123 lines
4.0 KiB
Python
123 lines
4.0 KiB
Python
import os
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import base64
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import json
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import pylab as pl
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from matplotlib.pylab import mpl
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import paho.mqtt.client as mqtt
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import random
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import time
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import numpy as np
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mpl.rcParams['font.sans-serif'] = ['Microsoft YaHei'] # 显示中文
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mpl.rcParams['axes.unicode_minus'] = False # 显示负号
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np.set_printoptions(threshold=np.inf)
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# 画出时域信号和频域信号图谱
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def draw_figur(data, fft_size, freqs, abs_xfft, sampling_rate, channel):
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fig = pl.figure()
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# 使用鼠标缩放图片
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def call_back(event):
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axtemp = event.inaxes
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x_min, x_max = axtemp.get_xlim()
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fanwei = (x_max - x_min) / 10
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if event.button == 'up':
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axtemp.set(xlim=(x_min + fanwei, x_max - fanwei))
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print('up')
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elif event.button == 'down':
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axtemp.set(xlim=(x_min - fanwei, x_max + fanwei))
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print('down')
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fig.canvas.draw_idle() # 绘图动作实时反映在图像上
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fig.canvas.mpl_connect('scroll_event', call_back)
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fig.canvas.mpl_connect('button_press_event', call_back)
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pl.subplot(3, 1, 1) # 截取幕布的一部分
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np.linspace(-5, 5, 10)
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pl.plot(data[:fft_size], color='r')
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pl.xlabel('点数')
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pl.ylabel('加速度值')
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pl.title('时域信号')
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pl.subplot(3, 1, 3) # 截取幕布的一部分
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np.linspace(-5, 5, 10)
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pl.title(f"频域信号(通道号：{channel})")
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pl.ylabel("振幅")
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pl.xlabel("频率(KHz)")
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pl.plot(freqs, abs_xfft)
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time_name = time.time()
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pl.show()
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# 连接成功回调
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class Mqtt_Subscriber:
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def __init__(self, central_ip='192.168.123.200', port=1883,
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topic_prefix='10B035041002230110003775/1/', callback_func=None,
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node_name='bci_', anonymous=True, timeout=60):
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self.topic_prefix = topic_prefix
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self.callback = callback_func
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self.broker_ip = central_ip
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self.broker_port = port
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self.timeout = timeout
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self.connected = False
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self.node_name = node_name
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if anonymous:
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self.node_name = self.node_name + str(random.randint(100000, 999999))
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self.Start()
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def Start(self):
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self.client = mqtt.Client(self.node_name)
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self.client.on_connect = self.on_connect
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self.client.on_message = self.default_on_message
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self.client.connect(self.broker_ip, self.broker_port, self.timeout)
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for i in range(12):
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topic_name = f'{self.topic_prefix}{i}/multivalue'
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self.client.subscribe(topic_name)
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self.client.loop_start()
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def default_on_message(self, client, userdata, msg):
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channel = int(msg.topic.split('/')[-2])
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if channel < 12:
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data = json.loads(msg.payload.decode('utf-8'))
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data_points = list(map(float, data['data']['sample_data']['data'].split(" ")))
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spectrum_data = list(map(float, data['data']['sample_data']['spectrum'].split(" ")))
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# Create directories if they don't exist
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os.makedirs(self.topic_prefix, exist_ok=True)
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# Save the data to a file
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filename = os.path.join(self.topic_prefix, f'{channel}_data.json')
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with open(filename, 'w', encoding='utf-8') as file:
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json.dump(data, file, ensure_ascii=False)
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if channel ==0:
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# Visualize the data
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draw_figur(data_points, 60000*10,
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np.linspace(0, int(60000), int(60000*10)) / 1000,
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spectrum_data, 1, channel)
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def on_connect(self, client, userdata, flags, rc):
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if rc == 0:
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self.connected = True
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else:
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raise Exception("连接到mqtt服务器失败。")
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def numpy_decoder(dct):
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if '__ndarray__' in dct:
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data = base64.b64decode(dct['__ndarray__'])
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return np.frombuffer(data, dtype=dct['dtype']).reshape(dct['shape'])
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return dct
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if __name__ == '__main__':
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p = Mqtt_Subscriber(topic_prefix='10B035041002230110003775/1/')
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while not p.connected:
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pass
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while True:
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time.sleep(1)
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