Clean Messy Data and Locate Extrema Using Live Editor Tasks
You can interactively preprocess data using sequences of Live Editor tasks, visualizing the data at each step. This example uses five tasks to clean noisy data with missing values and outliers in order to identify local minima and maxima. For more information on Live Editor tasks, see Add Interactive Tasks to a Live Script.
First, create and plot a vector of messy data, which contains four
NaN values and five outliers.
x = 1:100; data = cos(2*pi*0.05*x+2*pi*rand) + 0.5*randn(1,100); data(20:20:80) = NaN; data(10:20:90) = [-50 40 30 -45 35];
To plot the messy data, open the Create Plot task. Start by typing the keyword
plot in a code block, and then click
Create Plot when it appears in the menu. Select the plot type and input data to plot the data.
Fill Missing Data
NaN values in the data and visualize the results, open the Clean Missing Data task. Start by typing the keyword
missing in a code block, and then click
Clean Missing Data when it appears in the menu. Select the input data and the cleaning method to plot the filled data automatically.
You can now remove the outliers from the cleaned data in the previous task by using the Clean Outlier Data task. Type the keyword
outliers in a new code block and click
Clean Outlier Data to open the task. Select
cleanedData as the input data. You can customize the methods for cleaning and detecting outliers, and adjust the threshold to find more or fewer outliers.
Next, smooth the cleaned data from the previous task by using the Smooth Data task. Type the keyword
smooth and click the task when it appears. Select
cleanedData2, the output from the previous task, as the input data. Select a smoothing method, and adjust the smoothing factor for more or less smoothing.
Finally, start typing the keyword
extrema and click
Find Local Extrema. Use
smoothedData as the input data and change the extrema type to find both the local maxima and local minima of the cleaned, smoothed data. You can adjust the local extrema parameters to find more or fewer maxima and minima.
To view the code that a task used to generate the output and visualization, click the arrow at the bottom of the task window, above the plot.
The task displays the code block, which you can cut and paste to use or modify later in the existing script or a different program. For example:
Because the underlying code is now part of your live script, you can continue to use the variables created by the task for further processing. For example, you can use
maxIndices to find the corresponding local maxima values in the smoothed data, and then compute the average:
Live Editor Tasks
- Clean Missing Data | Clean Outlier Data | Find Change Points | Find Local Extrema | Smooth Data | Remove Trends