import pandas as pd
import numpy as np
from future_functions import *

# Load CSV Data

data = pd.read_csv('Data/EURUSDHours.csv')

data.columns = ['Date','open','high','low','close','AskVol']

data = data.set_index(pd.to_datetime(data.Date))

data = data[['open','high','low','close','AskVol']]

prices = data.drop_duplicates(keep=False)

hkaprices = prices.copy()
hkaprices['Symbol'] = 'SYMB'

HKA = OHLCresample(hkaprices,'15H')

def OHLCresample(DataFrame,TimeFrame,column='ask'):

    grouped = DataFrame.groupby('Symbol')

    if np.any(DataFrame.columns == 'Ask'):

        if column == 'ask':
            ask = grouped['Ask'].resample(TimeFrame).ohlc()
            askVol = grouped['AskVol'].resample(TimeFrame).count()
            resampled = pd.DataFrame(ask)
            resampled['AskVol'] = askVol

        elif column == 'bid':
            bid = grouped['Bid'].resample(TimeFrame).ohlc()
            bidVol = grouped['BidVol'].resample(TimeFrame).count()
            resampled = pd.DataFrame(bid)
            resampled['BidVol'] = bidVol

        else:

            raise ValueError('Column must be a string. Either ask or bid')

    elif np.any(DataFrame.columns == 'close'):
        open = grouped['open'].resample(TimeFrame).ohlc()
        close = grouped['close'].resample(TimeFrame).ohlc()
        high = grouped['high'].resample(TimeFrame).ohlc()
        low = grouped['low'].resample(TimeFrame).ohlc()
        askVol = grouped['AskVol'].resample(TimeFrame).ohlc()

        resampled = pd.DataFrame(open)
        resampled['high'] = high
        resampled['low'] = low
        resampled['close'] = close
        resampled['AskVol'] = askVol

    resampled = resampled.dropna()

    return resampled