Reverted freqtrade/templates/*hyperopt* files back to no shorting
This commit is contained in:
Sam Germain
@@ -55,10 +55,6 @@ class SampleHyperOpt(IHyperOpt):
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Integer(15, 45, name='fastd-value'),
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Integer(20, 50, name='adx-value'),
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Integer(20, 40, name='rsi-value'),
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Integer(75, 90, name='short-mfi-value'),
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Integer(55, 85, name='short-fastd-value'),
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Integer(50, 80, name='short-adx-value'),
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Integer(60, 80, name='short-rsi-value'),
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Categorical([True, False], name='mfi-enabled'),
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Categorical([True, False], name='fastd-enabled'),
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Categorical([True, False], name='adx-enabled'),
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@@ -76,60 +72,40 @@ class SampleHyperOpt(IHyperOpt):
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Buy strategy Hyperopt will build and use.
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"""
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long_conditions = []
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short_conditions = []
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# GUARDS AND TRENDS
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if 'mfi-enabled' in params and params['mfi-enabled']:
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long_conditions.append(dataframe['mfi'] < params['mfi-value'])
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short_conditions.append(dataframe['mfi'] > params['short-mfi-value'])
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if 'fastd-enabled' in params and params['fastd-enabled']:
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long_conditions.append(dataframe['fastd'] < params['fastd-value'])
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short_conditions.append(dataframe['fastd'] > params['short-fastd-value'])
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if 'adx-enabled' in params and params['adx-enabled']:
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long_conditions.append(dataframe['adx'] > params['adx-value'])
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short_conditions.append(dataframe['adx'] < params['short-adx-value'])
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if 'rsi-enabled' in params and params['rsi-enabled']:
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long_conditions.append(dataframe['rsi'] < params['rsi-value'])
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short_conditions.append(dataframe['rsi'] > params['short-rsi-value'])
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# TRIGGERS
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if 'trigger' in params:
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if params['trigger'] == 'boll':
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long_conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
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short_conditions.append(dataframe['close'] > dataframe['bb_upperband'])
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if params['trigger'] == 'macd_cross_signal':
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long_conditions.append(qtpylib.crossed_above(
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dataframe['macd'],
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dataframe['macdsignal']
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))
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short_conditions.append(qtpylib.crossed_below(
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dataframe['macd'],
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dataframe['macdsignal']
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))
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if params['trigger'] == 'sar_reversal':
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long_conditions.append(qtpylib.crossed_above(
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dataframe['close'],
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dataframe['sar']
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))
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short_conditions.append(qtpylib.crossed_below(
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dataframe['close'],
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dataframe['sar']
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))
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# Check that volume is not 0
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long_conditions.append(dataframe['volume'] > 0)
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short_conditions.append(dataframe['volume'] > 0)
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if long_conditions:
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dataframe.loc[
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reduce(lambda x, y: x & y, long_conditions),
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'buy'] = 1
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if short_conditions:
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dataframe.loc[
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reduce(lambda x, y: x & y, short_conditions),
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'enter_short'] = 1
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return dataframe
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return populate_buy_trend
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@@ -144,10 +120,6 @@ class SampleHyperOpt(IHyperOpt):
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Integer(50, 100, name='sell-fastd-value'),
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Integer(50, 100, name='sell-adx-value'),
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Integer(60, 100, name='sell-rsi-value'),
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Integer(1, 25, name='exit-short-mfi-value'),
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Integer(1, 50, name='exit-short-fastd-value'),
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Integer(1, 50, name='exit-short-adx-value'),
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Integer(1, 40, name='exit-short-rsi-value'),
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Categorical([True, False], name='sell-mfi-enabled'),
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Categorical([True, False], name='sell-fastd-enabled'),
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Categorical([True, False], name='sell-adx-enabled'),
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@@ -169,60 +141,40 @@ class SampleHyperOpt(IHyperOpt):
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Sell strategy Hyperopt will build and use.
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"""
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exit_long_conditions = []
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exit_short_conditions = []
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# GUARDS AND TRENDS
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if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
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exit_long_conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
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exit_short_conditions.append(dataframe['mfi'] < params['exit-short-mfi-value'])
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if 'sell-fastd-enabled' in params and params['sell-fastd-enabled']:
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exit_long_conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
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exit_short_conditions.append(dataframe['fastd'] < params['exit-short-fastd-value'])
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if 'sell-adx-enabled' in params and params['sell-adx-enabled']:
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exit_long_conditions.append(dataframe['adx'] < params['sell-adx-value'])
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exit_short_conditions.append(dataframe['adx'] > params['exit-short-adx-value'])
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if 'sell-rsi-enabled' in params and params['sell-rsi-enabled']:
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exit_long_conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
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exit_short_conditions.append(dataframe['rsi'] < params['exit-short-rsi-value'])
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# TRIGGERS
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if 'sell-trigger' in params:
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if params['sell-trigger'] == 'sell-boll':
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exit_long_conditions.append(dataframe['close'] > dataframe['bb_upperband'])
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exit_short_conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
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if params['sell-trigger'] == 'sell-macd_cross_signal':
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exit_long_conditions.append(qtpylib.crossed_above(
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dataframe['macdsignal'],
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dataframe['macd']
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))
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exit_short_conditions.append(qtpylib.crossed_below(
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dataframe['macdsignal'],
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dataframe['macd']
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))
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if params['sell-trigger'] == 'sell-sar_reversal':
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exit_long_conditions.append(qtpylib.crossed_above(
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dataframe['sar'],
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dataframe['close']
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))
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exit_short_conditions.append(qtpylib.crossed_below(
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dataframe['sar'],
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dataframe['close']
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))
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# Check that volume is not 0
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exit_long_conditions.append(dataframe['volume'] > 0)
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exit_short_conditions.append(dataframe['volume'] > 0)
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if exit_long_conditions:
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dataframe.loc[
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reduce(lambda x, y: x & y, exit_long_conditions),
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'sell'] = 1
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if exit_short_conditions:
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dataframe.loc[
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reduce(lambda x, y: x & y, exit_short_conditions),
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'exit_short'] = 1
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return dataframe
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return populate_sell_trend
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@@ -70,10 +70,6 @@ class AdvancedSampleHyperOpt(IHyperOpt):
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Integer(15, 45, name='fastd-value'),
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Integer(20, 50, name='adx-value'),
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Integer(20, 40, name='rsi-value'),
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Integer(75, 90, name='short-mfi-value'),
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Integer(55, 85, name='short-fastd-value'),
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Integer(50, 80, name='short-adx-value'),
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Integer(60, 80, name='short-rsi-value'),
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Categorical([True, False], name='mfi-enabled'),
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Categorical([True, False], name='fastd-enabled'),
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Categorical([True, False], name='adx-enabled'),
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@@ -91,59 +87,37 @@ class AdvancedSampleHyperOpt(IHyperOpt):
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Buy strategy Hyperopt will build and use
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"""
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long_conditions = []
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short_conditions = []
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# GUARDS AND TRENDS
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if 'mfi-enabled' in params and params['mfi-enabled']:
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long_conditions.append(dataframe['mfi'] < params['mfi-value'])
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short_conditions.append(dataframe['mfi'] > params['short-mfi-value'])
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if 'fastd-enabled' in params and params['fastd-enabled']:
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long_conditions.append(dataframe['fastd'] < params['fastd-value'])
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short_conditions.append(dataframe['fastd'] > params['short-fastd-value'])
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if 'adx-enabled' in params and params['adx-enabled']:
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long_conditions.append(dataframe['adx'] > params['adx-value'])
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short_conditions.append(dataframe['adx'] < params['short-adx-value'])
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if 'rsi-enabled' in params and params['rsi-enabled']:
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long_conditions.append(dataframe['rsi'] < params['rsi-value'])
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short_conditions.append(dataframe['rsi'] > params['short-rsi-value'])
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# TRIGGERS
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if 'trigger' in params:
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if params['trigger'] == 'boll':
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long_conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
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short_conditions.append(dataframe['close'] > dataframe['bb_upperband'])
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if params['trigger'] == 'macd_cross_signal':
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long_conditions.append(qtpylib.crossed_above(
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dataframe['macd'],
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dataframe['macdsignal']
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))
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short_conditions.append(qtpylib.crossed_below(
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dataframe['macd'],
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dataframe['macdsignal']
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dataframe['macd'], dataframe['macdsignal']
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))
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if params['trigger'] == 'sar_reversal':
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long_conditions.append(qtpylib.crossed_above(
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dataframe['close'],
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dataframe['sar']
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))
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short_conditions.append(qtpylib.crossed_below(
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dataframe['close'],
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dataframe['sar']
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dataframe['close'], dataframe['sar']
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))
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# Check that volume is not 0
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long_conditions.append(dataframe['volume'] > 0)
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short_conditions.append(dataframe['volume'] > 0)
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if long_conditions:
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dataframe.loc[
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reduce(lambda x, y: x & y, long_conditions),
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'buy'] = 1
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if short_conditions:
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dataframe.loc[
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reduce(lambda x, y: x & y, short_conditions),
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'enter_short'] = 1
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return dataframe
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return populate_buy_trend
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@@ -158,10 +132,6 @@ class AdvancedSampleHyperOpt(IHyperOpt):
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Integer(50, 100, name='sell-fastd-value'),
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Integer(50, 100, name='sell-adx-value'),
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Integer(60, 100, name='sell-rsi-value'),
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Integer(1, 25, name='exit_short-mfi-value'),
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Integer(1, 50, name='exit_short-fastd-value'),
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Integer(1, 50, name='exit_short-adx-value'),
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Integer(1, 40, name='exit_short-rsi-value'),
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Categorical([True, False], name='sell-mfi-enabled'),
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Categorical([True, False], name='sell-fastd-enabled'),
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Categorical([True, False], name='sell-adx-enabled'),
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@@ -183,59 +153,39 @@ class AdvancedSampleHyperOpt(IHyperOpt):
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"""
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# print(params)
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exit_long_conditions = []
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exit_short_conditions = []
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# GUARDS AND TRENDS
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if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
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exit_long_conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
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exit_short_conditions.append(dataframe['mfi'] < params['exit-short-mfi-value'])
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if 'sell-fastd-enabled' in params and params['sell-fastd-enabled']:
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exit_long_conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
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exit_short_conditions.append(dataframe['fastd'] < params['exit-short-fastd-value'])
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if 'sell-adx-enabled' in params and params['sell-adx-enabled']:
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exit_long_conditions.append(dataframe['adx'] < params['sell-adx-value'])
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exit_short_conditions.append(dataframe['adx'] > params['exit-short-adx-value'])
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if 'sell-rsi-enabled' in params and params['sell-rsi-enabled']:
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exit_long_conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
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exit_short_conditions.append(dataframe['rsi'] < params['exit-short-rsi-value'])
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# TRIGGERS
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if 'sell-trigger' in params:
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if params['sell-trigger'] == 'sell-boll':
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exit_long_conditions.append(dataframe['close'] > dataframe['bb_upperband'])
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exit_short_conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
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if params['sell-trigger'] == 'sell-macd_cross_signal':
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exit_long_conditions.append(qtpylib.crossed_above(
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dataframe['macdsignal'],
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dataframe['macd']
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))
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exit_long_conditions.append(qtpylib.crossed_below(
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dataframe['macdsignal'],
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dataframe['macd']
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))
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if params['sell-trigger'] == 'sell-sar_reversal':
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exit_long_conditions.append(qtpylib.crossed_above(
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dataframe['sar'],
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dataframe['close']
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))
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exit_long_conditions.append(qtpylib.crossed_below(
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dataframe['sar'],
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dataframe['close']
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))
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# Check that volume is not 0
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exit_long_conditions.append(dataframe['volume'] > 0)
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exit_short_conditions.append(dataframe['volume'] > 0)
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if exit_long_conditions:
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dataframe.loc[
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reduce(lambda x, y: x & y, exit_long_conditions),
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'sell'] = 1
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if exit_short_conditions:
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dataframe.loc[
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reduce(lambda x, y: x & y, exit_short_conditions),
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'exit_short'] = 1
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return dataframe
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return populate_sell_trend
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@@ -243,7 +193,6 @@ class AdvancedSampleHyperOpt(IHyperOpt):
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@staticmethod
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def generate_roi_table(params: Dict) -> Dict[int, float]:
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"""
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# TODO-lev?
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Generate the ROI table that will be used by Hyperopt
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This implementation generates the default legacy Freqtrade ROI tables.
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@@ -265,7 +214,6 @@ class AdvancedSampleHyperOpt(IHyperOpt):
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@staticmethod
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def roi_space() -> List[Dimension]:
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"""
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# TODO-lev?
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Values to search for each ROI steps
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Override it if you need some different ranges for the parameters in the
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@@ -286,7 +234,6 @@ class AdvancedSampleHyperOpt(IHyperOpt):
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@staticmethod
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def stoploss_space() -> List[Dimension]:
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"""
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# TODO-lev?
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Stoploss Value to search
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Override it if you need some different range for the parameter in the
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@@ -299,7 +246,6 @@ class AdvancedSampleHyperOpt(IHyperOpt):
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@staticmethod
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def trailing_space() -> List[Dimension]:
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"""
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# TODO-lev?
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Create a trailing stoploss space.
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You may override it in your custom Hyperopt class.
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Block a user