from QuantConnect import *
from QuantConnect.Parameters import *
from QuantConnect.Benchmarks import *
from QuantConnect.Brokerages import *
from QuantConnect.Util import *
from QuantConnect.Interfaces import *
from QuantConnect.Algorithm import *
from QuantConnect.Algorithm.Framework import *
from QuantConnect.Algorithm.Framework.Selection import *
from QuantConnect.Algorithm.Framework.Alphas import *
from QuantConnect.Algorithm.Framework.Portfolio import *
from QuantConnect.Algorithm.Framework.Execution import *
from QuantConnect.Algorithm.Framework.Risk import *
from QuantConnect.Indicators import *
from QuantConnect.Data import *
from QuantConnect.Data.Consolidators import *
from QuantConnect.Data.Custom import *
from QuantConnect.Data.Fundamental import *
from QuantConnect.Data.Market import *
from QuantConnect.Data.UniverseSelection import *
from QuantConnect.Notifications import *
from QuantConnect.Orders import *
from QuantConnect.Orders.Fees import *
from QuantConnect.Orders.Fills import *
from QuantConnect.Orders.Slippage import *
from QuantConnect.Scheduling import *
from QuantConnect.Securities import *
from QuantConnect.Securities.Equity import *
from QuantConnect.Securities.Forex import *
from QuantConnect.Securities.Interfaces import *
from datetime import date, datetime, timedelta
from QuantConnect.Python import *
from QuantConnect.Storage import *
QCAlgorithmFramework = QCAlgorithm
QCAlgorithmFrameworkBridge = QCAlgorithm
import math
import numpy as np
import pandas as pd
import scipy as sp




class RBreaker(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2020, 3, 1)  # Set Start Date
        self.SetCash(100000)  # Set Strategy Cash
        self.spy = self.AddEquity("SPY", Resolution.Hour)
        self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Margin)
        self.SetWarmup(2)
        self.R_breaker_dict = {}
        self.weight = 1.0
        
    def OnData(self, data):
        self.Debug('ON DATA')


class Resist_Support():
        
    def __init__(self, price_list):
        hi = price_list[0]
        cl = price_list[1]
        lo = price_list[2]
        self.pivot = np.mean(hi,lo,cl)
        
        self.r3 = hi + 2*(self.pivot-lo)
        self.r2 = self.pivot + hi-lo
        self.r1 = 2*(self.pivot-lo)
        self.s1 = 2*self.pivot-hi
        self.s2 = self.pivot-(hi-lo)
        self.s3 = lo-2*(hi-self.pivot)