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Refactor sell reason stats to return a dict

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This commit is contained in:
Matthias 2020-05-25 07:02:24 +02:00
parent 9d1ad70bb7
commit d17300fd84
1 changed files with 41 additions and 39 deletions
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80
freqtrade/optimize/optimize_reports.py
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@ -112,50 +112,40 @@ def generate_text_table(data: Dict[str, Dict], stake_currency: str, max_open_tra
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right") # type: ignore
def _generate_text_table_sell_reason(stake_currency: str, max_open_trades: int,
results: DataFrame) -> Tuple:
def generate_sell_reason_stats(stake_currency: str, max_open_trades: int,
results: DataFrame) -> List[Dict]:
"""
Generate small table outlining Backtest results
:param stake_currency: Stakecurrency used
:param max_open_trades: Max_open_trades parameter
:param results: Dataframe containing the backtest result
:return: Tuple of (List, Headers) containing the summary
:param results: Dataframe containing the backtest result for one strategy
:return: List of Dicts containing the metrics per Sell reason
"""
tabular_data = []
headers = [
"Sell Reason",
"Sells",
"Wins",
"Draws",
"Losses",
"Avg Profit %",
"Cum Profit %",
f"Tot Profit {stake_currency}",
"Tot Profit %",
]
for reason, count in results['sell_reason'].value_counts().iteritems():
result = results.loc[results['sell_reason'] == reason]
wins = len(result[result['profit_abs'] > 0])
draws = len(result[result['profit_abs'] == 0])
loss = len(result[result['profit_abs'] < 0])
profit_mean = round(result['profit_percent'].mean() * 100.0, 2)
profit_sum = round(result["profit_percent"].sum() * 100.0, 2)
profit_tot = result['profit_abs'].sum()
profit_mean = result['profit_percent'].mean()
profit_sum = result["profit_percent"].sum()
profit_percent_tot = round(result['profit_percent'].sum() * 100.0 / max_open_trades, 2)
tabular_data.append(
[
reason.value,
count,
wins,
draws,
loss,
profit_mean,
profit_sum,
profit_tot,
profit_percent_tot,
]
{
'sell_reason': reason.value,
'trades': count,
'wins': len(result[result['profit_abs'] > 0]),
'draws': len(result[result['profit_abs'] == 0]),
'losses': len(result[result['profit_abs'] < 0]),
'profit_mean': profit_mean,
'profit_mean_pct': round(profit_mean * 100, 2),
'profit_sum': profit_sum,
'profit_sum_pct': round(profit_sum * 100, 2),
'profit_total_abs': result['profit_abs'].sum(),
'profit_pct_total': profit_percent_tot,
}
)
return tabular_data, headers
return tabular_data
def generate_text_table_sell_reason(stake_currency: str,
@ -164,14 +154,26 @@ def generate_text_table_sell_reason(stake_currency: str,
Generate small table outlining Backtest results
:param stake_currency: Stakecurrency used
:param max_open_trades: Max_open_trades parameter
:param results: Dataframe containing the backtest result
:param results: Dataframe containing the backtest result for one strategy
:return: pretty printed table with tabulate as string
"""
tabular_data, headers = _generate_text_table_sell_reason(stake_currency,
max_open_trades, results)
return tabulate(tabular_data, headers=headers, tablefmt="orgtbl", stralign="right")
headers = [
'Sell Reason',
'Sells',
'Wins',
'Draws',
'Losses',
'Avg Profit %',
'Cum Profit %',
f'Tot Profit {stake_currency}',
'Tot Profit %',
]
sell_reason_stats = generate_sell_reason_stats(stake_currency, max_open_trades, results)
output = [[
t['sell_reason'], t['trades'], t['wins'], t['draws'], t['losses'],
t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'], t['profit_pct_total'],
] for t in sell_reason_stats]
return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right")
def _generate_strategy_summary(stake_currency: str, max_open_trades: str,