from pyisda.curve import YieldCurve, BadDay, SpreadCurve
from pyisda.utils import build_yc
from pyisda.cdsone import upfront_charge
from pyisda.legs import ContingentLeg, FeeLeg
from quantlib.settings import Settings
from quantlib.time.api import (
    Date, today, Period, Years, WeekendsOnly, Quarterly, CDS, Actual360,
    ModifiedFollowing )
from quantlib.quotes import SimpleQuote
from quantlib.termstructures.credit.api import SpreadCdsHelper
from quantlib.pricingengines.credit.isda_cds_engine import IsdaCdsEngine
import datetime
import array
import math
import numpy as np
import pandas as pd
from db import dbengine
from yieldcurve import YC

def get_spread(index, series):
    engine = dbengine("serenitasdb")
    df = pd.read_sql("SELECT date, tenor, closespread FROM index_quotes WHERE " \
                     "index = %(index)s and series = %(series)s",
                     engine,
                     params = {"index": index, "series": series},
                     parse_dates=['date'],
                     index_col = ['date', 'tenor'])
    df = df.unstack('tenor')
    return df

def test_sc(df):
    tenors = [Period(3, Years), Period(5, Years), Period(7, Years), Period(10, Years)]
    quotes = [SimpleQuote()]*3
    helpers = [SpreadCdsHelper(q, t, 1, WeekendsOnly(), Quarterly,
                               ModifiedFollowing, CDS, Actual360(), 0.4,
                               lastperiod = Actual360(True))
               for q, t in zip(quotes, tenors)]
    pdc = PiecewiseCreditDefaultCurve(
    for r in df.itertuples(index=False, name = None):
        quotes[0].value = v[1]
        quotes[1].value = v[2]
        quotes[2].value  = v[3]
        quotes[3].value = v[4]


def FEP(sc, recovery):
     pass

if __name__ == "__main__":
    settings = Settings()
    trade_date = datetime.date.today()
    settings.evaluation_date = today()
    start_date = datetime.date(2016, 6, 20)
    term_date = datetime.date(2021, 6, 20)

    dc = YC()
    isda_engine = "po"
    value_date = trade_date
    yc = build_yc(trade_date, True)
    spread = 0.007
    spread = array.array('d', [spread])
    value_date = datetime.date(2016, 7, 29)
    step_in_date = trade_date + datetime.timedelta(days=1)
    sc = SpreadCurve(trade_date, yc, start_date, step_in_date,
                     value_date, [term_date], spread, 0.4, True)
    sc_data = sc.inspect()['data']
    hazard_rate = math.log(1 + sc_data[0][1])
    expiration_date = datetime.date(2016, 9, 21)
    fee_leg = FeeLeg(start_date, term_date, True, 1, 1)
    default_leg = ContingentLeg(start_date, term_date, 1)
    fee_leg_expiry = FeeLeg(start_date, expiration_date, True, 1, 1)
    default_leg_expiry = ContingentLeg(start_date, expiration_date, 1)

    fee_leg_pv = fee_leg.pv(trade_date, step_in_date, trade_date,
                            yc, sc, True)
    default_leg_pv = default_leg.pv(trade_date, step_in_date, trade_date,
                                    yc, sc, 0.4)
    V1 = default_leg_pv - fee_leg_pv

    fee_leg_expiry_pv = fee_leg_expiry.pv(trade_date, step_in_date, trade_date,
                                          yc, sc, True)
    default_leg_expiry_pv  = default_leg_expiry.pv(trade_date, step_in_date, trade_date,
                                                   yc, sc, 0.4)
    V2 = default_leg_expiry_pv - fee_leg_expiry_pv

    forward_annuity = fee_leg.pv(trade_date, expiration_date+datetime.timedelta(days=1), trade_date,
                                 yc, sc, True)
    exercise_settlement = datetime.date(2016, 9, 25)
    print((0.007-0.01) * forward_annuity)

    forward_price = forward_annuity*(0.007-0.01) / (
        yc.discount_factor(exercise_settlement)*math.exp(-hazard_rate * (expiration_date-trade_date).days/365
        ))
    print(fee_leg.pv(trade_date, step_in_date, trade_date,
                     yc, sc, True))

    print(fee_leg.pv(trade_date, expiration_date + datetime.timedelta(days=1), trade_date,
                     yc, sc, True))