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I am currently trying to interpret my FTIR data. But due to a lot of background noise, my spectrum is quite spiky and fluctuating at some points. I want to try to smoothen my function to make the peaks in the spectrum more apparent.

My code looks like this:

ListLinePlot[{q2, q1}, ScalingFunctions -> {"Reverse", Identity},
PlotRange -> {{3100, 2700}, Automatic}, 
PlotLegends -> {"UV1", "PURE1"}, ImageSize -> Full, 
GridLines -> {{2870, 2960, 2925, 2850}, {}}, Black, 
Bold, FontSize -> 16], Style["Absorbance", Black, Bold, FontSize -> 16]}, 
TicksStyle -> Directive[FontSize -> 14]]

Giving the following plot:

enter image description here

So I would like to make it more smooth. Any ideas on how to do this? I've tried to find something, but I only came across Interpolating, but that did not really work because my data set is not just a list of numbers.

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    $\begingroup$ Interpolation accepts input data in various forms (input does not have to be just a list of numbers). If your q1 and q2 are lists of pairs you can use this form of Interpolation. If you post a small portion of your actual data (for example, q1[[;;10]] and q2[[;;10]]), it will make it easier for people to help you. $\endgroup$
    – kglr
    Commented Jul 4, 2017 at 17:29
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    $\begingroup$ Perhaps convolving your data with a suitable kernel (Gaussian perhaps) could help. $\endgroup$
    – Tucker
    Commented Jul 4, 2017 at 17:32
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    $\begingroup$ Note that smoothing can make some peaks less apparent. Do you have a definition for what constitutes a peak over and above the noise? Maybe something as simple as using the functions MovingAverage or MovingMedian or FindPeaks will suit your needs. $\endgroup$
    – JimB
    Commented Jul 4, 2017 at 17:45
  • $\begingroup$ Related: mathematica.stackexchange.com/questions/115444/… $\endgroup$
    – Michael E2
    Commented Jul 4, 2017 at 23:58

1 Answer 1

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I think LowpassFilter should do what you want. (I can't comment yet)

Edit: An example of how you could use it:

data = Table[{x, Sin[x] + RandomReal[{-0.1, 0.1}]}, {x, 0, 2 \[Pi], 0.01}];
data2 = Transpose[{data[[All, 1]], LowpassFilter[data[[All, 2]], 0.2]}];
ListPlot[{data, data2}, Joined -> True]
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  • $\begingroup$ Perhaps you can add some Mathematica code to show how this works on a some "test data"? $\endgroup$
    – Dunlop
    Commented Oct 17, 2017 at 18:25
  • $\begingroup$ sure, but note that there are also good examples in the documentation $\endgroup$
    – M. Stern
    Commented Oct 17, 2017 at 19:35

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