> For the complete documentation index, see [llms.txt](https://time-series-features.gitbook.io/hctsa-manual/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://time-series-features.gitbook.io/hctsa-manual/installing-and-using-hctsa/analyzing_visualizing/plotting_the_time_series.md). # Plotting the time series The *hctsa* package provides a simple means of plotting time series: the `TS_PlotTimeSeries` function. Its inputs are `TS_PlotTimeSeries(whatData,numPerGroup,whatTimeSeries,maxLength,plotOptions)`. The time series to plot, `whatTimeSeries`, can be `'all'`, the name of a group (in `TimeSeries.Group`), a keyword, a vector of indices, or `'grouped'` (or empty) to plot examples of each labeled group. ## Basic plotting For example, to plot a set of time series that have not been assigned groups, we can run the following: ``` whatData = 'norm'; % Get data from HCTSA_N.mat plotWhatTimeSeries = 'all'; % plot examples from all time series plotHowMany = 10; % how many to plot maxLength = 400; % maximum number of samples to plot for each time series plotOptions = struct('plotFreeForm',false); % plot each time series in its own subplot TS_PlotTimeSeries(whatData,plotHowMany,plotWhatTimeSeries,maxLength,plotOptions); ``` For an assorted set of time series (the 1000 time series of the [Empirical1000](https://doi.org/10.6084/m9.figshare.5436136) dataset, normalized into `HCTSA_N.mat`), this produces the following: ![](https://254595279-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-LEJuzw5fsQv4fwW3E7P%2Fuploads%2Fgit-blob-80d873eb3049cf432588b55f0ae1d3db8fcc9337%2FtimeSeriesPlot.png?alt=media) Showing 400 samples of 10 selected time series, equally spaced through the time series in `HCTSA_N.mat` (IDs 1, 112, 223, ..., 1000). Each title gives the time series's ID (in braces), name, keywords (in square brackets), and length. In this subplot layout, a time series longer than `maxLength` is shown as a randomly positioned segment of `maxLength` samples (its range is given in the title). ## Freeform plotting Many more custom plotting options are available by passing an options structure to `TS_PlotTimeSeries`, including the `'plotFreeForm'` option. Free-form plotting (the default, `plotFreeForm = true`) shows all time series in a single set of axes, which allows very many time series to be shown in one plot: ``` % Plot as a freeform plot without labeling time series: plotOptions = struct('plotFreeForm',true,'displayTitles',false); TS_PlotTimeSeries('norm',40,'all',300,plotOptions); ``` ![](https://254595279-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-LEJuzw5fsQv4fwW3E7P%2Fuploads%2Fgit-blob-a96f6b006423bb818652c8e7e9586ea07476834f%2Ffreeform_timeSeries_Plot.png?alt=media) producing an overview picture of the first 300 samples of 40 time series (spaced through the rows of the data matrix). Other fields of `plotOptions` (with their defaults) are: `displayTitles` (`true`), `howToFilter` (how to choose the time series to plot: `'evenly'`, `'firstcome'`, or `'rand'`; default `'evenly'`), `colorMap`, `LineWidth` (1), `newFigure` (`true`), `sortByLength` (`false`), and `carpetPlot` (`false`; plots the time series as a grayscale image). ## Dealing with groups of time series When the time series have been assigned groups (using `TS_LabelGroups`, [here](/hctsa-manual/installing-and-using-hctsa/analyzing_visualizing/grouping.md)), this information is automatically incorporated into `TS_PlotTimeSeries`, which then plots a given number of each time series group, and colors them accordingly: ``` numPerGroup = 5; % plot this many examples of each group of time series plotHow = 'grouped'; % plot examples of each assigned group of time series plotOptions = struct('plotFreeForm',false); % plot each time series in its own subplot TS_PlotTimeSeries('norm',numPerGroup,plotHow,500,plotOptions); ``` ![](https://254595279-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-LEJuzw5fsQv4fwW3E7P%2Fuploads%2Fgit-blob-9954f52318706aebc26d757d5f69494cce80fae5%2FGroupedTimeSeriesPlot.png?alt=media) Here we used the noisy/periodic dataset of 40 time series of length 500 (20 sums of sinusoids with added noise, keyword `noisy`, and 20 noise-free ones, keyword `periodic`), labeled using `TS_LabelGroups('norm',{'noisy','periodic'})`. The two labeled groups of time series are recognized by the function: red (`noisy`) and blue (`periodic`), and 5 time series from each group are plotted. These time series are no longer than `maxLength` (500 samples), so each is plotted in full. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. 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