merged latest development branch
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@@ -63,8 +63,8 @@ class Backtesting(object):
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self.strategy: IStrategy = StrategyResolver(self.config).strategy
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self.ticker_interval = self.strategy.ticker_interval
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self.tickerdata_to_dataframe = self.strategy.tickerdata_to_dataframe
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self.populate_buy_trend = self.strategy.populate_buy_trend
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self.populate_sell_trend = self.strategy.populate_sell_trend
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self.advise_buy = self.strategy.advise_buy
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self.advise_sell = self.strategy.advise_sell
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# Reset keys for backtesting
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self.config['exchange']['key'] = ''
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@@ -292,8 +292,8 @@ class Backtesting(object):
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pair_data['buy'], pair_data['sell'] = 0, 0 # cleanup from previous run
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ticker_data = self.populate_sell_trend(
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self.populate_buy_trend(pair_data))[headers].copy()
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ticker_data = self.advise_sell(
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self.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
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# to avoid using data from future, we buy/sell with signal from previous candle
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ticker_data.loc[:, 'buy'] = ticker_data['buy'].shift(1)
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@@ -75,7 +75,7 @@ class Hyperopt(Backtesting):
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return arg_dict
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@staticmethod
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def populate_indicators(dataframe: DataFrame) -> DataFrame:
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def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe['adx'] = ta.ADX(dataframe)
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macd = ta.MACD(dataframe)
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dataframe['macd'] = macd['macd']
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@@ -228,7 +228,7 @@ class Hyperopt(Backtesting):
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"""
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Define the buy strategy parameters to be used by hyperopt
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"""
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def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
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def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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Buy strategy Hyperopt will build and use
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"""
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@@ -270,7 +270,7 @@ class Hyperopt(Backtesting):
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self.strategy.minimal_roi = self.generate_roi_table(params)
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if self.has_space('buy'):
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self.populate_buy_trend = self.buy_strategy_generator(params)
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self.advise_buy = self.buy_strategy_generator(params)
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if self.has_space('stoploss'):
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self.strategy.stoploss = params['stoploss']
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@@ -351,7 +351,7 @@ class Hyperopt(Backtesting):
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)
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if self.has_space('buy'):
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self.strategy.populate_indicators = Hyperopt.populate_indicators # type: ignore
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self.strategy.advise_indicators = Hyperopt.populate_indicators # type: ignore
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dump(self.tickerdata_to_dataframe(data), TICKERDATA_PICKLE)
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self.exchange = None # type: ignore
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self.load_previous_results()
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@@ -360,7 +360,7 @@ class Hyperopt(Backtesting):
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logger.info(f'Found {cpus} CPU cores. Let\'s make them scream!')
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opt = self.get_optimizer(cpus)
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EVALS = max(self.total_tries//cpus, 1)
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EVALS = max(self.total_tries // cpus, 1)
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try:
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with Parallel(n_jobs=cpus) as parallel:
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for i in range(EVALS):
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