trim trades to the available ohlcv data before plotting profits
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@ -151,13 +151,20 @@ def load_trades(source: str, db_url: str, exportfilename: Path,
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return load_backtest_data(exportfilename)
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def extract_trades_of_period(dataframe: pd.DataFrame, trades: pd.DataFrame) -> pd.DataFrame:
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def extract_trades_of_period(dataframe: pd.DataFrame, trades: pd.DataFrame,
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date_index=False) -> pd.DataFrame:
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"""
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Compare trades and backtested pair DataFrames to get trades performed on backtested period
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:return: the DataFrame of a trades of period
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"""
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trades = trades.loc[(trades['open_time'] >= dataframe.iloc[0]['date']) &
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(trades['close_time'] <= dataframe.iloc[-1]['date'])]
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if date_index:
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trades_start = dataframe.index[0]
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trades_stop = dataframe.index[-1]
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else:
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trades_start = dataframe.iloc[0]['date']
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trades_stop = dataframe.iloc[-1]['date']
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trades = trades.loc[(trades['open_time'] >= trades_start) &
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(trades['close_time'] <= trades_stop)]
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return trades
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@ -385,6 +385,9 @@ def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
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# Combine close-values for all pairs, rename columns to "pair"
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df_comb = combine_dataframes_with_mean(data, "close")
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# Trim trades to available OHLCV data
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trades = extract_trades_of_period(df_comb, trades, date_index=True)
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# Add combined cumulative profit
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df_comb = create_cum_profit(df_comb, trades, 'cum_profit', timeframe)
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