Preview of the Data-Logging Interface

Real-Time Data Acquisition with Tk GUI

Looks like I finally got the interface working the way I want. Here's the source:

#!/usr/bin/python

import matplotlib
matplotlib.use('TkAgg')

from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2TkAgg
from matplotlib.backend_bases import key_press_handler

from matplotlib.figure import Figure
from matplotlib.pyplot import ion

import serial
from time import sleep, time
import Tkinter as _Tk

root = _Tk.Tk()
root.wm_title('Data-Logging')

spinBox = _Tk.Spinbox(root, from_=0, to=240)

sbLabel = _Tk.Label(root, text='How long would you like to test (in seconds): ')

raw_data = []
_time = []

f = Figure(figsize=(5,4), dpi=100)
a = f.add_subplot(111)
a.plot(_time, raw_data)
a.set_xlabel('Time')
a.set_ylabel('Input')
a.set_title('Light Reading')
ion()

canvas = FigureCanvasTkAgg(f, master=root)


toolbar = NavigationToolbar2TkAgg(canvas, root)
toolbar.update()

canvas._tkcanvas.pack(side='bottom', fill='both', expand=1)
canvas.get_tk_widget().pack(side='bottom', fill='both', expand=1)

def beginLogging():
    runTime = int(spinBox.get())
    
    arduino = serial.Serial('/dev/ttyACM0', 9600)
    sleep(2.0)
    arduino.flush()
    arduino.flushInput()
    arduino.flushOutput()

    arduino.write('s')
    startTime = time()

    while(arduino.isOpen()):
        raw_data.append(int(arduino.readline()))
        _time.append(time() - startTime)
        arduino.flush()
        a.plot(_time, raw_data)
        a.set_ylim(0, max(raw_data)+75)
        canvas.draw()
        if((time() - startTime) >= runTime):
            arduino.close()
   
#killButton = _Tk.Button(root, text='Quit', command = root.quit)
#killButton.pack(side = 'right', fill = 'both', expand = 0)

startButton = _Tk.Button(root, text='Start', command = beginLogging)
startButton.pack(side = 'right', fill = 'both', expand = 0)
 
spinBox.pack(side='right', fill='both', expand = 0)   
sbLabel.pack(side='right', fill='both', expand = 0)


def on_key_event(event):
    print('you pressed %s' %event.key)
    key_press_handler(event, canvas, toolbar)
    
canvas.mpl_connect('key_press_event', on_key_event)

root.mainloop()

Python Real-Time Plotting

Finally got a reasonable script running some real-time plots in python. Just included the serial part for future expansion:

#!/usr/bin/python

import serial
from Tkinter import *
from pylab import *
import time as _time

endTime = float(raw_input('How long would you like to simulate: '))

arduino = serial.Serial('/dev/ttyACM0', 9600)
arduino.write('a')
 
startTime = _time.time()    # constant for start time 

def timeDelta():  # method to get current time difference 
    return _time.time() - startTime 

x=[]
plot(x,sin(x))
xlabel('Time')
ylabel('Reading')
title('Test')
ion()

while(arduino.isOpen()):
    x.append(timeDelta())
    plot(x,sin(x))
    ylim([-1,1])
    xlim([0, timeDelta()])
    draw()
    if timeDelta() >= endTime:
        arduino.close()
show(block =True)

Python GUI

Made a GUI with python to control the on-board LED a few days ago. Seems to be really responsive. Also made the program in Visual C++ on Windows.

#!/usr/bin/python
from Tkinter import *
import serial

arduino = serial.Serial('/dev/ttyACM0', 9600)

def ledOn():
 arduino.write('a')
 return 

def ledOff():
 arduino.write('b')
 return 

app = Tk()
app.title("Blink")
app.geometry('125x75+200+200')

buttonON = Button(app, text = 'LED ON', command = ledOn)
buttonON.pack(padx = 10, pady = 5)

buttonOFF = Button(app, text = 'LED OFF', command = ledOff)
buttonOFF.pack(padx = 10, pady = 5)

app.mainloop()

Serial Communications

So I spent a good few hours trying to read data from my Arduino and write the stream to a .txt file. I was trying to implement this in C++ and eventually Qt. Well, after an hour or so of coding I finally was reading some strings from the board. the problem however was that it was very inconsistent. I have since switched to Python for this application an will soon be looking into developing a control interface with Qt and Python, as well as a data logging/plotting interface using matplotlib.


** more updates to come.