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Data Smoothing

All experimental data includes noise to varying degree. Noise can obscure important features like peaks, valleys, or peak widths, or make calculation of other signal features such as slopes, areas, peak widths and so forth difficult. Origin allows you to quickly smooth noisy signals to see significant features of your data. Each method offers different performance to best show significant aspects of your results. Savitzky-Golay seeks to preserve shapes of peaks; Adjacent Averaging does wide smoothing while FFT Smoothing allows you to eliminate noise above a specified frequency.

The data below shows a prominent peak with significant high frequency noise. With only three quick clicks of your mouse, application of an FFT filter eliminates high frequency noise.

 An Origin graph displaying line plots of the signal data and FFT Smoothing result.

Origin and Data Smoothing...

Origin provides the following data smoothing options:

  1. Savitzky-Golay

  2. Adjacent Averaging

  3. FFT Filter

All three smoothing methods are available from the Analysis:Smoothing menu, or from the Smoothing tool (Tools:Smooth). The smoothed data is placed in a newly created (hidden) worksheet named Smoothedn. The worksheet window label reports the type of smoothing that was performed. Additionally, the smoothed data is plotted in the active layer of the original graph.

The Smoothing tool allows you to replace the original data instead of creating a new worksheet. Learn more...

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