Add test for detail backtesting
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@ -787,17 +787,98 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
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for _, t in results.iterrows():
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assert len(t['orders']) == 2
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ln = data_pair.loc[data_pair["date"] == t["open_date"]]
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# Check open trade rate alignes to open rate
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# Check open trade rate aligns to open rate
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assert not ln.empty
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assert round(ln.iloc[0]["open"], 6) == round(t["open_rate"], 6)
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# check close trade rate alignes to close rate or is between high and low
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# check close trade rate aligns to close rate or is between high and low
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ln1 = data_pair.loc[data_pair["date"] == t["close_date"]]
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assert not ln1.empty
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assert (round(ln1.iloc[0]["open"], 6) == round(t["close_rate"], 6) or
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round(ln1.iloc[0]["low"], 6) < round(
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t["close_rate"], 6) < round(ln1.iloc[0]["high"], 6))
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@pytest.mark.parametrize('use_detail', [True, False])
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def test_backtest_one_detail(default_conf_usdt, fee, mocker, testdatadir, use_detail) -> None:
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default_conf_usdt['use_exit_signal'] = False
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mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
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mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
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mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
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if use_detail:
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default_conf_usdt['timeframe_detail'] = '1m'
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patch_exchange(mocker)
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def advise_entry(df, *args, **kwargs):
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# Mock function to force several entries
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df.loc[(df['rsi'] < 40), 'enter_long'] = 1
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return df
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def custom_entry_price(proposed_rate, **kwargs):
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return proposed_rate * 0.997
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backtesting = Backtesting(default_conf_usdt)
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backtesting._set_strategy(backtesting.strategylist[0])
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backtesting.strategy.populate_entry_trend = advise_entry
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backtesting.strategy.custom_entry_price = custom_entry_price
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pair = 'XRP/ETH'
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# Pick a timerange adapted to the pair we use to test
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timerange = TimeRange.parse_timerange('20191010-20191013')
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data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=['XRP/ETH'],
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timerange=timerange)
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if use_detail:
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data_1m = history.load_data(datadir=testdatadir, timeframe='1m', pairs=['XRP/ETH'],
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timerange=timerange)
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backtesting.detail_data = data_1m
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processed = backtesting.strategy.advise_all_indicators(data)
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min_date, max_date = get_timerange(processed)
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result = backtesting.backtest(
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processed=deepcopy(processed),
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start_date=min_date,
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end_date=max_date,
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max_open_trades=10,
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)
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results = result['results']
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assert not results.empty
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# Timeout settings from default_conf = entry: 10, exit: 30
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assert len(results) == (2 if use_detail else 3)
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assert 'orders' in results.columns
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data_pair = processed[pair]
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data_1m_pair = data_1m[pair] if use_detail else pd.DataFrame()
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late_entry = 0
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for _, t in results.iterrows():
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assert len(t['orders']) == 2
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entryo = t['orders'][0]
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entry_ts = datetime.fromtimestamp(entryo['order_filled_timestamp'] // 1000, tz=timezone.utc)
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if entry_ts > t['open_date']:
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late_entry += 1
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# Get "entry fill" candle
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ln = (data_1m_pair.loc[data_1m_pair["date"] == entry_ts]
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if use_detail else data_pair.loc[data_pair["date"] == entry_ts])
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# Check open trade rate aligns to open rate
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assert not ln.empty
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# assert round(ln.iloc[0]["open"], 6) == round(t["open_rate"], 6)
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assert round(ln.iloc[0]["low"], 6) <= round(
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t["open_rate"], 6) <= round(ln.iloc[0]["high"], 6)
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# check close trade rate aligns to close rate or is between high and low
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ln1 = data_pair.loc[data_pair["date"] == t["close_date"]]
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if use_detail:
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ln1_1m = data_1m_pair.loc[data_1m_pair["date"] == t["close_date"]]
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assert not ln1.empty or not ln1_1m.empty
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else:
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assert not ln1.empty
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ln2 = ln1_1m if ln1.empty else ln1
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assert (round(ln2.iloc[0]["low"], 6) <= round(
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t["close_rate"], 6) <= round(ln2.iloc[0]["high"], 6))
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assert late_entry > 0
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def test_backtest_timedout_entry_orders(default_conf, fee, mocker, testdatadir) -> None:
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# This strategy intentionally places unfillable orders.
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default_conf['strategy'] = 'StrategyTestV3CustomEntryPrice'
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