import pandas as pd
import pandas_datareader.data as web
import numpy as np
import math
import matplotlib.pyplot as plt
import datetime

# Stock Investors Financial Math
# https://www.fmlabs.com/reference/default.htm?url=SimpleMA.htm

# Alpha Vantage
# https://www.alphavantage.co/documentation/

# Pandas
# https://pandas.pydata.org/pandas-docs/stable/index.html

# Knowledge
# https://www.investopedia.com/articles/technical/02/050602.asp
# https://ntguardian.wordpress.com/2016/09/19/introduction-stock-market-data-python-1

key = '0UO7Z2MVZ2YSQSVE'


def sin(f, a, N):
	result = np.empty(0)
	for n in range(0, N):
		v = a*math.sin(2*math.pi*f*n/N)
		result = np.append(result, v)

	return result

def ema(data, alpha=0.75):
	result = np.empty(0)
	r = data[0]

	for v in data:
		r = alpha*r + (1-alpha)*v
		result = np.append(result, r)

	return result

def macd(data):
	ema_short = ema(data, alpha=0.85)
	ema_long = ema(data, alpha=0.925)

	return ema_short - ema_long

if 0:
	# Get stock price via data reader
	start = datetime.datetime(2016,1,1)
	end = datetime.date.today()
	apple = web.DataReader("AAPL", "av-monthly", start, end, api_key=key)
	type(apple)

pd_data = pd.read_csv("aapl.csv", names=['Dates', 'Price'])
np_data = np.flip(pd_data['Price'].to_numpy())

plt.plot(np_data, label='Price')
plt.plot(ema(np_data), label='EMA')
plt.plot(macd(np_data), label='MACD')
plt.legend()
plt.grid()
plt.show()