# 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 AlgorithmImports import * ### ### Regression algorithm illustrating how to request history data for different data mapping modes. ### class HistoryWithDifferentDataMappingModeRegressionAlgorithm(QCAlgorithm): def initialize(self): self.set_start_date(2013, 10, 6) self.set_end_date(2014, 1, 1) self._continuous_contract_symbol = self.add_future(Futures.Indices.SP_500_E_MINI, Resolution.DAILY).symbol def on_end_of_algorithm(self): history_results = [ self.history([self._continuous_contract_symbol], self.start_date, self.end_date, Resolution.DAILY, data_mapping_mode=data_mapping_mode) .droplevel(0, axis=0) .loc[self._continuous_contract_symbol] .close for data_mapping_mode in DataMappingMode ] if any(x.size != history_results[0].size for x in history_results): raise AssertionError("History results bar count did not match") # Check that close prices at each time are different for different data mapping modes for j in range(history_results[0].size): close_prices = set(history_results[i][j] for i in range(len(history_results))) if len(close_prices) != len(DataMappingMode): raise AssertionError("History results close prices should have been different for each data mapping mode at each time")