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remove openIndex and closeIndex from backtest-report
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parent
04cbc2cde5
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@ -429,8 +429,6 @@ class Edge:
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'profit_abs': '',
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'open_date': date_column[open_trade_index],
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'close_date': date_column[exit_index],
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'open_index': start_point + open_trade_index,
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'close_index': start_point + exit_index,
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'trade_duration': '',
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'open_rate': round(open_price, 15),
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'close_rate': round(exit_price, 15),
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@ -41,8 +41,6 @@ class BacktestResult(NamedTuple):
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profit_abs: float
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open_date: datetime
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close_date: datetime
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open_index: int
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close_index: int
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trade_duration: float
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open_at_end: bool
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open_rate: float
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@ -251,8 +249,6 @@ class Backtesting:
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open_date=buy_row.date,
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close_date=sell_row.date,
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trade_duration=trade_dur,
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open_index=buy_row.Index,
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close_index=sell_row.Index,
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open_at_end=False,
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open_rate=buy_row.open,
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close_rate=closerate,
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@ -268,8 +264,6 @@ class Backtesting:
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close_date=sell_row.date,
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trade_duration=int((
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sell_row.date - buy_row.date).total_seconds() // 60),
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open_index=buy_row.Index,
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close_index=sell_row.Index,
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open_at_end=True,
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open_rate=buy_row.open,
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close_rate=sell_row.open,
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@ -52,8 +52,10 @@ def backtest_result_to_list(results: DataFrame) -> List[List]:
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:param results: Dataframe containing results for one strategy
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:return: List of Lists containing the trades
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"""
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# Return 0 as "index" for compatibility reasons (for now)
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# TODO: Evaluate if we can remove this
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return [[t.pair, t.profit_percent, t.open_date.timestamp(),
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t.open_date.timestamp(), t.open_index - 1, t.trade_duration,
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t.open_date.timestamp(), 0, t.trade_duration,
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t.open_rate, t.close_rate, t.open_at_end, t.sell_reason.value]
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for index, t in results.iterrows()]
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@ -356,8 +356,6 @@ def test_process_expectancy(mocker, edge_conf, fee, risk_reward_ratio, expectanc
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'profit_abs': '',
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'open_date': np.datetime64('2018-10-03T00:05:00.000000000'),
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'close_date': np.datetime64('2018-10-03T00:10:00.000000000'),
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'open_index': 1,
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'close_index': 1,
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'trade_duration': '',
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'open_rate': 17,
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'close_rate': 17,
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@ -369,8 +367,6 @@ def test_process_expectancy(mocker, edge_conf, fee, risk_reward_ratio, expectanc
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'profit_abs': '',
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'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
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'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
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'open_index': 4,
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'close_index': 4,
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'trade_duration': '',
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'open_rate': 20,
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'close_rate': 20,
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@ -382,8 +378,6 @@ def test_process_expectancy(mocker, edge_conf, fee, risk_reward_ratio, expectanc
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'profit_abs': '',
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'open_date': np.datetime64('2018-10-03T00:30:00.000000000'),
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'close_date': np.datetime64('2018-10-03T00:40:00.000000000'),
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'open_index': 6,
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'close_index': 7,
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'trade_duration': '',
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'open_rate': 26,
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'close_rate': 34,
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@ -464,8 +464,6 @@ def test_backtest(default_conf, fee, mocker, testdatadir) -> None:
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),
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'close_date': pd.to_datetime([Arrow(2018, 1, 29, 22, 35, 0).datetime,
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Arrow(2018, 1, 30, 4, 10, 0).datetime], utc=True),
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'open_index': [78, 184],
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'close_index': [125, 192],
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'trade_duration': [235, 40],
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'open_at_end': [False, False],
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'open_rate': [0.104445, 0.10302485],
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@ -761,8 +759,6 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
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),
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'close_date': pd.to_datetime(['2018-01-29 20:45:00',
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'2018-01-30 05:35:00', ], utc=True),
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'open_index': [78, 184],
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'close_index': [125, 192],
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'trade_duration': [235, 40],
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'open_at_end': [False, False],
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'open_rate': [0.104445, 0.10302485],
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@ -779,8 +775,6 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
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'close_date': pd.to_datetime(['2018-01-29 20:45:00',
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'2018-01-30 05:35:00',
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'2018-01-30 08:30:00'], utc=True),
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'open_index': [78, 184, 185],
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'close_index': [125, 224, 205],
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'trade_duration': [47, 40, 20],
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'open_at_end': [False, False, False],
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'open_rate': [0.104445, 0.10302485, 0.122541],
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@ -214,8 +214,6 @@ def test_backtest_record(default_conf, fee, mocker):
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Arrow(2017, 11, 14, 22, 58, 00).datetime],
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"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
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"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
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"open_index": [1, 119, 153, 185],
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"close_index": [118, 151, 184, 199],
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"trade_duration": [123, 34, 31, 14],
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"open_at_end": [False, False, False, True],
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"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
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