chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
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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.
+
+from AlgorithmImports import *
+
+### <summary>
+### Regression algorithm asserting the behavior of the indicator history api
+### </summary>
+class IndicatorHistoryRegressionAlgorithm(QCAlgorithm):
+    '''Regression algorithm asserting the behavior of the indicator history api'''
+
+    def initialize(self):
+        '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
+        self.set_start_date(2013, 1, 1)
+        self.set_end_date(2014, 12, 31)
+
+        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
+
+    def on_data(self, slice: Slice):
+        self.bollinger_bands = BollingerBands("BB", 20, 2.0, MovingAverageType.SIMPLE)
+
+        if self.bollinger_bands.window.is_ready:
+            raise ValueError("Unexpected ready bollinger bands state")
+
+        indicatorHistory = self.indicator_history(self.bollinger_bands, self._symbol, 50)
+        
+        self.debug(f"indicatorHistory: {indicatorHistory}")
+
+        self.debug(f"data_frame: {indicatorHistory.data_frame}")
+
+        if not self.bollinger_bands.window.is_ready:
+            raise ValueError("Unexpected not ready bollinger bands state")
+
+        # we ask for 50 data points
+        if indicatorHistory.count != 50:
+            raise ValueError(f"Unexpected indicators values {indicatorHistory.count}")
+
+        for indicatorDataPoints in indicatorHistory:
+            middle_band = indicatorDataPoints["middle_band"]
+            self.debug(f"BB @{indicatorDataPoints.current}: middle_band: {middle_band} upper_band: {indicatorDataPoints.upper_band}")
+            if indicatorDataPoints == 0:
+                raise ValueError(f"Unexpected indicators point {indicatorDataPoints}")
+
+        currentValues = indicatorHistory.current
+        if len(currentValues) != 50 or len([x for x in currentValues if x.value == 0]) > 0:
+            raise ValueError(f"Unexpected indicators current values {len(currentValues)}")
+        upperBandPoints = indicatorHistory["upper_band"]
+        if len(upperBandPoints) != 50 or len([x for x in upperBandPoints if x.value == 0]) > 0:
+            raise ValueError(f"Unexpected indicators upperBandPoints values {len(upperBandPoints)}")
+
+        # We are done now!
+        self.quit()