# -*- coding: utf-8 -*-
"""
Spyder Editor

This is a temporary script file.
"""

from Modules.dataseries import dataseries
import numpy as np
import pandas as pd
import calendar
import datetime
import statsmodels.api as sm


crop = 'Heating_Oil'
month = 'Jan'
curyear = 2019
position = 'long'
abbr_to_num = {name: num for num, name in enumerate(calendar.month_abbr) if num}
monthnum = abbr_to_num[month]
out = []
startdate = []
enddate = []
duration = []
loopcount = 0

def getdate(str): # in form of date string 'month-day'
    mon = int(str.split('-')[0])
    day = int(str.split('-')[1])
    
    if datetime.date(curyear, mon, day) > datetime.date(curyear, monthnum, 15):
        curdate = datetime.date(curyear-1, mon, day)
    elif datetime.date(curyear, mon, day) > datetime.date(curyear, 1, 1) and datetime.date(curyear, mon, day) <= datetime.date(curyear, monthnum, 15):
        curdate = datetime.date(curyear, mon, day)
        
    return curdate

def getprice(str):
    curdate = getdate(str)
    mask = cur['Date'] == curdate
#    price = cur.query("Date == " + curdate.strftime("%Y-%m-%d")).Close[0]
    price = np.asarray(cur.loc[mask].Close)[0]
    return price
    
def test():
    out = []
    for i in range(len(data)):
        try:
            startprice = getprice(data.index[i][0])
            endprice = getprice(data.index[i][1])
            if position == 'short':
                out.append([data.index[i], startprice - endprice]) #Short
            else:
                out.append([data.index[i], endprice - startprice]) #Long
        except:
            continue
            
    return out

def getduration(i):
    first = data.index[i][0].split('-')
    second = data.index[i][1].split('-')
    try:
        if int(first[0]) <= int(second[0]):
            return ((datetime.date(2019,int(second[0]),int(second[1])) - datetime.date(2019,int(first[0]),int(first[1]))).days)
        else:
            return ((datetime.date(2020,int(second[0]),int(second[1])) - datetime.date(2019,int(first[0]),int(first[1]))).days)
    except:
        return 1000
    
# get current contract dataset

cur = dataseries(crop, month, curyear).dataseries


# add data cols by year
            
for year in range(2018,2020):
    df = dataseries(crop, month, year).dataseries
    npdf = np.asarray(df)
    for i in range(len(df)):
        for j in range(i+1,len(df)):
            startdate.append(str(df.Date[i].month) + '-' + str(df.Date[i].day))
            enddate.append(str(df.Date[j].month) + '-' + str(df.Date[j].day))
            if position == 'short':
                diff = df.Close[i] - df.Close[j]  # Short
            else:
                diff = df.Close[j] - df.Close[i]   # Long
            if diff <= 0:
                win = 0
            else:
                win = 1
            out.append(diff)
    
    df_yr = pd.DataFrame({'Start':startdate}).join(pd.DataFrame({'End':enddate})).join(pd.DataFrame({year:out}))
    df_yr = df_yr.set_index(['Start', 'End'])
    
    if loopcount == 0:
        data = df_yr
    else:
        data = data.join(df_yr, how='outer')
    
    loopcount+=1
    out = []
    del df_yr
    startdate = []
    enddate = []

data['mean'] = data.mean(axis=1)
data['winrate'] = (data.select_dtypes(include='float64').gt(0).sum(axis=1)-1)/(data.count(axis=1) - 1)
data['count'] = data.count(axis=1) - 2

for i in range(len(data.index)):
    duration.append(getduration(i))

data['dur'] = duration

#data = data.query("count >= " + str(int(loopcount*0.75)) + " and winrate >= 0.80 and mean > 0 and dur < 60")

# --------------- Test on curyear -----------------------

output = test()   

win = 0
sumtotal = 0
for j in range(len(output)):
    sumtotal += output[j][1]
    if output[j][1] >= 0: win += 1

print('Contract - ' + month)
print('Crop - ' + crop)
print('Total Profit - ' + str(sumtotal))
print('Win Rate - ' + str(win/len(output)))
print('Number of Trades - ' + str(len(output)))