Add Hyperopt file for AverageStrategy

2019-12-23 20:24:34 +01:00
parent 24fe931df2
commit 985f1868ac
2 changed files with 148 additions and 3 deletions
@@ -0,0 +1,148 @@
+import talib.abstract as ta
+from pandas import DataFrame
+from typing import Dict, Any, Callable, List
+from functools import reduce
+
+from skopt.space import Categorical, Dimension, Integer, Real
+
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+from freqtrade.optimize.hyperopt_interface import IHyperOpt
+
+shortRangeBegin = 10
+shortRangeEnd = 40
+mediumRangeBegin = 50
+mediumRangeEnd = 150
+
+
+class AverageHyperopt(IHyperOpt):
+    """
+    Hyperopt file for optimizing AverageStrategy.
+    Uses ranges of EMA periods to find the best parameter combination.
+    """
+
+    @staticmethod
+    def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
+
+        for short in range(shortRangeBegin, shortRangeEnd):
+            dataframe[f'maShort({short})'] = ta.EMA(dataframe, timeperiod=short)
+
+        for medium in range(mediumRangeBegin, mediumRangeEnd):
+            dataframe[f'maMedium({medium})'] = ta.EMA(dataframe, timeperiod=medium)
+
+        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 = []
+
+            # TRIGGERS
+            if 'trigger' in params:
+                for short in range(shortRangeBegin, shortRangeEnd):
+                    for medium in range(mediumRangeBegin, mediumRangeEnd):
+                        if params['trigger'] == f"cross_short({short})_above_medium({medium})":
+                            conditions.append(qtpylib.crossed_above(
+                                dataframe[f'maShort({short})'], dataframe[f'maMedium({medium})']))
+
+            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
+        """
+        buyTriggerList = []
+        for short in range(shortRangeBegin, shortRangeEnd):
+            for medium in range(mediumRangeBegin, mediumRangeEnd):
+                buyTriggerList.append(
+                    f'cross_short({short})_above_medium({medium}')
+        return [
+            Categorical(buyTriggerList, 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 = []
+
+            # TRIGGERS
+            if 'sell-trigger' in params:
+                for short in range(shortRangeBegin, shortRangeEnd):
+                    for medium in range(mediumRangeBegin, mediumRangeEnd):
+                        if params['sell-trigger'] == f'cross_medium({medium})_above_short({short})':
+                            conditions.append(qtpylib.crossed_above(
+                                dataframe[f'maMedium({medium})'], dataframe[f'maShort({short})']))
+
+            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
+        """
+        sellTriggerList = []
+        for short in range(shortRangeBegin, shortRangeEnd):
+            for medium in range(mediumRangeBegin, mediumRangeEnd):
+                sellTriggerList.append(
+                    f'cross_medium(medium)_above_short({short})')
+
+        return [
+            Categorical(sellTriggerList, name='sell-trigger')
+        ]
+
+    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[
+            (
+                qtpylib.crossed_above(
+                    dataframe['maShort'], dataframe['maMedium'])
+            ),
+            '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['maMedium'], dataframe['maShort'])
+            ),
+            'sell'] = 1
+
+        return dataframe