2.2.4. Multiple data sets in one plot

Multiple(x,y) pairs arguments create multiple graphs with a single call to plot. For example, these statements plot three related functions of x: y = 2cos(x), y = cos(x), and y = 0.5cos(x), in the interval 0 ≤ x ≤ 2π.

This chunk introduces the idea of plotting multiple data sets in MATLAB. Instead of creating separate plots for different functions, you can combine them into a single plot using the plot command with multiple (x, y) pairs. For instance, in the example provided, three different cosine functions are plotted on the same graph. This allows for a direct comparison of the functions over the same range of x values, enhancing the analysis and visual understanding.

Think of this as comparing three different perspectives during a presentation. Just as you can display three charts on one screen to see how they relate to each other, in MATLAB, you can plot multiple functions on one graph to analyze their relationships at a glance.

x = 0:pi/100:2pi; y1 = 2cos(x); y2 = cos(x); y3 = 0.5*cos(x); plot(x,y1,'--',x,y2,'-',x,y3,':')

In this chunk, a specific example is given for how to plot the three cosine functions using the MATLAB code. First, it creates a vector x that ranges from 0 to 2π with increments of π/100. Then, it defines three different cosine functions: y1 is twice the cosine of x, y2 is the standard cosine function, and y3 is half the cosine function. Finally, the plot command combines these three functions in a single call, with different line styles for each curve ('--' for dashed, '-' for solid, and ':' for dotted). This demonstrates how to effectively visualize multiple related functions at once.

Consider this like arranging different decorations for a holiday party. Each type of decoration (e.g., balloons, lights, and banners) has its own style. By preparing and displaying them together, you can create a cohesive and visually appealing environment, much like how these different functions together create a comprehensive graph.

xlabel('0 ≤ x ≤ 2π') ylabel('Cosine functions') legend('2cos(x)','cos(x)','0.5cos(x)') title('Typical example of multiple plots') axis([0 2*pi -3 3])

This chunk focuses on enhancing the clarity of the plot by adding labels and a legend. The xlabel and ylabel functions are used to label the x-axis and y-axis respectively, providing context about what each axis represents. The legend function helps identify which curve corresponds to each mathematical function, and the title function gives the entire plot a descriptive heading. Finally, the axis command sets the display limits for both axes, ensuring that all relevant parts of the graph are visible.

Imagine you are at a science fair. Alongside each experiment, there are labels explaining what each display is about and signs indicating which project belongs to whom. Similarly, in MATLAB, labels and legends act as guides for readers, allowing them to understand and follow the visual information presented in the graph.

The result of multiple data sets in one graph plot is shown in Figure 2.3.

This chunk describes the output of the plotting commands. The resulting graph illustrates the three cosine functions plotted together on the same axes, providing a visual representation that allows for easy comparisons of their behaviors over the specified interval. Both the shapes and values of the functions can be seen in relation to each other, facilitating a deeper understanding of how they differ and how they are similar.

Think of the output of the plot as a team of players showing off their skills together on a field. Just like fans can appreciate how each player performs in relation to the others during a game, viewers of the plot can observe how the different cosine functions behave compared to one another, making it easier to recognize patterns and differences.

By default, MATLAB uses line style and color to distinguish the data sets plotted in the graph. However, you can change the appearance of these graphic components or add annotations to the graph to help explain your data for presentation.

The final chunk highlights that while MATLAB automatically assigns colors and line styles to different plots, users have the option to customize these elements. Customization allows for enhanced visual appeal and clarity, particularly when presenting data to an audience. Users can choose specific colors, styles, and markers to ensure that each plotted data set is distinct and easily interpretable.

Think of customizing a graph like dressing for an important occasion. You might choose specific colors and styles for your outfit to make a statement and ensure that you stand out. Similarly, customizing the plot's appearance helps convey the intended message and makes it visually effective for the audience.

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