Real-Time Plots with kst and a Microcontroller
Lots of programs take data from a file and create an X-Y graph under Linux. Desktop applications like xplot, gnuplot or even PHPlot do a great job. But, what if you want to see how a physical process changes and use a real-time plot on your Linux machine?
I couldn't find this capability for a long time. Then, I discovered kst. kst is a fast, large-data set, real-time viewing and plotting program, and it's part of the KDE suite.
You need to have some way to get real-time sensor data into the kst program. I've used Arduino microcontrollers to automate different things, so it seemed only natural to combine one of these boards with kst to build an easy-to-use and very capable real-time data-gathering system. Because it's open-source-based, expansion and customization are possible.
In this article, I show how to link all the parts together to produce a real-time plot of live data and explain how to install and test kst. I also cover Arduino programming environment installation, so you can get the board programmed and stream data right into a Linux notebook.
kst can read text-based data from a file and has basic data analysis capabilities. As part of the KDE suite of applications, it is available on virtually all modern Linux distributions.
The easiest way to put kst on your machine is with your distribution's package manager. I used Synaptic under Xubuntu for the installation on my ASUS 64-bit Core Duo X83-VM notebook.
Once installed, kst appears under the Applications and Accessories pull-down tabs on the desktop taskbar.
Below is a small segment of some temperature and light-level data that I captured. The data snapshot will be used to test kst. Later, this same format will be used to stream real-time data from the Arduino into our Linux machine. Copy the data into a text file named testdata.txt:
74.64|444 74.64|448 74.64|452 74.64|450 74.64|447 74.64|439 74.64|435
Then start kst. The main kst window will show the task bar across the top and the kst QuickStart window in the middle.
Click on the Data Wizard button at the bottom of the Kst QuickStart pop-up pane. Figure 1 shows the kst toolbar, data source and configure data source windows. The pop-up Data Source pane will appear. Enter the data filename, testdata.txt. Press the Configure button. The Configure Data Source pane appears. Enter the custom delimiter character to separate the values in the data set. I used the vertical bar as a delimiter between the temperature and light-level values.
Once the delimiter character is set, click the Apply then the OK buttons to save the settings and close the window. Click Next on the Data Source pane to bring up the Select Data pop-up window.
In the Data Source pane, hold down the Ctrl key and select numbers 1 and 2 in the left-hand pane. These correspond to the temperature (left) and light-level (right) values in the data file. Once selected, click the right-pointing arrow to copy the data streams to the right-hand pane. Using two data streams will give two separate graphs, one for temperature and one for light levels, referenced by a common line number. Temperature and light levels will appear on the y-axis, and the line numbers will appear across the x-axis on each respective plot.
Plot customization is done with several pop-up windows. Click anywhere on the top (temperature) plot label to bring up the Edit Plot pop-up window. Select the Appearance tab to edit the labels. kst assigns its own default labels. In my case, I changed the x and y labels to reflect the data that the plot was showing, namely the temperature, light levels and time interval. Modify the label fonts, font sizes, justification and other assorted options to your tastes. Other tabs under this window control how data is plotted on the x and y axes and the range of numbers displayed. Whenever you make a change on one of these tabs, be sure to click the Apply button then the OK buttons to save the changes.
This sets up a template for future runs with that data file. It doesn't matter if the file is static or grows over time. kst will start plotting what's in the file the next time the template is selected. Assign an appropriate name to the template file.
Now that you've installed and tested kst with a static data file, it's time to program the Arduino to sense the environment (temperature and light level), then stream the data out over the USB line to the notebook.
Practical Task Scheduling Deployment
July 20, 2016 12:00 pm CDT
One of the best things about the UNIX environment (aside from being stable and efficient) is the vast array of software tools available to help you do your job. Traditionally, a UNIX tool does only one thing, but does that one thing very well. For example, grep is very easy to use and can search vast amounts of data quickly. The find tool can find a particular file or files based on all kinds of criteria. It's pretty easy to string these tools together to build even more powerful tools, such as a tool that finds all of the .log files in the /home directory and searches each one for a particular entry. This erector-set mentality allows UNIX system administrators to seem to always have the right tool for the job.
Cron traditionally has been considered another such a tool for job scheduling, but is it enough? This webinar considers that very question. The first part builds on a previous Geek Guide, Beyond Cron, and briefly describes how to know when it might be time to consider upgrading your job scheduling infrastructure. The second part presents an actual planning and implementation framework.
Join Linux Journal's Mike Diehl and Pat Cameron of Help Systems.
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With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
This ebook takes a look at some of the practical applications of the Linux on Power platform and ways you might bring all the performance power of this open architecture to bear for your organization. There are no smoke and mirrors here—just hard, cold, empirical evidence provided by independent sources. I also consider some innovative ways Linux on Power will be used in the future.Get the Guide