A function to create X and Y training matrices for sequence modeling

createXY.py

def create_X_Y(ts: np.array, lag=1, n_ahead=1, target_index=0) -> tuple:
    """
    A method to create X and Y matrix from a time series array for the training of 
    deep learning models 
    """
    # Extracting the number of features that are passed from the array 
    n_features = ts.shape[1]
    
    # Creating placeholder lists
    X, Y = [], []

    if len(ts) - lag <= 0:
        X.append(ts)
    else:
        for i in range(len(ts) - lag - n_ahead):
            Y.append(ts[(i + lag):(i + lag + n_ahead), target_index])
            X.append(ts[i:(i + lag)])

    X, Y = np.array(X), np.array(Y)

    # Reshaping the X array to an RNN input shape 
    X = np.reshape(X, (X.shape[0], lag, n_features))

    return X, Y

if len(ts) - lag <= 0: X.append(ts)
Could you explain what you do here? This will create a feature frame but no target variable?