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Merge pull request #3053 from freqtrade/hyperopt_default_volume

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Hyperopt - add default volume > 0 filter
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hroff-1902 2020-03-11 08:17:54 +03:00 committed by GitHub
commit ed5b0ee36b
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4 changed files with 21 additions and 0 deletions
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3
docs/hyperopt.md
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@ -159,6 +159,9 @@ So let's write the buy strategy using these values:
dataframe['macd'], dataframe['macdsignal']
))
# Check that volume is not 0
conditions.append(dataframe['volume'] > 0)
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),

6
freqtrade/templates/base_hyperopt.py.j2
View File

@ -66,6 +66,9 @@ class {{ hyperopt }}(IHyperOpt):
dataframe['close'], dataframe['sar']
))
# Check that the candle had volume
conditions.append(dataframe['volume'] > 0)
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
@ -111,6 +114,9 @@ class {{ hyperopt }}(IHyperOpt):
dataframe['sar'], dataframe['close']
))
# Check that the candle had volume
conditions.append(dataframe['volume'] > 0)
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),

6
freqtrade/templates/sample_hyperopt.py
View File

@ -78,6 +78,9 @@ class SampleHyperOpt(IHyperOpt):
dataframe['close'], dataframe['sar']
))
# Check that volume is not 0
conditions.append(dataframe['volume'] > 0)
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
@ -138,6 +141,9 @@ class SampleHyperOpt(IHyperOpt):
dataframe['sar'], dataframe['close']
))
# Check that volume is not 0
conditions.append(dataframe['volume'] > 0)
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),

6
freqtrade/templates/sample_hyperopt_advanced.py
View File

@ -93,6 +93,9 @@ class AdvancedSampleHyperOpt(IHyperOpt):
dataframe['close'], dataframe['sar']
))
# Check that volume is not 0
conditions.append(dataframe['volume'] > 0)
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
@ -153,6 +156,9 @@ class AdvancedSampleHyperOpt(IHyperOpt):
dataframe['sar'], dataframe['close']
))
# Check that volume is not 0
conditions.append(dataframe['volume'] > 0)
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),