LabPlot 2.8.1 released

We’re happy to announce the availability of the first minor patch release of the big release we made two months ago. This release contains minor improvements and bug fixes only.

In the plot we now allow to change the background color for axis labels. This is useful if you place the axis labels above the axis line and don’t want to see an underlying line in the bounding box of the label. The default setting is that the background remain transparent.

For the cursor, the tool used to measure positions and distances in the plots, we now allow you to copy the values in the result window to the clipboard.

When pasting new values into LabPlot’s spreadsheet, the auto-detection of the datatime format has been improved. We now better recognize the different formats produced in external programs and being pasted into LabPlot.

Many smaller improvements were included in the dialog for the creation of the live-data sources related to the handling of errors coming from remote servers like MQTT brokers, etc. Besides the more stable behavior, the user now also gets clearer notifications about what went wrong. Furthermore, when reading live data it is possible to generate the timestamp column in LabPlot for the data being read also for TCP and UDP network sources. This was only possible for MQTT sources in the past.

The bug fixes address some of the annoying issues that were known for quite some time already, but also new issues reported by the users after the release 2.8. Below is the list of all relevant bug fixes:

  • Fixed compiling with Cantor 20.08.X and X>0
  • Fixed drawing lines between points of datetime data
  • Fixed drawing axis tick label in color when in HTML mode
  • Fixed size of dock widgets when changing between them
  • BUG 389920 – removed sub-window shadow remnants when closing the project
  • BUG 428029 – changed font of text label for newer Qt versions
  • BUG 428813 – solved full screen not restored (also fixed full screen on macOS)
  • BUG 428698 – solved crash when doing drag&drop between different main windows
  • Fixed missing settings dialog on macOS
  • Parser improvements (found in “Generate Function Values”):
    • Fixed Crash using variable name of pre-defined functions as function (“sin()”)
    • Allow variable names containing function names (“sina”)
    • Correctly remove variables when changing name
    • Use application number locale
    • Insert predefined functions with correct number of arguments

We encourage everybody to update to 2.8.1 to enjoy these improvements.

5 thoughts to “LabPlot 2.8.1 released”

  1. I just started messing around with the software and put in some data from a chromatogram and plotted it. I’m wondering if there’s a way to get it calculate the areas of the peaks in the chromatogram?

    1. You can use the integration to calculate the area of the peaks. For this, do a right click on your curve and select Analysis/Integration and specify the start and the end points of your peak. In the results field the value of the integration (i.e. the area below the peak) will be shown.

      P.S.: Providing help and support in the comment area of the homepage is not so flexible. We have a dedicated room in Matrix that is much more comfortable in such cases (https://labplot.kde.org/support/). Please consider using it if you need more and more faster replies.

  2. I read in the “features” page of this blog that:

    “CAS variables holding array-like data (Maxima lists, Python lists and tuples, etc.) can be used as the source for LabPlot curves”

    I’m wondering if the reverse is possible, i.e.: using the powerful commands of, say, octave, to do some signal processing on the data you have in a labplot’s spreadsheet.

    In case you are curious, I need to apply a Hilbert transform to some circuit response simulated using Ngspice circuit simulator and imported into labplot using the included Ngspice import filter (thanks! :-). Labplot doesn’t have a Hilbert transform, but octave does. The “obvious” solution would be to import the simulation data into octave, do the processing there and then import and plot the result into labplot, but this is cumbersome as octave doesn’t have support for importing the Ngspice output data format. I have to use a python script to do the conversions, which is also tedious.

    1. To enable this, we’d need to expose LabPlot’s data containers to the different CASs like octave. etc. For this we need to provide an API around our structures. Such API would allow not only to access our data containers but also to control/scrip the application. We’re thinking about this “scripting” already but it will take some time until we’ve implemented it. The implementation of the Hilbert-transformation is much easier and we need it anyway in the application independent of octave and co. 🙂 This feature landed in master recently. Please give it a try.

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