Matlab Paper Plot
by 周祥荣
Generate IEEE/Elsevier publication-ready MATLAB figures with consistent styles, vector exports, and LaTeX captions.
Free
Works with the AI tools you already use
See it in action
You say
Plot my RMSE results against SNR from -10 to 30 dB. Compare my 'DeepNet' method with MUSIC and the CRLB for a sensor array paper.
Your agent does
% Generated Publication-Ready Plot init_figure('square'); plot(snr, crlb, '-.p', 'Color', [0.49 0.18 0.56], 'DisplayName', 'CRLB'); plot(snr, music_err, '--s', 'Color', [0.00 0.45 0.74], 'DisplayName', 'MUSIC'); plot(snr, deepnet_err, '-o', 'Color', [1.0 0 0], 'LineWidth', 1.8, 'DisplayName', 'DeepNet (Proposed)'); save_figure(gcf, 'rmse_vs_snr');
Output: rmse_vs_snr.eps, rmse_vs_snr.png, rmse_vs_snr.fig Caption: Fig. 1. RMSE performance versus SNR for the deep learning-based DOA estimator.
About this skill
Professional Scientific Visualization in MATLAB
Creating publication-ready figures in MATLAB is a tedious process of tweaking font sizes, line weights, and export resolutions. This skill automates the generation of journal-grade plots that adhere to IEEE, Elsevier, and Springer academic standards, ensuring your research looks professional and consistent.
What it does
- Role-Based Styling: Automatically assigns specific colors and line styles based on method types (e.g., Proposed Method vs. Baselines vs. CRB).
- Multi-Format Export: Generates vector EPS for LaTeX, high-res PNG for slides, and .fig files for future editing in one workflow.
- Smart Layouts: Manages figure positioning and aspect ratios for single plots, comparisons, or spectra to fit perfectly in paper columns.
- Academic Compliance: Enforces Helvetica fonts, proper line weights (1.8pt+), and readable marker sizes for high-impact factor journals.
Why use this skill?
Prompting an AI for plots often results in "default-looking" MATLAB figures with thin lines and small fonts that fail peer review. This skill uses a strict binding style guide to ensure your Proposed Method is always visible on top, markers are distinct, and captions are written in proper academic tense without redundant parameter clutter.
The Output
You receive optimized MATLAB source code, a set of exported files (EPS/PNG/FIG), and a clean LaTeX caption ready to be dropped into your manuscript.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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