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MATLAB Plot Customization

MATLAB offers powerful tools for creating and customizing plots. By mastering plot customization, you can create visually appealing and informative graphs that effectively communicate your data.

Basic Plot Customization

Start with a simple plot and gradually enhance its appearance:

x = 0:0.1:2*pi;
y = sin(x);
plot(x, y)
title('Sine Wave')
xlabel('X-axis')
ylabel('Y-axis')
grid on

This code creates a basic sine wave plot with a title, axis labels, and grid lines.

Customizing Line Properties

Modify line properties to change the plot's appearance:

plot(x, y, 'r--', 'LineWidth', 2)
hold on
plot(x, cos(x), 'b-.', 'LineWidth', 1.5)
legend('sin(x)', 'cos(x)')

This example plots two functions with different line styles, colors, and widths. The hold on command allows multiple plots on the same axes.

Adjusting Axes

Fine-tune your plot by modifying the axes:

axis([0 2*pi -1.2 1.2])
set(gca, 'XTick', 0:pi/2:2*pi)
set(gca, 'XTickLabel', {'0', '\pi/2', '\pi', '3\pi/2', '2\pi'})
box on

This code sets the axis limits, customizes tick marks, and adds a box around the plot.

Adding Annotations

Enhance your plot with text annotations and arrows:

text(pi/2, 1, '\leftarrow sin(\pi/2) = 1')
annotation('arrow', [0.7 0.6], [0.5 0.3])

Use text() to add labels at specific coordinates and annotation() to draw arrows or shapes.

Customizing Figure Properties

Modify the overall figure appearance:

figure('Color', [0.9 0.9 0.9], 'Position', [100 100 800 500])
set(gcf, 'Name', 'Custom Plot', 'NumberTitle', 'off')

This code sets the figure background color, size, and title.

Best Practices

  • Use consistent colors and styles for related data series
  • Choose appropriate axis scales and limits for your data
  • Add legends and labels to improve plot readability
  • Consider color-blind friendly palettes for accessibility
  • Use MATLAB Multiple Plots techniques for complex data visualization

Advanced Customization

For more complex visualizations, explore MATLAB's specialized plotting functions:

By mastering these plot customization techniques, you'll be able to create professional-quality visualizations that effectively communicate your data and findings.