mirror of
https://github.com/freqtrade/freqtrade.git
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ruff format: tests/data
This commit is contained in:
Matthias
@@ -41,18 +41,17 @@ from tests.conftest_trades import MOCK_TRADE_COUNT
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def test_get_latest_backtest_filename(testdatadir, mocker):
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with pytest.raises(ValueError, match=r"Directory .* does not exist\."):
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get_latest_backtest_filename(testdatadir / 'does_not_exist')
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get_latest_backtest_filename(testdatadir / "does_not_exist")
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with pytest.raises(ValueError,
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match=r"Directory .* does not seem to contain .*"):
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with pytest.raises(ValueError, match=r"Directory .* does not seem to contain .*"):
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get_latest_backtest_filename(testdatadir)
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testdir_bt = testdatadir / "backtest_results"
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res = get_latest_backtest_filename(testdir_bt)
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assert res == 'backtest-result.json'
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assert res == "backtest-result.json"
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res = get_latest_backtest_filename(str(testdir_bt))
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assert res == 'backtest-result.json'
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assert res == "backtest-result.json"
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mocker.patch("freqtrade.data.btanalysis.json_load", return_value={})
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@@ -61,8 +60,8 @@ def test_get_latest_backtest_filename(testdatadir, mocker):
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def test_get_latest_hyperopt_file(testdatadir):
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res = get_latest_hyperopt_file(testdatadir / 'does_not_exist', 'testfile.pickle')
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assert res == testdatadir / 'does_not_exist/testfile.pickle'
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res = get_latest_hyperopt_file(testdatadir / "does_not_exist", "testfile.pickle")
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assert res == testdatadir / "does_not_exist/testfile.pickle"
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res = get_latest_hyperopt_file(testdatadir.parent)
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assert res == testdatadir.parent / "hyperopt_results.pickle"
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@@ -73,33 +72,35 @@ def test_get_latest_hyperopt_file(testdatadir):
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# Test with absolute path
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with pytest.raises(
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OperationalException,
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match="--hyperopt-filename expects only the filename, not an absolute path."):
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match="--hyperopt-filename expects only the filename, not an absolute path.",
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):
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get_latest_hyperopt_file(str(testdatadir.parent), str(testdatadir.parent))
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def test_load_backtest_metadata(mocker, testdatadir):
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res = load_backtest_metadata(testdatadir / 'nonexistant.file.json')
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res = load_backtest_metadata(testdatadir / "nonexistant.file.json")
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assert res == {}
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mocker.patch('freqtrade.data.btanalysis.get_backtest_metadata_filename')
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mocker.patch('freqtrade.data.btanalysis.json_load', side_effect=Exception())
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with pytest.raises(OperationalException,
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match=r"Unexpected error.*loading backtest metadata\."):
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load_backtest_metadata(testdatadir / 'nonexistant.file.json')
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mocker.patch("freqtrade.data.btanalysis.get_backtest_metadata_filename")
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mocker.patch("freqtrade.data.btanalysis.json_load", side_effect=Exception())
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with pytest.raises(
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OperationalException, match=r"Unexpected error.*loading backtest metadata\."
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):
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load_backtest_metadata(testdatadir / "nonexistant.file.json")
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def test_load_backtest_data_old_format(testdatadir, mocker):
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filename = testdatadir / "backtest-result_test222.json"
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mocker.patch('freqtrade.data.btanalysis.load_backtest_stats', return_value=[])
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mocker.patch("freqtrade.data.btanalysis.load_backtest_stats", return_value=[])
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with pytest.raises(OperationalException,
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match=r"Backtest-results with only trades data are no longer supported."):
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with pytest.raises(
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OperationalException,
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match=r"Backtest-results with only trades data are no longer supported.",
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):
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load_backtest_data(filename)
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def test_load_backtest_data_new_format(testdatadir):
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filename = testdatadir / "backtest_results/backtest-result.json"
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bt_data = load_backtest_data(filename)
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assert isinstance(bt_data, DataFrame)
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@@ -122,13 +123,11 @@ def test_load_backtest_data_new_format(testdatadir):
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def test_load_backtest_data_multi(testdatadir):
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filename = testdatadir / "backtest_results/backtest-result_multistrat.json"
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for strategy in ('StrategyTestV2', 'TestStrategy'):
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for strategy in ("StrategyTestV2", "TestStrategy"):
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bt_data = load_backtest_data(filename, strategy=strategy)
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assert isinstance(bt_data, DataFrame)
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assert set(bt_data.columns) == set(
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BT_DATA_COLUMNS)
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assert set(bt_data.columns) == set(BT_DATA_COLUMNS)
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assert len(bt_data) == 179
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# Test loading from string (must yield same result)
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@@ -136,21 +135,20 @@ def test_load_backtest_data_multi(testdatadir):
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assert bt_data.equals(bt_data2)
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with pytest.raises(ValueError, match=r"Strategy XYZ not available in the backtest result\."):
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load_backtest_data(filename, strategy='XYZ')
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load_backtest_data(filename, strategy="XYZ")
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with pytest.raises(ValueError, match=r"Detected backtest result with more than one strategy.*"):
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load_backtest_data(filename)
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@pytest.mark.usefixtures("init_persistence")
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@pytest.mark.parametrize('is_short', [False, True])
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@pytest.mark.parametrize("is_short", [False, True])
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def test_load_trades_from_db(default_conf, fee, is_short, mocker):
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create_mock_trades(fee, is_short)
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# remove init so it does not init again
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init_mock = mocker.patch('freqtrade.data.btanalysis.init_db', MagicMock())
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init_mock = mocker.patch("freqtrade.data.btanalysis.init_db", MagicMock())
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trades = load_trades_from_db(db_url=default_conf['db_url'])
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trades = load_trades_from_db(db_url=default_conf["db_url"])
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assert init_mock.call_count == 1
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assert len(trades) == MOCK_TRADE_COUNT
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assert isinstance(trades, DataFrame)
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@@ -159,38 +157,46 @@ def test_load_trades_from_db(default_conf, fee, is_short, mocker):
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assert "profit_ratio" in trades.columns
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for col in BT_DATA_COLUMNS:
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if col not in ['index', 'open_at_end']:
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if col not in ["index", "open_at_end"]:
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assert col in trades.columns
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trades = load_trades_from_db(db_url=default_conf['db_url'], strategy=CURRENT_TEST_STRATEGY)
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trades = load_trades_from_db(db_url=default_conf["db_url"], strategy=CURRENT_TEST_STRATEGY)
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assert len(trades) == 4
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trades = load_trades_from_db(db_url=default_conf['db_url'], strategy='NoneStrategy')
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trades = load_trades_from_db(db_url=default_conf["db_url"], strategy="NoneStrategy")
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assert len(trades) == 0
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def test_extract_trades_of_period(testdatadir):
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pair = "UNITTEST/BTC"
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# 2018-11-14 06:07:00
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timerange = TimeRange('date', None, 1510639620, 0)
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timerange = TimeRange("date", None, 1510639620, 0)
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data = load_pair_history(pair=pair, timeframe='1m',
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datadir=testdatadir, timerange=timerange)
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data = load_pair_history(pair=pair, timeframe="1m", datadir=testdatadir, timerange=timerange)
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trades = DataFrame(
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{'pair': [pair, pair, pair, pair],
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'profit_ratio': [0.0, 0.1, -0.2, -0.5],
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'profit_abs': [0.0, 1, -2, -5],
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'open_date': to_datetime([datetime(2017, 11, 13, 15, 40, 0, tzinfo=timezone.utc),
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datetime(2017, 11, 14, 9, 41, 0, tzinfo=timezone.utc),
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datetime(2017, 11, 14, 14, 20, 0, tzinfo=timezone.utc),
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datetime(2017, 11, 15, 3, 40, 0, tzinfo=timezone.utc),
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], utc=True
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),
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'close_date': to_datetime([datetime(2017, 11, 13, 16, 40, 0, tzinfo=timezone.utc),
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datetime(2017, 11, 14, 10, 41, 0, tzinfo=timezone.utc),
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datetime(2017, 11, 14, 15, 25, 0, tzinfo=timezone.utc),
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datetime(2017, 11, 15, 3, 55, 0, tzinfo=timezone.utc),
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], utc=True)
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})
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{
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"pair": [pair, pair, pair, pair],
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"profit_ratio": [0.0, 0.1, -0.2, -0.5],
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"profit_abs": [0.0, 1, -2, -5],
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"open_date": to_datetime(
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[
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datetime(2017, 11, 13, 15, 40, 0, tzinfo=timezone.utc),
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datetime(2017, 11, 14, 9, 41, 0, tzinfo=timezone.utc),
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datetime(2017, 11, 14, 14, 20, 0, tzinfo=timezone.utc),
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datetime(2017, 11, 15, 3, 40, 0, tzinfo=timezone.utc),
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],
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utc=True,
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),
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"close_date": to_datetime(
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[
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datetime(2017, 11, 13, 16, 40, 0, tzinfo=timezone.utc),
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datetime(2017, 11, 14, 10, 41, 0, tzinfo=timezone.utc),
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datetime(2017, 11, 14, 15, 25, 0, tzinfo=timezone.utc),
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datetime(2017, 11, 15, 3, 55, 0, tzinfo=timezone.utc),
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],
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utc=True,
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),
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}
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)
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trades1 = extract_trades_of_period(data, trades)
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# First and last trade are dropped as they are out of range
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assert len(trades1) == 2
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@@ -206,44 +212,47 @@ def test_analyze_trade_parallelism(testdatadir):
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res = analyze_trade_parallelism(bt_data, "5m")
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assert isinstance(res, DataFrame)
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assert 'open_trades' in res.columns
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assert res['open_trades'].max() == 3
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assert res['open_trades'].min() == 0
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assert "open_trades" in res.columns
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assert res["open_trades"].max() == 3
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assert res["open_trades"].min() == 0
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def test_load_trades(default_conf, mocker):
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db_mock = mocker.patch("freqtrade.data.btanalysis.load_trades_from_db", MagicMock())
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bt_mock = mocker.patch("freqtrade.data.btanalysis.load_backtest_data", MagicMock())
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load_trades("DB",
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db_url=default_conf.get('db_url'),
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exportfilename=default_conf.get('exportfilename'),
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no_trades=False,
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strategy=CURRENT_TEST_STRATEGY,
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)
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load_trades(
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"DB",
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db_url=default_conf.get("db_url"),
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exportfilename=default_conf.get("exportfilename"),
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no_trades=False,
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strategy=CURRENT_TEST_STRATEGY,
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)
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assert db_mock.call_count == 1
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assert bt_mock.call_count == 0
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db_mock.reset_mock()
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bt_mock.reset_mock()
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default_conf['exportfilename'] = Path("testfile.json")
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load_trades("file",
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db_url=default_conf.get('db_url'),
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exportfilename=default_conf.get('exportfilename'),
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)
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default_conf["exportfilename"] = Path("testfile.json")
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load_trades(
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"file",
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db_url=default_conf.get("db_url"),
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exportfilename=default_conf.get("exportfilename"),
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)
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assert db_mock.call_count == 0
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assert bt_mock.call_count == 1
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db_mock.reset_mock()
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bt_mock.reset_mock()
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default_conf['exportfilename'] = "testfile.json"
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load_trades("file",
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db_url=default_conf.get('db_url'),
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exportfilename=default_conf.get('exportfilename'),
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no_trades=True
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)
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default_conf["exportfilename"] = "testfile.json"
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load_trades(
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"file",
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db_url=default_conf.get("db_url"),
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exportfilename=default_conf.get("exportfilename"),
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no_trades=True,
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)
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assert db_mock.call_count == 0
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assert bt_mock.call_count == 0
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@@ -251,7 +260,7 @@ def test_load_trades(default_conf, mocker):
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def test_calculate_market_change(testdatadir):
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pairs = ["ETH/BTC", "ADA/BTC"]
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data = load_data(datadir=testdatadir, pairs=pairs, timeframe='5m')
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data = load_data(datadir=testdatadir, pairs=pairs, timeframe="5m")
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result = calculate_market_change(data)
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assert isinstance(result, float)
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assert pytest.approx(result) == 0.01100002
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@@ -259,7 +268,7 @@ def test_calculate_market_change(testdatadir):
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def test_combine_dataframes_with_mean(testdatadir):
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pairs = ["ETH/BTC", "ADA/BTC"]
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data = load_data(datadir=testdatadir, pairs=pairs, timeframe='5m')
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data = load_data(datadir=testdatadir, pairs=pairs, timeframe="5m")
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df = combine_dataframes_with_mean(data)
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assert isinstance(df, DataFrame)
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assert "ETH/BTC" in df.columns
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@@ -269,11 +278,9 @@ def test_combine_dataframes_with_mean(testdatadir):
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def test_combined_dataframes_with_rel_mean(testdatadir):
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pairs = ["ETH/BTC", "ADA/BTC"]
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data = load_data(datadir=testdatadir, pairs=pairs, timeframe='5m')
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data = load_data(datadir=testdatadir, pairs=pairs, timeframe="5m")
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df = combined_dataframes_with_rel_mean(
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data,
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datetime(2018, 1, 12, tzinfo=timezone.utc),
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datetime(2018, 1, 28, tzinfo=timezone.utc)
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data, datetime(2018, 1, 12, tzinfo=timezone.utc), datetime(2018, 1, 28, tzinfo=timezone.utc)
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)
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assert isinstance(df, DataFrame)
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assert "ETH/BTC" not in df.columns
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@@ -281,14 +288,14 @@ def test_combined_dataframes_with_rel_mean(testdatadir):
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assert "mean" in df.columns
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assert "rel_mean" in df.columns
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assert "count" in df.columns
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assert df.iloc[0]['count'] == 2
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assert df.iloc[-1]['count'] == 2
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assert len(df) < len(data['ETH/BTC'])
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assert df.iloc[0]["count"] == 2
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assert df.iloc[-1]["count"] == 2
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assert len(df) < len(data["ETH/BTC"])
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def test_combine_dataframes_with_mean_no_data(testdatadir):
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pairs = ["ETH/BTC", "ADA/BTC"]
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data = load_data(datadir=testdatadir, pairs=pairs, timeframe='6m')
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data = load_data(datadir=testdatadir, pairs=pairs, timeframe="6m")
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with pytest.raises(ValueError, match=r"No data provided\."):
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combine_dataframes_with_mean(data)
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@@ -298,60 +305,63 @@ def test_create_cum_profit(testdatadir):
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bt_data = load_backtest_data(filename)
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timerange = TimeRange.parse_timerange("20180110-20180112")
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df = load_pair_history(pair="TRX/BTC", timeframe='5m',
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datadir=testdatadir, timerange=timerange)
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df = load_pair_history(pair="TRX/BTC", timeframe="5m", datadir=testdatadir, timerange=timerange)
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cum_profits = create_cum_profit(df.set_index('date'),
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bt_data[bt_data["pair"] == 'TRX/BTC'],
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"cum_profits", timeframe="5m")
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cum_profits = create_cum_profit(
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df.set_index("date"), bt_data[bt_data["pair"] == "TRX/BTC"], "cum_profits", timeframe="5m"
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)
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assert "cum_profits" in cum_profits.columns
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assert cum_profits.iloc[0]['cum_profits'] == 0
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assert pytest.approx(cum_profits.iloc[-1]['cum_profits']) == 9.0225563e-05
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assert cum_profits.iloc[0]["cum_profits"] == 0
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assert pytest.approx(cum_profits.iloc[-1]["cum_profits"]) == 9.0225563e-05
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def test_create_cum_profit1(testdatadir):
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filename = testdatadir / "backtest_results/backtest-result.json"
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bt_data = load_backtest_data(filename)
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# Move close-time to "off" the candle, to make sure the logic still works
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bt_data['close_date'] = bt_data.loc[:, 'close_date'] + DateOffset(seconds=20)
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bt_data["close_date"] = bt_data.loc[:, "close_date"] + DateOffset(seconds=20)
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timerange = TimeRange.parse_timerange("20180110-20180112")
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df = load_pair_history(pair="TRX/BTC", timeframe='5m',
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datadir=testdatadir, timerange=timerange)
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df = load_pair_history(pair="TRX/BTC", timeframe="5m", datadir=testdatadir, timerange=timerange)
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cum_profits = create_cum_profit(df.set_index('date'),
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bt_data[bt_data["pair"] == 'TRX/BTC'],
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"cum_profits", timeframe="5m")
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cum_profits = create_cum_profit(
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df.set_index("date"), bt_data[bt_data["pair"] == "TRX/BTC"], "cum_profits", timeframe="5m"
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)
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assert "cum_profits" in cum_profits.columns
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assert cum_profits.iloc[0]['cum_profits'] == 0
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assert pytest.approx(cum_profits.iloc[-1]['cum_profits']) == 9.0225563e-05
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assert cum_profits.iloc[0]["cum_profits"] == 0
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assert pytest.approx(cum_profits.iloc[-1]["cum_profits"]) == 9.0225563e-05
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with pytest.raises(ValueError, match='Trade dataframe empty.'):
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create_cum_profit(df.set_index('date'), bt_data[bt_data["pair"] == 'NOTAPAIR'],
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"cum_profits", timeframe="5m")
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with pytest.raises(ValueError, match="Trade dataframe empty."):
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create_cum_profit(
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df.set_index("date"),
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bt_data[bt_data["pair"] == "NOTAPAIR"],
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"cum_profits",
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timeframe="5m",
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)
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def test_calculate_max_drawdown(testdatadir):
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filename = testdatadir / "backtest_results/backtest-result.json"
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bt_data = load_backtest_data(filename)
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||||
_, hdate, lowdate, hval, lval, drawdown = calculate_max_drawdown(
|
||||
bt_data, value_col="profit_abs")
|
||||
bt_data, value_col="profit_abs"
|
||||
)
|
||||
assert isinstance(drawdown, float)
|
||||
assert pytest.approx(drawdown) == 0.29753914
|
||||
assert isinstance(hdate, Timestamp)
|
||||
assert isinstance(lowdate, Timestamp)
|
||||
assert isinstance(hval, float)
|
||||
assert isinstance(lval, float)
|
||||
assert hdate == Timestamp('2018-01-16 19:30:00', tz='UTC')
|
||||
assert lowdate == Timestamp('2018-01-16 22:25:00', tz='UTC')
|
||||
assert hdate == Timestamp("2018-01-16 19:30:00", tz="UTC")
|
||||
assert lowdate == Timestamp("2018-01-16 22:25:00", tz="UTC")
|
||||
|
||||
underwater = calculate_underwater(bt_data)
|
||||
assert isinstance(underwater, DataFrame)
|
||||
|
||||
with pytest.raises(ValueError, match='Trade dataframe empty.'):
|
||||
with pytest.raises(ValueError, match="Trade dataframe empty."):
|
||||
calculate_max_drawdown(DataFrame())
|
||||
|
||||
with pytest.raises(ValueError, match='Trade dataframe empty.'):
|
||||
with pytest.raises(ValueError, match="Trade dataframe empty."):
|
||||
calculate_underwater(DataFrame())
|
||||
|
||||
|
||||
@@ -370,7 +380,7 @@ def test_calculate_csum(testdatadir):
|
||||
assert csum_min1 == csum_min + 5
|
||||
assert csum_max1 == csum_max + 5
|
||||
|
||||
with pytest.raises(ValueError, match='Trade dataframe empty.'):
|
||||
with pytest.raises(ValueError, match="Trade dataframe empty."):
|
||||
csum_min, csum_max = calculate_csum(DataFrame())
|
||||
|
||||
|
||||
@@ -388,9 +398,7 @@ def test_calculate_expectancy(testdatadir):
|
||||
assert pytest.approx(expectancy) == 5.820687070932315e-06
|
||||
assert pytest.approx(expectancy_ratio) == 0.07151374226574791
|
||||
|
||||
data = {
|
||||
'profit_abs': [100, 200, 50, -150, 300, -100, 80, -30]
|
||||
}
|
||||
data = {"profit_abs": [100, 200, 50, -150, 300, -100, 80, -30]}
|
||||
df = DataFrame(data)
|
||||
expectancy, expectancy_ratio = calculate_expectancy(df)
|
||||
|
||||
@@ -407,10 +415,10 @@ def test_calculate_sortino(testdatadir):
|
||||
|
||||
sortino = calculate_sortino(
|
||||
bt_data,
|
||||
bt_data['open_date'].min(),
|
||||
bt_data['close_date'].max(),
|
||||
bt_data["open_date"].min(),
|
||||
bt_data["close_date"].max(),
|
||||
0.01,
|
||||
)
|
||||
)
|
||||
assert isinstance(sortino, float)
|
||||
assert pytest.approx(sortino) == 35.17722
|
||||
|
||||
@@ -424,10 +432,10 @@ def test_calculate_sharpe(testdatadir):
|
||||
|
||||
sharpe = calculate_sharpe(
|
||||
bt_data,
|
||||
bt_data['open_date'].min(),
|
||||
bt_data['close_date'].max(),
|
||||
bt_data["open_date"].min(),
|
||||
bt_data["close_date"].max(),
|
||||
0.01,
|
||||
)
|
||||
)
|
||||
assert isinstance(sharpe, float)
|
||||
assert pytest.approx(sharpe) == 44.5078669
|
||||
|
||||
@@ -441,40 +449,69 @@ def test_calculate_calmar(testdatadir):
|
||||
|
||||
calmar = calculate_calmar(
|
||||
bt_data,
|
||||
bt_data['open_date'].min(),
|
||||
bt_data['close_date'].max(),
|
||||
bt_data["open_date"].min(),
|
||||
bt_data["close_date"].max(),
|
||||
0.01,
|
||||
)
|
||||
)
|
||||
assert isinstance(calmar, float)
|
||||
assert pytest.approx(calmar) == 559.040508
|
||||
|
||||
|
||||
@pytest.mark.parametrize('start,end,days, expected', [
|
||||
(64900, 176000, 3 * 365, 0.3945),
|
||||
(64900, 176000, 365, 1.7119),
|
||||
(1000, 1000, 365, 0.0),
|
||||
(1000, 1500, 365, 0.5),
|
||||
(1000, 1500, 100, 3.3927), # sub year
|
||||
(0.01000000, 0.01762792, 120, 4.6087), # sub year BTC values
|
||||
])
|
||||
@pytest.mark.parametrize(
|
||||
"start,end,days, expected",
|
||||
[
|
||||
(64900, 176000, 3 * 365, 0.3945),
|
||||
(64900, 176000, 365, 1.7119),
|
||||
(1000, 1000, 365, 0.0),
|
||||
(1000, 1500, 365, 0.5),
|
||||
(1000, 1500, 100, 3.3927), # sub year
|
||||
(0.01000000, 0.01762792, 120, 4.6087), # sub year BTC values
|
||||
],
|
||||
)
|
||||
def test_calculate_cagr(start, end, days, expected):
|
||||
|
||||
assert round(calculate_cagr(days, start, end), 4) == expected
|
||||
|
||||
|
||||
def test_calculate_max_drawdown2():
|
||||
values = [0.011580, 0.010048, 0.011340, 0.012161, 0.010416, 0.010009, 0.020024,
|
||||
-0.024662, -0.022350, 0.020496, -0.029859, -0.030511, 0.010041, 0.010872,
|
||||
-0.025782, 0.010400, 0.012374, 0.012467, 0.114741, 0.010303, 0.010088,
|
||||
-0.033961, 0.010680, 0.010886, -0.029274, 0.011178, 0.010693, 0.010711]
|
||||
values = [
|
||||
0.011580,
|
||||
0.010048,
|
||||
0.011340,
|
||||
0.012161,
|
||||
0.010416,
|
||||
0.010009,
|
||||
0.020024,
|
||||
-0.024662,
|
||||
-0.022350,
|
||||
0.020496,
|
||||
-0.029859,
|
||||
-0.030511,
|
||||
0.010041,
|
||||
0.010872,
|
||||
-0.025782,
|
||||
0.010400,
|
||||
0.012374,
|
||||
0.012467,
|
||||
0.114741,
|
||||
0.010303,
|
||||
0.010088,
|
||||
-0.033961,
|
||||
0.010680,
|
||||
0.010886,
|
||||
-0.029274,
|
||||
0.011178,
|
||||
0.010693,
|
||||
0.010711,
|
||||
]
|
||||
|
||||
dates = [dt_utc(2020, 1, 1) + timedelta(days=i) for i in range(len(values))]
|
||||
df = DataFrame(zip(values, dates), columns=['profit', 'open_date'])
|
||||
df = DataFrame(zip(values, dates), columns=["profit", "open_date"])
|
||||
# sort by profit and reset index
|
||||
df = df.sort_values('profit').reset_index(drop=True)
|
||||
df = df.sort_values("profit").reset_index(drop=True)
|
||||
df1 = df.copy()
|
||||
drawdown, hdate, ldate, hval, lval, drawdown_rel = calculate_max_drawdown(
|
||||
df, date_col='open_date', value_col='profit')
|
||||
df, date_col="open_date", value_col="profit"
|
||||
)
|
||||
# Ensure df has not been altered.
|
||||
assert df.equals(df1)
|
||||
|
||||
@@ -486,23 +523,26 @@ def test_calculate_max_drawdown2():
|
||||
assert hval > lval
|
||||
assert drawdown == 0.091755
|
||||
|
||||
df = DataFrame(zip(values[:5], dates[:5]), columns=['profit', 'open_date'])
|
||||
with pytest.raises(ValueError, match='No losing trade, therefore no drawdown.'):
|
||||
calculate_max_drawdown(df, date_col='open_date', value_col='profit')
|
||||
df = DataFrame(zip(values[:5], dates[:5]), columns=["profit", "open_date"])
|
||||
with pytest.raises(ValueError, match="No losing trade, therefore no drawdown."):
|
||||
calculate_max_drawdown(df, date_col="open_date", value_col="profit")
|
||||
|
||||
df1 = DataFrame(zip(values[:5], dates[:5]), columns=['profit', 'open_date'])
|
||||
df1.loc[:, 'profit'] = df1['profit'] * -1
|
||||
df1 = DataFrame(zip(values[:5], dates[:5]), columns=["profit", "open_date"])
|
||||
df1.loc[:, "profit"] = df1["profit"] * -1
|
||||
# No winning trade ...
|
||||
drawdown, hdate, ldate, hval, lval, drawdown_rel = calculate_max_drawdown(
|
||||
df1, date_col='open_date', value_col='profit')
|
||||
df1, date_col="open_date", value_col="profit"
|
||||
)
|
||||
assert drawdown == 0.043965
|
||||
|
||||
|
||||
@pytest.mark.parametrize('profits,relative,highd,lowdays,result,result_rel', [
|
||||
([0.0, -500.0, 500.0, 10000.0, -1000.0], False, 3, 4, 1000.0, 0.090909),
|
||||
([0.0, -500.0, 500.0, 10000.0, -1000.0], True, 0, 1, 500.0, 0.5),
|
||||
|
||||
])
|
||||
@pytest.mark.parametrize(
|
||||
"profits,relative,highd,lowdays,result,result_rel",
|
||||
[
|
||||
([0.0, -500.0, 500.0, 10000.0, -1000.0], False, 3, 4, 1000.0, 0.090909),
|
||||
([0.0, -500.0, 500.0, 10000.0, -1000.0], True, 0, 1, 500.0, 0.5),
|
||||
],
|
||||
)
|
||||
def test_calculate_max_drawdown_abs(profits, relative, highd, lowdays, result, result_rel):
|
||||
"""
|
||||
Test case from issue https://github.com/freqtrade/freqtrade/issues/6655
|
||||
@@ -511,12 +551,13 @@ def test_calculate_max_drawdown_abs(profits, relative, highd, lowdays, result, r
|
||||
"""
|
||||
init_date = datetime(2020, 1, 1, tzinfo=timezone.utc)
|
||||
dates = [init_date + timedelta(days=i) for i in range(len(profits))]
|
||||
df = DataFrame(zip(profits, dates), columns=['profit_abs', 'open_date'])
|
||||
df = DataFrame(zip(profits, dates), columns=["profit_abs", "open_date"])
|
||||
# sort by profit and reset index
|
||||
df = df.sort_values('profit_abs').reset_index(drop=True)
|
||||
df = df.sort_values("profit_abs").reset_index(drop=True)
|
||||
df1 = df.copy()
|
||||
drawdown, hdate, ldate, hval, lval, drawdown_rel = calculate_max_drawdown(
|
||||
df, date_col='open_date', starting_balance=1000, relative=relative)
|
||||
df, date_col="open_date", starting_balance=1000, relative=relative
|
||||
)
|
||||
# Ensure df has not been altered.
|
||||
assert df.equals(df1)
|
||||
|
||||
|
||||
Reference in New Issue
Block a user