The next release 2.9 will again come with many very useful and interesting new features. Today we want to talk about a new feature in the area of the data analysis that has been included into LabPlot’s master branch recently.

Though it is possible in LabPlot to access many different computer algebra systems and programming languages with a plethora of packages relevant in scientific communities, it is sometimes useful and desired to perform the analysis of data in a more visual and interactive way. For this kind of analysis LabPlot already supports algorithms and computations like the Fourier Transformation, smoothing, interpolations, Fourier filter, etc (see this blog post for a couple of examples). To this list we have now added the Hilbert Transform.

The Hilbert Transform has many applications, especially in signal processing. Below is an example produced in LabPlot that shows the time response of a super regenerative receiver to an ultra-wideband (very short) pulse consisting of few oscillating cycles enclosed within a Gaussian-like envelope (for high-Q receivers) or within a bilateral exponential envelope (for low-Q receivers).


Hilbert Transformation Example

In this example, the use of the Hilbert Transform helps you visualize and confirm the envelope shape and to find some signal features, like the position and the value of the maximum envelope point, which would be very difficult to determine otherwise.

The current development versions (i.e. the code being finalized and prepared for the next release) is available from our download section and can already be used to try out this new feature.