paper-plot

name	paper-plot
description	Generate publication-quality matplotlib figures in real academic paper styles. Two modes: from-data (pick a pre-built catalog style, fill in your numbers) and from-image (reproduce an uploaded paper figure as a matplotlib script). Use for "把数据画成论文图", "用某风格画我的数据", "复现这张图", or a named catalog style. Drawing only, no paper reading; route journal-compliance figures (IEEE/Elsevier/Nature specs) to academic-figure.
category	research-learning-knowledge
tags	["matplotlib","plotting","figures","paper","reproduction","visualization"]
version	1.0.0

Paper Plot

Produce paper-quality matplotlib figures, either by filling a pre-built style with your data or by reproducing an uploaded paper figure. All outputs are dpi=300 PNG.

<skill-dir> below is this skill's directory — substitute the absolute path announced when the skill loads. On Windows, prefix script runs with PYTHONUTF8=1 when reading/writing UTF-8 (see resources).

Pick a mode

You have…	Mode	Read
Data + a target style (or a style name)	from-data	references/modes/from-data.md
A paper figure image to recreate	from-image	references/modes/from-image.md

If unsure which style fits the data, from-data explains how to infer it from the data shape; from-image explains how to match an image to a style or build from scratch.

Style catalog (from-data)

Style	Type	Script	适用场景
bar_paired_delta	柱状图	scripts/bar_memevolve.py	Baseline vs method 配对对比 + 增益箭头
bar_grouped_hatch	柱状图	scripts/bar_spice.py	多方法消融，主方法斜线填充，柱顶数值
line_confidence_band	折线图	scripts/line_selfdistill.py	带置信区间的训练曲线
line_training_curve	折线图	scripts/line_aime.py	垂直断点线 + 水平参考线
line_loss_with_inset	折线图	scripts/line_loss_inset.py	L 形 spine + 局部放大 inset
scatter_tsne_cluster	散点图	scripts/scatter_tsne.py	t-SNE 聚类 + 注释框
scatter_broken_axis	散点图	scripts/scatter_break.py	折断 X 轴，多 marker 系列
radar_dual_series	雷达图	scripts/radar_dora.py	双方法多维对比，正八边形网格

Per-style exact parameters (rcParams, colors, font sizes, spines, ticks) live in references/styles/<style>.md — read the matching file before generating.

Running a script

# default output name in the current directory:
python <skill-dir>/scripts/<script>.py
# or choose the output path:
python <skill-dir>/scripts/<script>.py my_figure.png

Each script embeds its data near the top (clearly marked) — copy the script, swap the data block, then run. The output path is argv[1] (defaults to a *_repro.png name in the working directory). line_selfdistill.py emits two figures (argv[1], argv[2]).

Dependencies & caveats

• Needs matplotlib, numpy. scatter_break.py also needs scipy; the usetex=True styles (bar_grouped_hatch, line_confidence_band, line_loss_with_inset, scatter_tsne_cluster) require a working LaTeX install — swap to text.usetex: False if LaTeX is unavailable.

Resources

• Modes: references/modes/from-data.md, references/modes/from-image.md
• Styles: references/styles/ — 8 parameter files
• From-scratch analysis: references/reproduction_guide.md
• Scripts: scripts/ — 8 style scripts + classwise_iou_table.py (from-image example)
• Gallery: assets/originals/ — 10 paper figures used to derive the styles (visual reference for from-image matching)