def getPrediction2(stock_name):
stock_data = getStockData(stock_name)
if not stock_data[0]:
print("Sorry, the stock you requested is not in our database.")
print("Please enter another stock.")
return []
roc = mm.getRateOfChange(stock_data) # array
if not roc:
roc = [0]
stoch_os = mm.getStochasticOscillator(stock_data) # array
asi = mm.getASI(stock_data) # array
curPrice = mm.getCurPrice(stock_data[4])
data = []
for i in stock_data[4]:
data = [i] + data
arima_prediction = mm.getARIMA(data) # double
fourier_prediction = mm.getFourier(data)
prediction = mm.aggregatePrediction(roc, stoch_os, asi, curPrice,
arima_prediction, fourier_prediction)
data.append(prediction[0])
#graph_data(stock_data[0], data, stock_name)
return [
roc[0], stoch_os[0], asi[0], curPrice, arima_prediction,
fourier_prediction[0], prediction[0], prediction[1], stock_name
]
def getOutputtedPrediction(stock_name):
stock_data = techController.getStockData(stock_name)
num_predictions = 36 # HAS TO be at most as much as num_predictions in Fourier Model
lastCloses = []
for i in range(num_predictions):
stock_data[0].pop(0)
stock_data[1].pop(0)
lastCloses.append(stock_data[4].pop(0))
currentClose = stock_data[4][0]
stock_data[2].pop(0)
stock_data[3].pop(0)
roc = mm.getRateOfChange(stock_data) # array
stoch_os = mm.getStochasticOscillator(stock_data) # array
asi = mm.getASI(stock_data) # array
data = []
for i in stock_data[4]:
data = [i] + data
arima_prediction = mm.getARIMA(data) # double
fourier_predictions = mm.getFourier(data)
prediction = mm.aggregatePrediction( roc, stoch_os, asi,currentClose, arima_prediction, fourier_predictions)
print(prediction)
return [prediction[0], prediction[1], arima_prediction, fourier_predictions,lastCloses]
def getPrediction(stock_name):
stock_data = getStockData(stock_name)
roc = mm.getRateOfChange(stock_data) #array
stoch_os = mm.getStochasticOscillator(stock_data) #array
asi = mm.getASI(stock_data) #array
data = []
for i in stock_data[4]:
data = [i] + data
arima_prediction = mm.getARIMA(data) #double
fourier_prediction = mm.getFourier(data)
prediction = mm.aggregatePrediction(roc, stoch_os, asi, arima_prediction, fourier_prediction)
data.append(prediction)
graph_data(stock_data[0], data, stock_name)
return
def getOutputtedPrediction(stock_name):
stock_data = techController.getStockData(stock_name)
lastTime = stock_data[0].pop()
lastOpen = stock_data[1].pop()
lastClose = stock_data[4].pop()
lastHigh = stock_data[2].pop()
lastLow = stock_data[3].pop()
roc = mm.getRateOfChange(stock_data) # array
stoch_os = mm.getStochasticOscillator(stock_data) # array
asi = mm.getASI(stock_data) # array
arima_prediction = mm.getARIMA(stock_data[4]) # double
fourier_prediction = mm.getFourier(stock_data[4])[0]
prediction = mm.aggregatePrediction(roc, stoch_os, asi, arima_prediction,
fourier_prediction)
return [prediction, arima_prediction, fourier_prediction, lastClose]