main.py 文件源码

def predict_result():
    ser = serial.Serial(  # ????????????
        port='COM6',
        baudrate=1200,
        parity=serial.PARITY_ODD,
        stopbits=serial.STOPBITS_TWO,
        bytesize=serial.SEVENBITS
    )
    serial_data = []
    plt.xlim(0, 100)
    plt.ylim(300, 700)
    plt.title('GSR')
    plt.ion()
    i = 0
    j = 0
    id = 0
    while True:
        line = ser.readline()
        line = int(line)
        serial_data.append(line)
        if i > 100:
            plt.xlim(i - 100, i)
        plt.plot(serial_data)
        i += 1
        j += 1
        if j >= 50:
            clf = joblib.load('model\\happy_model.m')
            select = joblib.load('model\\vector_select.m')
            vector = getattr.get_vector(serial_data)
            new_vector = select.transform(vector)
            print(new_vector)
            result = clf.predict(new_vector)
            if result[0] == '2':
                clf = joblib.load('model\\sad_model.m')
                result = clf.predict(new_vector)
            j = 0
            plt.plot([i, i], [300, 700], 'r--')
            if result[0] == '1':
                plt.annotate('happy', xy=(i, 600), xytext=(i - 10, 600), arrowprops=dict(facecolor='red', shrink=0.05))
                res = 1
                database.insert(id, res)
            elif result[0] == '2':
                plt.annotate('normal', xy=(i, 600), xytext=(i - 10, 600), arrowprops=dict(facecolor='blue', shrink=0.05))
                res = 0
                database.insert(id, res)
            else:
                plt.annotate('sad', xy=(i, 600), xytext=(i - 10, 600),arrowprops=dict(facecolor='black', shrink=0.05))
                res = 2
                database.insert(id, res)
            print(result)
            id += 1
        plt.pause(0.001)