chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
5008 changed files with 910633 additions and 0 deletions
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+/*
+ * 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 System.Linq;
+using System.Collections.Generic;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm illustrating how to request history data for different data mapping modes.
+    /// </summary>
+    public class HistoryWithDifferentDataMappingModeRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _continuousContractSymbol;
+
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 6);
+            SetEndDate(2014, 1, 1);
+            _continuousContractSymbol = AddFuture(Futures.Indices.SP500EMini, Resolution.Daily).Symbol;
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            var dataMappingModes = ((DataMappingMode[])Enum.GetValues(typeof(DataMappingMode))).ToList();
+            var historyResults = dataMappingModes.Select(dataMappingMode =>
+            {
+                return History(new [] { _continuousContractSymbol }, StartDate, EndDate, Resolution.Daily, dataMappingMode: dataMappingMode).ToList();
+            }).ToList();
+
+            if (historyResults.Any(x => x.Count != historyResults[0].Count))
+            {
+                throw new RegressionTestException("History results bar count did not match");
+            }
+
+            // Check that all history results have a mapping date at some point in the history
+            HashSet<DateTime> mappingDates = new HashSet<DateTime>();
+            for (int i = 0; i < historyResults.Count; i++)
+            {
+                var underlying = historyResults[i].First().Bars.Keys.First().Underlying;
+                int mappingsCount = 0;
+
+                foreach (var slice in historyResults[i])
+                {
+                    var dataUnderlying = slice.Bars.Keys.First().Underlying;
+                    if (dataUnderlying != underlying)
+                    {
+                        underlying = dataUnderlying;
+                        mappingsCount++;
+                        mappingDates.Add(slice.Time.Date);
+                    }
+                }
+
+                if (mappingsCount == 0)
+                {
+                    throw new RegressionTestException($"History results for {dataMappingModes[i]} data mapping mode did not contain any mappings");
+                }
+            }
+
+            if (mappingDates.Count < dataMappingModes.Count)
+            {
+                throw new RegressionTestException($"History results should have had different mapping dates for each data mapping mode");
+            }
+
+            // Check that close prices at each time are different for different data mapping modes
+            for (int j = 0; j < historyResults[0].Count; j++)
+            {
+                var closePrices = historyResults.Select(hr => hr[j].Bars.First().Value.Close).ToHashSet();
+                if (closePrices.Count != dataMappingModes.Count)
+                {
+                    throw new RegressionTestException($"History results close prices should have been different for each data mapping mode at each time");
+                }
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 970;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 488;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-3.738"},
+            {"Tracking Error", "0.087"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}