Question

我正在尝试在python中编写一些用于数据分段的代码，这是我的代码它由两个功能组成。我使用了python 3.5

def windowz(data, size):
    start = 0
    while start < len(data):
        yield start, start + size
        start += (size / 2)

def segment_dap(x_train,y_train,window_size):
    segments = np.zeros(((len(x_train)//(window_size//2))-1,window_size,9))
    labels = np.zeros(((len(y_train)//(window_size//2))-1))
    i_segment = 0
    i_label = 0
    for (start,end) in windowz(x_train,window_size):
        if(len(x_train[start:end]) == window_size):
            m = stats.mode(y_train[start:end])
            segments[i_segment] = x_train[start:end]
            labels[i_label] = m[0]
            i_label+=1
            i_segment+=1
    return segments, labels

input_width = 23
if dataset =="dap":
    print ("dap seg")
    input_width = 25
    print ("segmenting signal...")
    train_x, train_y = segment_dap(x_train,y_train,input_width)
    test_x, test_y = segment_dap(x_test,y_test,input_width)
    print ("signal segmented.")

但是这段代码给了我以下警告

    Warning (from warnings module):
  File "C:\Users\hp\Downloads\Deep-Learning-for-Human-Activity-Recognition-master\ModelCreation\RNN\FFLSTM\fflstm.py", line 37
    if(len(x_train[start:end]) == window_size):
VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future

Warning (from warnings module):
  File "C:\Users\hp\Downloads\Deep-Learning-for-Human-Activity-Recognition-master\ModelCreation\RNN\FFLSTM\fflstm.py", line 38
    m = stats.mode(y_train[start:end])
VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future

Warning (from warnings module):
  File "C:\Users\hp\Downloads\Deep-Learning-for-Human-Activity-Recognition-master\ModelCreation\RNN\FFLSTM\fflstm.py", line 39
    segments[i_segment] = x_train[start:end]
VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future

Answer 1

(size / 2) in：

def windowz(data, size):
    start = 0
    while start < len(data):
        yield start, start + size
        start += (size / 2)

会给你一个浮动。你可以强制它是一个整数：

(size // 2)

Python - 使用非整数而不是整数

1 个答案: