from analytics import Portfolio, BlackSwaption, Index, VolatilitySurface, Swaption
import pandas as pd
from pandas.tseries.offsets import BDay
import numpy as np
import datetime

option_delta = Index.from_tradeid(874)
option1 = BlackSwaption.from_tradeid(7, option_delta)
option2 = BlackSwaption.from_tradeid(8, option_delta)

portf = Portfolio([option1, option2, option_delta])
date_range = pd.bdate_range(option_delta.trade_date,
                            pd.Timestamp('2017-04-25'), freq = 'B')
pnl = []
for date in date_range:
    portf.trade_date = date.date()
    portf.mark(source="BAML", model="black")
    pnl.append(portf.pnl)
df = pd.DataFrame({'pnl': pnl}, index=date_range)

# option_delta = Index.from_tradeid(870)
# option1 = BlackSwaption.from_tradeid(5, option_delta)
# option2 = BlackSwaption.from_tradeid(6, option_delta)

# portf = Portfolio([option1, option2, option_delta])
# date_range = pd.bdate_range(option_delta.trade_date,
#                             pd.Timestamp('2017-04-19'), freq = 'B')
# pnl = []
# for date in date_range:
#     portf.trade_date = date.date()
#     try:
#         portf.mark(source="BAML", model="black")
#     except ValueError:
#         try:
#             portf.mark(source="GS", model="black")
#         except ValueError:
#             pnl.append(None)
#             continue
#     pnl.append(portf.pnl)
# df = pd.DataFrame({'pnl': pnl}, index=date_range)