# 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 *

from collections import deque
from math import isclose

class CustomIndicatorWithExtensionAlgorithm(QCAlgorithm):
 def initialize(self) -> None:
 self.set_start_date(2013, 10, 9)
 self.set_end_date(2013, 10, 9)

 self._spy = self.add_equity("SPY", Resolution.MINUTE).symbol

 self._sma_values = []
 self._period = 10

 self._sma = self.sma(self._spy, self._period, Resolution.MINUTE)
 self._sma.updated += self.on_sma_updated

 self._custom_sma = CustomSimpleMovingAverage("My SMA", self._period)
 self._ext = IndicatorExtensions.of(self._custom_sma, self._sma)
 self._ext.updated += self.on_indicator_extension_updated

 self._sma_minus_custom = IndicatorExtensions.minus(self._sma, self._custom_sma)
 self._sma_minus_custom.updated += self.on_minus_updated

 self._sma_was_updated = False
 self._custom_sma_was_updated = False
 self._sma_minus_custom_was_updated = False

 def on_sma_updated(self, sender: object, updated: IndicatorDataPoint) -> None:
 self._sma_was_updated = True

 if self._sma.is_ready:
 self._sma_values.append(self._sma.current.value)

 def on_indicator_extension_updated(self, sender: object, updated: IndicatorDataPoint) -> None:
 self._custom_sma_was_updated = True

 sma_last_values = self._sma_values[-self._period:]
 expected = sum(sma_last_values) / len(sma_last_values)

 if not isclose(expected, self._custom_sma.value):
 raise AssertionError(f"Expected the custom SMA to calculate the moving average of the last {self._period} values of the SMA. "
 f"Current expected: {expected}. Actual {self._custom_sma.value}.")

 self.debug(f"{self._sma.current.value} :: {self._custom_sma.value} :: {updated}")

 def on_minus_updated(self, sender: object, updated: IndicatorDataPoint) -> None:
 self._sma_minus_custom_was_updated = True

 expected = self._sma.current.value - self._custom_sma.value

 if not isclose(expected, self._sma_minus_custom.current.value):
 raise AssertionError(f"Expected the composite minus indicator to calculate the difference between the SMA and custom SMA indicators. "
 f"Expected: {expected}. Actual {self._sma_minus_custom.current.value}.")

 def on_end_of_algorithm(self) -> None:
 if not (self._sma_was_updated and self._custom_sma_was_updated and self._sma_minus_custom_was_updated):
 raise AssertionError("Expected all indicators to have been updated.")

# Custom indicator
class CustomSimpleMovingAverage(PythonIndicator):
 def __init__(self, name: str, period: int) -> None:
 self.name = name
 self.value = 0
 self.warm_up_period = period
 self._queue = deque(maxlen=period)

 def update(self, input: BaseData) -> bool:
 self._queue.appendleft(input.value)
 count = len(self._queue)
 self.value = sum(self._queue) / count

 return count == self._queue.maxlen