Initial commit — scientific-viz skill

Claude Code skill for publication-quality scientific visualisations: chart, architecture, flowchart, comparison, pipeline. Bundles matplotlib publication defaults (300 DPI, serif font, colorblind palette), NADEZHDA project palette, Mermaid conventions, and ready-to-use templates. Contents: - SKILL.md — behaviour spec (5 types, generation pipeline) - README.md — human-facing entry: when, install, examples - reference/chart_patterns.md — Pareto/bar/radar/heatmap snippets - templates/architecture_nadezhda.md — Mermaid templates for Teacher-Student / LUPI / fusion Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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+# scientific-viz
+
+Claude Code skill for **publication-quality scientific visualizations** — charts (matplotlib/seaborn), neural-network architecture diagrams (matplotlib patches *or* Mermaid), block-scheme flowcharts, training-pipeline diagrams, and benchmark comparison figures. Tuned for the CVGL / NADEZHDA project but reusable for any deep-learning paper.
+
+> Behaviour spec — see [`SKILL.md`](SKILL.md). This file is the human-facing entry point.
+
+## When to use
+
+- Need a figure for a paper / report / slide deck and want it consistent with project style.
+- Want a Pareto plot (params vs R@1), grouped bar, radar, heatmap, or training curve.
+- Need a Teacher–Student / multi-modal fusion architecture diagram.
+- Need a Mermaid flowchart embeddable in Obsidian for an LUPI / KD pipeline.
+- Want a quick comparison figure across CVGL benchmarks (University-1652, GeoText-1652, GTA-UAV, VisLoc).
+
+## Invocation
+
+```text
+/scientific-viz <type> "<description>"
+```
+
+Where `<type> ∈ {chart, architecture, flowchart, comparison, pipeline}`.
+
+**Examples**
+
+```text
+/scientific-viz chart        "R@1 comparison across methods on University-1652"
+/scientific-viz architecture "Teacher-Student LUPI pipeline"
+/scientific-viz flowchart    "Training progressive staging 3 phases"
+/scientific-viz comparison   "Backbone candidates: params vs R@1"
+/scientific-viz pipeline     "LUPI distillation flow with 7 losses"
+```
+
+## Five visualisation types
+
+| Type | Output | Use for |
+|------|--------|---------|
+| `chart` | Python script (`.py`) **+** `.png` (300 DPI) **+** `.pdf` (vector) | metric comparisons, ablations, distributions, training curves |
+| `architecture` | matplotlib patches Python (complex) **or** Mermaid (Obsidian-embeddable) | Teacher/Student, backbone stages, fusion modules, head designs |
+| `flowchart` | Mermaid (`graph TD` / `graph LR`) + optional Python | training/inference pipeline, experimental workflow, data processing |
+| `comparison` | Python `.py` + `.png/.pdf` | Pareto front, grouped bar, radar/spider, heatmap |
+| `pipeline` | Mermaid + matplotlib | LUPI distillation flow, augmentation chain, edge deployment |
+
+## Publication-quality defaults (charts)
+
+Every generated `chart` / `comparison` / `pipeline` Python script starts with this rcParams block:
+
+```python
+import matplotlib
+matplotlib.rcParams.update({
+    'font.family': 'serif',
+    'font.size': 11,
+    'axes.labelsize': 12,
+    'axes.titlesize': 13,
+    'legend.fontsize': 10,
+    'xtick.labelsize': 10,
+    'ytick.labelsize': 10,
+    'figure.dpi': 300,
+    'savefig.dpi': 300,
+    'savefig.bbox': 'tight',
+    'axes.grid': True,
+    'grid.alpha': 0.3,
+})
+```
+
+Hard requirements baked in:
+
+- ≥ 300 DPI, vector PDF + raster PNG saved side-by-side.
+- Times New Roman / DejaVu Serif, ≥ 10 pt.
+- Colorblind-safe palette (Okabe-Ito or `tab10`).
+- English axis labels for publications, optional Russian for internal reports.
+- Light-gray grid (`alpha=0.3`), tight layout, no clipped labels.
+
+## NADEZHDA project palette (consistent across figures)
+
+| Component | Colour | Hex |
+|-----------|--------|-----|
+| Teacher | Deep blue | `#1f77b4` |
+| Student | Orange | `#ff7f0e` |
+| Satellite modality | Green | `#2ca02c` |
+| Drone modality | Red | `#d62728` |
+| Street-view | Purple | `#9467bd` |
+| Depth | Brown | `#8c564b` |
+| Text | Pink | `#e377c2` |
+| Loss / gradient | Gray | `#7f7f7f` |
+| Edge / Jetson | Teal | `#17becf` |
+
+## Mermaid conventions (architecture / flowchart / pipeline)
+
+- `graph TD` — vertical flow (Teacher → Student stack).
+- `graph LR` — horizontal pipeline (input → backbone → neck → heads).
+- Thick arrows = main data flow · dashed arrows = gradient / loss signals.
+- Loss labels on arrows: `L_task`, `L_LUPI`, `L_feat`, `L_RKD`, `L_seg`, `L_CVD_MI`, `L_CVD_Recon`.
+- `style` / `classDef` to mark Teacher (blue), Student (orange), shared (green).
+
+Ready-to-use templates: [`templates/architecture_nadezhda.md`](templates/architecture_nadezhda.md).
+
+## Standard tensor shapes (for architecture annotations)
+
+```
+Input:      [B, 3, 256, 256]
+Stage 1:    [B,  32,  96,  96]
+Stage 2:    [B,  64,  48,  48]
+Stage 3:    [B, 128,  24,  24]
+Stage 4:    [B, 256,  12,  12]
+Descriptor: [B, 512]   L2-normalized
+```
+
+## Installation
+
+Drop this repo into your vault's Claude Code skills directory:
+
+```bash
+git clone https://git.lissad.keenetic.name/Pikaliov/scientific-viz.git \
+    .claude/skills/scientific-viz
+```
+
+Or as a submodule:
+
+```bash
+git submodule add https://git.lissad.keenetic.name/Pikaliov/scientific-viz.git \
+    .claude/skills/scientific-viz
+```
+
+Claude Code picks up the skill on the next session. Verify with `/help` — `/scientific-viz` should appear in the user-invocable list.
+
+**Runtime dependencies** (charts & comparison types):
+
+```bash
+pip install matplotlib seaborn numpy
+```
+
+Mermaid output requires no Python — the diagram block embeds directly into Obsidian, GitHub-flavoured Markdown, or Quarto.
+
+## File layout
+
+```
+scientific-viz/
+├── README.md                                — this file
+├── SKILL.md                                 — behaviour spec (5 types, generation pipeline)
+├── reference/
+│   └── chart_patterns.md                    — canonical Pareto/grouped-bar/radar/heatmap snippets
+└── templates/
+    └── architecture_nadezhda.md             — Mermaid templates for Teacher-Student / LUPI / fusion
+```
+
+## Hard constraints
+
+- ❌ Никаких внешних API (OpenRouter, Gemini и т. п.) — только локальные библиотеки.
+- ❌ Никакой растровой генерации архитектур через `PIL.ImageDraw` — только matplotlib `patches` или Mermaid.
+- ✅ Всегда сохранять и `.py` скрипт, и результат (`.png`/`.pdf`) — рядом, рядом с заметкой / в `attachments/figures/`.
+- ✅ Каждое значение в графике должно иметь источник (комментарий в коде или caption под фигурой).
+- ✅ Для Obsidian — Mermaid-блок встраивается прямо в `.md`, без ссылок на внешние файлы.
+- ✅ Для публикаций — английский язык подписей; для внутренних отчётов — RU допустим.
+
+## Worked example
+
+```text
+/scientific-viz comparison "Pareto front: backbone params vs R@1 on University-1652, mark NADEZHDA target at 8.5M"
+```
+
+Expected output:
+
+- `pareto_params_r1.py` — full matplotlib script with palette, grid, edge-budget shaded region, NADEZHDA marker as star.
+- `pareto_params_r1.png` (300 DPI) + `pareto_params_r1.pdf` (vector) saved next to the script.
+- Inline annotation list (Sample4Geo, VimGeo, QDFL, MobileGeo, (MGS)², NADEZHDA target).
+- Source comment at the top of the script linking to `1_lit_research/СИНТЕЗ_всех_статей_для_LUPI_CVGL.md` rows.
+
+See [`reference/chart_patterns.md`](reference/chart_patterns.md) for the canonical pattern this expands from.
+
+## Allowed tools
+
+`Read`, `Write`, `Edit`, `Bash`, `Glob`, `Grep` — the skill writes Python scripts and Mermaid blocks directly into the vault, then optionally executes the script via `Bash` to produce the rendered `.png`/`.pdf`.
+
+## Related skills
+
+- `/analyze-paper` — surfaces the numbers this skill plots.
+- `/synthesize-review` — produces the cross-paper tables that feed `comparison` figures.
+- `/generate-hypothesis` — the hypotheses whose evidence is plotted.