SKILL.md
Plot From Image
Reproduce a paper figure by analyzing the image and leveraging accumulated style knowledge.
Workflow
1. Measure Proportions
python3 -c "from PIL import Image; img=Image.open('fig.png'); print(img.size, f'AR={img.size[0]/img.size[1]:.2f}')"Set figsize=(FW, FH) so FW/FH matches the original AR exactly.
2. Match to Existing Style
Check if the figure matches a pre-built style (fastest path):
| Figure type | Check for |
|---|---|
| Grouped/paired bar | barpaireddelta or bargroupedhatch |
| Line with shaded bands | lineconfidenceband |
| Line with cut lines or reference | linetrainingcurve |
| Loss curve + zoom panel | linelosswith_inset |
| Scattered clusters | scattertsnecluster |
| Broken x-axis | scatterbrokenaxis |
| Polygon web chart | radardualseries |
If matched → read ../plot-from-data/references/<name>.md for exact parameters → adapt ../plot-from-data/scripts/<script>.py.
3. If No Match → Analyze From Scratch
Read references/reproduction_guide.md for the full analysis checklist covering:
- Font family detection (serif vs sans-serif, LaTeX vs not)
- Spine & tick style (L-shape, 4-sided, arrows, in/out direction)
- Color identification (tab10 vs custom)
- Grid style (dashed, dotted, none)
- Special elements (insets, broken axes, radar grids, annotation boxes)
4. Build & Iterate
Write script → python3 <script>.py → visually compare → fix proportions/colors → re-runKey iteration checklist:
- AR matches original (measure with PIL)
- Font family correct (serif for LaTeX papers, sans-serif for system fonts)
- Colors within ±10 RGB of original
- Spine style matches (L vs 4-sided)
- Tick direction matches (in vs out)
- Grid style matches
- Legend placement matches
- Annotations/labels position matches
Accumulated Experience
From 9 reproduced figures across 7 papers, key lessons:
- Smooth training curves: use EMA with
alpha=0.95-0.97before plotting, not raw noisy data - Radar labels:
label_r = 1.10-1.15(NOT 1.2+, which creates excess whitespace) - Inset figures: measure left/right panel pixel ratio from original → set
add_axeswidths accordingly - Broken axis: use two subplots with
wspace=0.05, break symbol only at bottom spine - t-SNE annotation boxes: unified dark edge color
#2C3E50, cluster-color facecolor withalpha=0.28 - Confidence bands:
fill_betweenwithalpha=0.18-0.22, same color as line
Resources
- Analysis guide:
references/reproduction_guide.md— step-by-step checklist for new images - Style library:
../plot-from-data/references/— 8 pre-built style parameter files - Script templates:
../plot-from-data/scripts/— 8 working reproduction scripts - Originals:
../originals/— paper figures used in development