[teamai] Push 87 resource(s) from XingfenD
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# Graphical Abstract / 图形摘要模板
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本文件用于生成「期刊投稿 Graphical Abstract / 论文图形摘要 / 投稿封面图」:
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- 期刊投稿要求附带的 Graphical Abstract
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- 论文一图概览("一图讲清主贡献")
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- 答辩首页 / 组会汇报首页里的研究亮点图
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特征:
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- 极简、紧凑、4 部分核心叙事(问题 → 方法 → 关键过程 → 结果)
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- 横向左→右 或 中心展开布局
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- 白底、低饱和工程色、≤3 主色,**像高质量期刊图形摘要,绝不像营销海报**
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- 文字精炼到短语,禁止段落式说明
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## 适用范围
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- Elsevier / ACS / Wiley / Springer / IEEE 等期刊投稿要求的 Graphical Abstract
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- arXiv / 预印本 README 顶部的"研究一图"
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- 论文 supplementary 或 highlight figure
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- 答辩 / 汇报"研究亮点"页
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## 何时使用
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- 用户提到「graphical abstract / 图形摘要 / 投稿摘要图 / 一图讲清 / highlight figure」
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- 用户希望视觉「期刊封面级摘要图,简洁克制学术风」
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- 用户已能用 1-2 句话讲清"这篇论文做了什么、得到了什么"
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不要使用:
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- 用户要的是「方法 pipeline 总览」 → 用 `academic-figures/method-pipeline-overview.md`
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- 用户要的是「开题 / 答辩首页总览图」 → 用 `academic-figures/research-overview-poster.md`
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- 用户要的是「机制 / 机理图」 → 用 `academic-figures/mechanism-diagram.md`
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- 用户要的是「营销 / 品牌 / 杂志封面感」 → 用 `poster-and-campaigns/editorial-cover.md`
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## 缺失信息优先提问顺序
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1. 研究主题(一句话;写在标题或图注里)
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2. 目标期刊或目标场景(决定纵横比 + 主色调;不同期刊偏好不同)
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3. 4 个核心要素:研究问题 / 方法或系统 / 关键过程或机制 / 主要结果
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4. 是否有"研究对象"的简化示意(颗粒 / 分子 / 器件 / 流程)
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5. 标签语言(中文 / 英文 / 双语;多数期刊要求英文)
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6. 比例(默认横向 16:9 / 2:1;部分期刊要求方形 1:1,要先确认)
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## 主模板:横向 4 段式 Graphical Abstract
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📖 描述
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整张图横向流动:从最左边的「研究问题 / 研究对象」开始,依次到「方法 / 系统」、「关键过程 / 机制」、「主要结果」。四个区域比例均匀,文字精炼到短语,视觉层级清晰,整体像高质量工程类期刊摘要图。
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📝 提示词
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```json
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{
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"type": "学术期刊图形摘要(Graphical Abstract)",
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"goal": "生成一张可直接用于期刊投稿的 Graphical Abstract,要求极简、白底、工程化克制配色、几秒内可读、绝无营销海报感",
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"canvas": {
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"aspect_ratio": "{argument name=\"aspect_ratio\" default=\"2:1\"}",
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"background": "pure white #FFFFFF",
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"outer_padding": "60px around the diagram",
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"render_quality": "vector-clean look, anti-aliased edges, sharp text, suitable for grayscale print"
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},
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"title_block": {
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"enabled": "{argument name=\"title_block_enabled\" default=\"false\"}",
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"title": "{argument name=\"title\" default=\"\"}",
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"rule": "most journals do not allow titles inside the graphical abstract; enable only when user explicitly requested a title"
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},
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"sections": [
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{
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"id": "P1",
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"role": "Problem",
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"label": "{argument name=\"problem_label\" default=\"Research Problem\"}",
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"summary": "{argument name=\"problem_summary\" default=\"a short phrase stating the gap, e.g. 'unstable combustion under variable moisture'\"}",
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"depiction": "{argument name=\"problem_depiction\" default=\"a minimal line-art sketch of the studied object or scenario\"}"
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},
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{
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"id": "P2",
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"role": "Method",
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"label": "{argument name=\"method_label\" default=\"Method\"}",
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"summary": "{argument name=\"method_summary\" default=\"a short phrase, e.g. 'thermogravimetric + kinetics analysis'\"}",
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"depiction": "{argument name=\"method_depiction\" default=\"a minimal schematic of the analytical or experimental setup\"}"
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},
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{
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"id": "P3",
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"role": "Process",
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"label": "{argument name=\"process_label\" default=\"Key Mechanism\"}",
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"summary": "{argument name=\"process_summary\" default=\"a short phrase, e.g. 'two-stage volatile combustion'\"}",
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"depiction": "{argument name=\"process_depiction\" default=\"a small mechanism strip with 2-3 sub-steps, line-art style\"}"
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},
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{
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"id": "P4",
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"role": "Result",
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"label": "{argument name=\"result_label\" default=\"Outcome\"}",
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"summary": "{argument name=\"result_summary\" default=\"a short phrase, e.g. 'optimized excess-air ratio reduces NOx by ~X%'\"}",
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"depiction": "{argument name=\"result_depiction\" default=\"a minimal qualitative chart sketch (no fabricated numbers) or a result icon (gauge / bar)\"}"
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}
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],
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"section_block_style": {
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"shape": "implicit columns separated by generous whitespace, NOT four heavy rectangles in a row",
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"header_text": "section label in bold sans-serif, 12-13pt, top-aligned",
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"summary_text": "single phrase, 10pt regular, max 2 lines, no period",
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"depiction_size": "around 35-50% of column height, vertically centered"
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},
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"connectors": {
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"style": "thin arrows (1.2px) with simple triangle arrowheads, dark gray #334155, between adjacent sections only",
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"rule": "no crossing, no curved decorative arcs; arrows convey 'leads to' / 'analyzed by' relationships",
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"label_arrows": "false by default; only add label when the relationship is non-trivial"
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},
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"color_palette": {
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"rule": "≤ 3 main colors total, drawn from a low-saturation engineering set: deep blue #1E3A8A / slate blue #3B82F6 / charcoal #1F2937; allow ONE low-saturation accent (e.g. amber #F59E0B for a heat / risk highlight) only if the user signaled a thermal or risk emphasis",
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"must_print_grayscale_readable": true
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},
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"typography": {
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"language": "{argument name=\"language\" default=\"english\"}",
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"rule": "english → Inter / Helvetica / Arial; chinese → PingFang SC / Source Han Sans; bilingual → english as primary, chinese as smaller secondary line",
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"consistency": "all section headers identical size; all summaries identical size; never mix serif and sans-serif"
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},
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"constraints": {
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"must_keep": [
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"all four sections visually equal-weight, no section dominates",
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"white background, no gradient, no decorative pattern, no photographic background",
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"language matches the target journal (default english)",
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"summaries are short phrases, never full sentences with periods",
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"the figure must look like it could appear on an Elsevier / ACS / IEEE table of contents page",
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"every numerical claim must come from the user; if absent, render qualitatively"
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],
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"avoid": [
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"marketing-poster aesthetics, brand campaign aesthetics, magazine cover aesthetics",
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"3D effects, drop shadows, gradients, glossy fills, lens flare, motion blur",
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"exaggerated flames, smoke, sparks (even when the topic is combustion)",
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"cartoon mascots, emoji, decorative icons, hand-drawn wobble",
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"stock-photo-style realistic backgrounds",
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"fabricated numbers, percentages, equations, or chart data not provided by the user",
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"saturated colors (no neon, no vivid), more than 3 main colors",
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"watermarks, copyright stamps, vendor logos"
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]
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}
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}
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```
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### 参数策略
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- **必问**:4 个 `*_summary`(问题 / 方法 / 关键过程 / 结果)至少能给出短语
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- **可默认**:`aspect_ratio`(2:1)、`background`(白色)、`color_palette`(深蓝/灰蓝/黑灰)
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- **可随机**:每个 section 的 `*_depiction` 具体造型(用户给了对象/方法名时可推断;否则反问)
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### 自动补全策略
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- 用户只给主题但没给 4 段 → 反问 4 个 summary,**禁止编造研究内容**
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- 用户给了定性贡献但没数 → 用 `qualitatively shows` / `consistently reduces` 这类无数字表达
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- 用户给了数(如"NOx 降低 18%")→ 直接写 `~18%`,不要伪造其他指标
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- 用户说"中文期刊 / 中文摘要图" → 切换中文 + 字体 PingFang / 思源黑
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## 变体 1:中心展开式(Hub-and-spoke)
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```json
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{
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"type": "中心展开式 Graphical Abstract",
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"modify": {
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"layout": "中心放置研究对象 / 核心系统的简化示意,向外辐射出 3-4 个扇区,每个扇区代表一个核心要素(问题、方法、机制、结果之一)",
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"rule": "扇区在视觉上等权,使用细线条分隔;中央对象占画面 30-40%",
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"use_case": "适合系统型研究、平台型研究,或难以线性叙事的多模态贡献"
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}
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}
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```
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适用:综合性研究、系统性贡献(如新平台、新框架)。
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## 变体 2:方形 1:1(部分期刊要求)
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```json
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{
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"type": "方形 Graphical Abstract",
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"modify": {
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"aspect_ratio": "1:1",
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"layout": "2×2 网格,左上 = 问题 / 对象,右上 = 方法,左下 = 关键过程,右下 = 结果",
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"rule": "四象限严格等大、对齐;象限间留出统一间距;箭头沿 Z 字型走 P1 → P2 → P3 → P4",
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"use_case": "ACS / Wiley 等部分期刊要求方形 Graphical Abstract"
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}
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}
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```
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适用:投稿要求方形比例的期刊。
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## 变体 3:竖版(社交媒体 / 预印本卡片)
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```json
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{
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"type": "竖版 Graphical Abstract",
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"modify": {
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"aspect_ratio": "3:4",
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"layout": "上 → 下 四段式:Problem → Method → Mechanism → Outcome",
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"rule": "宽度紧凑,每段保留呼吸空间;适合手机端或 Twitter / LinkedIn 卡片预览",
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"use_case": "用于社交媒体推广预印本、Lab 主页 highlight 卡"
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}
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}
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```
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适用:投稿之外的科研宣传,但仍保持学术克制风格。
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## 避免事项
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- 把 Graphical Abstract 画成"全文压缩版"——塞进所有方法步骤、所有公式、所有结果
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- 用任何形式的渐变 / 玻璃质感 / 光晕 / 3D → 立刻像营销图
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- 中英文标签随意混用(除非显式要求双语)
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- 在没有真实数据时画出带具体数值的柱图 / 折线(**严格禁止虚构数据**;只能定性展示)
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- 用饱和 brand 色或霓虹色——期刊摘要图应保持低饱和工程色
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- 把研究对象画成超现实 3D 渲染(学术风需要的是简化线稿)
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- 加期刊 logo / 水印 / "submitted to ..." 等标签
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# 机理示意图模板
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本文件用于生成「学术机理示意图 / 因果链路 / 转化路径 / 演化机制图」:
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- 论文正文里的机制 / 机理分析图
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- 反应 / 转化 / 退化路径图
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- 因果链路 / 多阶段演化图
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- 答辩 PPT 的机制说明页
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特征:
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- 中心对象 + 多阶段转化路径 + 结果区域
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- 阶段化标注(干燥 → 热解 → 燃烧 → 氧化 → 排放,或类似的因果序列)
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- 白底 + 工程化低饱和配色(深蓝 / 灰蓝 / 黑灰为主,可加 ≤1 种低饱和暖色作为高温/风险强调)
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- 学术克制风格,**绝对不是营销插画或科普海报**
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## 适用范围
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- 燃烧 / 化学反应 / 催化 / 退化 / 老化 / 腐蚀 / 衰减 等机制示意
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- 生物 / 医药 / 药物作用 / 分子互作 等通路图(学术风,非科普插画)
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- 材料相变 / 损伤演化 / 失效路径
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- 因果链分析图 / 演化路径图
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## 何时使用
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- 用户提到「机理 / 机制 / 反应路径 / 转化 / 演化 / 因果 / 通路 / 失效路径」
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- 用户希望视觉「论文里的机制图,不是科普插画也不是营销图」
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- 用户已能给出阶段顺序或转化关系
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不要使用:
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- 用户要的是「方法 pipeline / 系统总览」 → 用 `academic-figures/method-pipeline-overview.md`
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- 用户要的是「实验装置 / 测试系统」 → 用 `academic-figures/scientific-schematic.md`
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- 用户要的是「业务流程 / 决策图」 → 用 `technical-diagrams/flowchart-decision.md`
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- 用户要的是「教学步骤、温暖插画感」 → 用 `infographics/step-by-step-infographic.md`
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## 缺失信息优先提问顺序
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1. 机制 / 现象总名称(写在标题或图注里)
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2. 中心研究对象是什么(颗粒 / 分子 / 器件 / 组织 / 反应体系)
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3. 阶段顺序(建议 3-6 个阶段;超过 6 个考虑分组)
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4. 每个阶段:阶段名 + 主导过程的极简描述(短语化)
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5. 是否有分支 / 平行路径 / 反馈环
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6. 是否需要标注高温区 / 风险区 / 关键反应区等局部强调
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7. 标签语言(中文 / 英文 / 双语;论文图通常英文)
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8. 比例(默认横向 16:9;机制图也常见 4:3)
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## 主模板:中心对象 + 多阶段转化 + 结果区
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📖 描述
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中心是研究对象的简化示意(颗粒 / 分子结构 / 器件 / 反应体系),周围以"阶段化转化路径"展开:从初始态经过若干中间机制阶段到达最终结果区。所有连接以学术克制风格的箭头表达,禁止戏剧化效果(无火焰、无浓烟、无炫光)。
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📝 提示词
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```json
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{
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"type": "学术机理示意图(mechanism / pathway figure)",
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"goal": "生成一张可直接放进工程类或自然科学论文正文的机制示意图,强调因果路径清晰、学术克制、可单色印刷可读",
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"canvas": {
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"aspect_ratio": "{argument name=\"aspect_ratio\" default=\"16:9\"}",
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"background": "pure white #FFFFFF",
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"outer_padding": "60px around the diagram",
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"render_quality": "vector-clean look, anti-aliased edges, sharp text"
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},
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"title_caption": {
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"figure_label": "{argument name=\"figure_label\" default=\"Figure X.\"}",
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"caption": "{argument name=\"caption\" default=\"Schematic of the proposed mechanism.\"}",
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"position": "bottom-center, italic serif or compact sans-serif, smaller font size"
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},
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"central_object": {
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"label": "{argument name=\"object_label\" default=\"Biomass particle\"}",
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"depiction": "{argument name=\"object_depiction\" default=\"a simplified cross-sectional sketch of a porous biomass particle, line-art style, no photo realism\"}",
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"position": "horizontally centered, occupying roughly 25-35% of canvas width",
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"style": "thin line-art / engineering schematic, no 3D, no shading, no hyperreal texture"
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},
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"stages": {
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"count": "{argument name=\"stage_count\" default=\"5\"}",
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"items": [
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{
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"id": "M1",
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"name": "{argument name=\"stage_1_name\" default=\"Drying\"}",
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"summary": "{argument name=\"stage_1_summary\" default=\"moisture evaporation under heating\"}",
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"highlight": "{argument name=\"stage_1_highlight\" default=\"none\"}"
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},
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{
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"id": "M2",
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"name": "{argument name=\"stage_2_name\" default=\"Pyrolysis\"}",
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"summary": "{argument name=\"stage_2_summary\" default=\"thermal decomposition releasing volatiles\"}",
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"highlight": "{argument name=\"stage_2_highlight\" default=\"reaction zone\"}"
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},
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{
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"id": "M3",
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"name": "{argument name=\"stage_3_name\" default=\"Volatile Combustion\"}",
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"summary": "{argument name=\"stage_3_summary\" default=\"gas-phase combustion of released volatiles\"}",
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"highlight": "{argument name=\"stage_3_highlight\" default=\"high-temperature region\"}"
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||||
},
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{
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"id": "M4",
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||||
"name": "{argument name=\"stage_4_name\" default=\"Char Oxidation\"}",
|
||||
"summary": "{argument name=\"stage_4_summary\" default=\"surface oxidation of the remaining char\"}",
|
||||
"highlight": "{argument name=\"stage_4_highlight\" default=\"none\"}"
|
||||
},
|
||||
{
|
||||
"id": "M5",
|
||||
"name": "{argument name=\"stage_5_name\" default=\"Emission Formation\"}",
|
||||
"summary": "{argument name=\"stage_5_summary\" default=\"formation of NOx, CO, particulate matter\"}",
|
||||
"highlight": "{argument name=\"stage_5_highlight\" default=\"emission risk region\"}"
|
||||
}
|
||||
]
|
||||
},
|
||||
"result_region": {
|
||||
"enabled": "{argument name=\"result_region_enabled\" default=\"true\"}",
|
||||
"label": "{argument name=\"result_region_label\" default=\"Outcome\"}",
|
||||
"items": "{argument name=\"result_region_items\" default=\"temperature distribution, combustion efficiency, emission characteristics\"}",
|
||||
"position": "rightmost block or bottom-right region, visually separated from stages but stylistically consistent"
|
||||
},
|
||||
"stage_block_style": {
|
||||
"shape": "rounded rectangle (corner radius ~6px) OR stage label + leader line directly attached to the central object",
|
||||
"size_per_stage": "consistent across all stages",
|
||||
"fill": "very light tint (e.g. #F1F5F9, #ECFEFF) — at most 2 different tints; use a low-saturation warm tint (e.g. #FEF3C7) only for stages whose 'highlight' is non-none",
|
||||
"border": "1.2px solid dark gray #334155",
|
||||
"title_text": "stage name in bold sans-serif (Helvetica / Inter / Arial / PingFang / Source Han Sans for CJK), 11-12pt",
|
||||
"summary_text": "single phrase, 9-10pt regular, no full sentence, no period"
|
||||
},
|
||||
"connectors": {
|
||||
"style": "thin arrows (1.2px) with simple triangle arrowheads, dark gray #334155",
|
||||
"rule": "connect stages in causal / temporal order, no crossing, no decorative curves; only label arrows when carrying a named quantity (e.g. 'heat flux', 'O2', 'volatiles')",
|
||||
"feedback_loop": {
|
||||
"enabled": "{argument name=\"feedback_loop\" default=\"false\"}",
|
||||
"rule": "if true, add one curved dashed arrow looping back, labeled e.g. 'self-propagating heat'"
|
||||
}
|
||||
},
|
||||
"highlight_strategy": {
|
||||
"rule": "for stages whose 'highlight' is non-none, apply ONLY a subtle low-saturation tint background (e.g. #FEF3C7 for high-temperature; #FEE2E2 for emission risk). NEVER use flames, smoke, glow, lens flare, or 3D heat-map effects",
|
||||
"max_highlighted_stages": 2
|
||||
},
|
||||
"constraints": {
|
||||
"must_keep": [
|
||||
"central object visually anchors the figure; stages radiate or flow outward in a stable reading order",
|
||||
"white background, no gradient, no decorative pattern",
|
||||
"color palette ≤ 3 main colors, must remain readable in grayscale print",
|
||||
"only sans-serif typography, no script / handwritten / display fonts",
|
||||
"stage labels are short phrases, never full sentences",
|
||||
"the figure must look like it came from a journal article, not a popular-science illustration",
|
||||
"all arrows aligned, no crossings unless the mechanism genuinely requires it"
|
||||
],
|
||||
"avoid": [
|
||||
"exaggerated flames, smoke, sparks, glow, lens flare, motion blur",
|
||||
"3D rendering, metallic highlights, glossy fills",
|
||||
"cartoon mascots, emoji, decorative icons, hand-drawn wobble",
|
||||
"photo-realistic photography of equipment, products, or scenery",
|
||||
"marketing poster aesthetics, magazine cover aesthetics",
|
||||
"fabricated numbers, equations, or chemical formulas not provided by the user",
|
||||
"saturated brand-style colors (no neon, no vivid)",
|
||||
"watermarks, copyright stamps, vendor logos"
|
||||
]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### 参数策略
|
||||
|
||||
- **必问**:`object_label` / `object_depiction`、阶段名、阶段顺序
|
||||
- **可默认**:`aspect_ratio`(16:9)、`background`(白色)、`figure_label` / `caption`、配色 tint
|
||||
- **可随机**:每个 stage 的 `summary` 措辞(用户给了大意可学术化润色)、`highlight` 是否启用(无明确说明时默认 none)
|
||||
|
||||
### 自动补全策略
|
||||
|
||||
- 用户给出现象名 + 阶段数但没说每阶段细节 → 反问,**禁止编造不存在的物理 / 化学过程**
|
||||
- 用户给出阶段名但没给摘要 → 用学术化短语补全(保持 ≤6 词)
|
||||
- 用户没说有没有反馈环 → 默认 `feedback_loop: false`
|
||||
- 用户说"中文论文 / 答辩" → 切换标签为中文 + 字体 PingFang / 思源黑
|
||||
|
||||
## 变体 1:左 → 中 → 右 三段式因果链
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "三段式因果链机制图",
|
||||
"modify": {
|
||||
"layout": "左侧 = 初始条件 / 触发因素;中间 = 多阶段转化机制;右侧 = 最终结果 / 表征",
|
||||
"rule": "三段之间用粗一些的分隔留白(视觉分组),但保持统一描边和字体;左右两侧文字精炼到 ≤4 项",
|
||||
"use_case": "需要清晰区分'起因 → 过程 → 结果'的机制图,例如'生物质燃烧 → 多阶段反应 → 排放与残炭'"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:燃烧 / 反应工程、退化老化、损伤演化、临床因果通路(学术风)。
|
||||
|
||||
## 变体 2:循环 / 自激发机制
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "循环自激发机制图",
|
||||
"modify": {
|
||||
"layout": "阶段排成环形,箭头沿环顺时针方向;中央写出循环驱动力或关键中间产物",
|
||||
"annotation": "环上选 1-2 个箭头加 dashed 样式标注 'positive feedback' / 'self-propagating'",
|
||||
"use_case": "正反馈机制、自催化反应、慢性退化循环"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:自催化、链式反应、热失控、慢性炎症通路。
|
||||
|
||||
## 变体 3:多分支竞争路径
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "多分支竞争机制图",
|
||||
"modify": {
|
||||
"layout": "中心对象向外分出 2-3 条平行路径,每条代表一种竞争性机制;末端各自连到不同的结果区",
|
||||
"annotation": "每条路径起点处标注控制条件(temperature / O2 partial pressure / pH 等)",
|
||||
"use_case": "需要表达'相同前体在不同条件下走不同机制'的对比型机理图"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:路径选择性反应、相分离、不同温度区间下的反应主导机制。
|
||||
|
||||
## 避免事项
|
||||
|
||||
- 用渲染感火焰 / 浓烟 / 爆炸 / 炫光来"装专业" → 立刻沦为营销插画
|
||||
- 阶段块大小不一、字号混乱、字体混用衬线 + 无衬线
|
||||
- 用 emoji 或卡通图标当阶段图示
|
||||
- 用饱和 / 霓虹 / 渐变背景代替克制工程色
|
||||
- 把不存在的化学方程、物理常数、温度数值塞进图里(**严格禁止虚构数据**)
|
||||
- 把"机制示意图"画成完整设备剖视图(应该用 `scientific-schematic.md`)
|
||||
- 把对比 / 多工况结果(应该用 `multi-condition-comparison.md`)混进机制图
|
||||
+264
@@ -0,0 +1,264 @@
|
||||
# 论文方法 Pipeline 总览图模板
|
||||
|
||||
本文件用于生成"论文 method 章节首页那张总览图":
|
||||
|
||||
- 顶会论文 method 章节首图(CVPR / NeurIPS / ICLR / ACL / SIGGRAPH 等)
|
||||
- 系统总览 / pipeline figure
|
||||
- 综述论文 framework 概念图
|
||||
- 实验装置 / 数据流总览
|
||||
- 答辩 PPT 方法概览
|
||||
|
||||
特征:
|
||||
|
||||
- 横向 3-6 个 stage 块
|
||||
- 每个 stage 之间有清晰的有向数据流
|
||||
- 每个 stage 有:阶段名称 + 简化插图 + 输入 / 输出小标
|
||||
- 整体白底 / 浅灰底,黑色或深灰主线条
|
||||
- 出版物字体(Helvetica / Inter / Arial),克制的辅助色
|
||||
- **极简、几何精确、可单色印刷可读**
|
||||
|
||||
## 适用范围
|
||||
|
||||
- 论文 method overview / framework figure
|
||||
- 综述论文 pipeline 总览
|
||||
- 系统总览图("我们的方法分 4 步:...")
|
||||
- 数据流 / 信号流总览
|
||||
- 实验流程总览
|
||||
|
||||
## 何时使用
|
||||
|
||||
- 用户提到 "论文 / paper / method / pipeline / framework / overview / 综述 / 顶会 / arXiv"
|
||||
- 用户希望视觉「极简、白底、黑线、几何精确、像 CVPR 论文那种总览图」
|
||||
- 用户已有具体的 stage 描述
|
||||
|
||||
不要使用:
|
||||
|
||||
- 用户要的是「神经网络架构图」(layer 块 + tensor shape)→ 用 `academic-figures/neural-network-architecture.md`
|
||||
- 用户要的是「概念 / 原理示意图」(自由度高的科学示意)→ 用 `academic-figures/scientific-schematic.md`
|
||||
- 用户要的是「步骤教程」(插画感、温暖)→ 用 `infographics/step-by-step-infographic.md`
|
||||
- 用户要的是「工程系统架构图」(暗色 + 半透明色块)→ 用 `technical-diagrams/system-architecture.md`
|
||||
- 用户要的是「业务流程图」 → 用 `technical-diagrams/flowchart-decision.md`
|
||||
|
||||
## 缺失信息优先提问顺序
|
||||
|
||||
1. 方法 / 系统的总名称(写在图标题或图注里)
|
||||
2. 阶段数(建议 3-6 个,超过 6 个考虑分层)
|
||||
3. 每个阶段的:名称 + 主操作 + 输入 + 输出
|
||||
4. 数据形态(图像 / 文本 / 点云 / 音频 / 多模态)—— 决定 stage 内的简化插图
|
||||
5. 是否有跳连 / 反馈环 / 多分支
|
||||
6. 比例(横向 16:9 或 2:1,符合论文双栏格式)
|
||||
7. 是否需要英文标签(论文图通常英文)
|
||||
|
||||
## 主模板:横向 N 阶段方法 pipeline 图
|
||||
|
||||
📖 描述
|
||||
|
||||
整张图横向流动:从最左边的输入开始,依次经过 3-6 个矩形 / 圆角矩形阶段块,每个块内有简化插图 + 阶段名 + 输入输出小标,箭头串联,最右边输出结果。整体克制、对齐严格、几何精确。
|
||||
|
||||
📝 提示词
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "学术论文方法 Pipeline 总览图(method overview figure)",
|
||||
"goal": "生成一张可直接放进顶会论文 method 章节首页的 pipeline 总览图,要求极简、白底、几何精确、出版物级可读",
|
||||
"canvas": {
|
||||
"aspect_ratio": "{argument name=\"aspect_ratio\" default=\"16:9\"}",
|
||||
"background": "pure white #FFFFFF or very light gray #FAFAFA",
|
||||
"outer_padding": "60px around the diagram",
|
||||
"render_quality": "vector-clean look, anti-aliased edges, sharp text"
|
||||
},
|
||||
"title_caption": {
|
||||
"figure_label": "{argument name=\"figure_label\" default=\"Figure 1.\"}",
|
||||
"caption": "{argument name=\"caption\" default=\"Overview of our proposed pipeline.\"}",
|
||||
"position": "bottom-center, italic serif or compact sans-serif, smaller font size"
|
||||
},
|
||||
"input": {
|
||||
"label": "{argument name=\"input_label\" default=\"Input Image\"}",
|
||||
"thumbnail": "{argument name=\"input_thumbnail\" default=\"a small representative thumbnail (e.g. an RGB image, a text snippet, a point cloud)\"}",
|
||||
"position": "leftmost, vertically centered"
|
||||
},
|
||||
"stages": {
|
||||
"count": "{argument name=\"stage_count\" default=\"4\"}",
|
||||
"items": [
|
||||
{
|
||||
"id": "S1",
|
||||
"name": "{argument name=\"stage_1_name\" default=\"Feature Extractor\"}",
|
||||
"icon_or_glyph": "{argument name=\"stage_1_glyph\" default=\"a stack of 3 small horizontal bars representing CNN feature maps\"}",
|
||||
"sub_label": "{argument name=\"stage_1_sub\" default=\"ResNet-50\"}"
|
||||
},
|
||||
{
|
||||
"id": "S2",
|
||||
"name": "{argument name=\"stage_2_name\" default=\"Multi-scale Encoder\"}",
|
||||
"icon_or_glyph": "{argument name=\"stage_2_glyph\" default=\"a small triangle / pyramid representing multi-scale\"}",
|
||||
"sub_label": "{argument name=\"stage_2_sub\" default=\"FPN-style\"}"
|
||||
},
|
||||
{
|
||||
"id": "S3",
|
||||
"name": "{argument name=\"stage_3_name\" default=\"Cross-attention Decoder\"}",
|
||||
"icon_or_glyph": "{argument name=\"stage_3_glyph\" default=\"two interleaved arrows representing cross-attention\"}",
|
||||
"sub_label": "{argument name=\"stage_3_sub\" default=\"Transformer\"}"
|
||||
},
|
||||
{
|
||||
"id": "S4",
|
||||
"name": "{argument name=\"stage_4_name\" default=\"Prediction Head\"}",
|
||||
"icon_or_glyph": "{argument name=\"stage_4_glyph\" default=\"a small grid representing dense prediction\"}",
|
||||
"sub_label": "{argument name=\"stage_4_sub\" default=\"MLP × 2\"}"
|
||||
}
|
||||
]
|
||||
},
|
||||
"output": {
|
||||
"label": "{argument name=\"output_label\" default=\"Predicted Mask\"}",
|
||||
"thumbnail": "{argument name=\"output_thumbnail\" default=\"a small representative output (e.g. a segmentation mask, a 3D model, a generated image)\"}",
|
||||
"position": "rightmost, vertically centered"
|
||||
},
|
||||
"stage_block_style": {
|
||||
"shape": "rounded rectangle (corner radius ~6px)",
|
||||
"size_per_stage": "around 120px wide × 80px tall, all stages identical size",
|
||||
"fill": "very light tint (e.g. #F1F5F9, #ECFEFF, #FEF9C3) — at most 2 different tints used to group stages by category",
|
||||
"border": "1.2px solid dark gray #334155",
|
||||
"title_text": "stage name in bold sans-serif (Helvetica / Inter / Arial), 11-12pt, top-center inside block",
|
||||
"icon_position": "centered inside block, takes ~50% of block height",
|
||||
"sub_label_text": "sub-label in italic gray, below stage name"
|
||||
},
|
||||
"connectors": {
|
||||
"style": "thin black arrows (1.2px) with simple triangle arrowheads",
|
||||
"rule": "horizontal flow left → right; small label above arrow only when carrying intermediate data type (e.g. 'feature map H/4 × W/4 × 256')",
|
||||
"skip_connections": {
|
||||
"enabled": "{argument name=\"skip_connections\" default=\"false\"}",
|
||||
"rule": "if true, draw curved arrows that arc above the main flow with dashed style, label them 'skip' / 'residual'"
|
||||
}
|
||||
},
|
||||
"extras": {
|
||||
"loss_branch": {
|
||||
"enabled": "{argument name=\"loss_branch_enabled\" default=\"false\"}",
|
||||
"label": "{argument name=\"loss_branch_label\" default=\"L = L_cls + λ L_reg\"}",
|
||||
"rule": "if enabled, draw a small dashed branch from output back to a 'Loss' box, formula in italic"
|
||||
},
|
||||
"color_legend": {
|
||||
"enabled": "{argument name=\"color_legend_enabled\" default=\"false\"}",
|
||||
"rule": "if multiple stage tints are used, add a tiny legend bottom-right explaining each color group"
|
||||
}
|
||||
},
|
||||
"constraints": {
|
||||
"must_keep": [
|
||||
"all stage blocks identical size and vertically aligned",
|
||||
"white or near-white background, no gradient, no decoration",
|
||||
"only sans-serif typography, no script / handwritten / display fonts",
|
||||
"color palette ≤ 4 colors total, must remain readable in grayscale print",
|
||||
"input thumbnail and output thumbnail same size, both have a thin border",
|
||||
"arrows must not overlap stage blocks; labels must not collide with arrows",
|
||||
"use English labels by default unless user requested otherwise",
|
||||
"the figure should look like it came directly from a CVPR / NeurIPS PDF"
|
||||
],
|
||||
"avoid": [
|
||||
"3D effects, drop shadows, gradients, glossy fills",
|
||||
"cartoon icons, emoji, hand-drawn wobble",
|
||||
"saturated colors (no neon, no vivid)",
|
||||
"Helvetica + serif mixed in same diagram",
|
||||
"decorative background patterns / textures",
|
||||
"illustrative photo backgrounds inside stage blocks",
|
||||
"stage blocks of unequal size or unaligned baselines",
|
||||
"Chinese mixed with English labels unless explicitly bilingual"
|
||||
]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### 参数策略
|
||||
|
||||
- **必问**:`stage_count`、每个 stage 的名称
|
||||
- **可默认**:`aspect_ratio`(16:9)、`background`(白色)、`figure_label` / `caption`、stage 块尺寸 / 颜色
|
||||
- **可随机**:每个 stage 内的 `icon_or_glyph` 具体造型(用户没指定时可推断)
|
||||
|
||||
### 自动补全策略
|
||||
|
||||
- 用户给出方法名和"我有 4 个 stage"但没说每 stage 是什么 → 反问(不能瞎编算法细节)
|
||||
- 用户给出 stage 名但没给 sub_label → 留空或自动推断(可推断时填上 "ResNet-50" 这种典型选项)
|
||||
- 用户没说有没有跳连 → 默认 `skip_connections: false`
|
||||
- 用户没说有没有 loss → 默认 `loss_branch: false`(只在用户明确要 training pipeline 时才加)
|
||||
- 用户说"中文论文" / "答辩" → 切换标签为中文 + 字体 PingFang / 思源黑
|
||||
|
||||
## 变体 1:双行多分支 pipeline
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "双行多分支 pipeline 图",
|
||||
"modify": {
|
||||
"layout": "上下两行 stages 平行流动;中间用 fusion block 汇合",
|
||||
"use_case": "多模态融合方法(如 visual + text,或 RGB + depth)",
|
||||
"rule": "上行处理一种模态、下行处理另一种,最后中央汇合到 fusion block 再到输出"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:多模态、双流网络、teacher-student 方法。
|
||||
|
||||
## 变体 2:训练 + 推理两套 pipeline 对照
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "Training vs Inference 对照 pipeline 图",
|
||||
"modify": {
|
||||
"layout": "上下两行:上行 'Training Phase'(含 loss、ground truth 输入、梯度回流),下行 'Inference Phase'(仅前向、轻量化)",
|
||||
"annotation": "左侧用大括号标 'Training' / 'Inference'",
|
||||
"use_case": "需要明确区分训练和推理流程的方法"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:知识蒸馏、自监督预训练、半监督方法。
|
||||
|
||||
## 变体 3:迭代 / Recurrent pipeline
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "迭代式 / 循环 pipeline 图",
|
||||
"modify": {
|
||||
"layout": "stages 横向,但最后一个 stage 有一条曲线箭头回到第二个 stage,形成循环",
|
||||
"annotation": "在循环箭头上标 'iterate × N' 或 'until convergence'",
|
||||
"use_case": "迭代优化、扩散去噪、Diffusion model timestep 流"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:扩散模型、迭代细化方法、能量模型。
|
||||
|
||||
## 变体 4:工程类技术路线图(左 / 中 / 右 三段式)
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "工程类技术路线图(engineering research roadmap)",
|
||||
"modify": {
|
||||
"layout": "左 / 中 / 右 三段式:左侧 = 研究对象与背景(简化线稿示意),中间 = 多步骤分析路径(4-7 个学术化模块),右侧 = 输出与结果导向(3-4 个短语化结论方向)",
|
||||
"rule": "三段宽度比约 2:5:2;左右两侧用学术化短语 + 简化线稿,禁止商业图标 / 写实渲染 / 火焰浓烟特效;中间分析路径模块大小统一、对齐严格、连接关系简洁",
|
||||
"tone": "更接近高质量 Graphical Abstract 与方法路线图融合的工程论文图,不是 office 流程框图,也不是商业海报",
|
||||
"stage_naming_examples_for_engineering": [
|
||||
"fuel / material characterization",
|
||||
"kinetics / thermodynamics analysis",
|
||||
"experimental setup OR numerical model",
|
||||
"boundary / operating condition design",
|
||||
"process simulation or experiment",
|
||||
"field / behavior evaluation",
|
||||
"emission / performance analysis"
|
||||
],
|
||||
"color_palette": "deep blue / slate blue / charcoal as main; one low-saturation amber accent for high-temperature or risk modules ONLY when user signaled it; ≤ 3 main colors total",
|
||||
"data_authenticity": "if no real data is provided, do NOT invent equations, kinetic constants, temperature values, emission factors, or chart numbers; render module summaries as qualitative phrases only",
|
||||
"use_case": "能源动力 / 燃烧 / 热能工程 / 环境工程 / 材料 / 化工 等工程方向的开题答辩、综述论文、Methods 章节首图;区别于 CS/CV pipeline 的横向 stage 块结构"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:能源动力、燃烧、热能工程、环境工程、化工、材料等工程方向的研究路线图与高质量 Graphical Abstract 融合需求;CS/CV/ML 类首选主模板。
|
||||
|
||||
## 避免事项
|
||||
|
||||
- 用渐变 / drop shadow / 玻璃质感 → 立刻 "PPT 风" 而不是论文风
|
||||
- stage 块大小不一 / 高度不齐
|
||||
- 用 emoji / 卡通图标当 stage glyph
|
||||
- 用 Comic Sans / 手写体当标题字体
|
||||
- 颜色超过 4 种或饱和度过高
|
||||
- 输入输出缩略图分辨率明显不同
|
||||
- 箭头穿过 stage 块或标签碰撞
|
||||
- 中英文标签混用(除非显式双语)
|
||||
- 把"对比方法"也画在同一 pipeline 上(应该用 `qualitative-comparison-grid.md`)
|
||||
- 把网络层细节(卷积核大小、激活函数)塞进 pipeline 图(这属于 `neural-network-architecture.md` 的范畴)
|
||||
+218
@@ -0,0 +1,218 @@
|
||||
# 多工况 / 多条件结果对比图模板
|
||||
|
||||
本文件用于生成「同一研究对象在不同工况 / 条件 / 组别下的多面板结果对比图」:
|
||||
|
||||
- 不同温度 / 压力 / 浓度 / 配比 / 时间下的实验或仿真结果
|
||||
- 不同处理组 / 对照组 / 工艺方案的并列结果
|
||||
- 多面板 (a)(b)(c)(d) 形式的论文 result figure
|
||||
|
||||
特征:
|
||||
|
||||
- 2×2 / 1×3 / 1×4 等统一网格布局
|
||||
- **所有 panel 严格统一**:相同尺寸、相同色彩逻辑、相同图例、相同字体层级、相同边距
|
||||
- 白底、低饱和工程色,论文结果图风格
|
||||
- **无真实数据时只做定性表达,禁止虚构数值 / 等值线 / 色标范围**
|
||||
|
||||
## 适用范围
|
||||
|
||||
- 工程 / 物理 / 化学 / 能源 / 材料 / 环境方向的多工况结果对比
|
||||
- 燃烧 / 流场 / 温度场 / 应力场 / 浓度场 等场图对比
|
||||
- 不同处理组 / 不同剂量 / 不同时间点 的实验对照
|
||||
- 同一指标在多个 condition 下的多面板可视化
|
||||
|
||||
## 何时使用
|
||||
|
||||
- 用户提到「多工况 / 多条件 / 不同 X 下的对比 / panel (a)(b)(c)(d) / 结果对比图」
|
||||
- 用户希望视觉「论文 result figure,不是营销信息图」
|
||||
- 比较的是**同一对象在不同条件下的同类结果**
|
||||
|
||||
不要使用:
|
||||
|
||||
- 用户要的是「不同方法在同一样本上的输出对比」(行=样本,列=方法) → 用 `academic-figures/qualitative-comparison-grid.md`
|
||||
- 用户要的是「单个 publication-ready 图表」(bar / line / scatter) → 用 `academic-figures/publication-chart.md`
|
||||
- 用户要的是「营销 / 信息图风格的二元对比」 → 用 `infographics/comparison-infographic.md`
|
||||
|
||||
## 缺失信息优先提问顺序
|
||||
|
||||
1. 比较对象是什么(同一现象 / 同一指标)
|
||||
2. 比较的是哪些工况 / 条件(建议 2-6 个;超过 6 个考虑分两张图)
|
||||
3. 每个 panel 显示的是什么(场图 / 折线 / 柱图 / 等值线 / 显微图)—— 必须**所有 panel 同类型**
|
||||
4. 是否有真实数据(**关键**:决定是定性图还是定量图)
|
||||
5. 网格布局(2×2 / 1×3 / 1×4 / 2×3)
|
||||
6. 标签语言(中文 / 英文 / 双语)
|
||||
7. 共享图例 / 共享色标(强烈建议共享)
|
||||
|
||||
## 主模板:N panel 多工况对比(统一规格)
|
||||
|
||||
📖 描述
|
||||
|
||||
整张图按统一网格分割成 N 个 panel,每个 panel 展示同一类结果在不同工况下的表现。所有 panel 共享色标 / 图例 / 字体层级 / 边距。子图标记为 (a)(b)(c)(d),标签简短克制。**绝对不允许每个 panel 自成一套风格。**
|
||||
|
||||
📝 提示词
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "学术多工况结果对比图(multi-condition comparison figure)",
|
||||
"goal": "生成一张可直接放进论文 results 章节的多面板对比图,要求所有 panel 严格统一、白底、低饱和工程色、可单色印刷可读",
|
||||
"canvas": {
|
||||
"aspect_ratio": "{argument name=\"aspect_ratio\" default=\"4:3\"}",
|
||||
"background": "pure white #FFFFFF",
|
||||
"outer_padding": "50px around the grid",
|
||||
"inter_panel_gap": "16-20px, identical horizontal and vertical",
|
||||
"render_quality": "vector-clean look, anti-aliased, sharp text"
|
||||
},
|
||||
"title_caption": {
|
||||
"figure_label": "{argument name=\"figure_label\" default=\"Figure X.\"}",
|
||||
"caption": "{argument name=\"caption\" default=\"Comparison of results under varying conditions.\"}",
|
||||
"position": "bottom-center, italic serif or compact sans-serif, smaller font size"
|
||||
},
|
||||
"grid_layout": {
|
||||
"rows": "{argument name=\"rows\" default=\"2\"}",
|
||||
"cols": "{argument name=\"cols\" default=\"2\"}",
|
||||
"panel_count": "{argument name=\"panel_count\" default=\"4\"}",
|
||||
"rule": "rows × cols == panel_count; all panels identical size; consistent vertical and horizontal alignment"
|
||||
},
|
||||
"panels": {
|
||||
"panel_type": "{argument name=\"panel_type\" default=\"contour-field\"}",
|
||||
"panel_type_options": "contour-field | line-chart | bar-chart | heatmap | micrograph | flow-field | bubble-chart",
|
||||
"rule": "ALL panels MUST share the same panel_type; never mix bar with line within the same comparison figure",
|
||||
"items": [
|
||||
{
|
||||
"id": "(a)",
|
||||
"condition_label": "{argument name=\"panel_a_label\" default=\"Condition A\"}",
|
||||
"condition_detail": "{argument name=\"panel_a_detail\" default=\"e.g. excess-air ratio λ = 1.0\"}"
|
||||
},
|
||||
{
|
||||
"id": "(b)",
|
||||
"condition_label": "{argument name=\"panel_b_label\" default=\"Condition B\"}",
|
||||
"condition_detail": "{argument name=\"panel_b_detail\" default=\"e.g. excess-air ratio λ = 1.2\"}"
|
||||
},
|
||||
{
|
||||
"id": "(c)",
|
||||
"condition_label": "{argument name=\"panel_c_label\" default=\"Condition C\"}",
|
||||
"condition_detail": "{argument name=\"panel_c_detail\" default=\"e.g. excess-air ratio λ = 1.4\"}"
|
||||
},
|
||||
{
|
||||
"id": "(d)",
|
||||
"condition_label": "{argument name=\"panel_d_label\" default=\"Condition D\"}",
|
||||
"condition_detail": "{argument name=\"panel_d_detail\" default=\"e.g. excess-air ratio λ = 1.6\"}"
|
||||
}
|
||||
]
|
||||
},
|
||||
"panel_style": {
|
||||
"frame": "thin border 1px #1F2937 OR clean axis lines without outer frame, applied identically to all panels",
|
||||
"label_position": "(a) (b) (c) (d) at top-left of each panel, bold sans-serif, 11pt",
|
||||
"condition_label_position": "centered above each panel OR inside each panel top-right, identical position across all panels",
|
||||
"axis_labels": "shared if possible; if shown, identical font size, identical tick density across panels",
|
||||
"internal_titles": "AVOID per-panel decorative titles; rely on (a)(b)(c)(d) + condition label only"
|
||||
},
|
||||
"shared_legend": {
|
||||
"enabled": "{argument name=\"shared_legend_enabled\" default=\"true\"}",
|
||||
"position": "{argument name=\"shared_legend_position\" default=\"right-of-grid\"}",
|
||||
"rule": "single legend / colorbar shared across ALL panels; never give each panel its own legend with different range",
|
||||
"colorbar_range": "{argument name=\"colorbar_range\" default=\"qualitative-low-to-high\"}",
|
||||
"colorbar_range_rule": "if user provided a numerical range, use it; otherwise render as a qualitative gradient labeled 'low → high' with NO fabricated numerical ticks"
|
||||
},
|
||||
"color_logic": {
|
||||
"rule": "≤ 3 main colors total; if a sequential colormap is used, choose a perceptually uniform low-saturation engineering colormap (e.g. viridis-like, blue-to-orange, gray-to-deep-blue); apply the SAME colormap and SAME range to every panel",
|
||||
"must_print_grayscale_readable": true
|
||||
},
|
||||
"data_authenticity": {
|
||||
"user_provided_real_data": "{argument name=\"has_real_data\" default=\"false\"}",
|
||||
"rule_when_false": "render the panels as QUALITATIVE schematics: smooth gradient fields, generic shapes, no numerical tick labels on the colorbar, no specific values in axes; explicitly avoid the visual impression of a real dataset",
|
||||
"rule_when_true": "use the user-provided values; never extrapolate, interpolate, or invent additional values"
|
||||
},
|
||||
"constraints": {
|
||||
"must_keep": [
|
||||
"all panels identical size, identical aspect, identical position scheme",
|
||||
"shared color logic and shared legend across all panels",
|
||||
"white background, no gradient backdrop, no decorative pattern",
|
||||
"(a)(b)(c)(d) labels in identical position and identical style across all panels",
|
||||
"only sans-serif typography, identical font family across all panels",
|
||||
"the figure should look like it came from a results section of an engineering or science journal"
|
||||
],
|
||||
"avoid": [
|
||||
"different colormap or different color range per panel",
|
||||
"different chart type per panel (e.g. mixing bar and line)",
|
||||
"decorative panel titles, hero panel that visually dominates the rest",
|
||||
"saturated brand colors, neon, vivid gradients",
|
||||
"3D effects, drop shadows, glossy fills, lens flare",
|
||||
"fabricated numerical tick values, fabricated colorbar ranges, fabricated isolines",
|
||||
"marketing-poster aesthetics, infographic-collage aesthetics",
|
||||
"watermarks, copyright stamps"
|
||||
]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### 参数策略
|
||||
|
||||
- **必问**:`panel_count`、`panel_type`(所有 panel 同一类型)、`has_real_data`
|
||||
- **可默认**:`aspect_ratio`、`grid_layout`(2×2 是最常见)、`shared_legend_enabled`(true)
|
||||
- **可随机**:每个 condition 的 `*_detail` 措辞(用户给了控制变量名时可学术化)
|
||||
|
||||
### 自动补全策略
|
||||
|
||||
- 用户没说有没有真实数据 → **必须先确认**:`has_real_data` = false 时全图走定性渲染
|
||||
- 用户给了不同 condition 但没说每 panel 的具体取值 → 在 condition_detail 里用占位短语(如 `λ = X1`),**不要编造数字**
|
||||
- 用户给了 panel 数但 row × col 不匹配 → 自动选最接近正方的网格(2×2 / 2×3 / 3×3)
|
||||
- 用户说"中文论文 / 答辩" → 切换标签为中文 + 字体 PingFang / 思源黑
|
||||
|
||||
## 变体 1:横向 1×N(适合窄 panel 比较)
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "横向 1×N 多工况对比",
|
||||
"modify": {
|
||||
"layout": "rows = 1, cols = N(建议 N ≤ 4)",
|
||||
"use_case": "panel 内部是窄柱图 / 窄折线,更适合横向铺开;或论文双栏排版需要横向单行"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:单栏 / 双栏论文格式中的横向比较。
|
||||
|
||||
## 变体 2:行列双因子矩阵(M×N)
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "双因子矩阵对比",
|
||||
"modify": {
|
||||
"layout": "rows = M(一种因子的不同水平),cols = N(另一种因子的不同水平)",
|
||||
"rule": "顶部一行写列因子标签,最左一列写行因子标签;panel 内部样式严格统一",
|
||||
"use_case": "需要同时变化两个独立变量(如温度 × 含水率,或时间 × 浓度)"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:双因子实验设计的结果展示,正交试验结果可视化。
|
||||
|
||||
## 变体 3:定性场图渲染(无真实数据)
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "定性场图多工况对比",
|
||||
"modify": {
|
||||
"panel_type": "contour-field",
|
||||
"data_authenticity": {
|
||||
"user_provided_real_data": false,
|
||||
"rule": "render smooth qualitative gradient fields with NO numerical tick labels and NO specific isoline values; the colorbar shows 'low → high' as a qualitative scale only",
|
||||
"intent": "visually communicate 'higher temperature in panel (b)' without claiming any specific value"
|
||||
},
|
||||
"use_case": "答辩 / 开题阶段尚未拿到数据,需要先讲清研究思路时使用"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:示意性结果对比、方法论说明阶段。
|
||||
|
||||
## 避免事项
|
||||
|
||||
- 给每个 panel 用不同 colormap / 不同 range → 直接破坏可比性
|
||||
- 在没有真实数据时画出带具体数值的等值线 / 色标刻度(**严格禁止虚构数据**)
|
||||
- 让某一 panel 视觉权重明显大于其他 panel(不允许"主图 + 辅图"的结构)
|
||||
- 在每个 panel 加独立的装饰性标题
|
||||
- 把不同类型的图(bar / line / contour)混排在同一对比图里
|
||||
- 使用饱和 brand 色或霓虹渐变
|
||||
- 把"对比方法"的逻辑(行=样本×列=方法)误用到本模板(请改用 `qualitative-comparison-grid.md`)
|
||||
- 加水印 / 期刊 logo / 设备品牌标
|
||||
+219
@@ -0,0 +1,219 @@
|
||||
# 神经网络架构图模板
|
||||
|
||||
本文件用于生成"论文中那种神经网络架构图":
|
||||
|
||||
- Transformer / Encoder-Decoder 架构图
|
||||
- U-Net / FPN / 多尺度网络架构
|
||||
- GAN / Diffusion / VAE 架构
|
||||
- Attention 机制示意
|
||||
- 自定义模型架构图
|
||||
|
||||
特征:
|
||||
|
||||
- 多个 layer 块按数据流方向排布(横向或竖向)
|
||||
- 每个 layer 块有:层名 + tensor shape 标注(H × W × C)
|
||||
- 跳连 / residual / attention 连线清晰
|
||||
- 颜色编码不同 layer 类型(Conv / Attention / FC / Norm)
|
||||
- 出版物级,白底克制
|
||||
|
||||
## 适用范围
|
||||
|
||||
- 论文中的 model architecture figure
|
||||
- 综述论文 framework
|
||||
- 答辩 PPT 模型介绍页
|
||||
- 教学 slide 中的网络示意
|
||||
|
||||
## 何时使用
|
||||
|
||||
- 用户提到 "网络架构 / network architecture / model architecture / Transformer / U-Net / GAN / Diffusion / VAE"
|
||||
- 用户希望「层级清晰、tensor shape 标准、跳连一目了然」
|
||||
- 用户希望视觉「论文风、白底、彩色编码 layer 类型」
|
||||
|
||||
不要使用:
|
||||
|
||||
- 用户要的是「方法 pipeline 总览」(多 stage 业务流)→ 用 `academic-figures/method-pipeline-overview.md`
|
||||
- 用户要的是「系统架构图」(前端 + 后端 + DB)→ 用 `technical-diagrams/system-architecture.md`
|
||||
- 用户要的是「数据流向 / ER 图」 → 用 `technical-diagrams/er-diagram.md`
|
||||
- 用户要的是「概念示意 / 注意力可视化」(自由度高)→ 用 `academic-figures/scientific-schematic.md`
|
||||
|
||||
## 缺失信息优先提问顺序
|
||||
|
||||
1. 模型类型(Encoder-Decoder / U-Net / Transformer / GAN / Diffusion / 自定义)
|
||||
2. 主干网络层数 / 每层类型(如「6 层 Transformer encoder + 6 层 decoder + 8 头 attention」)
|
||||
3. Tensor shape(输入分辨率 / 通道数 / 序列长度)
|
||||
4. 是否有跳连 / residual / cross-attention
|
||||
5. 是否有 multi-task / multi-head 输出
|
||||
6. 是否要中文标签(论文图通常英文)
|
||||
7. 比例(横向 16:9 / 2:1,符合论文双栏)
|
||||
|
||||
## 主模板:Transformer / Encoder-Decoder 架构图
|
||||
|
||||
📖 描述
|
||||
|
||||
整张图横向流动:左输入 embedding → 多层 encoder 块 → cross-attention → 多层 decoder 块 → 右输出 head。每个 layer 块标注层类型与 tensor shape,跳连用弧形虚线。
|
||||
|
||||
📝 提示词
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "神经网络架构图(neural network architecture diagram)",
|
||||
"goal": "生成论文级别的网络架构图:层级清晰、tensor shape 标注、跳连分明、可单色印刷可读",
|
||||
"canvas": {
|
||||
"aspect_ratio": "{argument name=\"aspect_ratio\" default=\"16:9\"}",
|
||||
"background": "white #FFFFFF",
|
||||
"outer_padding": "60px"
|
||||
},
|
||||
"model_meta": {
|
||||
"name": "{argument name=\"model_name\" default=\"Our Transformer\"}",
|
||||
"input_spec": "{argument name=\"input_spec\" default=\"Input Image: 224×224×3\"}",
|
||||
"output_spec": "{argument name=\"output_spec\" default=\"Class Logits: 1000\"}"
|
||||
},
|
||||
"layer_groups": {
|
||||
"rule": "use color-coded blocks per layer type — keep palette ≤ 5 muted academic colors",
|
||||
"color_legend": [
|
||||
{ "type": "Embedding / PatchEmbed", "fill": "#E0E7FF", "border": "#6366F1" },
|
||||
{ "type": "Self-Attention", "fill": "#FEE2E2", "border": "#DC2626" },
|
||||
{ "type": "Cross-Attention", "fill": "#FEF3C7", "border": "#D97706" },
|
||||
{ "type": "Feed Forward / MLP", "fill": "#D1FAE5", "border": "#059669" },
|
||||
{ "type": "Norm / Residual", "fill": "#F3F4F6", "border": "#6B7280" }
|
||||
]
|
||||
},
|
||||
"layers": {
|
||||
"count": "{argument name=\"layer_count\" default=\"8\"}",
|
||||
"items": [
|
||||
{ "id": "L1", "type": "Embedding / PatchEmbed", "name": "Patch Embed", "shape": "196×768" },
|
||||
{ "id": "L2", "type": "Norm / Residual", "name": "LayerNorm", "shape": "196×768" },
|
||||
{ "id": "L3", "type": "Self-Attention", "name": "Multi-head Self-Attn (×8)", "shape": "196×768", "annotation": "× N=6 (encoder)" },
|
||||
{ "id": "L4", "type": "Feed Forward / MLP", "name": "FFN", "shape": "196×768" },
|
||||
{ "id": "L5", "type": "Cross-Attention", "name": "Cross-Attn", "shape": "K×768" },
|
||||
{ "id": "L6", "type": "Self-Attention", "name": "Decoder Self-Attn", "shape": "K×768", "annotation": "× N=6 (decoder)" },
|
||||
{ "id": "L7", "type": "Feed Forward / MLP", "name": "FFN", "shape": "K×768" },
|
||||
{ "id": "L8", "type": "Norm / Residual", "name": "Output Head (Linear)", "shape": "K×C" }
|
||||
]
|
||||
},
|
||||
"block_style": {
|
||||
"shape": "rounded rectangle (corner radius 4-6px)",
|
||||
"size_rule": "blocks of same layer type share identical width and height; visually grouped",
|
||||
"border": "1.2px solid (use the type's border color)",
|
||||
"fill": "use the type's fill color (very light tint)",
|
||||
"label_text": "layer name on first line (sans-serif bold 10-11pt) + tensor shape on second line (monospace italic 9pt)",
|
||||
"annotation_text": "if 'annotation' present (e.g. '× N=6'), draw it as a curly brace with label on the right side of the repeated block"
|
||||
},
|
||||
"connections": {
|
||||
"main_flow": {
|
||||
"style": "thin black solid arrows (1.2px), horizontal left → right",
|
||||
"arrowhead": "small filled triangle"
|
||||
},
|
||||
"residual": {
|
||||
"enabled": "{argument name=\"residual_enabled\" default=\"true\"}",
|
||||
"style": "curved dashed arrow arcing above the main flow, label '+' near join",
|
||||
"rule": "draw residual from input of attention block to its output"
|
||||
},
|
||||
"cross_attention": {
|
||||
"enabled": "{argument name=\"cross_attention_enabled\" default=\"true\"}",
|
||||
"style": "horizontal arrow from encoder side feeding into decoder cross-attn, label 'K, V'",
|
||||
"rule": "encoder output is shown as K, V input to decoder cross-attn"
|
||||
}
|
||||
},
|
||||
"extras": {
|
||||
"show_param_count": {
|
||||
"enabled": "{argument name=\"show_params\" default=\"false\"}",
|
||||
"rule": "if true, add parameter count below each major group (e.g. '85M params')"
|
||||
},
|
||||
"highlight_novelty": {
|
||||
"enabled": "{argument name=\"highlight_novelty\" default=\"true\"}",
|
||||
"rule": "if true, surround the user's contributed module with a thicker dashed orange border + label 'Ours' / 'Novel'"
|
||||
}
|
||||
},
|
||||
"constraints": {
|
||||
"must_keep": [
|
||||
"tensor shapes are accurate and labeled in monospace font",
|
||||
"color encodes layer type consistently across the figure",
|
||||
"all layers of the same type have identical block size",
|
||||
"white background, no gradient, no decoration",
|
||||
"all labels in English by default (or all Chinese if explicitly requested), no mixing",
|
||||
"must remain readable when printed in grayscale (rely on shape and label, not color alone)",
|
||||
"novel contribution (if any) is clearly marked"
|
||||
],
|
||||
"avoid": [
|
||||
"3D extruded blocks, drop shadows, glossy fills",
|
||||
"rainbow palette (>5 colors)",
|
||||
"cartoon icons, emoji",
|
||||
"freeform 'art-style' blobs instead of crisp rectangles",
|
||||
"tensor shapes typeset in proportional font",
|
||||
"arrows crossing through blocks",
|
||||
"missing tensor shape labels (the figure is then useless for paper review)",
|
||||
"unlabeled cross-attention (must say K, V)"
|
||||
]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### 参数策略
|
||||
|
||||
- **必问**:`layer_count`、每层的 `type` 和 `shape`
|
||||
- **可默认**:`aspect_ratio`(16:9)、`background`(白)、`color_legend`(默认 5 类配色)、`block_style`
|
||||
- **可随机**:blocks 内每行的精确字号 / padding,annotation 摆放位置
|
||||
|
||||
### 自动补全策略
|
||||
|
||||
- 用户给「我用 Transformer」但没给细节 → 反问关键参数(层数、头数、隐藏维度、序列长度);不要瞎编模型规模
|
||||
- 用户给「U-Net」 → 自动用 contracting + expansive 双臂布局变体(见变体 2)
|
||||
- 用户没说有没有 residual → 默认 `residual_enabled: true`(绝大多数现代网络都有)
|
||||
- 用户没说有没有 novelty → 默认 `highlight_novelty: true`(论文图一般要标自己的贡献)
|
||||
- 用户没说参数量 → 默认 `show_params: false`(除非用户提到模型规模对比)
|
||||
|
||||
## 变体 1:U-Net / FPN 双臂架构
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "U-Net / FPN 双臂架构图",
|
||||
"modify": {
|
||||
"layout": "U 形:左臂下采样(contracting path)+ 中央 bottleneck + 右臂上采样(expansive path),每层之间有水平 skip connection",
|
||||
"annotation": "skip 用横向虚线箭头标注,特征图用渐窄 / 渐宽的矩形示意 spatial 维度变化"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:U-Net、FPN、HRNet、所有 encoder-decoder 分割网络。
|
||||
|
||||
## 变体 2:GAN / Diffusion 双网络对抗 / 多步推理
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "GAN / Diffusion 架构图",
|
||||
"modify": {
|
||||
"layout_gan": "上方 Generator(noise → image)+ 下方 Discriminator(image → real/fake),中间共享生成图像作为 D 的输入",
|
||||
"layout_diffusion": "横向 timestep 序列 t=T → t=0,每个 timestep 是同一个 U-Net 实例,标 't' 嵌入条件"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:GAN 系列、扩散模型、Score-based 模型。
|
||||
|
||||
## 变体 3:Multi-task / Multi-head 输出
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "多任务 / 多头输出架构图",
|
||||
"modify": {
|
||||
"layout": "共享 backbone 在中央 → 右侧分叉成 2-4 个 task head(如 classification head / regression head / segmentation head)",
|
||||
"annotation": "每个 head 旁边标对应 loss 函数和权重 λ"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:多任务学习、检测 + 分割、辅助监督。
|
||||
|
||||
## 避免事项
|
||||
|
||||
- tensor shape 缺失或随便写 → 论文图核心信息没了
|
||||
- 用渐变 / 3D 立方体堆叠 → 像 PPT 不像论文
|
||||
- 颜色 ≥ 6 种 → 失去 layer 类型语义
|
||||
- 没有 residual / cross-attention 标注(如果架构里有)→ 误导读者
|
||||
- 用 Comic Sans / 手写字体
|
||||
- 跳连箭头穿过 layer 块
|
||||
- 同一类 layer 块大小不一致
|
||||
- 中英文标签混用
|
||||
- 把"训练 loss"画进结构图(应该单独一张 training figure 或 caption 里说明)
|
||||
- 在结构图里塞具体超参数表(应该走 table,不进 figure)
|
||||
@@ -0,0 +1,252 @@
|
||||
# Publication-Ready 数据图表模板
|
||||
|
||||
本文件用于生成"论文 / 报告里出现的标准数据图表":
|
||||
|
||||
- Bar chart / grouped bar chart(消融实验、方法对比)
|
||||
- Line chart / 训练曲线(loss / accuracy 随 epoch)
|
||||
- Scatter plot(性能-效率 trade-off)
|
||||
- Box plot / Violin plot(统计分布)
|
||||
- Heatmap(confusion matrix / attention map / 相关性矩阵)
|
||||
|
||||
特征:
|
||||
|
||||
- matplotlib / seaborn / R ggplot2 出版物风
|
||||
- 含坐标轴 + 标签 + 单位 + 图例 + 误差棒 + 显著性标记
|
||||
- 字体 ≥ 10pt(确保打印可读)
|
||||
- 配色克制(≤ 6 色),可单色印刷
|
||||
- 网格线极淡或无
|
||||
|
||||
> ⚠️ 重要免责声明:**本模板生成的是"出版级图表的视觉呈现",不是真实数据可视化**。GPT Image 2 不能保证坐标和数据的精确对应。
|
||||
>
|
||||
> - 如果你需要"展示一张论文图表的样子" / "做封面 / hero 配图" → 用本模板
|
||||
> - 如果你需要"用真实数据生成可发表的图表" → 请用 matplotlib / seaborn / ggplot2 / Plotly
|
||||
|
||||
## 适用范围
|
||||
|
||||
- 论文方法对比 chart 的视觉示例
|
||||
- 教学 slide 中"看一眼这个图就懂"的演示图
|
||||
- Blog / 公众号配图 — "我们的方法在这个 chart 上表现"
|
||||
- 投资人 deck 中的"数据 mock"
|
||||
- 演示用、可视化教学用的图表
|
||||
|
||||
## 何时使用
|
||||
|
||||
- 用户提到 "publication chart / matplotlib 风 / seaborn 风 / 论文图表 / bar chart / line chart / scatter / heatmap / confusion matrix"
|
||||
- 用户希望「白底、克制、可单色、像 NeurIPS 论文那种图表」
|
||||
- 用户**明确知道**这只是视觉呈现,不依赖坐标精度
|
||||
|
||||
不要使用:
|
||||
|
||||
- 用户要的是「真实数据可视化产出」 → 推荐 matplotlib / seaborn / Plotly
|
||||
- 用户要的是「KPI 仪表盘 / 数据回顾」 → 用 `infographics/kpi-dashboard-infographic.md`
|
||||
- 用户要的是「商业 PPT 数据页」 → 用 `slides-and-visual-docs/visual-report-page.md`
|
||||
- 用户要的是「手绘风信息图」 → 用 `infographics/hand-drawn-infographic.md`
|
||||
|
||||
## 缺失信息优先提问顺序
|
||||
|
||||
1. 图表类型(bar / line / scatter / box / violin / heatmap / pie)
|
||||
2. 主题("我们方法在 ImageNet 上的 accuracy vs baselines")
|
||||
3. X 轴和 Y 轴名称 + 单位
|
||||
4. 数据系列数量(单一系列 / 多系列)
|
||||
5. 是否有误差棒、显著性标记 *
|
||||
6. 配色基调(学术克制 / 强调对比 / 黑白单色)
|
||||
7. 图标题 + caption(论文 figure 一般有 caption)
|
||||
|
||||
## 主模板:Publication-Ready Bar Chart(默认)
|
||||
|
||||
📖 描述
|
||||
|
||||
整张图是一张标准学术 bar chart:横轴为方法 / 类别,纵轴为指标,多个方法对比,含误差棒、显著性 *、图例。整体白底,sans-serif 字体,限定配色。
|
||||
|
||||
📝 提示词
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "Publication-Ready Bar Chart(学术出版级条形图)",
|
||||
"goal": "生成视觉呈现一张论文 / 报告中的 bar chart,要求白底、克制、专业、可单色印刷",
|
||||
"canvas": {
|
||||
"aspect_ratio": "{argument name=\"aspect_ratio\" default=\"4:3\"}",
|
||||
"background": "white #FFFFFF",
|
||||
"outer_padding": "60px"
|
||||
},
|
||||
"title": {
|
||||
"text": "{argument name=\"title\" default=\"Accuracy on ImageNet-1K\"}",
|
||||
"position": "top-center, sans-serif bold 13pt",
|
||||
"subtitle": "{argument name=\"subtitle\" default=\"\"}"
|
||||
},
|
||||
"axes": {
|
||||
"x_axis": {
|
||||
"label": "{argument name=\"x_label\" default=\"Method\"}",
|
||||
"categories": [
|
||||
"{argument name=\"cat1\" default=\"ResNet-50\"}",
|
||||
"{argument name=\"cat2\" default=\"ViT-B\"}",
|
||||
"{argument name=\"cat3\" default=\"Swin-B\"}",
|
||||
"{argument name=\"cat4\" default=\"ConvNeXt-B\"}",
|
||||
"{argument name=\"cat5\" default=\"Ours\"}"
|
||||
],
|
||||
"tick_label_rotation": "0deg or 30deg if labels are long"
|
||||
},
|
||||
"y_axis": {
|
||||
"label": "{argument name=\"y_label\" default=\"Top-1 Accuracy (%)\"}",
|
||||
"range": "{argument name=\"y_range\" default=\"75 to 86\"}",
|
||||
"tick_format": "decimal or percent",
|
||||
"gridlines": "very faint horizontal gridlines (light gray dashed, low opacity)"
|
||||
}
|
||||
},
|
||||
"bars": {
|
||||
"style": "vertical bars, ~30-40% width of category slot, gap between bars",
|
||||
"color_rule": {
|
||||
"default": "use a single muted color for all baselines (e.g. slate blue #64748B), highlight 'Ours' bar in accent color (e.g. orange #D97706 or red #DC2626)",
|
||||
"alternative": "if comparing methods grouped by family, use 2-3 muted colors to encode family"
|
||||
},
|
||||
"value_labels": {
|
||||
"enabled": "{argument name=\"value_labels_enabled\" default=\"true\"}",
|
||||
"rule": "show numeric value above each bar, sans-serif 9pt bold, e.g. '82.3'"
|
||||
}
|
||||
},
|
||||
"error_bars": {
|
||||
"enabled": "{argument name=\"error_bars_enabled\" default=\"true\"}",
|
||||
"style": "thin black T-bar at top of each bar, ±std or ±95% CI",
|
||||
"annotation": "mention what the error represents in caption (e.g. 'error bars show ±1 std over 5 runs')"
|
||||
},
|
||||
"significance_markers": {
|
||||
"enabled": "{argument name=\"significance_enabled\" default=\"false\"}",
|
||||
"rule": "if true, draw thin horizontal brackets between compared bars, with * / ** / *** annotation above (p<0.05 / p<0.01 / p<0.001)"
|
||||
},
|
||||
"legend": {
|
||||
"enabled": "{argument name=\"legend_enabled\" default=\"false\"}",
|
||||
"rule": "only show legend if multiple colors / groups used; place top-right inside or outside the plot area",
|
||||
"items": ["Baselines", "Ours"]
|
||||
},
|
||||
"caption": {
|
||||
"enabled": "{argument name=\"caption_enabled\" default=\"true\"}",
|
||||
"label": "{argument name=\"figure_label\" default=\"Figure 3.\"}",
|
||||
"text": "{argument name=\"caption_text\" default=\"Top-1 accuracy on ImageNet-1K. Our method outperforms all baselines while using fewer parameters. Error bars show ±1 std over 5 runs.\"}",
|
||||
"style": "below the chart, italic serif or compact sans-serif, justified, smaller font"
|
||||
},
|
||||
"constraints": {
|
||||
"must_keep": [
|
||||
"white background, no gradient, no pattern fills",
|
||||
"sans-serif fonts only (Helvetica / Inter / Arial); axis tick labels ≥ 9pt, axis labels ≥ 11pt, title ≥ 13pt",
|
||||
"color palette ≤ 6 colors, must remain readable in grayscale",
|
||||
"all axes have labels and units",
|
||||
"no 3D bar effects, no perspective tilt",
|
||||
"if multiple bars per category, group them with consistent spacing",
|
||||
"Ours bar is visually distinguishable (color or annotation)"
|
||||
],
|
||||
"avoid": [
|
||||
"rainbow colors / saturated palette",
|
||||
"3D extruded bars / pie charts (3D distorts perception)",
|
||||
"missing axis labels or units",
|
||||
"unreadable tick labels (too small or rotated awkwardly)",
|
||||
"decorative background images / textures",
|
||||
"emoji / cartoon icons inside or around bars",
|
||||
"value labels overlapping bars or each other",
|
||||
"random / irrelevant accent colors",
|
||||
"fake precision: don't render bar heights to imply real numbers — keep it clearly illustrative"
|
||||
]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### 参数策略
|
||||
|
||||
- **必问**:图表类型(如果不是 bar)、`title`、`x_label` / `y_label` / 单位、`categories`
|
||||
- **可默认**:`aspect_ratio`(4:3)、`background`(白)、`error_bars_enabled`(true)、`value_labels_enabled`(true)、`legend_enabled`(false 单系列时)
|
||||
- **可随机**:bar 宽度、tick 数量、网格线密度(在合理范围)
|
||||
|
||||
### 自动补全策略
|
||||
|
||||
- 用户给"我有 5 个方法的 accuracy 对比" → 自动用 default 5 categories,highlight 最后一个为 Ours
|
||||
- 用户没指定 y_range → 推断(基于数值范围 ± 5%)
|
||||
- 用户没说 error → 默认开启 error_bars(论文标准做法)
|
||||
- 用户没说 significance → 默认关闭(除非是统计学论文)
|
||||
- 用户说"不是 bar" → 切换到对应变体
|
||||
|
||||
## 变体 1:Line Chart(训练曲线 / 时间序列)
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "Publication-Ready Line Chart(学术出版级折线图)",
|
||||
"modify": {
|
||||
"x_axis_typical": "epoch / step / time / iteration",
|
||||
"y_axis_typical": "loss / accuracy / metric",
|
||||
"lines_count": "1-5 series, each a different muted color",
|
||||
"line_style": "solid 1.5px main line + optional shaded area (semi-transparent same color) for std band",
|
||||
"markers": "optional small markers at sparse intervals (circles / triangles), not on every point",
|
||||
"legend": "always enabled for multi-series, top-right or below",
|
||||
"rule_extra": "axes can be log-scale if data spans orders of magnitude (label as 'log scale')"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:训练曲线、time series 趋势、ablation 随超参变化、scaling laws。
|
||||
|
||||
## 变体 2:Scatter Plot(trade-off 图)
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "Publication-Ready Scatter Plot(学术出版级散点图)",
|
||||
"modify": {
|
||||
"typical_use": "performance vs efficiency trade-off (e.g. accuracy vs FLOPs / latency / params)",
|
||||
"x_axis_typical": "compute / params / latency (often log scale)",
|
||||
"y_axis_typical": "accuracy / metric",
|
||||
"point_style": "filled circles, size encodes a third dimension (e.g. model size), color encodes a category (e.g. method family)",
|
||||
"label_each_point": "small text label next to each point with method name (no leader lines unless crowded)",
|
||||
"ours_emphasis": "Our method points are larger and use accent color + black border",
|
||||
"frontier_line": "optional: draw a Pareto frontier curve to show 'we push the frontier'"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:性能-效率 trade-off、参数 vs 准确率、Pareto frontier。
|
||||
|
||||
## 变体 3:Heatmap(confusion matrix / attention map / 相关性)
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "Publication-Ready Heatmap(学术出版级热力图)",
|
||||
"modify": {
|
||||
"grid": "N × N(默认 5×5 至 10×10)",
|
||||
"color_map": "sequential — viridis / Blues / Reds / 灰阶;diverging(如相关矩阵)— RdBu_r 红蓝双向",
|
||||
"cell_annotation": "show numeric value inside each cell in monospace, color flips for readability on dark cells",
|
||||
"axes_label": "row labels = ground truth, column labels = predicted(confusion matrix 场景)",
|
||||
"colorbar": "right side vertical colorbar with label and ticks",
|
||||
"rule_extra": "always include colorbar; never use rainbow colormap for sequential data (jet 已被学界淘汰)"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:confusion matrix、attention 权重可视化、相关性矩阵、ablation grid。
|
||||
|
||||
## 变体 4:Box Plot / Violin Plot(统计分布)
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "Publication-Ready Box / Violin Plot(学术出版级分布图)",
|
||||
"modify": {
|
||||
"typical_use": "compare distributions across methods / conditions / groups",
|
||||
"elements": "box (Q1, median, Q3) + whiskers (1.5 IQR) + outlier dots; violin 形状叠加显示密度",
|
||||
"median_line_emphasis": "median 线粗实线,颜色区分 group",
|
||||
"annotation": "可叠加 swarm / strip plot 显示每个数据点",
|
||||
"rule_extra": "如果用 violin,violin 内部仍画 box;不要纯 violin(损失中位数信息)"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:实验重复结果分布、跨数据集 / 跨用户 / 跨条件分布对比。
|
||||
|
||||
## 避免事项
|
||||
|
||||
- 用 3D 柱 / 3D 饼 → 严重不专业
|
||||
- 用彩虹 / jet colormap 表示连续值(学界已抛弃)
|
||||
- 漏掉单位 / 漏掉坐标轴标签
|
||||
- value 标签过小读不清
|
||||
- 没有 caption 或 caption 没解释 error bar
|
||||
- 把 4-5 个不相关 chart 拼一张(应该用 multi-panel figure 模板,每个 sub 图独立)
|
||||
- 假装精确(暗示这是真数据但其实是 illustrative)
|
||||
- 用花哨字体(Comic Sans / 手写体)
|
||||
- 加水印 / 装饰背景
|
||||
- 漏掉图例(多系列必须有)
|
||||
- 多 series 但配色完全相同
|
||||
- 漏掉 Ours 高亮(论文图通常要让 reviewer 一眼看出你的)
|
||||
+224
@@ -0,0 +1,224 @@
|
||||
# 多方法 Qualitative 对比网格模板
|
||||
|
||||
本文件用于生成"论文 qualitative results 对比网格":
|
||||
|
||||
- CV 论文:多方法分割 / 检测 / 生成结果对比
|
||||
- NLP 论文:多方法生成文本对比(截图式)
|
||||
- 3D / 重建论文:多方法重建结果对比
|
||||
- Diffusion / 图像生成论文:不同 prompt × 不同方法的网格
|
||||
- Ablation study 的视觉对比
|
||||
|
||||
特征:
|
||||
|
||||
- 严格的网格:行 = 样本 / 输入,列 = 方法(含 GT 和 Ours)
|
||||
- 列首行有方法名(带 citation)
|
||||
- Ours 列通常加边框 / 高亮
|
||||
- 单元格内容统一(图片 / 文本片段 / heatmap)
|
||||
- 网格之间留细 gap,整体白底
|
||||
- 可附 caption 解释
|
||||
|
||||
## 适用范围
|
||||
|
||||
- 论文 qualitative results section
|
||||
- Ablation study 的视觉对比
|
||||
- 顶会 supplementary 大网格图
|
||||
- 综述论文 method gallery
|
||||
- 答辩 PPT 对比页
|
||||
|
||||
## 何时使用
|
||||
|
||||
- 用户提到 "qualitative / 对比图 / comparison grid / methods comparison / ablation visual"
|
||||
- 用户希望「行=样本、列=方法的标准论文对比网格」
|
||||
|
||||
不要使用:
|
||||
|
||||
- 用户要的是「双产品消费对比」 → 用 `infographics/comparison-infographic.md`
|
||||
- 用户要的是「多人头像网格」 → 用 `avatars-and-profile/character-grid-portrait.md`
|
||||
- 用户要的是「数据图表」 → 用 `academic-figures/publication-chart.md`
|
||||
- 用户要的是「视频帧序列」 → 用 `storyboards-and-sequences/`
|
||||
|
||||
## 缺失信息优先提问顺序
|
||||
|
||||
1. 行数(样本数,建议 3-6 行)
|
||||
2. 列数(方法数,建议 3-6 列,含 Input/GT 和 Ours)
|
||||
3. 每列的方法名(含 citation 引用,如 "Method A [12]")
|
||||
4. 单元格内容类型(RGB 图 / mask / heatmap / 文本片段 / 3D 渲染)
|
||||
5. 是否要 row labels(左侧标"Sample 1 / 2 / ..."或"Easy / Medium / Hard")
|
||||
6. 是否要在某些位置加红框 zoom-in(focus area)
|
||||
7. 是否要 caption 注释
|
||||
|
||||
## 主模板:Qualitative comparison grid (M rows × N cols)
|
||||
|
||||
📖 描述
|
||||
|
||||
整张图是严格的 M×N 网格:每一行是一个样本,每一列是一个方法。最左可加 row labels,最上一行是列首(方法名 + citation)。Ours 列加边框高亮,可在某些 cell 内画红色 zoom-in 框。
|
||||
|
||||
📝 提示词
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "Qualitative Comparison Grid(论文级多方法多样本对比网格)",
|
||||
"goal": "生成一张可直接放进论文 qualitative results 章节的网格对比图,要求严格对齐、清晰列首、Ours 高亮、可单色印刷可读",
|
||||
"canvas": {
|
||||
"aspect_ratio": "{argument name=\"aspect_ratio\" default=\"4:3\"}",
|
||||
"background": "white #FFFFFF",
|
||||
"outer_padding": "40px"
|
||||
},
|
||||
"grid": {
|
||||
"rows": "{argument name=\"rows\" default=\"4\"}",
|
||||
"cols": "{argument name=\"cols\" default=\"5\"}",
|
||||
"cell_size_rule": "all cells identical size; gap between cells 4-6px",
|
||||
"cell_aspect": "{argument name=\"cell_aspect\" default=\"square\"}"
|
||||
},
|
||||
"headers": {
|
||||
"column_headers": {
|
||||
"enabled": true,
|
||||
"items": [
|
||||
{ "id": "C1", "label": "{argument name=\"col1_name\" default=\"Input\"}" },
|
||||
{ "id": "C2", "label": "{argument name=\"col2_name\" default=\"Method A [12]\"}" },
|
||||
{ "id": "C3", "label": "{argument name=\"col3_name\" default=\"Method B [34]\"}" },
|
||||
{ "id": "C4", "label": "{argument name=\"col4_name\" default=\"Method C [56]\"}" },
|
||||
{ "id": "C5", "label": "{argument name=\"col5_name\" default=\"Ours\"}", "highlight": true }
|
||||
],
|
||||
"style": "centered above each column, sans-serif bold 11pt, citations in smaller superscript or in [brackets]"
|
||||
},
|
||||
"row_labels": {
|
||||
"enabled": "{argument name=\"row_labels_enabled\" default=\"true\"}",
|
||||
"items": [
|
||||
"{argument name=\"row1_label\" default=\"Sample 1\"}",
|
||||
"{argument name=\"row2_label\" default=\"Sample 2\"}",
|
||||
"{argument name=\"row3_label\" default=\"Sample 3\"}",
|
||||
"{argument name=\"row4_label\" default=\"Sample 4\"}"
|
||||
],
|
||||
"style": "rotated 90° on the left margin OR placed above each row in italic 10pt"
|
||||
}
|
||||
},
|
||||
"cell_content": {
|
||||
"type": "{argument name=\"content_type\" default=\"rgb_image\"}",
|
||||
"options_explained": {
|
||||
"rgb_image": "natural images / photos",
|
||||
"segmentation_mask": "color-coded mask overlays",
|
||||
"heatmap": "viridis / jet style heatmap",
|
||||
"depth_map": "grayscale or turbo colormap",
|
||||
"text_snippet": "rendered text block in a code-like box",
|
||||
"3d_render": "rendered 3D mesh from a fixed viewpoint",
|
||||
"side_by_side": "two halves: input | result"
|
||||
},
|
||||
"consistency_rule": "all cells in the same row should depict the SAME underlying sample so the comparison is fair"
|
||||
},
|
||||
"highlights": {
|
||||
"ours_column": {
|
||||
"enabled": true,
|
||||
"style": "thicker border 1.5px in deep red / accent color (e.g. #DC2626) around each Ours cell"
|
||||
},
|
||||
"zoom_in_boxes": {
|
||||
"enabled": "{argument name=\"zoom_in_enabled\" default=\"false\"}",
|
||||
"rule": "if true, draw small red rectangles inside cells highlighting interesting regions; same red box appears at the same coordinate across the row to make comparison fair",
|
||||
"callout_style": "optional zoomed crop placed below the row, connected by thin lines"
|
||||
}
|
||||
},
|
||||
"caption": {
|
||||
"enabled": "{argument name=\"caption_enabled\" default=\"true\"}",
|
||||
"label": "{argument name=\"figure_label\" default=\"Figure 4.\"}",
|
||||
"text": "{argument name=\"caption_text\" default=\"Qualitative comparison with state-of-the-art methods. Our method (last column) preserves fine details and reduces artifacts.\"}",
|
||||
"style": "below the grid, italic serif or compact sans-serif, justified, smaller font"
|
||||
},
|
||||
"constraints": {
|
||||
"must_keep": [
|
||||
"all cells identical size and tightly aligned",
|
||||
"white or near-white background, no gradient",
|
||||
"column headers clearly above each column with citation",
|
||||
"Ours column visually distinguished (border / shaded header)",
|
||||
"row content depicts the same sample across all methods",
|
||||
"if zoom-in boxes used, position is identical across the row",
|
||||
"labels in English by default, no mixing with Chinese unless requested",
|
||||
"must remain interpretable in grayscale print"
|
||||
],
|
||||
"avoid": [
|
||||
"different cell sizes between rows / columns",
|
||||
"random colors as cell backgrounds (cells are content, not decoration)",
|
||||
"missing citations on baseline methods",
|
||||
"ours column hidden or unmarked",
|
||||
"rotated cells / tilted layouts (must be axis-aligned)",
|
||||
"decorative emoji / cartoon icons inside cells",
|
||||
"varying content type per row (e.g. one row mask, next row RGB) without explicit row label",
|
||||
"more than 6 cols (becomes unreadable in two-column paper format)"
|
||||
]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### 参数策略
|
||||
|
||||
- **必问**:`rows`、`cols`、每列方法名(含 citation)、`content_type`
|
||||
- **可默认**:`aspect_ratio`(4:3)、`row_labels_enabled`(true)、`caption_enabled`(true)
|
||||
- **可随机**:列间 gap 精确像素、字体大小(在合理范围内)
|
||||
|
||||
### 自动补全策略
|
||||
|
||||
- 用户给 "我有 4 个方法 + ours" → 自动加上 Input 列(成为 5 列:Input / M1 / M2 / M3 / M4 / Ours,共 6 列)
|
||||
- 用户没给 row labels → 默认用 "Sample 1, 2, 3, ..." 或反问是否要分难易度
|
||||
- 用户没给 citation → 提示 "建议加 [n] 引用占位" 而不是擅自编造
|
||||
- 用户说 "ablation study" → 列名改为 "w/o A", "w/o B", "Full" 等消融变体
|
||||
- 用户说 "需要 zoom-in" → 启用 `zoom_in_enabled` 并提示需要标 region 坐标
|
||||
|
||||
## 变体 1:纯文本 NLP qualitative 对比
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "NLP qualitative comparison grid",
|
||||
"modify": {
|
||||
"content_type": "text_snippet",
|
||||
"cell_aspect": "tall rectangle (e.g. 2:3 portrait)",
|
||||
"cell_styling": "monospace font in cell, black text on white, with key tokens highlighted in colored boxes",
|
||||
"row_labels": "input prompt / question 显示在每一行最左",
|
||||
"use_case": "对比多个 LLM / 翻译 / summarization 输出"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:NLP 论文生成结果对比、机器翻译质量对比。
|
||||
|
||||
## 变体 2:分割 mask 多列对比(含彩色 overlay)
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "Segmentation mask comparison grid",
|
||||
"modify": {
|
||||
"content_type": "segmentation_mask",
|
||||
"cell_styling": "RGB image base + 半透明 mask 叠加;每类颜色一致;GT 列与 Ours 列容易对比",
|
||||
"extras": "在 cells 下方可加 'mIoU: 0.78' 等定量指标小字",
|
||||
"color_legend": "图右下角附小图例:颜色 → 类别名"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:语义分割、实例分割、医学影像分割论文。
|
||||
|
||||
## 变体 3:Diffusion / 生成模型 prompt × method 矩阵
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "Generation prompt × method matrix",
|
||||
"modify": {
|
||||
"rows": "different text prompts (left labels show prompt text)",
|
||||
"cols": "different generation methods or different sampling steps",
|
||||
"cell_content": "generated images, all from same prompt across the row",
|
||||
"extras": "可在 ours 列加 '↑ +0.3 CLIP score' 小标"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:扩散模型、文本到图像生成、图像编辑方法对比。
|
||||
|
||||
## 避免事项
|
||||
|
||||
- 单元格大小不一致 → 完全失去对比意义
|
||||
- 缺 citation → 同行评审会扣分
|
||||
- Ours 列没有标记 → 读者不知道哪个是你的
|
||||
- 同一行的样本不一致(这一行第一列是猫,第二列是狗)→ 对比不成立
|
||||
- 添加渐变 / 阴影 / 圆角过大 → 不像论文
|
||||
- 用 emoji 或 cartoon 装饰 → 严重不专业
|
||||
- 列数 > 6 → 论文双栏排版下看不清
|
||||
- 没有 caption → 读者不知道这张图想说什么
|
||||
- zoom-in 框位置在不同 cell 不一致 → 对比不公平
|
||||
+223
@@ -0,0 +1,223 @@
|
||||
# 开题 / 答辩 / 汇报研究总览图模板
|
||||
|
||||
本文件用于生成「开题答辩首页 / 论文汇报首页 / 组会引导页的研究总览图」:
|
||||
|
||||
- 硕博开题答辩首页的研究框架图
|
||||
- 中期 / 终期答辩首页的总览图
|
||||
- 组会 / 学术汇报 PPT 的引导页
|
||||
- Lab 主页 / 课题介绍的研究总览
|
||||
|
||||
特征:
|
||||
|
||||
- 高层级、易读、适合 PPT 一页展示
|
||||
- 5 个核心模块:背景 / 目标 / 研究模块 1 / 研究模块 2 / 预期结果
|
||||
- 白底、低饱和工程色、≤3 主色,**论文图感而非商业咨询路演图**
|
||||
- 文字精炼到短语,禁止文字墙
|
||||
|
||||
## 适用范围
|
||||
|
||||
- 开题 / 中期 / 答辩首页(学术汇报)
|
||||
- 组会引导页 / 课题汇报 / Lab meeting cover
|
||||
- 项目立项书的研究框架图(学术风)
|
||||
- Faculty 个人主页 / Lab 主页的"current research"区块
|
||||
|
||||
## 何时使用
|
||||
|
||||
- 用户提到「开题 / 答辩 / 总览图 / 研究框架 / PPT 首页 / 引导页 / lab 主页」
|
||||
- 用户希望视觉「学术答辩 PPT 首页风,正式克制工程化,不要咨询路演风」
|
||||
- 用户已能给出 5 个左右的核心模块
|
||||
|
||||
不要使用:
|
||||
|
||||
- 用户要的是「期刊投稿 Graphical Abstract」 → 用 `academic-figures/graphical-abstract.md`
|
||||
- 用户要的是「方法 pipeline」 → 用 `academic-figures/method-pipeline-overview.md`
|
||||
- 用户要的是「商业 / 投资人路演封面」 → 用 `slides-and-visual-docs/visual-report-page.md`
|
||||
- 用户要的是「品牌主视觉海报」 → 用 `poster-and-campaigns/brand-poster.md`
|
||||
|
||||
## 缺失信息优先提问顺序
|
||||
|
||||
1. 课题 / 研究主题(写在标题区)
|
||||
2. 答辩类型(开题 / 中期 / 终期 / 组会 / 立项)—— 决定语气与模块构成
|
||||
3. 5 个核心模块的命名(默认是:背景 / 目标 / 研究内容 1 / 研究内容 2 / 预期结果)
|
||||
4. 是否需要主观点 / 关键问题(强烈建议有,写在背景模块下方)
|
||||
5. 是否需要研究对象简化示意(颗粒 / 器件 / 流程 / 系统)
|
||||
6. 标签语言(中文 / 英文 / 双语;中文答辩通常中文为主,可英文副标题)
|
||||
7. 比例(默认 16:9 适配 PPT;4:3 适配旧 PPT 模板)
|
||||
|
||||
## 主模板:上中下三层 + 五模块研究总览
|
||||
|
||||
📖 描述
|
||||
|
||||
整张图按"上方主题 + 中间核心模块 + 下方结果导向"分成三层。中间层包含 4-5 个研究内容模块,呈现层级清晰、对齐严格的学术布局,**绝对不像商业路演 PPT**。
|
||||
|
||||
📝 提示词
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "学术研究总览图(research overview / framework figure for thesis defense)",
|
||||
"goal": "生成一张可直接放进开题答辩 / 论文汇报 PPT 首页的研究总览图,要求正式克制、白底、工程化配色、明显论文图感、绝无商业路演感",
|
||||
"canvas": {
|
||||
"aspect_ratio": "{argument name=\"aspect_ratio\" default=\"16:9\"}",
|
||||
"background": "pure white #FFFFFF",
|
||||
"outer_padding": "60px around the diagram",
|
||||
"render_quality": "vector-clean look, anti-aliased edges, sharp text"
|
||||
},
|
||||
"title_block": {
|
||||
"main_title": "{argument name=\"main_title\" default=\"Research Overview\"}",
|
||||
"subtitle": "{argument name=\"subtitle\" default=\"e.g. thesis topic in one short phrase\"}",
|
||||
"occasion_label": "{argument name=\"occasion_label\" default=\"Thesis Proposal Defense\"}",
|
||||
"position": "top-center, main_title in bold sans-serif 18-22pt, subtitle in regular 12-14pt below, occasion_label in italic gray 10pt at top-right"
|
||||
},
|
||||
"background_section": {
|
||||
"label": "{argument name=\"background_label\" default=\"Background & Problem\"}",
|
||||
"summary": "{argument name=\"background_summary\" default=\"a short phrase stating why this matters and what gap exists\"}",
|
||||
"key_question": "{argument name=\"key_question\" default=\"a single research question, expressed as one sentence ≤ 18 words\"}",
|
||||
"position": "upper-middle band, full width, visually anchored as 'context'"
|
||||
},
|
||||
"objective_section": {
|
||||
"label": "{argument name=\"objective_label\" default=\"Objective\"}",
|
||||
"summary": "{argument name=\"objective_summary\" default=\"a short phrase stating the research goal\"}",
|
||||
"position": "directly below background, narrower than background, centered"
|
||||
},
|
||||
"research_modules": {
|
||||
"count": "{argument name=\"module_count\" default=\"3\"}",
|
||||
"items": [
|
||||
{
|
||||
"id": "RM1",
|
||||
"name": "{argument name=\"module_1_name\" default=\"Characterization\"}",
|
||||
"summary": "{argument name=\"module_1_summary\" default=\"a short phrase stating what is studied / measured\"}",
|
||||
"method_hint": "{argument name=\"module_1_method\" default=\"thermogravimetric analysis\"}"
|
||||
},
|
||||
{
|
||||
"id": "RM2",
|
||||
"name": "{argument name=\"module_2_name\" default=\"Modeling\"}",
|
||||
"summary": "{argument name=\"module_2_summary\" default=\"a short phrase stating the modeling / simulation focus\"}",
|
||||
"method_hint": "{argument name=\"module_2_method\" default=\"CFD combustion model\"}"
|
||||
},
|
||||
{
|
||||
"id": "RM3",
|
||||
"name": "{argument name=\"module_3_name\" default=\"Optimization\"}",
|
||||
"summary": "{argument name=\"module_3_summary\" default=\"a short phrase stating optimization or application focus\"}",
|
||||
"method_hint": "{argument name=\"module_3_method\" default=\"parameter sweep + emission analysis\"}"
|
||||
}
|
||||
],
|
||||
"layout": "horizontal row of equal-width modules in the central band, all modules identical size and identical style"
|
||||
},
|
||||
"expected_outcome_section": {
|
||||
"label": "{argument name=\"outcome_label\" default=\"Expected Outcomes\"}",
|
||||
"items": "{argument name=\"outcome_items\" default=\"3-4 short phrases listing deliverables, e.g. 'kinetics database', 'optimized operating window', 'engineering recommendations'\"}",
|
||||
"position": "bottom band, full width, visually distinct from research_modules but stylistically consistent"
|
||||
},
|
||||
"module_block_style": {
|
||||
"shape": "rounded rectangle (corner radius ~8px) OR stage label + thin underline",
|
||||
"size_per_module": "all modules identical size, vertically aligned",
|
||||
"fill": "very light tint (e.g. #F1F5F9, #ECFEFF) — at most 2 different tints; modules of the same role share the same tint",
|
||||
"border": "1.2px solid #334155",
|
||||
"title_text": "module name in bold sans-serif (PingFang SC / Source Han Sans for CJK; Inter / Helvetica / Arial for english), 13-14pt",
|
||||
"summary_text": "single phrase, 10-11pt regular, 1-2 lines max, no period",
|
||||
"method_hint_text": "italic gray 9-10pt, below summary"
|
||||
},
|
||||
"connectors": {
|
||||
"style": "thin arrows (1.2px) with simple triangle arrowheads, dark gray #334155",
|
||||
"rule": "vertical flow background → objective → modules → outcomes; modules are horizontally parallel (no inter-module arrows unless logically required)",
|
||||
"decoration": "none; no curved arcs, no dashed unless explicitly indicating a feedback loop"
|
||||
},
|
||||
"color_palette": {
|
||||
"rule": "≤ 3 main colors total, drawn from a low-saturation engineering set: deep blue #1E3A8A / slate blue #3B82F6 / charcoal #1F2937; allow ONE low-saturation accent (e.g. amber #F59E0B) for the outcome band only if user signaled emphasis",
|
||||
"must_print_grayscale_readable": true
|
||||
},
|
||||
"typography": {
|
||||
"language": "{argument name=\"language\" default=\"chinese\"}",
|
||||
"rule": "chinese → PingFang SC / Source Han Sans; english → Inter / Helvetica / Arial; bilingual → primary line larger, secondary line smaller and gray",
|
||||
"consistency": "all module titles identical size; all summaries identical size; never mix serif and sans-serif"
|
||||
},
|
||||
"constraints": {
|
||||
"must_keep": [
|
||||
"all research modules identical size, vertically aligned, equal weight",
|
||||
"white background, no gradient, no decorative pattern",
|
||||
"language and font consistent across the entire figure",
|
||||
"summaries are short phrases, never full paragraphs",
|
||||
"the figure must look like the cover slide of an academic defense, not a corporate roadmap or pitch deck",
|
||||
"color palette ≤ 3 main colors, must remain readable in grayscale print"
|
||||
],
|
||||
"avoid": [
|
||||
"consulting / pitch-deck aesthetics, brand campaign aesthetics",
|
||||
"decorative icons, emoji, mascots, hand-drawn wobble",
|
||||
"3D rendering, glossy fills, lens flare, drop shadow blocks",
|
||||
"stock-photo backgrounds, photographic hero images",
|
||||
"fabricated quantitative claims (no '+30% efficiency', '150 samples' unless user provided them)",
|
||||
"saturated brand colors, neon, vivid gradients",
|
||||
"dense text walls; no module summary should exceed 2 lines",
|
||||
"watermarks, copyright stamps, university / lab logos unless explicitly requested"
|
||||
]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### 参数策略
|
||||
|
||||
- **必问**:`main_title`、5 个核心模块(背景 / 目标 / 研究内容 1-N / 预期结果)的命名
|
||||
- **可默认**:`aspect_ratio`(16:9)、`background`(白色)、`color_palette`(深蓝/灰蓝/黑灰)
|
||||
- **可随机**:`method_hint` 措辞(用户给出方法名时可学术化);`occasion_label`(开题 / 中期 / 终期 / 组会)
|
||||
|
||||
### 自动补全策略
|
||||
|
||||
- 用户给出主题但没给模块 → 反问 3-4 个研究模块,**禁止编造研究内容**
|
||||
- 用户给出 `key_question` 超过 18 词 → 主动建议精简或拆成 2 个子问题
|
||||
- 用户没给 expected outcomes → 用占位短语(如 "deliverable 1: ...")并标注待用户补充
|
||||
- 用户说"中文答辩 / 中文 PPT" → `language` 默认中文,主标题中文 + 英文副标题(小一号 + 灰色)
|
||||
|
||||
## 变体 1:中心主题 + 周围模块(辐射式)
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "中心主题 + 周围模块的研究总览",
|
||||
"modify": {
|
||||
"layout": "中央放置研究主题 / 研究对象的简化示意;周围呈环形或四象限放置 4 个研究模块;下方留出预期结果带",
|
||||
"rule": "中央对象占画面 25-30%;周围模块等大、等距、对齐严格",
|
||||
"use_case": "适合系统型 / 平台型课题,研究模块之间是平行而非前后依赖关系"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:平台型课题、综合性课题、研究方向多支并行的总览。
|
||||
|
||||
## 变体 2:左右双栏(左 = 研究内容,右 = 路线 / 时间表)
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "左右双栏研究总览",
|
||||
"modify": {
|
||||
"layout": "左栏 = 研究内容模块(垂直堆叠 3-4 个);右栏 = 时间表 / 路线 / 里程碑(gantt 风极简)",
|
||||
"rule": "左右栏宽度比约 3:2;右栏时间轴用细线 + 节点圆,节点旁标月份或学期",
|
||||
"use_case": "开题答辩需要明确"做什么 + 什么时候做"的项目计划"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:开题答辩、项目立项书需要附进度计划的场景。
|
||||
|
||||
## 变体 3:极简版(只显示研究模块,无 timeline / 无 outcome 带)
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "极简研究总览",
|
||||
"modify": {
|
||||
"layout": "去掉 expected_outcome_section,去掉时间轴;只保留 title + background/key_question + 3-4 个研究模块",
|
||||
"use_case": "组会汇报引导页或 lab meeting cover,只需快速点出'这次要讲什么'"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
适用:组会 / Lab meeting / 课程汇报。
|
||||
|
||||
## 避免事项
|
||||
|
||||
- 把研究总览图画成商业咨询路演风(深色背景 + 大色块 + brand 色) → 立刻"非学术"
|
||||
- 用 emoji / 商业图标 / 卡通插画装饰研究模块
|
||||
- 把研究模块写成完整段落,每个模块超过 2 行 → 视觉拥挤
|
||||
- 在"预期结果"中编造具体百分比 / 数据指标(**严格禁止虚构数据**)
|
||||
- 让某一研究模块明显大于其他(应该等权)
|
||||
- 用饱和 / 渐变 / 玻璃质感装饰背景
|
||||
- 强加学校 / 实验室 logo 或 watermark(除非用户明确要求)
|
||||
- 把方法 pipeline 详细图(应该用 `method-pipeline-overview.md`)塞进总览图中
|
||||
+219
@@ -0,0 +1,219 @@
|
||||
# 概念 / 原理示意图模板
|
||||
|
||||
本文件用于生成"科学概念 / 原理 / 实验装置"示意图:
|
||||
|
||||
- 物理 / 化学 / 生物 实验装置图
|
||||
- 算法 / 数学 概念示意(如 attention 机制、流形、坐标系)
|
||||
- 机制 / 通路 / 过程示意(细胞通路、化学反应)
|
||||
- 教科书风原理图
|
||||
- Nature / Science 综述里的"我们这个领域大概是这样工作的"概念图
|
||||
|
||||
特征:
|
||||
|
||||
- **自由度极高**:每张科学示意图都长得不一样,不像 pipeline / network 那样可被网格化
|
||||
- 极简白底 / 浅灰底
|
||||
- 几何精确:标尺 / 坐标轴 / 角度对齐
|
||||
- 简化但非卡通的风格(科学严谨)
|
||||
- 标注线 + 编号 + 公式
|
||||
- 出版物字体(Helvetica / Inter / Computer Modern 数学公式)
|
||||
|
||||
> 设计判断:**这类图自由度极高、变化丰富,强行 JSON 反而限制构图**。本模板采用「**结构化自然语言提示词 + 关键参数 + 示例**」的混合形式,把控约束但不锁死构图。
|
||||
|
||||
## 适用范围
|
||||
|
||||
- 实验装置示意(光学 / 力学 / 流体 / 化学反应器)
|
||||
- 生物机制 / 通路 / 解剖示意
|
||||
- 算法 / 数学概念可视化(attention / convex set / manifold / 坐标变换)
|
||||
- 物理过程示意(波 / 场 / 粒子轨迹)
|
||||
- 综述论文里"领域 big picture"概念图
|
||||
|
||||
## 何时使用
|
||||
|
||||
- 用户提到 "schematic / illustration / 示意图 / 原理图 / 实验装置 / 机制图 / Nature 风 / 教科书风"
|
||||
- 用户希望"自由构图、白底、几何精确、有学术感"
|
||||
- 用户的内容是「单一概念 / 单一装置 / 单一机制」而非「pipeline / 网络 / 多方法」
|
||||
|
||||
不要使用:
|
||||
|
||||
- 用户要的是「方法 pipeline」(多 stage 流)→ 用 `academic-figures/method-pipeline-overview.md`
|
||||
- 用户要的是「神经网络架构」 → 用 `academic-figures/neural-network-architecture.md`
|
||||
- 用户要的是「数据图表」 → 用 `academic-figures/publication-chart.md`
|
||||
- 用户要的是「手绘卡通示意」 → 用 `infographics/hand-drawn-infographic.md`
|
||||
- 用户要的是「儿童科普」 → 用 `scenes-and-illustrations/picture-book-scene.md`
|
||||
|
||||
## 缺失信息优先提问顺序
|
||||
|
||||
1. 要解释什么概念 / 装置 / 机制?(一句话定义)
|
||||
2. 主体是什么?(中央那个核心实体——分子 / 细胞 / 透镜 / 反应器 / 矩阵 / ...)
|
||||
3. 配套元素?(标注线 / 公式 / 坐标 / 参数)
|
||||
4. 风格倾向(Nature 综述风 / 教科书风 / 顶会论文严肃风 / BioRender 友好风)
|
||||
5. 是否需要数学公式标注?需要的话哪些?
|
||||
6. 是否中英文(默认英文)
|
||||
7. 比例(论文常用 1:1、4:3、16:9)
|
||||
|
||||
## 主模板:科学概念 / 原理示意图(自然语言结构化)
|
||||
|
||||
📖 描述
|
||||
|
||||
整张图围绕一个中心概念 / 装置 / 机制展开,用极简几何元素 + 标注线 + 公式 + 简洁辅助色构成,达到出版物级的清晰度和严谨感。
|
||||
|
||||
📝 提示词(结构化自然语言模板)
|
||||
|
||||
```
|
||||
A scientific schematic illustration in the style of {argument name="reference_style" default="a Nature / Science methods figure"}.
|
||||
|
||||
CORE CONCEPT
|
||||
The figure illustrates: {argument name="core_concept" default="how cross-attention works between a query sequence and a key/value sequence"}.
|
||||
|
||||
CENTRAL SUBJECT
|
||||
The visual centerpiece is {argument name="central_subject" default="a 2D matrix grid representing query × key dot products, with arrows feeding in queries from the left and keys from the top"}.
|
||||
|
||||
SUPPORTING ELEMENTS
|
||||
{argument name="supporting_elements" default="(1) a softmax curve diagram on the right showing how raw scores become attention weights; (2) a small inset showing the resulting weighted sum producing the output"}.
|
||||
|
||||
Each supporting element is positioned with deliberate spacing and connected to the central subject by thin labeled arrows or leader lines.
|
||||
|
||||
ANNOTATIONS
|
||||
- Use leader lines (thin black, no arrowheads or tiny arrowheads) to label specific parts of the central subject.
|
||||
- Each label is in {argument name="label_font" default="11pt sans-serif (Helvetica / Inter / Arial)"}.
|
||||
- {argument name="annotation_count" default="4-6"} labels total — do NOT overcrowd.
|
||||
- Use lowercase italic letters (a, b, c) for sub-figure labels in the top-left of each panel.
|
||||
|
||||
EQUATIONS
|
||||
{argument name="equations_list" default="Show one or two key equations near the relevant region. Use Computer Modern / serif math font, italic variables. Example: Attn(Q,K,V) = softmax(QK^T / √d_k) V"}
|
||||
|
||||
Equations should be small but readable, placed adjacent to the part of the figure they explain (not floating in the corner).
|
||||
|
||||
COLOR PALETTE
|
||||
- Limit total to {argument name="color_count" default="3-4"} muted, academic colors:
|
||||
- {argument name="primary_color" default="deep blue #1E3A8A"} — for the central subject
|
||||
- {argument name="secondary_color" default="warm orange #D97706"} — for the highlighted / contrasting flow
|
||||
- {argument name="neutral_color" default="medium gray #475569"} — for annotation lines and supporting structures
|
||||
- white background, near-white shading for sub-regions
|
||||
- The figure must remain readable when printed in grayscale: rely on shape and labels, not color alone.
|
||||
|
||||
LAYOUT
|
||||
- {argument name="layout_style" default="single-panel, central subject occupies ~60% of the canvas, supporting elements arranged around it"}.
|
||||
- Generous whitespace (~25% of canvas), rigorous alignment to an invisible grid.
|
||||
- Aspect ratio: {argument name="aspect_ratio" default="4:3"}.
|
||||
|
||||
STYLE ENFORCEMENT
|
||||
- Crisp vector-clean lines (no anti-aliasing artifacts, no jitter)
|
||||
- All shapes are geometrically precise (perfect circles, exact angles)
|
||||
- All text typeset, NEVER hand-drawn lettering
|
||||
- Background pure white #FFFFFF or very light gray
|
||||
- NO 3D extrusion, NO drop shadow, NO gradient fill, NO glossy highlight
|
||||
- NO cartoon characters, NO emoji, NO decorative ornaments
|
||||
- Should look like it was generated with TikZ / Inkscape / Adobe Illustrator for a peer-reviewed publication
|
||||
|
||||
CAPTION (optional, drawn below figure)
|
||||
{argument name="caption_text" default="Figure 2. Illustration of the cross-attention mechanism. Queries (Q) attend to keys (K) via scaled dot-product, producing attention weights that aggregate values (V)."}
|
||||
```
|
||||
|
||||
### 参数策略
|
||||
|
||||
- **必问**:`core_concept`、`central_subject` 至少一句话描述
|
||||
- **可默认**:`reference_style`(Nature methods 风)、`color_count`(3-4)、配色三件套(深蓝 + 橙 + 灰)、`label_font`、`aspect_ratio`
|
||||
- **可随机**:annotation 摆放角度、leader line 走向(应避开关键内容)、equations 是否启用
|
||||
|
||||
### 自动补全策略
|
||||
|
||||
- 用户给"我要画 attention 机制示意图"但没说细节 → 自动用 default 给出 cross-attention 示意,问用户是否还需要 self-attention 单独一张
|
||||
- 用户给"光学双缝干涉实验" → central_subject = 双缝挡板 + 屏幕 + 入射光,supporting = 干涉条纹小图 + 公式 d sinθ = mλ
|
||||
- 用户给"细胞 receptor 信号通路" → 用 BioRender 友好风:圆角细胞膜 + 受体 + 配体 + 内部信号链
|
||||
- 用户没给 reference_style:根据领域猜——CV/ML 用 "顶会论文风";生物用 "BioRender / Nature methods 风";物理用 "教科书 + 公式风"
|
||||
- 用户说"我要无英文,全中文" → 切换 label_font 为思源黑 / 宋体 + 公式保留 LaTeX 数学体
|
||||
|
||||
## 变体 1:实验装置示意图(光学 / 化学)
|
||||
|
||||
```
|
||||
Modify the main template:
|
||||
|
||||
CENTRAL SUBJECT
|
||||
A precise schematic of an experimental apparatus, drawn in side view (orthographic projection).
|
||||
|
||||
LAYOUT
|
||||
- Equipment components arranged from left to right along the optical / fluid path:
|
||||
light source / reactant inlet → first optical / chemical element → second element → ... → detector / outlet
|
||||
- Components shown as simplified geometric primitives:
|
||||
- Lasers / lamps: small box with arrows indicating beam direction
|
||||
- Lenses: standard biconvex / planoconvex symbol (two arcs)
|
||||
- Mirrors: thin angled lines with hatching on the back
|
||||
- Reactors: round-bottom flask outline
|
||||
- Detectors: rectangular box with diagonal corner stripes
|
||||
- Beam / fluid path drawn as a thin colored line (e.g. red for light, blue for fluid)
|
||||
|
||||
ANNOTATIONS
|
||||
- Each component labeled with its role and (if relevant) a parameter (e.g. f = 50mm, λ = 532nm)
|
||||
- Arrows show direction of light / flow
|
||||
|
||||
VIBE
|
||||
Like a JOSA / Optics Letters experimental setup figure, or like a chemistry textbook reaction apparatus.
|
||||
```
|
||||
|
||||
适用:光学实验、化学反应装置、流体 / 力学装置、半导体制造流程示意。
|
||||
|
||||
## 变体 2:生物 / 医学机制示意(BioRender 风)
|
||||
|
||||
```
|
||||
Modify the main template:
|
||||
|
||||
CENTRAL SUBJECT
|
||||
A simplified biological structure (cell membrane / cell / tissue / organ / molecule).
|
||||
|
||||
STYLE
|
||||
- BioRender-friendly: rounded organic shapes, slightly stylized but anatomically reasonable
|
||||
- Color-coded biology palette: warm membrane (peach / coral), cool nucleus / organelles (blue / purple), bright signaling molecules (yellow / green)
|
||||
- 3D suggestion via subtle shading (single-direction soft shading, no harsh highlights)
|
||||
|
||||
ANNOTATIONS
|
||||
- Each structure labeled with its biological name (italic Latin / standard nomenclature)
|
||||
- Signaling pathways drawn as arrows with mechanism keywords ("phosphorylation", "binding", "translocation")
|
||||
- If multi-step, number each step and provide a brief side caption
|
||||
|
||||
VIBE
|
||||
Like a Cell / Nature review pathway figure, balanced between scientific accuracy and visual approachability.
|
||||
```
|
||||
|
||||
适用:分子生物学通路、细胞机制、解剖示意、药物作用机制。
|
||||
|
||||
## 变体 3:数学 / 算法概念可视化
|
||||
|
||||
```
|
||||
Modify the main template:
|
||||
|
||||
CENTRAL SUBJECT
|
||||
A mathematical / algorithmic concept rendered as geometry:
|
||||
- vectors as arrows, matrices as grids, functions as curves, manifolds as surfaces
|
||||
- coordinate systems with labeled axes (x, y, z), origin marked
|
||||
|
||||
STYLE
|
||||
- Clean TikZ / Asymptote aesthetic
|
||||
- Heavy use of LaTeX-rendered equations integrated into the figure
|
||||
- Greek letters and mathematical symbols throughout
|
||||
- Sparingly use color — usually 2 colors (black + one accent) to highlight what's being discussed
|
||||
|
||||
ANNOTATIONS
|
||||
- Equation snippets next to relevant geometry
|
||||
- Brief textual descriptions on the side ("optimal transport plan minimizes ...")
|
||||
- Sub-figure labels (a), (b), (c) for multi-panel concept figures
|
||||
|
||||
VIBE
|
||||
Like a figure from "Convex Optimization" by Boyd, or from a SIGGRAPH technical paper.
|
||||
```
|
||||
|
||||
适用:优化理论、几何 / 拓扑、概率分布、信号处理、计算机图形数学基础。
|
||||
|
||||
## 避免事项
|
||||
|
||||
- 卡通化、夸张化的元素 → 失去科学严谨感
|
||||
- 渐变 / 玻璃质感 / drop shadow → 像 PPT 不像论文
|
||||
- 颜色超过 4 种 / 高饱和 / 霓虹色
|
||||
- 公式用非数学字体(必须斜体变量 + serif 数学体)
|
||||
- 中英文混排(除非显式双语)
|
||||
- 装饰性背景纹理 / 图案
|
||||
- 标注线穿过主体 / 标签碰撞
|
||||
- 用 emoji 当生物 / 化学元素图标
|
||||
- 多个互不相关概念塞在一张图(应拆分)
|
||||
- 模糊或低分辨率(论文图必须矢量级清晰)
|
||||
- 自由手绘风的"草图感" → 用 `infographics/hand-drawn-infographic.md` 才对,本模板必须几何精确
|
||||
Reference in New Issue
Block a user