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My goal is to build a temperature gradient map over a floor plan to display minute changes in temp. via uniformly distributed sensors.

As far as I understand most heatmap tools available work with point density to produce heatmaps whereas what I'm looking for is a gradient based on varying values of individual points (sensors) on the map. I.e. something like this...

which I nicked from here.

From what I've gathered interpolation will definitely be involved and it may just be Radial Basis Function Interpolation because it wouldn't require a grid as per this post.

I've used the Anaconda distribution thus far. The data from sensors will be extracted from timescaleDB and the positions of sensors will be lat/long.

I've done very minor experimentation with the code from the link above and got this result. Radial Basis Function Interpolation

So here are my questions. Multiple python libraries have interpolation as a built-in function but which one of the libraries would be the best for the task described above? What parts of documentation should I read up on from libraries which can help me with this specific problem? Any good resource recommendations for this topic? Would anything else be required for this apart from interpolation?

Thanks in advance!

P.S. This is a side project I'd like to work on as a student, not commercial in any way shape or form.

SomeGuy
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1 Answers1

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I like scipy.interpolate library. It has a lot of nice functions, the simplest that would work for you would probably be the scipy.interpolate.interp2d(), and if you want to go with an non linear distribution of sensors griddata() is very useful.

alexpiers
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