Plotting and Visualization

Overview of Plotting in MATLAB

Plotting in MATLAB is one of its most powerful and frequently used features. As soon as you have numeric data, you can create visual representations with just a few commands. This chapter introduces the general idea of plotting in MATLAB and what you can expect to do, without going deeply into any specific plot type or customization option. Those topics are covered in the child chapters.

MATLAB plots are built around figure windows that display graphical objects, such as lines, points, and axes. When you call a plotting function with some data, MATLAB automatically creates a figure (if one does not already exist), draws the plot, and sets up axes with scales and tick marks. The result is an interactive window where you can zoom, pan, and inspect data visually.

The Basic Plotting Workflow

The typical workflow for creating plots in MATLAB follows a simple pattern. First, you prepare or compute your data in variables. Then, you call a plotting function with those variables as inputs. Finally, you optionally adjust the appearance of the plot, save it, or use it to support further analysis.

For example, if you compute a vector x and a corresponding vector y, you can call a plotting function such as plot(x, y) to draw a 2D line plot. MATLAB determines the horizontal axis from x, the vertical axis from y, and generates a figure with default labels and styles. As you learn more, you will see how this basic idea extends to many other types of plots.

The same general approach applies whether you are visualizing simple sequences, measurements from files, or the results of more complex computations. MATLAB encourages you to think of plots as another way of looking at variables in your workspace, closely connected to the commands you run.

Figures, Axes, and Graphical Objects

Every plot you create lives inside a figure window. Inside each figure, there are one or more axes regions that define the coordinate system for your data. When you call a plotting command, MATLAB automatically creates these graphical containers, but you can also control them more precisely if needed.

The figure is the outer window that you see on your screen. The axes are the rectangular area within the figure where the data appear, including the tick marks and the box around the plot. Lines, markers, text, and other graphical elements are all objects that belong to these axes. This structure becomes important when you want to customize your visualizations, arrange multiple plots, or interactively edit graphics.

For beginners, you can think of a figure as the page and the axes as a particular graph on that page. As you advance, you will see how to work with several axes in a single figure, manage multiple figures at once, and control individual graphical properties.

Interactive Exploration Tools

MATLAB figure windows come with interactive tools that let you explore plots without writing more code. After you create a plot, you can use toolbar buttons for panning, zooming, rotating 3D views, and data cursor inspection, depending on the type of plot.

For instance, zooming allows you to focus on a region of interest in your data by clicking and dragging on the plot. Panning lets you move the visible area without changing the scale. Data cursor tools can show the exact numeric values at specific points when you click on them. These features are especially helpful when you are getting to know a dataset or checking the details of a computation.

The same interactive environment supports editing certain graphical properties, so you can adjust styles or annotations directly within the figure window. More detailed interactive editing tools are described later in the course.

Variety of Plot Types

MATLAB supports many different plot types that address a wide range of visualization needs. The most basic example is a 2D line plot, which connects data points in order and shows how one variable depends on another. Beyond that, you can create bar charts for categorical comparisons, scatter plots for point clouds, stem plots for discrete sequences, histograms for distributions, and much more.

For data with three coordinates, 3D plots and surface plots help you visualize relationships that depend on two independent variables. Specialized functions exist for images, signals, contours, and other common scientific and engineering data representations.

Although many plots are created with simple commands like plot, bar, or scatter, each of these functions has its own set of options for specifying inputs and appearance. The later chapters in this section describe particular plot families and how to work with them.

Connecting Plots with Scripts and Live Scripts

When you run commands directly in the Command Window, you can quickly create exploratory plots. For more organized work, it is common to place plotting commands inside scripts or live scripts. This lets you recreate figures reliably, keep a record of how they were generated, and share the process with others.

A typical script might load or compute some data, produce one or more figures, and save them to files. Live scripts extend this idea with a richer interface that combines code, text, equations, and plots in a single interactive document. Using scripts to manage plots is an important step toward reproducible analysis and clear communication of results.

Saving and Exporting Visualizations

Once you have a figure that communicates your results, you often need to save it. MATLAB allows you to save figures in several formats. You can store the entire figure in a MATLAB specific file, which preserves all graphical objects for later editing. You can also export figures as images, such as PNG or JPEG, or as documents suitable for reports and publications, such as PDF.

The choice of format depends on what you plan to do with the figure. For quick sharing or inclusion in slides, image formats are convenient. For printed reports or documents that require scaling, vector formats can provide higher quality. MATLAB includes commands and interactive options for saving figures, all of which you will encounter later in this section.

Plotting as Part of Data Analysis

Plotting is not just about creating attractive pictures. In MATLAB, plots are an integral part of data analysis. Visualizations help you detect patterns, anomalies, trends, and relationships that may not be obvious from numbers alone. You will often alternate between numeric operations and plotting commands as you explore a problem.

For example, you might compute summary statistics, then visualize the data distribution, then refine your analysis based on what the plot reveals. This interplay supports better understanding and decision making. As you gain experience, you will learn to choose appropriate plot types for different questions and to read plots critically.

Relationship to Advanced Plotting

This chapter introduces the general ideas behind visualization in MATLAB. Basic 2D plots, customizing axes and appearance, combining multiple plots, and labeling are all developed in the subsequent chapters in this section. More specialized layouts and plot types, such as subplots, 3D plots, and interactive editing with graphics handles, are covered in the separate section on advanced plotting for beginners.

It is helpful to see basic and advanced plotting as a continuum. You start from simple commands that create standard plots with minimal input. Over time, you add more control, introduce multiple axes or dimensions, and tap into the full graphics system. The upcoming chapters progressively guide you through this path.