# 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 SecuritySessionRegressionAlgorithm import SecuritySessionRegressionAlgorithm

### <summary>
### Regression algorithm to validate SecurityCache.Session with Futures.
### Ensures OHLCV are consistent with Tick data.
### </summary>
class SecuritySessionWithFuturesRegressionAlgorithm(SecuritySessionRegressionAlgorithm):
 def initialize_security(self):
 self.set_start_date(2013, 10, 7)
 self.set_end_date(2013, 10, 8)
 self.security = self.add_future(Futures.Metals.GOLD, Resolution.TICK)
 self.bid_price = 0
 self.ask_price = 0
 self.bid_high = 0
 self.bid_low = float('inf')
 self.ask_low = float('inf')
 self.ask_high = 0
 self.previous_open_interest = 0

 def is_within_market_hours(self, current_date_time):
 return self.security.exchange.hours.is_open(current_date_time, False)

 def accumulate_session_data(self, data):
 symbol = self.security.symbol
 
 for tick in data.ticks[symbol]:
 if tick.tick_type == TickType.TRADE:
 self.volume += tick.quantity
 
 if self.current_date.date() == tick.time.date():
 # Same trading day
 if tick.bid_price != 0:
 self.bid_price = tick.bid_price
 self.bid_low = min(self.bid_low, tick.bid_price)
 self.bid_high = max(self.bid_high, tick.bid_price)
 
 if tick.ask_price != 0:
 self.ask_price = tick.ask_price
 self.ask_low = min(self.ask_low, tick.ask_price)
 self.ask_high = max(self.ask_high, tick.ask_price)
 
 if self.bid_price != 0 and self.ask_price != 0:
 mid_price = (self.bid_price + self.ask_price) / 2
 if self.open == 0:
 self.open = mid_price
 self.close = mid_price
 
 if self.bid_high != 0 and self.ask_high != 0:
 self.high = max(self.high, (self.bid_high + self.ask_high) / 2)
 
 if self.bid_low != float('inf') and self.ask_low != float('inf'):
 self.low = min(self.low, (self.bid_low + self.ask_low) / 2)
 
 else:
 # New trading day
 if self.previous_session_bar is not None:
 session = self.security.session
 if (self.previous_session_bar['open'] != session[1].open
 or self.previous_session_bar['high'] != session[1].high
 or self.previous_session_bar['low'] != session[1].low
 or self.previous_session_bar['close'] != session[1].close
 or self.previous_session_bar['volume'] != session[1].volume
 or self.previous_session_bar['open_interest'] != session[1].open_interest):
 raise RegressionTestException("Mismatch in previous session bar (OHLCV)")

 # This is the first data point of the new session
 self.open = (self.bid_price + self.ask_price) / 2
 self.low = float('inf')
 self.bid_low = float('inf')
 self.ask_low = float('inf')
 self.volume = 0
 self.current_date = tick.time
 
 def validate_session_bars(self):
 session = self.security.session
 # At this point the data was consolidated (market close)

 # Save previous session bar
 self.previous_session_bar = {
 'date': self.current_date,
 'open': self.open,
 'high': self.high,
 'low': self.low,
 'close': self.close,
 'volume': self.volume,
 'open_interest': self.security.open_interest
 }

 if self.security_was_removed:
 self.previous_session_bar = None
 self.security_was_removed = False
 return

 # Check current session values
 if (not self._are_equal(session.open, self.open)
 or not self._are_equal(session.high, self.high)
 or not self._are_equal(session.low, self.low)
 or not self._are_equal(session.close, self.close)
 or not self._are_equal(session.volume, self.volume)
 or not self._are_equal(session.open_interest, self.security.open_interest)):
 raise RegressionTestException("Mismatch in current session bar (OHLCV)")