hyperopts/sample_hyperopt_advanced.py @@ -0,0 +1,261 @@ +# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement + +from functools import reduce +from math import exp +from typing import Any, Callable, Dict, List +from datetime import datetime + +import numpy as np# noqa F401 +import talib.abstract as ta +from pandas import DataFrame +from skopt.space import Categorical, Dimension, Integer, Real + +import freqtrade.vendor.qtpylib.indicators as qtpylib +from freqtrade.optimize.hyperopt_interface import IHyperOpt + + +class AdvancedSampleHyperOpts(IHyperOpt): + """ + This is a sample hyperopt to inspire you. + Feel free to customize it. + + More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md + + You should: + - Rename the class name to some unique name. + - Add any methods you want to build your hyperopt. + - Add any lib you need to build your hyperopt. + + You must keep: + - The prototypes for the methods: populate_indicators, indicator_space, buy_strategy_generator. + + The roi_space, generate_roi_table, stoploss_space methods are no longer required to be + copied in every custom hyperopt. However, you may override them if you need the + 'roi' and the 'stoploss' spaces that differ from the defaults offered by Freqtrade. + + This sample illustrates how to override these methods. + """ + @staticmethod + def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame: + dataframe['adx'] = ta.ADX(dataframe) + macd = ta.MACD(dataframe) + dataframe['macd'] = macd['macd'] + dataframe['macdsignal'] = macd['macdsignal'] + dataframe['mfi'] = ta.MFI(dataframe) + dataframe['rsi'] = ta.RSI(dataframe) + stoch_fast = ta.STOCHF(dataframe) + dataframe['fastd'] = stoch_fast['fastd'] + dataframe['minus_di'] = ta.MINUS_DI(dataframe) + # Bollinger bands + bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2) + dataframe['bb_lowerband'] = bollinger['lower'] + dataframe['bb_upperband'] = bollinger['upper'] + dataframe['sar'] = ta.SAR(dataframe) + return dataframe + + @staticmethod + def buy_strategy_generator(params: Dict[str, Any]) -> Callable: + """ + Define the buy strategy parameters to be used by hyperopt + """ + def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame: + """ + Buy strategy Hyperopt will build and use + """ + conditions = [] + # GUARDS AND TRENDS + if 'mfi-enabled' in params and params['mfi-enabled']: + conditions.append(dataframe['mfi'] < params['mfi-value']) + if 'fastd-enabled' in params and params['fastd-enabled']: + conditions.append(dataframe['fastd'] < params['fastd-value']) + if 'adx-enabled' in params and params['adx-enabled']: + conditions.append(dataframe['adx'] > params['adx-value']) + if 'rsi-enabled' in params and params['rsi-enabled']: + conditions.append(dataframe['rsi'] < params['rsi-value']) + + # TRIGGERS + if 'trigger' in params: + if params['trigger'] == 'bb_lower': + conditions.append(dataframe['close'] < dataframe['bb_lowerband']) + if params['trigger'] == 'macd_cross_signal': + conditions.append(qtpylib.crossed_above( + dataframe['macd'], dataframe['macdsignal'] + )) + if params['trigger'] == 'sar_reversal': + conditions.append(qtpylib.crossed_above( + dataframe['close'], dataframe['sar'] + )) + + if conditions: + dataframe.loc[ + reduce(lambda x, y: x & y, conditions), + 'buy'] = 1 + + return dataframe + + return populate_buy_trend + + @staticmethod + def indicator_space() -> List[Dimension]: + """ + Define your Hyperopt space for searching strategy parameters + """ + return [ + Integer(10, 25, name='mfi-value'), + Integer(15, 45, name='fastd-value'), + Integer(20, 50, name='adx-value'), + Integer(20, 40, name='rsi-value'), + Categorical([True, False], name='mfi-enabled'), + Categorical([True, False], name='fastd-enabled'), + Categorical([True, False], name='adx-enabled'), + Categorical([True, False], name='rsi-enabled'), + Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger') + ] + + @staticmethod + def sell_strategy_generator(params: Dict[str, Any]) -> Callable: + """ + Define the sell strategy parameters to be used by hyperopt + """ + def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame: + """ + Sell strategy Hyperopt will build and use + """ + # print(params) + conditions = [] + # GUARDS AND TRENDS + if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']: + conditions.append(dataframe['mfi'] > params['sell-mfi-value']) + if 'sell-fastd-enabled' in params and params['sell-fastd-enabled']: + conditions.append(dataframe['fastd'] > params['sell-fastd-value']) + if 'sell-adx-enabled' in params and params['sell-adx-enabled']: + conditions.append(dataframe['adx'] < params['sell-adx-value']) + if 'sell-rsi-enabled' in params and params['sell-rsi-enabled']: + conditions.append(dataframe['rsi'] > params['sell-rsi-value']) + + # TRIGGERS + if 'sell-trigger' in params: + if params['sell-trigger'] == 'sell-bb_upper': + conditions.append(dataframe['close'] > dataframe['bb_upperband']) + if params['sell-trigger'] == 'sell-macd_cross_signal': + conditions.append(qtpylib.crossed_above( + dataframe['macdsignal'], dataframe['macd'] + )) + if params['sell-trigger'] == 'sell-sar_reversal': + conditions.append(qtpylib.crossed_above( + dataframe['sar'], dataframe['close'] + )) + + if conditions: + dataframe.loc[ + reduce(lambda x, y: x & y, conditions), + 'sell'] = 1 + + return dataframe + + return populate_sell_trend + + @staticmethod + def sell_indicator_space() -> List[Dimension]: + """ + Define your Hyperopt space for searching sell strategy parameters + """ + return [ + Integer(75, 100, name='sell-mfi-value'), + Integer(50, 100, name='sell-fastd-value'), + Integer(50, 100, name='sell-adx-value'), + Integer(60, 100, name='sell-rsi-value'), + Categorical([True, False], name='sell-mfi-enabled'), + Categorical([True, False], name='sell-fastd-enabled'), + Categorical([True, False], name='sell-adx-enabled'), + Categorical([True, False], name='sell-rsi-enabled'), + Categorical(['sell-bb_upper', + 'sell-macd_cross_signal', + 'sell-sar_reversal'], name='sell-trigger') + ] + + @staticmethod + def generate_roi_table(params: Dict) -> Dict[int, float]: + """ + Generate the ROI table that will be used by Hyperopt + + This implementation generates the default legacy Freqtrade ROI tables. + + Change it if you need different number of steps in the generated + ROI tables or other structure of the ROI tables. + + Please keep it aligned with parameters in the 'roi' optimization + hyperspace defined by the roi_space method. + """ + roi_table = {} + roi_table[0] = params['roi_p1'] + params['roi_p2'] + params['roi_p3'] + roi_table[params['roi_t3']] = params['roi_p1'] + params['roi_p2'] + roi_table[params['roi_t3'] + params['roi_t2']] = params['roi_p1'] + roi_table[params['roi_t3'] + params['roi_t2'] + params['roi_t1']] = 0 + + return roi_table + + @staticmethod + def roi_space() -> List[Dimension]: + """ + Values to search for each ROI steps + + Override it if you need some different ranges for the parameters in the + 'roi' optimization hyperspace. + + Please keep it aligned with the implementation of the + generate_roi_table method. + """ + return [ + Integer(10, 120, name='roi_t1'), + Integer(10, 60, name='roi_t2'), + Integer(10, 40, name='roi_t3'), + Real(0.01, 0.04, name='roi_p1'), + Real(0.01, 0.07, name='roi_p2'), + Real(0.01, 0.20, name='roi_p3'), + ] + + @staticmethod + def stoploss_space() -> List[Dimension]: + """ + Stoploss Value to search + + Override it if you need some different range for the parameter in the + 'stoploss' optimization hyperspace. + """ + return [ + Real(-0.5, -0.02, name='stoploss'), + ] + + def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + """ + Based on TA indicators. Should be a copy of from strategy + must align to populate_indicators in this file + Only used when --spaces does not include buy + """ + dataframe.loc[ + ( + (dataframe['close'] < dataframe['bb_lowerband']) & + (dataframe['mfi'] < 16) & + (dataframe['adx'] > 25) & + (dataframe['rsi'] < 21) + ), + 'buy'] = 1 + + return dataframe + + def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + """ + Based on TA indicators. Should be a copy of from strategy + must align to populate_indicators in this file + Only used when --spaces does not include sell + """ + dataframe.loc[ + ( + (qtpylib.crossed_above( + dataframe['macdsignal'], dataframe['macd'] + )) & + (dataframe['fastd'] > 54) + ), + 'sell'] = 1 + return dataframe