wehub-resource-sync
88 lines
3.7 KiB
Python
88 lines
3.7 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from AlgorithmImports import *
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from collections import deque
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from math import isclose
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class CustomIndicatorWithExtensionAlgorithm(QCAlgorithm):
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def initialize(self) -> None:
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self.set_start_date(2013, 10, 9)
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self.set_end_date(2013, 10, 9)
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self._spy = self.add_equity("SPY", Resolution.MINUTE).symbol
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self._sma_values = []
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self._period = 10
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self._sma = self.sma(self._spy, self._period, Resolution.MINUTE)
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self._sma.updated += self.on_sma_updated
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self._custom_sma = CustomSimpleMovingAverage("My SMA", self._period)
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self._ext = IndicatorExtensions.of(self._custom_sma, self._sma)
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self._ext.updated += self.on_indicator_extension_updated
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self._sma_minus_custom = IndicatorExtensions.minus(self._sma, self._custom_sma)
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self._sma_minus_custom.updated += self.on_minus_updated
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self._sma_was_updated = False
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self._custom_sma_was_updated = False
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self._sma_minus_custom_was_updated = False
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def on_sma_updated(self, sender: object, updated: IndicatorDataPoint) -> None:
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self._sma_was_updated = True
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if self._sma.is_ready:
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self._sma_values.append(self._sma.current.value)
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def on_indicator_extension_updated(self, sender: object, updated: IndicatorDataPoint) -> None:
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self._custom_sma_was_updated = True
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sma_last_values = self._sma_values[-self._period:]
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expected = sum(sma_last_values) / len(sma_last_values)
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if not isclose(expected, self._custom_sma.value):
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raise AssertionError(f"Expected the custom SMA to calculate the moving average of the last {self._period} values of the SMA. "
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f"Current expected: {expected}. Actual {self._custom_sma.value}.")
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self.debug(f"{self._sma.current.value} :: {self._custom_sma.value} :: {updated}")
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def on_minus_updated(self, sender: object, updated: IndicatorDataPoint) -> None:
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self._sma_minus_custom_was_updated = True
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expected = self._sma.current.value - self._custom_sma.value
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if not isclose(expected, self._sma_minus_custom.current.value):
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raise AssertionError(f"Expected the composite minus indicator to calculate the difference between the SMA and custom SMA indicators. "
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f"Expected: {expected}. Actual {self._sma_minus_custom.current.value}.")
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def on_end_of_algorithm(self) -> None:
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if not (self._sma_was_updated and self._custom_sma_was_updated and self._sma_minus_custom_was_updated):
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raise AssertionError("Expected all indicators to have been updated.")
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# Custom indicator
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class CustomSimpleMovingAverage(PythonIndicator):
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def __init__(self, name: str, period: int) -> None:
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self.name = name
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self.value = 0
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self.warm_up_period = period
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self._queue = deque(maxlen=period)
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def update(self, input: BaseData) -> bool:
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self._queue.appendleft(input.value)
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count = len(self._queue)
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self.value = sum(self._queue) / count
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return count == self._queue.maxlen
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