import os
import time
import statistics
import pandas as pd
import numpy as np
from pandas_datareader import data

dir_path = os.path.dirname(os.path.realpath(__file__))

start_date = '2014-01-01'
end_date = '2018-01-01'
SRC_DATA_FILENAME = dir_path + '/goog_data.pkl'

try:
    goog_data = pd.read_pickle(SRC_DATA_FILENAME)
    print('File data found...reading GOOG data')
except FileNotFoundError:
    print('File not found...downloading the GOOG data')
    goog_data = data.DataReader('GOOG', 'yahoo', start_date, end_date)
    goog_data.to_pickle(SRC_DATA_FILENAME)

goog_data_signal = pd.DataFrame(index=goog_data.index)
goog_data_signal['price'] = goog_data['Adj Close']
close = goog_data_signal['price']
exe_start_time = time.time()

import statistics as stats
import math as math

time_period = 20 # history length for Simple Moving Average for middle band
stdev_factor = 2 # Standard Deviation Scaling factor for the upper and lower bands

history = []
sma_values = []
upper_band = []
lower_band = []

""" Calculate BBAND """

for close_price in close:
    history.append(close_price)
    if len(history) > time_period:
        del(history[0])

    sma = stats.mean(history) # BBAND_Middle
    sma_values.append(sma)

    variance = 0

    # Calculate variance using pure python
    for hist_price in history:
        variance = variance + ((hist_price - sma) ** 2)

    stdev = math.sqrt(variance / len(history))
    upper_band.append(sma + stdev_factor * stdev)
    lower_band.append(sma - stdev_factor * stdev)

""" Draw Gragh """
goog_data = goog_data.assign(ClosePrice=pd.Series(close, index=goog_data.index))
goog_data = goog_data.assign(MiddleBollingerBand20DaySMA=pd.Series(sma_values, index=goog_data.index))
goog_data = goog_data.assign(UpperBollingerBand20DaysSMA2StddevFactor=pd.Series(upper_band, index=goog_data.index))
goog_data = goog_data.assign(LowerBollingerBand20DaysSMA2StddevFactor=pd.Series(lower_band, index=goog_data.index))

import matplotlib.pyplot as plt

fig = plt.figure()
ax1 = fig.add_subplot(111, ylabel='Google price in $')
goog_data['ClosePrice'].plot(ax=ax1, color='g', lw=2., legend=True)
goog_data['MiddleBollingerBand20DaySMA'].plot(ax=ax1, color='b', lw=2., legend=True)
goog_data['UpperBollingerBand20DaysSMA2StddevFactor'].plot(ax=ax1, color='y', lw=2., legend=True)
goog_data['LowerBollingerBand20DaysSMA2StddevFactor'].plot(ax=ax1, color='r', lw=2., legend=True)
plt.savefig(dir_path + '/bbands.png')
plt.show()