MATLAB - 2D Line Plot

MATLAB - Modern 2D Line Plots

A 2D line plot is one of the most fundamental and powerful tools for data visualization in MATLAB. It’s used to explore the relationship between two variables, typically by plotting data points on a Cartesian plane and connecting them with lines. Mastering plotting is essential for data analysis, reporting scientific results, and debugging algorithms.

The plot Function

The core function for creating 2D plots is plot. While it has many syntaxes, modern MATLAB programming emphasizes a more readable and flexible approach using name-value pairs for customization.

Common Syntaxes

% 1. Basic Plotting
plot(X, Y)

% 2. Plotting with Line Specification (classic shorthand)
plot(X, Y, LineSpec)

% 3. Plotting with Name-Value Pairs (Modern & Recommended)
plot(X, Y, 'PropertyName', PropertyValue, ...)

% 4. Plotting multiple lines at once
plot(X1, Y1, X2, Y2, ...)

Explanation

• plot(X, Y): Creates a 2D line plot of the data in vector Y versus the corresponding values in vector X. X and Y must have the same number of elements.
• plot(X, Y, LineSpec): An older but still common shorthand to specify line style, marker symbol, and color. For example, '--or' specifies a dashed (--) red (r) line with circle (o) markers.
• plot(X, Y, 'PropertyName', PropertyValue): The recommended modern approach. It’s more explicit and readable. You can set dozens of properties like 'LineWidth', 'Color', 'Marker', 'MarkerSize', etc. This method is far more flexible and powerful.

Example 1: A Complete, Well-Documented Plot

A good plot is more than just a line; it has labels, a title, and is easy to read. Let’s plot a sine wave and annotate it properly.

% 1. Prepare the data
x = linspace(0, 2*pi, 200); % Create 200 points from 0 to 2*pi for a smooth curve
y = sin(x);

% 2. Create the plot
figure; % Create a new figure window to avoid overwriting existing plots
plot(x, y, 'LineWidth', 2); % Use a thicker line for better visibility

% 3. Annotate the plot (CRITICAL for communication)
title('Sine Wave from 0 to 2π');
xlabel('Angle [rad]');
ylabel('Amplitude');
grid on; % Add a grid for easier reading
axis([0 2*pi -1.2 1.2]); % Set axis limits for a clean look

When you run this code, a new figure window will appear. It will display a smooth blue sine wave that oscillates between -1 and 1. The plot will have a title, labeled x and y axes, and a grid in the background.

Example 2: Plotting Multiple Lines & Using a Legend

To compare different datasets, you often need to plot them on the same axes. The hold on command is essential for this.

% 1. Prepare data for two functions
x = linspace(0, 2*pi, 100);
y1 = sin(x);
y2 = cos(x);

% 2. Plot the first line
figure;
plot(x, y1, 'DisplayName', 'sin(x)', 'Color', 'blue', 'LineWidth', 2);

hold on; % Tell MATLAB to add subsequent plots to the same axes

% 3. Plot the second line
plot(x, y2, 'DisplayName', 'cos(x)', 'Color', 'red', 'LineStyle', '--', 'LineWidth', 2);

hold off; % Release the hold on the axes

% 4. Add final annotations
title('Sine and Cosine Functions');
xlabel('Angle [rad]');
ylabel('Amplitude');
grid on;
legend('show'); % Display the legend using the 'DisplayName' properties

This script generates a plot with two curves: a solid blue line for the sine function and a dashed red line for the cosine function. A legend is displayed, correctly identifying which line corresponds to which function.

Example 3: Creating a Scatter Plot from Experimental Data

Sometimes you want to show individual data points without a connecting line. This is called a scatter plot and is perfect for experimental data.

% Simulate some noisy experimental data
x_data = 1:10;
y_data = 2*x_data + 1 + randn(size(x_data)); % y = 2x + 1 with some noise

% Create a scatter plot using markers without a line
figure;
plot(x_data, y_data, 'o', ...
    'MarkerFaceColor', 'g', ... % Fill the markers with green
    'MarkerEdgeColor', 'k', ... % Black edges for markers
    'MarkerSize', 8); % Make markers larger

% Annotate the plot
title('Noisy Experimental Data');
xlabel('Measurement ID');
ylabel('Measured Value');
grid on;

This will produce a plot showing ten circular markers with green faces and black edges. The points will roughly follow an upward-sloping line, but with random variations, representing noise.

Practical Advice

• Always Label Your Axes: A plot without labels is meaningless.
• Use figure: Start a new plot with figure to avoid accidentally drawing over a previous one.
• Prioritize Readability: Use name-value pairs ('LineWidth', 2) for clarity over cryptic short-forms ('--r'). Your future self will thank you.
• Save Your Work: Use saveas(gcf, 'myPlot.png') or the more modern exportgraphics(gca, 'myPlot.pdf') to save your plot for reports and presentations.