ieee-figure

name

ieee-figure

description

Produce publication-grade result figures for IEEE communications papers (JSAC, TWC, TC/TCOM, WCL, CL) — correct column widths, embedded fonts, vector output (PDF/EPS), grayscale- and colorblind-safe palettes, readable fonts, and the comms-standard plot types: BER/outage vs SNR on a log y-axis, achievable/sum rate vs SNR or antennas, convergence curves, CDFs, the analysis-line + simulation-marker overlay, learning curves (NMSE vs SNR, training/validation loss), and ISAC plots (rate–CRB tradeoff, beampattern, ROC). Use whenever the user wants to make or fix a figure for a comms paper: "make a result plot", "BER curve", "误码率曲线", "中断概率图", "和速率曲线", "收敛曲线", "仿真图", "NMSE曲线", "训练损失曲线", "CRB折中图", "波束方向图", "IEEE figure", "single/double column figure", "图太小看不清". For deciding which metrics to plot, use ieee-experiments; for captions-as-argument, see ieee-writing.

IEEE Publication Figures

Use this skill to generate or repair figures that will survive IEEE production: vector, correctly sized for the column, with embedded fonts and readable text at print size.

Core stance

• Size to the column from the start. Single-column ≈ 3.5 in (88.9 mm) wide; double-column ≈ 7.16 in (181.6 mm). Design at final size so fonts end up readable — never shrink a big figure.
• Vector first. Output PDF or EPS for line/vector art; embed fonts. Use high-res raster only for photographic content (≥ 300 dpi color/grayscale, ≥ 600 dpi for line art / combinations).
• Readable and grayscale-safe. Minimum ~8 pt text at final size; distinguish series by marker/linestyle/hatch as well as colour so the figure survives B/W printing; use a colorblind-safe palette.
• Comms axis conventions. Error/outage curves use a log y-axis (semilogy); keep the SNR range wide enough to show the high-SNR slope (diversity order); define the SNR axis (transmit vs receive). Plot a derived expression as a line and its Monte-Carlo check as markers.
• One panel, one question. No two panels answer the same thing. The figure must be legible and self-explanatory with its caption.
• No fabricated data. Plot only the user's real numbers; if data is missing, ask or stub with a clearly labelled placeholder.

When to open extra files

File	Open when
references/ieee-figure-spec.md	Sizing, resolution, fonts, colour/grayscale, file format, multi-panel layout, caption rules, submission checklist
references/matplotlib-patterns.md	Concrete matplotlib setup (rcParams for embedded fonts, sizing, palettes) and ready patterns for BER/outage-vs-SNR (semilog), rate vs SNR/antennas, analysis-vs-simulation overlay, convergence, CDF, NMSE-vs-SNR, training/validation loss, and ISAC plots (rate–CRB tradeoff, beampattern, ROC)

Workflow

1. Target column: ask single- or double-column; set the width accordingly.
2. Pick the chart type that matches the result (see matplotlib-patterns.md): BER/outage vs SNR (semilog y) for reliability, line vs SNR/antennas for rate/efficiency, analysis-line + simulation-marker overlay to validate a derivation, objective-vs-iteration for convergence, CDF for distributions.
3. Set the rendering rcParams first (embedded fonts, sans-serif, sizes) — before any plotting.
4. Plot the real data; encode each scheme redundantly (colour + marker/linestyle). Use semilogy for error/outage; floor the y-axis at the lowest reliably simulated value.
5. Label fully: axis titles with units (dB, bps/Hz), defined SNR axis, legend; text ≥ 8 pt.
6. Export .pdf (or .eps) as primary and a 300–600 dpi .png preview.
7. Grayscale check: convert to gray and confirm series are still distinguishable.
8. Return the script, the output paths, and a one-line caption draft.

Output format

1. Script: a self-contained, runnable plotting script (matplotlib) using the user's data.
2. Outputs: the vector file path + a PNG preview path.
3. Caption: a one-sentence draft stating what the figure shows (the question it answers).
4. Checks: confirmation of size, font embedding, and grayscale legibility.