Smooth noisy data in the Live Editor
The Smooth Data task lets you interactively smooth noisy data. The task automatically generates MATLAB® code for your live script.
Using this task, you can:
Customize the method for smoothing data in a workspace variable.
Adjust parameters to generate less or more smoothing.
Automatically visualize the smoothed data.
To add the Smooth Data task to a live script in the MATLAB Editor:
On the Live Editor tab, select Task > Smooth Data.
In a code block in the script, type a relevant keyword, such as
noisy. Select Smooth
Data from the suggested command completions.
Smoothing method— Method for smoothing data
Moving mean(default) |
Local linear regression|
Local quadratic regression|
Robust local linear regression|
Robust local quadratic regression|
Savitzky-Golay polynomial filter| ...
Specify the smoothing method as one of the following options, which operate over local windows of data.
Moving average. This method is useful for reducing periodic trends in data.
|Moving median. This method is useful for reducing periodic trends in data when outliers are present.|
|Gaussian-weighted moving average.|
|Linear regression. This method can be computationally expensive, but it results in fewer discontinuities.|
|Quadratic regression. This method is slightly more computationally expensive than local linear regression.|
|Robust linear regression. This method is a more computationally expensive version of local linear regression, but it is more robust to outliers.|
|Robust quadratic regression. This method is a more computationally expensive version of local quadratic regression, but it is more robust to outliers.|
|Savitzky-Golay polynomial filter, which smooths according to a polynomial of specified degree, and is fitted over each window. This method can be more effective than other methods when the data varies rapidly.|
Moving window— Window for smoothing methods
Specify the window type and size for the smoothing method instead of specifying a general smoothing factor.
|Specified window length centered about the current point.|
|Specified window containing the number of elements before the current point and the number of elements after the current point.|
Window sizes are relative to the X-axis variable units.