MATLAB Figure Beautifier (beautify_figure.m)

A MATLAB function to systematically enhance the aesthetics of figures for presentations and publications.

Purpose

The beautify_figure.m script provides a comprehensive set of tools to improve the visual appeal of MATLAB figures. It allows for customization of fonts, colors, line styles, markers, grid, legend, titles, and much more. It can handle figures with multiple subplots, tiled layouts, and tabs, applying consistent styling throughout.

Basic Usage

To apply default beautification settings to the current figure:

% Generate a sample plot
figure;
plot(rand(10,3));
title('My Sample Plot');

% Beautify it!
beautify_figure();

To apply custom settings:

my_params.font_name = 'Helvetica';
my_params.plot_line_width = 2;
beautify_figure(my_params);

To apply to specific axes:

h_axes1 = subplot(1,2,1); plot(rand(5)); title('First Plot');
h_axes2 = subplot(1,2,2); scatter(rand(10,1), rand(10,1)); title('Second Plot');
beautify_figure([h_axes1, h_axes2]); % Apply default to specific axes

Using the Beautify Figure App (GUI)

For users who prefer a graphical interface, this project also includes BeautifyFigureApp.mlapp. This app provides an interactive way to apply many of the beautification settings available in the beautify_figure.m script.

To launch the app:

1. Open BeautifyFigureApp.mlapp in the MATLAB editor.
2. Click the "Run" button in the editor's toolbar. Alternatively, if the project is packaged as a MATLAB App (.mlappinstall file), you can install it via the MATLAB Apps tab and then run it from the Apps toolbar.

The app allows you to:

• Load and apply settings to the currently active figure.
• Adjust parameters through various UI controls (dropdowns, checkboxes, spinners).
• Import and export parameter presets as .mat files.
• Access a built-in help dialog for app usage.

While the app covers many common parameters, the full range of options and fine-grained control (especially for complex parameters like custom color palettes as matrices or detailed marker style cycling) is available through the beautify_figure.m script directly. Note: Advanced features like Stats Overlay are configurable via the beautify_figure.m script, but GUI controls in the BeautifyFigureApp.mlapp are planned for a future update.

Parameters

The beautify_figure.m script offers a wide range of customizable parameters. These are passed as fields in a structure. For a detailed list of all parameters and their default values, please refer to the extensive help text within the beautify_figure.m script itself (e.g., by typing help beautify_figure in MATLAB).

Key parameters include:

• style_preset: String, e.g., 'default', 'publication', 'presentation_light', 'minimalist'. Applies a predefined set of styles.
• font_name: Font family (e.g., 'Arial', 'Helvetica'). (Can be part of a preset).
• base_font_size: Base font size for scaling elements.
• plot_line_width: Base line width for plotted data.
• color_palette: Predefined palettes ('default_matlab', 'lines', 'parula', 'viridis', 'turbo', 'cividis', etc.) or custom RGB matrix.
• export_settings: Structure for controlling automatic figure export (see details below).
• stats_overlay: Structure for basic statistical overlay (see details below).

Font Considerations

For the most predictable visual results, it is recommended to specify font names (e.g., via the font_name parameter or within style presets) that are known to be installed on your system.

While beautify_figure.m requests specific fonts (like 'Swiss 721 BT' as a default or 'Helvetica Neue' in certain presets), MATLAB may automatically substitute these with available system fonts if the requested ones are not found. This substitution ensures that the script runs without error, but the visual appearance may differ from the intended design if the specified fonts are not present on the user's system. You can use the listfonts command in MATLAB to see available system fonts.

Features

• Configurable style presets (e.g., 'publication', 'presentation_light', 'minimalist') for quick common setups.
• Font and text property adjustments (size, weight, color, font family).
• Control over line styles, markers, and color palettes.
• Automatic scaling of elements based on subplot density.
• Support for tiled layouts and figure tabs.
• Interactive legends (clickable items to toggle plot visibility, R2019b+).
• Axes styling (box, grid, tick direction, layer).
• Optional automatic export of figures to various formats (PNG, PDF, EPS, etc.).
• Automated Panel Labeling: Automatically add panel labels like 'A', 'B', 'C' or 'a)', 'b)' to subplots/tiles.
• Basic Statistical Overlay: Display basic statistics (mean, std, min, max, N, etc.) for plotted data directly on the figure.

Examples

The basic usage examples above demonstrate how to apply default settings, custom parameters, or target specific axes. Below are more detailed examples of the preset and export functionalities.

Detailed Features

Style Presets

The style_preset parameter allows you to quickly apply a predefined collection of settings tailored for common use cases. User-defined parameters will always override any values set by a preset.

Available presets:

• 'default': The standard beautification settings.
• 'publication': Optimized for academic publications. Typically uses standard fonts (e.g., Arial or Times), appropriate font sizes, thinner lines for potentially dense plots, a black and white color scheme for axes/text, and a clear color palette for plots. Grid is often major lines only.
• 'presentation_light': Suited for presentations on light backgrounds. Uses larger fonts, clear lines, and bright, distinct color palettes (e.g., 'turbo' is the default for this preset).
• 'minimalist': A clean, uncluttered look with minimal gridlines, often using only left and bottom axes, and a grayscale or simple color scheme.

Example:

% Apply the 'publication' preset
beautify_figure('style_preset', 'publication');

% Use 'presentation_light' but customize the font
my_settings.style_preset = 'presentation_light';
my_settings.font_name = 'Helvetica'; % Overrides preset font
my_settings.color_palette = 'viridis'; % Overrides preset palette
beautify_figure(my_settings);

Automatic Figure Export

The export_settings parameter (a structure) allows for direct export of the beautified figure.

Key export_settings fields:

• enabled (boolean): Set to true to activate export. Default: false.
• filename (string): The desired name for the output file, without the extension (e.g., 'my_plot'). Default: 'beautified_figure'.
• format (string): The export format. Common options: 'png', 'jpeg', 'pdf', 'eps', 'svg', 'tiff'. Default: 'png'.
• resolution (numeric): Resolution in Dots Per Inch (DPI) for raster formats (like PNG, JPEG, TIFF). Default: 300.
• open_exported_file (boolean): If true, attempts to open the exported file using the system's default application. Default: false.
• renderer (string): MATLAB renderer to use (e.g., 'painters', 'opengl'). Relevant for the print command fallback. Default: 'painters'.
• ui (boolean): If true (and MATLAB R2020a+), attempts to use exportgraphics. Otherwise, uses print -noui. Default: false.

Example:

% Beautify and export to PDF
figure;
plot(1:10, (1:10).^2);
title('Square Values');

export_options.export_settings.enabled = true;
export_options.export_settings.filename = 'squares_plot';
export_options.export_settings.format = 'pdf';
export_options.export_settings.resolution = 300; % Good for vector PDF too
beautify_figure(export_options); 
% This will create 'squares_plot.pdf'

Basic Statistical Overlay

This feature allows for the display of basic statistical information (like mean, standard deviation, N, etc.) for a chosen plot directly on the figure. This is useful for quickly conveying key data characteristics. Settings are managed via the stats_overlay structure.

Key stats_overlay parameters:

• enabled (boolean): Set to true to enable the statistical overlay. Default: false.
• statistics (cell array of strings): Specifies which statistics to display. Options: 'mean', 'std', 'min', 'max', 'N', 'median', 'sum'. Default: {'mean', 'std'}.
• position (string): Position of the stats text box on the axes (e.g., 'northeast_inset', 'southwest_inset'). Default: 'northeast_inset'.
• precision (integer): Number of decimal places for the displayed statistical values. Default: 2.
• target_plot_handle_tag (string): The Tag property of a specific plot object (e.g., a line or scatter plot) from which to calculate statistics. If empty, the function attempts to use the first valid plot object found in the axes. Default: ''.
• font_scale_factor (numeric): Multiplier for the font size, relative to the axes labels' font size. Default: 0.9.
• text_color (color spec): Color of the statistics text. If empty ([]), inherits from params.text_color.
• font_name (string): Font name for the statistics text. If empty ([]), inherits from params.font_name.
• background_color (color spec or string): Background color of the stats text box. Can be an RGB triplet, a standard MATLAB color string (e.g., 'yellow'), or 'figure' to match the figure background. If empty ([]), no background is drawn.
• edge_color (color spec or string): Edge color of the stats text box. Can be an RGB triplet, a color string, or 'axes' to match the axes color. If empty ([]), no edge is drawn.

Example:

figure; 
plot(1:20, randn(1,20) + 10, 'Tag', 'TemperatureData', 'LineWidth', 1.5);
title('Experimental Data');

my_settings.stats_overlay.enabled = true;
my_settings.stats_overlay.statistics = {'mean', 'std', 'N', 'max'};
my_settings.stats_overlay.target_plot_handle_tag = 'TemperatureData'; % Target this specific plot
my_settings.stats_overlay.position = 'southeast_inset';
my_settings.stats_overlay.background_color = [0.95 0.95 0.85]; % Light yellow background
my_settings.stats_overlay.edge_color = [0.5 0.5 0.5];      % Gray border
beautify_figure(my_settings);
% Expected: A text box in the bottom-right of the plot showing mean, std, N, and max
% for the 'TemperatureData' line, with a light yellow background and gray border.

Recent Enhancements and Current Status

BeautifyFigureApp.mlapp Improvements

The accompanying GUI, BeautifyFigureApp.mlapp, has received several updates to enhance its robustness and user experience:

• Preset Loading: Loading presets from .mat files is now more resilient. If a preset file is missing some parameters, the App will apply the settings that are present and issue a warning to the user detailing which settings were skipped or defaulted.
• Input Validation: Validation has been added for the "Custom Color Palette" and "Statistics" text input fields. The App now provides uialert warnings if the input in these fields is malformed (e.g., an invalid matrix string for the color palette, or an unparseable cell array string for statistics).
• Font Selection: The font name dropdown list population is more robust and includes better fallbacks if system fonts cannot be fully enumerated, ensuring the App remains functional.

Test Script (test_beautify_figure.m) Enhancements

The test_beautify_figure.m script has been significantly expanded to improve test coverage and verify the stability of beautify_figure.m under various conditions. New test cases include:

• Applying beautification to an empty figure (a figure with no axes or plotted data) to ensure no errors occur.
• Processing figures that contain UI tabs (uitabgroup), verifying that axes within each tab are correctly identified and beautified.
• Handling of invalid parameters passed to beautify_figure.m, ensuring that the function logs appropriate warnings/errors and does not crash, instead applying default or valid portions of parameters where possible.

Status of beautify_figure.m Refactoring

The beautify_figure.m script is continuously maintained, with ongoing efforts to improve its functionality and robustness. Future updates may include further refactoring and feature enhancements.

Dependencies

• MATLAB (R2019b or newer recommended for full feature compatibility, especially interactive legends).

License

This project is licensed under the MIT License. See the LICENSE.md file for details.