human
Solve the following python programming problem given the following code:
# For Feature Extraction we use a technique called window overlapping (Pierluigi Casale, Oriol Pujol, and Petia Radeva. Human activity recognition from accelerometer
# data using a wearable device. Pattern Recognition and Image Analysis, pages 289–296, 2011). It has an overlap of 50% between the different
# time series. As a time window 1 second is use --> corresponds to 52 samplings (52 Hz frequency)
# Then we start with the sequencing
# Slicing needs to be done as follows:
# - it is not possible that 2 activities are grouped in one sequence (would falsify the outcome of the mean value)
# - therefore only labels with the same value are grouped into one sequence
# @params: array_data is list of array that contains the grouped data
# @output: data_list which contains numpy arrays with the respective windows

def grouping(array_data):
    start = int(0)
    end = int(52)
    data_list = []
    length = np.size(array_data, 0)
    while start < length-52:
        if(array_data[start][4] != array_data[end-1][4]):        # this control sequence is necessary to ensure that not two of the same
            while(array_data[start][4] != array_data[end-1][4]): # labels are in one window
                end = end -1
            newArray = array_data[slice(start, end)]
            start = end
            end = end + 52
        else:
            newArray = array_data[slice(start, end)]
            start = start + 26
            end = end + 26
        data_list.append(newArray)
        if(end-52 > length - 1):
            end = length-1

    # Comment in to show the size and length of the data_list array
    # print(np.size(data_list))
    # print(len(data_list))
    return data_list

# This is an additional function which could be called to print a data list to a text file (e.g to examine it)
# Comment in for printing the data to a text file
# def sysout_to_text(dataList):
#     file = open("tempFile", "w")
#     for item in dataList:
#         file.write("%s\n" % item)
#     file.close()
Given the above code, generate some markdown instructions for it.
assistant
#Here is Python code to print a data list to a text file (e.

Feature Engineering
The goal is to extract features from the preprocessed numpy array
But before we have to do a preprocessing step
1. Step is to sequence the data in windows with 52 instances
Sidenote: it is of high importance to not mix two labels into the same window