Update backtest-result_new
fixing the calculation of profit_abs - which was incorrect previously.
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@ -268,7 +268,7 @@ def test_create_cum_profit(testdatadir):
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"cum_profits", timeframe="5m")
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"cum_profits", timeframe="5m")
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assert "cum_profits" in cum_profits.columns
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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 cum_profits.iloc[0]['cum_profits'] == 0
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assert pytest.approx(cum_profits.iloc[-1]['cum_profits']) == 8.723007518796964e-06
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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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def test_create_cum_profit1(testdatadir):
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@ -286,7 +286,7 @@ def test_create_cum_profit1(testdatadir):
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"cum_profits", timeframe="5m")
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"cum_profits", timeframe="5m")
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assert "cum_profits" in cum_profits.columns
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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 cum_profits.iloc[0]['cum_profits'] == 0
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assert pytest.approx(cum_profits.iloc[-1]['cum_profits']) == 8.723007518796964e-06
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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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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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create_cum_profit(df.set_index('date'), bt_data[bt_data["pair"] == 'NOTAPAIR'],
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@ -299,13 +299,13 @@ def test_calculate_max_drawdown(testdatadir):
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_, hdate, lowdate, hval, lval, drawdown = calculate_max_drawdown(
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_, hdate, lowdate, hval, lval, drawdown = calculate_max_drawdown(
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bt_data, value_col="profit_abs")
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bt_data, value_col="profit_abs")
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assert isinstance(drawdown, float)
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assert isinstance(drawdown, float)
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assert pytest.approx(drawdown) == 0.12071099
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assert pytest.approx(drawdown) == 0.29753914
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assert isinstance(hdate, Timestamp)
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assert isinstance(hdate, Timestamp)
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assert isinstance(lowdate, Timestamp)
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assert isinstance(lowdate, Timestamp)
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assert isinstance(hval, float)
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assert isinstance(hval, float)
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assert isinstance(lval, float)
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assert isinstance(lval, float)
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assert hdate == Timestamp('2018-01-25 01:30:00', tz='UTC')
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assert hdate == Timestamp('2018-01-16 19:30:00', tz='UTC')
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assert lowdate == Timestamp('2018-01-25 03:50:00', tz='UTC')
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assert lowdate == Timestamp('2018-01-16 22:25:00', tz='UTC')
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underwater = calculate_underwater(bt_data)
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underwater = calculate_underwater(bt_data)
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assert isinstance(underwater, DataFrame)
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assert isinstance(underwater, DataFrame)
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@ -324,8 +324,9 @@ def test_calculate_csum(testdatadir):
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assert isinstance(csum_min, float)
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assert isinstance(csum_min, float)
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assert isinstance(csum_max, float)
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assert isinstance(csum_max, float)
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assert csum_min < 0.01
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assert csum_min < csum_max
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assert csum_max > 0.02
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assert csum_min < 0.0001
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assert csum_max > 0.0002
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csum_min1, csum_max1 = calculate_csum(bt_data, 5)
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csum_min1, csum_max1 = calculate_csum(bt_data, 5)
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assert csum_min1 == csum_min + 5
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assert csum_min1 == csum_min + 5
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@ -354,7 +354,7 @@ def test_generate_profit_graph(testdatadir):
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profit = find_trace_in_fig_data(figure.data, "Profit")
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profit = find_trace_in_fig_data(figure.data, "Profit")
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assert isinstance(profit, go.Scatter)
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assert isinstance(profit, go.Scatter)
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drawdown = find_trace_in_fig_data(figure.data, "Max drawdown 35.69%")
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drawdown = find_trace_in_fig_data(figure.data, "Max drawdown 73.89%")
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assert isinstance(drawdown, go.Scatter)
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assert isinstance(drawdown, go.Scatter)
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parallel = find_trace_in_fig_data(figure.data, "Parallel trades")
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parallel = find_trace_in_fig_data(figure.data, "Parallel trades")
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assert isinstance(parallel, go.Scatter)
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assert isinstance(parallel, go.Scatter)
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