Files
quantconnect--lean/Tests/Python/DataConsolidatorPythonWrapperTests.cs
T
Colton Sellers d2d99b1f10
Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
Algorithm Sampling and Statistics Fixes (#5936)
* Implement scheduled event sampling solution

* Use UTC time, only update daily portfolio value once a day

* For daily resolutions sample chart always

* Cleanup

* Drop resample daily all together

* Force final sample

* Regression updates

* FIx LiveResultHandler to update portfolio and benchmark values outside of sampling event

* Name the daily sampling event

* Address review pt 1

* Drop force and use reference wrapper

* Adjust tests

* Fix warning for Benchmark Timezone Misalignment and also add test

* Fix for daily resolution orders and test adjustments

* Also warn on universe settings with daily resolution

* Update missed regression

* Fix reference wrapper use

* Update regression after rebase

* Add values back in for Daylight Algo

* Have statistics builder skip day 1 performance

* Regression adjustments

* Test adjustments

* Update regression unit test

* Adjust some regressions starts to show performance values

* Add hourly algorithm for beta comparison

* Address missing Python regression changes

* Remove null comment
2021-10-05 19:31:25 -03:00

235 lines
9.2 KiB
C#

/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
using System;
using NUnit.Framework;
using Python.Runtime;
using System.Collections.Generic;
using QuantConnect.Data.Market;
using QuantConnect.Python;
namespace QuantConnect.Tests.Python
{
[TestFixture]
public class DataConsolidatorPythonWrapperTests
{
[Test]
public void UpdatePyConsolidator()
{
using (Py.GIL())
{
var module = PythonEngine.ModuleFromString(Guid.NewGuid().ToString(),
"from AlgorithmImports import *\n" +
"class CustomConsolidator():\n" +
" def __init__(self):\n" +
" self.UpdateWasCalled = False\n" +
" self.InputType = QuoteBar\n" +
" self.OutputType = QuoteBar\n" +
" self.Consolidated = None\n" +
" self.WorkingData = None\n" +
" def Update(self, data):\n" +
" self.UpdateWasCalled = True\n");
var customConsolidator = module.GetAttr("CustomConsolidator").Invoke();
var wrapper = new DataConsolidatorPythonWrapper(customConsolidator);
var time = DateTime.Today;
var period = TimeSpan.FromMinutes(1);
var bar1 = new QuoteBar
{
Time = time,
Symbol = Symbols.SPY,
Bid = new Bar(1, 2, 0.75m, 1.25m),
LastBidSize = 3,
Ask = null,
LastAskSize = 0,
Value = 1,
Period = period
};
wrapper.Update(bar1);
bool called;
customConsolidator.GetAttr("UpdateWasCalled").TryConvert(out called);
Assert.True(called);
}
}
[Test]
public void ScanPyConsolidator()
{
using (Py.GIL())
{
var module = PythonEngine.ModuleFromString(Guid.NewGuid().ToString(),
"from AlgorithmImports import *\n" +
"class CustomConsolidator():\n" +
" def __init__(self):\n" +
" self.ScanWasCalled = False\n" +
" self.InputType = QuoteBar\n" +
" self.OutputType = QuoteBar\n" +
" self.Consolidated = None\n" +
" self.WorkingData = None\n" +
" def Scan(self,time):\n" +
" self.ScanWasCalled = True\n");
var customConsolidator = module.GetAttr("CustomConsolidator").Invoke();
var wrapper = new DataConsolidatorPythonWrapper(customConsolidator);
var time = DateTime.Today;
var period = TimeSpan.FromMinutes(1);
wrapper.Scan(DateTime.Now);
bool called;
customConsolidator.GetAttr("ScanWasCalled").TryConvert(out called);
Assert.True(called);
}
}
[Test]
public void InputTypePyConsolidator()
{
using (Py.GIL())
{
var module = PythonEngine.ModuleFromString(Guid.NewGuid().ToString(),
"from AlgorithmImports import *\n" +
"class CustomConsolidator():\n" +
" def __init__(self):\n" +
" self.InputType = QuoteBar\n" +
" self.OutputType = QuoteBar\n" +
" self.Consolidated = None\n" +
" self.WorkingData = None\n");
var customConsolidator = module.GetAttr("CustomConsolidator").Invoke();
var wrapper = new DataConsolidatorPythonWrapper(customConsolidator);
var time = DateTime.Today;
var period = TimeSpan.FromMinutes(1);
var type = wrapper.InputType;
Assert.True(type == typeof(QuoteBar));
}
}
[Test]
public void OutputTypePyConsolidator()
{
using (Py.GIL())
{
var module = PythonEngine.ModuleFromString(Guid.NewGuid().ToString(),
"from AlgorithmImports import *\n" +
"class CustomConsolidator():\n" +
" def __init__(self):\n" +
" self.InputType = QuoteBar\n" +
" self.OutputType = QuoteBar\n" +
" self.Consolidated = None\n" +
" self.WorkingData = None\n");
var customConsolidator = module.GetAttr("CustomConsolidator").Invoke();
var wrapper = new DataConsolidatorPythonWrapper(customConsolidator);
var time = DateTime.Today;
var period = TimeSpan.FromMinutes(1);
var type = wrapper.OutputType;
Assert.True(type == typeof(QuoteBar));
}
}
[Test]
public void RunRegressionAlgorithm()
{
var parameter = new RegressionTests.AlgorithmStatisticsTestParameters("CustomConsolidatorRegressionAlgorithm",
new Dictionary<string, string> {
{"Total Trades", "49"},
{"Average Win", "0.25%"},
{"Average Loss", "-0.01%"},
{"Compounding Annual Return", "65.750%"},
{"Drawdown", "0.300%"},
{"Expectancy", "2.577"},
{"Net Profit", "1.067%"},
{"Sharpe Ratio", "6.873"},
{"Probabilistic Sharpe Ratio", "89.382%"},
{"Loss Rate", "80%"},
{"Win Rate", "20%"},
{"Profit-Loss Ratio", "16.88"},
{"Alpha", "0.34"},
{"Beta", "0.351"},
{"Annual Standard Deviation", "0.068"},
{"Annual Variance", "0.005"},
{"Information Ratio", "0.865"},
{"Tracking Error", "0.118"},
{"Treynor Ratio", "1.336"},
{"Total Fees", "$69.81"}
},
Language.Python,
AlgorithmStatus.Completed);
AlgorithmRunner.RunLocalBacktest(parameter.Algorithm,
parameter.Statistics,
parameter.AlphaStatistics,
parameter.Language,
parameter.ExpectedFinalStatus);
}
[Test]
public void AttachAndTriggerEvent()
{
using (Py.GIL())
{
var module = PythonEngine.ModuleFromString(Guid.NewGuid().ToString(),
"from AlgorithmImports import *\n" +
"class ImplementingClass():\n" +
" def __init__(self):\n" +
" self.EventCalled = False\n" +
" self.Consolidator = CustomConsolidator(timedelta(minutes=1))\n" +
" self.Consolidator.DataConsolidated += self.ConsolidatorEvent\n" +
" def ConsolidatorEvent(self, sender, bar):\n" +
" self.EventCalled = True\n" +
"class CustomConsolidator(QuoteBarConsolidator):\n" +
" def __init__(self,span):\n" +
" self.Span = span");
var implementingClass = module.GetAttr("ImplementingClass").Invoke();
var customConsolidator = implementingClass.GetAttr("Consolidator");
var wrapper = new DataConsolidatorPythonWrapper(customConsolidator);
bool called;
implementingClass.GetAttr("EventCalled").TryConvert(out called);
Assert.False(called);
var time = DateTime.Today;
var period = TimeSpan.FromMinutes(1);
var bar1 = new QuoteBar
{
Time = time,
Symbol = Symbols.SPY,
Bid = new Bar(1, 2, 0.75m, 1.25m),
LastBidSize = 3,
Ask = null,
LastAskSize = 0,
Value = 1,
Period = period
};
wrapper.Update(bar1);
wrapper.Scan(time.AddMinutes(1));
implementingClass.GetAttr("EventCalled").TryConvert(out called);
Assert.True(called);
}
}
}
}