Merge pull request QuantConnect#3774 from AlexCatarino/feature-3773-a…

…dds-train-feature-examples

Adds Examples for Train Feature

Algorithm.CSharp/QuantConnect.Algorithm.CSharp.csproj

@@ -179,7 +179,7 @@
     <Compile Include="CustomUniverseSelectionRegressionAlgorithm.cs" />
     <Compile Include="OnEndOfDayRegressionAlgorithm.cs" />
     <Compile Include="TrainingInitializeRegressionAlgorithm.cs" />
-    <Compile Include="TrainingScheduledRegressionAlgorithm.cs" />
+    <Compile Include="TrainingExampleAlgorithm.cs" />
     <Compile Include="UniverseUnchangedRegressionAlgorithm.cs" />
     <Compile Include="USTreasuryYieldCurveDataAlgorithm.cs" />
     <Compile Include="SECReportDataAlgorithm.cs" />

Algorithm.CSharp/TrainingExampleAlgorithm.cs

@@ -0,0 +1,51 @@
+/*
+ * 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;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Example algorithm showing how to use QCAlgorithm.Train method
+    /// <meta name="tag" content="using quantconnect" />
+    /// <meta name="tag" content="training" />
+    /// </summary>
+    public class TrainingExampleAlgorithm : QCAlgorithm
+    {
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 7);
+            SetEndDate(2013, 10, 14);
+
+            AddEquity("SPY", Resolution.Daily);
+
+            // Set TrainingMethod to be executed immediately
+            Train(TrainingMethod);
+
+            // Set TrainingMethod to be executed at 8:00 am every Sunday
+            Train(DateRules.Every(DayOfWeek.Sunday), TimeRules.At(8, 0), TrainingMethod);
+        }
+
+        private void TrainingMethod()
+        {
+            Log($"Start training at {Time}");
+            // Use the historical data to train the machine learning model
+            var history = History("SPY", 200, Resolution.Daily);
+
+            // ML code:
+
+        }
+    }
+}

Algorithm.CSharp/TrainingInitializeRegressionAlgorithm.cs

@@ -38,7 +38,19 @@ public override void Initialize()
             // this should cause the algorithm to fail
             // the regression test sets the time limit to 30 seconds and there's one extra
             // minute in the bucket, so a two minute sleep should result in RuntimeError
-            Schedule.TrainingNow(() => Thread.Sleep(TimeSpan.FromMinutes(2.5)));
+            Train(() => Thread.Sleep(TimeSpan.FromMinutes(2.5)));
+
+            // DateRules.Tomorrow combined with TimeRules.Midnight enforces that this event schedule will
+            // have exactly one time, which will fire between the first data point and the next day at
+            // midnight. So after the first data point, it will run this event and sleep long enough to
+            // exceed the static max algorithm time loop time and begin to consume from the leaky bucket
+            // the regression test sets the "algorithm-manager-time-loop-maximum" value to 30 seconds
+            Train(DateRules.Tomorrow, TimeRules.Midnight, () =>
+            {
+                // this will consume the single 'minute' available in the leaky bucket
+                // and the regression test will confirm that the leaky bucket is empty
+                Thread.Sleep(TimeSpan.FromMinutes(1));
+            });
         }
 
         public bool CanRunLocally => false;

Algorithm.Python/QuantConnect.Algorithm.Python.csproj

@@ -87,6 +87,7 @@
     <Content Include="TradingEconomicsCalendarIndicatorAlgorithm.py" />
     <Content Include="OnEndOfDayRegressionAlgorithm.py" />
     <Content Include="SECReportDataAlgorithm.py" />
+    <None Include="TrainingInitializeRegressionAlgorithm.py" />
     <Content Include="UniverseUnchangedRegressionAlgorithm.py" />
     <Content Include="USEnergyInformationAdministrationAlgorithm.py" />
     <None Include="NLTKSentimentTradingAlgorithm.py" />

Algorithm.Python/TrainingInitializeRegressionAlgorithm.py

@@ -0,0 +1,52 @@
+# 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.
+
+from clr import AddReference
+AddReference("System")
+AddReference("QuantConnect.Algorithm")
+AddReference("QuantConnect.Common")
+
+from System import *
+from QuantConnect import *
+from QuantConnect.Algorithm import *
+from time import sleep
+
+### <summary>
+### This regression algorithm is expected to fail and verifies that a training event
+### created in Initialize will get run AND it will cause the algorithm to fail if it
+### exceeds the "algorithm-manager-time-loop-maximum" config value, which the regression
+### test sets to 0.5 minutes.
+### </summary>
+class TrainingInitializeRegressionAlgorithm(QCAlgorithm):
+    '''Example algorithm showing how to use QCAlgorithm.Train method'''
+
+    def Initialize(self):
+
+        self.SetStartDate(2013, 10, 7)
+        self.SetEndDate(2013, 10, 11)
+
+        self.AddEquity("SPY", Resolution.Daily)
+
+        # this should cause the algorithm to fail
+        # the regression test sets the time limit to 30 seconds and there's one extra
+        # minute in the bucket, so a two minute sleep should result in RuntimeError
+        self.Train(lambda: sleep(150))
+
+        # DateRules.Tomorrow combined with TimeRules.Midnight enforces that this event schedule will
+        # have exactly one time, which will fire between the first data point and the next day at
+        # midnight. So after the first data point, it will run this event and sleep long enough to
+        # exceed the static max algorithm time loop time and begin to consume from the leaky bucket
+        # the regression test sets the "algorithm-manager-time-loop-maximum" value to 30 seconds
+        self.Train(self.DateRules.Tomorrow, self.TimeRules.Midnight, lambda: sleep(60))
+                    # this will consume the single 'minute' available in the leaky bucket
+                    # and the regression test will confirm that the leaky bucket is empty