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Merge pull request #3847 from freqtrade/edge_fix_nan

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Implement division/0 checks for win and loss columns in edge
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Matthias 2020-10-09 10:27:41 +02:00 committed by GitHub
commit 62859455f7
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2 changed files with 62 additions and 2 deletions
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6
freqtrade/edge/edge_positioning.py
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@ -310,8 +310,10 @@ class Edge:
# Calculating number of losing trades, average win and average loss # Calculating number of losing trades, average win and average loss
df['nb_loss_trades'] = df['nb_trades'] - df['nb_win_trades'] df['nb_loss_trades'] = df['nb_trades'] - df['nb_win_trades']
df['average_win'] = df['profit_sum'] / df['nb_win_trades'] df['average_win'] = np.where(df['nb_win_trades'] == 0, 0.0,
df['average_loss'] = df['loss_sum'] / df['nb_loss_trades'] df['profit_sum'] / df['nb_win_trades'])
df['average_loss'] = np.where(df['nb_loss_trades'] == 0, 0.0,
df['loss_sum'] / df['nb_loss_trades'])
# Win rate = number of profitable trades / number of trades # Win rate = number of profitable trades / number of trades
df['winrate'] = df['nb_win_trades'] / df['nb_trades'] df['winrate'] = df['nb_win_trades'] / df['nb_trades']

58
tests/edge/test_edge.py
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@ -499,3 +499,61 @@ def test_process_expectancy_remove_pumps(mocker, edge_conf, fee,):
assert final['TEST/BTC'].stoploss == -0.9 assert final['TEST/BTC'].stoploss == -0.9
assert final['TEST/BTC'].nb_trades == len(trades_df) - 1 assert final['TEST/BTC'].nb_trades == len(trades_df) - 1
assert round(final['TEST/BTC'].winrate, 10) == 0.0 assert round(final['TEST/BTC'].winrate, 10) == 0.0
def test_process_expectancy_only_wins(mocker, edge_conf, fee,):
edge_conf['edge']['min_trade_number'] = 2
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
freqtrade.exchange.get_fee = fee
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
trades = [
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:05:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:10:00.000000000'),
'open_index': 1,
'close_index': 1,
'trade_duration': '',
'open_rate': 15,
'close_rate': 17,
'exit_type': 'sell_signal'},
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
'open_index': 4,
'close_index': 4,
'trade_duration': '',
'open_rate': 10,
'close_rate': 20,
'exit_type': 'sell_signal'},
{'pair': 'TEST/BTC',
'stoploss': -0.9,
'profit_percent': '',
'profit_abs': '',
'open_date': np.datetime64('2018-10-03T00:30:00.000000000'),
'close_date': np.datetime64('2018-10-03T00:40:00.000000000'),
'open_index': 6,
'close_index': 7,
'trade_duration': '',
'open_rate': 26,
'close_rate': 134,
'exit_type': 'sell_signal'}
]
trades_df = DataFrame(trades)
trades_df = edge._fill_calculable_fields(trades_df)
final = edge._process_expectancy(trades_df)
assert 'TEST/BTC' in final
assert final['TEST/BTC'].stoploss == -0.9
assert final['TEST/BTC'].nb_trades == len(trades_df)
assert round(final['TEST/BTC'].winrate, 10) == 1.0
assert round(final['TEST/BTC'].risk_reward_ratio, 10) == float('inf')
assert round(final['TEST/BTC'].expectancy, 10) == float('inf')