def InjectTestData():
#init a new forecast object, fill it with anything
Forecast(
rank = 1,
symbol = "GOOG",
company = "Google, Inc.",
exchange = "NASDAQ",
industry = "Technology",
#predictions
openPredPrice = list(550.0+5.0*(np.random.ranf(11)-0.5)),
closePredPrice = list(550.0+5.0*(np.random.ranf(11)-0.5)),
highPredPrice = list(555.0+10.0*(np.random.ranf(11)-0.5)),
lowPredPrice = list(545.0+10.0*(np.random.ranf(11)-0.5)),
volumePred = list(np.random.randint(1850000,2150000, 11)),
dayOfPred = ['M','Tu','W','Th','F',
'M','Tu','W','Th', 'F',
'M','Tu','W','Th', 'F',
'M','Tu','W','Th', 'F',
'M','Tu','W','Th', 'F',
'M','Tu','W','Th', 'F',
'M'],
#History lists
openPriceHistory = list(550.0+5.0*(np.random.ranf(10)-0.5)),
closePriceHistory = list(550.0+5.0*(np.random.ranf(10)-0.5)),
highPriceHistory = list(560.0+10.0*(np.random.ranf(10)-0.5)),
lowPriceHistory = list(540.0+10.0*(np.random.ranf(10)-0.5)),
volumeHistory = list(np.random.randint(1850000,2150000, 10)),
#prediction validation value, R2
openPredR2 = 1.0 + (np.random.ranf(1)[0] - 0.5)/10.0,
closePredR2 = 1.0 + (np.random.ranf(1)[0] - 0.5)/10.0,
highPredR2 = 1.0 + (np.random.ranf(1)[0] - 0.5)/10.0,
lowPredR2 = 1.0 + (np.random.ranf(1)[0] - 0.5)/10.0,
volumePredR2 = 1.0 + (np.random.ranf(1)[0] - 0.5)/10.0,
openPredSlope = 1.0 + (np.random.ranf(1)[0] - 0.5)/10.0,
closePredSlope = 1.0 + (np.random.ranf(1)[0] - 0.5)/10.0,
highPredSlope = 1.0 + (np.random.ranf(1)[0] - 0.5)/10.0,
lowPredSlope = 1.0 + (np.random.ranf(1)[0] - 0.5)/10.0,
volumePredSlope = 1.0 + (np.random.ranf(1)[0] - 0.5)/10.0,
openModelAccuracy = 1,
closeModelAccuracy = 2,
highModelAccuracy = 2,
lowModelAccuracy = 3
).put()
StockList(
rank = 1,
symbol = "GOOG",
company = "Google, Inc.",
exchange = "NASDAQ",
currentPrice = 550.0+5.0*(np.random.ranf(1)[0]-0.5),
forecastedPrice = 550.0+5.0*(np.random.ranf(1)[0]-0.5),
modelAccuracy = np.random.randint(1,4,1)[0]
).put()
