def prepare_data():
openp = data_original[:, 1].tolist()[0:]
highp = data_original[:, 2].tolist()[0:]
lowp = data_original[:, 3].tolist()[0:]
closep = data_original[:, 4].tolist()[0:]
volumep = data_original[:, 5].tolist()[0:]
#open = data_original['Open'].rolling(21).mean()
#high = data_original['High'].rolling(21).mean()
#low = data_original['low'].rolling(21).mean()
close = pd.DataFrame(closep).rolling(21, min_periods=0).mean()
close_ema = pd.DataFrame(closep).ewm(span=21,min_periods=21-1 ,adjust=False).mean()
print(close)
print("ema: ", close_ema)
#macdk= ta.MACD(np.array(closep))
#print("macd ",macdk)
x_i = np.column_stack((openp, highp, lowp, closep, volumep,close))
print("len", (len(x_i)))
# print("X_i",x_i)
y_i = closep
x, y = np.array(x_i), np.array(y_i)
tr_date, ts_date, X_train, X_test, Y_train, Y_test = create_Xt_Yt(timestamp, x, y)
return tr_date, ts_date, X_train, X_test, Y_train, Y_test
print("fun prepare_Data ended!!! ")
def data_sets(labels, volumep1, p_sets, y_i, timestamp):
for i in range(1, len(p_sets), 1):
ps = p_sets[i]
label = labels[i]
x_i = np.column_stack(ps)
x_i, y_i = np.array(x_i), np.array(y_i)
#print('ps: ' + str(i) + "", ps)
print("len of p: " + str(i) + ": ", len(ps))
#print('x_ ' + str(i) + ": ", x_i)
tr_date, ts_date, X_train, X_test, Y_train, Y_test = create_Xt_Yt(
timestamp, x_i, y_i)
prepare_model(i, label, volumep1, tr_date, ts_date, X_train, X_test,
Y_train, Y_test)
def prepare_data(data_original, timestamp):
openp = data_original[:, 1].tolist()[0:]
highp = data_original[:, 2].tolist()[0:]
lowp = data_original[:, 3].tolist()[0:]
closep = data_original[:, 4].tolist()[0:]
volumep = data_original[:, 5].tolist()[0:]
x_i = np.column_stack((openp, highp, lowp, closep, volumep))
print("len", (len(x_i)))
# print("X_i",x_i)
y_i = closep
x, y = np.array(x_i), np.array(y_i)
tr_date, ts_date, X_train, X_test, Y_train, Y_test = create_Xt_Yt(
timestamp, x, y)
return tr_date, ts_date, X_train, X_test, Y_train, Y_test
def prepare_data(data_original, timestamp):
openp = data_original[:, 1].tolist()[0:]
highp = data_original[:, 2].tolist()[0:]
lowp = data_original[:, 3].tolist()[0:]
closep = data_original[:, 4].tolist()[0:]
volumep = data_original[:, 5].tolist()[0:]
x, y = [], []
x_i = np.column_stack((openp, highp, lowp, closep, volumep))
print("len", (len(x_i)))
# print("X_i",x_i)
y_i = volumep
# print("closeP: ",pd.DataFrame(y_i))
x, y = np.array(x_i), np.array(y_i)
# print("X",X)
tr_date, ts_date, X_train, X_test, Y_train, Y_test = create_Xt_Yt(
timestamp, x, y)
return tr_date, ts_date, X_train, X_test, Y_train, Y_test
print("fun prepare_Data ended!!! ")
def prepare_data(data_original, timestamp):
'''
openp = data_original[:, 1].tolist()[0:]
highp = data_original[:, 2].tolist()[0:]
lowp = data_original[:, 3].tolist()[0:]
closep = data_original[:, 4].tolist()[0:]
volumep = data_original[:, 5].tolist()[0:]
'''
openp = data_original.ix[:, 'Open'].tolist()[0:]
highp = data_original.ix[:, 'High'].tolist()[0:]
lowp = data_original.ix[:, 'Low'].tolist()[0:]
closep = data_original.ix[:, 'Close'].tolist()[0:]
volumep = data_original.ix[:, 'Volume_(BTC)'].tolist()[0:]
print(openp)
#volumecp = data_original.ix[:, 'Volume_(Currency)'].tolist()[1:]
x, y = [], []
X, Y = [], []
for i in range(0, len(data_original), STEP):
try:
o = openp[i:i + window]
h = highp[i:i + window]
l = lowp[i:i + window]
c = closep[i:i + window]
v = volumep[i:i + window]
#vc = volumecp[i:i + window]
#volat = volatility[i:i + window]
print("o ", o)
o = (np.array(o) - np.mean(o)) / np.std(o)
print("mean o ", o)
h = (np.array(h) - np.mean(h)) / np.std(h)
l = (np.array(l) - np.mean(l)) / np.std(l)
c = (np.array(c) - np.mean(c)) / np.std(c)
v = (np.array(v) - np.mean(v)) / np.std(v)
#vc = (np.array(vc) - np.mean(vc)) / np.std(vc)
#volat = (np.array(volat) - np.mean(volat)) / np.std(volat)
x_i = np.column_stack((o, h, l, c, v))
x_i = x_i.flatten()
y_i = (closep[i + window + FORECAST] -
closep[i + window]) / closep[i + window]
if np.isnan(x_i).any():
continue
except Exception as e:
break
x.append(x_i)
y.append(y_i)
'''
x_i = np.column_stack((openp, highp, lowp, closep, volumep))
print("len", (len(x_i)))
# print("X_i",x_i)
y_i = closep
# print("closeP: ",pd.DataFrame(y_i))
'''
x, y = np.array(x), np.array(y)
# print("X",X)
print(len(x), len(y))
tr_date, ts_date, X_train, X_test, Y_train, Y_test = create_Xt_Yt(
timestamp, x, y)
return tr_date, ts_date, X_train, X_test, Y_train, Y_test
print("fun prepare_Data ended!!! ")