实时绘图以使用绘图监视数据

Question

我正在尝试通过在测试室中丢弃的一组传感器实时获取数据。我们使用matplotlib成功地做到了这一点，但是最好使用绘图，因为这些图可以在其他环境中导出和可视化（考虑到我们的最终目标）。我看到了一些示例 and “ https://dash.plotly.com/live-updates” rel =“ nofollow noreferrer”>在这里，但它不符合我们所拥有的，因为传感器数据采集，数据列表正在不断更新，不通过等式（取决于时间步长集）。传感器由NIDAQMX软件包（国家仪器传感器）读取 - 但显然没有问题。这是我们用Matplotlib绘制的工作代码（传感器的名称存储在列表中，而不是在此处描述）：

import nidaqmx
from nidaqmx.constantsimport(TerminalConfiguration,VoltageUnits,ThermocoupleType,CJCSource,TemperatureUnits,ResistanceConfiguration,ExcitationSource,RTDType)
from datetime import datetime,date
import time
import numpy as np
import pandas as pd
import plotly.express as px
import matplotlib.pyplot as plt
import matplotlib.animation as animation

sensor_name = "sensor_1"
list_voltage_rse = [...]

date_time = []
data = []
tempo = []
t_min = 2
t_max = 40
time_step = 10
N = 100
x_len = N
k = 1
i = 0
y_range = [t_min, t_max]


#read data from DAQ (specified sensor)

def readdaq():

    with nidaqmx.Task() as task:
       first_inicio = datetime.now()

       if sensor_name in list_voltage_rse:
        task.ai_channels.add_ai_voltage_chan(sensor_name,terminal_config=TerminalConfiguration.RSE,units=VoltageUnits.VOLTS)

       first_fim = datetime.now()
       tempo_leitura = (first_fim - first_inicio).total_seconds()

       task.start()

       value = task.read()

       print(value)

       task.stop()

#Write Data Function

def writefiledata(t, x):
    # Open File
    file = open("tempdata.txt", "a")
    # Write Data
    time = str(t)
    value = str(round(x, 2))
    file.write(time + "\t" + value)
    file.write("\n")
    # Close File
    file.close()

#Create figure for plotting

fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
xs = list(range(0, N))
ys = [0] * x_len
ax.set_ylim(y_range)

#Create a blank line. We will update the line in animate

line, = ax.plot(xs, ys)

#Configure Plot

plt.title('Temperature')
plt.xlabel('t [s]')
plt.ylabel('Temp [degC]')
plt.grid()

#Logging Temperature Data from DAQ Device

def logging(i, ys):
    inicio = datetime.now()
    value = readdaq()
    print("T =", round(value,1), "[degC]")
    data.append(value)

final = datetime.now()
tempo_leitura = (final - inicio).total_seconds()
print(tempo_leitura)

time.sleep(time_step - tempo_leitura)
global k
k = k + 1
writefiledata(k*time_step, value)
# Add y to list
ys.append(value)
# Limit y list to set number of items
ys = ys[-x_len:]
# Update line with new Y values
line.set_ydata(ys)
return line,

ani = animation.FuncAnimation(fig,logging,fargs=(ys,),interval=100,blit=True)
plt.show()

我希望此代码能够帮助您了解我想要的内容。