LSTM-related Python code __python

1. I first on the source code

The following code is written by a person lstm input data processing:

def load_data (filename, Seq_len, Normalise_window):
    f = open (filename, ' RB '). Read ()
    data = F.split (' \ n ')

    Sequence_length = seq_len + 1 result
    = [] for
    index in range (LEN (data)-Sequence_length):
        result.append (data [Index:index + sequence_length])
    
    If Normalise_window: Result
        = normalise_windows [result] result

    = Np.array (result)

    row = round (0.9 * Result.shape[0])
    train = Result[:row,:
    np.random.shuffle (train)
    X_train = train[:,: -1]
    Y_ Train = train[:,-1]
    x_test = Result[row:,: -1]
    y_test = Result[row:,-1]

    X_train = Np.reshape (X_train, (x_ Train.shape[0], x_train.shape[1], 1)
    x_test = Np.reshape (X_test, (x_test.shape[0), x_test.shape[1], 1  

    ) return [X_train, Y_train, X_test, Y_test]

No further, take a step in the data

For example, the source data is

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

Then I agreed that the step size is 3, then the data obtained is [1,2,3], [2,3,4], ..., [13,14,15]

2. Code interpretation

X_train = train[:,:-1]

This code indicates that every row in the train is removed, but for the column, the last column is not taken

GitHub Source: Lstm_learn