rsi_lookback = (rsi_lookback * 2) – 1 # From exponential to smoothed
# Get the difference in price from previous step
delta = []
for i in range(len(Data)):
try:
diff = Data[i, what1] – Data[i – 1, what1]
delta = np.append(delta, diff)
except IndexError:
pass
delta = np.insert(delta, 0, 0, axis = 0)
delta = delta[1:]
# Make the positive gains (up) and negative gains (down) Series
up, down = delta.copy(), delta.copy()
up[up < 0] = 0
down[down > 0] = 0
up = np.array(up)
down = np.array(down)
roll_up = up
roll_down = down
roll_up = np.reshape(roll_up, (-1, 1))
roll_down = np.reshape(roll_down, (-1, 1))
roll_up = adder(roll_up, 3)
roll_down = adder(roll_down, 3)
roll_up = ema(roll_up, 2, rsi_lookback, what2, 1)
roll_down = ema(abs(roll_down), 2, rsi_lookback, what2, 1)
roll_up = roll_up[rsi_lookback:, 1:2]
roll_down = roll_down[rsi_lookback:, 1:2]
Data = Data[rsi_lookback + 1:,]
RS = roll_up / roll_down
RSI = (100.0 – (100.0 / (1.0 + RS)))
RSI = np.array(RSI)
RSI = np.reshape(RSI, (-1, 1))
RSI = RSI[1:,]
Data = np.concatenate((Data, RSI), axis = 1)