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refactor: improve variable naming

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Matthias
2025-04-27 11:05:51 +02:00
parent 22ba0e61e3
commit 3ca7407b09
1 changed files with 9 additions and 7 deletions
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16
freqtrade/data/btanalysis.py
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@@ -491,11 +491,12 @@ def load_exit_signal_candles(backtest_dir: Path) -> dict[str, dict[str, pd.DataF
return load_backtest_analysis_data(backtest_dir, "exited") return load_backtest_analysis_data(backtest_dir, "exited")
def analyze_trade_parallelism(results: pd.DataFrame, timeframe: str) -> pd.DataFrame: def analyze_trade_parallelism(trades: pd.DataFrame, timeframe: str) -> pd.DataFrame:
""" """
Find overlapping trades by expanding each trade once per period it was open Find overlapping trades by expanding each trade once per period it was open
and then counting overlaps. and then counting overlaps.
:param results: Results Dataframe - can be loaded :param trades: Trades Dataframe - can be loaded from backtest, or created
via trade_list_to_dataframe
:param timeframe: Timeframe used for backtest :param timeframe: Timeframe used for backtest
:return: dataframe with open-counts per time-period in timeframe :return: dataframe with open-counts per time-period in timeframe
""" """
@@ -512,11 +513,11 @@ def analyze_trade_parallelism(results: pd.DataFrame, timeframe: str) -> pd.DataF
inclusive="left", inclusive="left",
) )
) )
for row in results[["open_date", "close_date"]].iterrows() for row in trades[["open_date", "close_date"]].iterrows()
] ]
deltas = [len(x) for x in dates] deltas = [len(x) for x in dates]
dates = pd.Series(pd.concat(dates).values, name="date") dates = pd.Series(pd.concat(dates).values, name="date")
df2 = pd.DataFrame(np.repeat(results.values, deltas, axis=0), columns=results.columns) df2 = pd.DataFrame(np.repeat(trades.values, deltas, axis=0), columns=trades.columns)
df2 = pd.concat([dates, df2], axis=1) df2 = pd.concat([dates, df2], axis=1)
df2 = df2.set_index("date") df2 = df2.set_index("date")
@@ -526,17 +527,18 @@ def analyze_trade_parallelism(results: pd.DataFrame, timeframe: str) -> pd.DataF
def evaluate_result_multi( def evaluate_result_multi(
results: pd.DataFrame, timeframe: str, max_open_trades: IntOrInf trades: pd.DataFrame, timeframe: str, max_open_trades: IntOrInf
) -> pd.DataFrame: ) -> pd.DataFrame:
""" """
Find overlapping trades by expanding each trade once per period it was open Find overlapping trades by expanding each trade once per period it was open
and then counting overlaps and then counting overlaps
:param results: Results Dataframe - can be loaded :param trades: Trades Dataframe - can be loaded from backtest, or created
via trade_list_to_dataframe
:param timeframe: Frequency used for the backtest :param timeframe: Frequency used for the backtest
:param max_open_trades: parameter max_open_trades used during backtest run :param max_open_trades: parameter max_open_trades used during backtest run
:return: dataframe with open-counts per time-period in freq :return: dataframe with open-counts per time-period in freq
""" """
df_final = analyze_trade_parallelism(results, timeframe) df_final = analyze_trade_parallelism(trades, timeframe)
return df_final[df_final["open_trades"] > max_open_trades] return df_final[df_final["open_trades"] > max_open_trades]