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A题/图像/1模型背景与架构.md

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+DIAGRAM_MACRO_LOGIC
+```mermaid
+graph TD
+  subgraph StageA [Step 1: Data Processing]
+    A1[OCV Fitting]
+  end
+
+  subgraph StageB [Step 2: Core Modeling]
+    B1[Power Map]
+    B2[CPL Closure]
+    B3[Thermal Dynamics]
+  end
+
+  subgraph StageC [Step 3: Application]
+    C1[Scenario Analysis]
+    C2[Uncertainty Quantification]
+    C3[Aging Forecast]
+  end
+
+  StageA --> StageB
+  StageB --> StageC
+```
+
+DIAGRAM_SYSTEM_INTERACTION
+```mermaid
+flowchart LR
+  I1[Screen Brightness L(t)] --> BS[Battery System]
+  I2[CPU Load C(t)] --> BS
+  I3[Network Activity N(t)] --> BS
+  I4[GPS Usage G(t)] --> BS
+  I5[Ambient Temperature T_a(t)] --> BS
+```
+
+DIAGRAM_CPL_LOOP
+```mermaid
+flowchart LR
+  P[Total Power P_tot] --> I[Current I (CPL Solve)]
+  I --> V[Terminal Voltage V_term]
+  V --> P
+```

A题/图像/prompt.md

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+TASK: Generate publication-quality, O-Prize-standard visuals for an MCM/ICM paper on smartphone battery drain. You MUST output the COMPLETE generation code for each required figure (plots + flowcharts/diagrams), plus a single “run-all” entrypoint that reproduces every figure deterministically.
+
+CRITICAL REQUIREMENT (NON-NEGOTIABLE): PRESERVE EXISTING CONTENT INTEGRITY
+- You MUST NOT rewrite, restructure, or renumber ANY existing paper sections or text.
+- You MUST NOT change any existing model equations or definitions.
+- Your job is ONLY to output code + figure manifest + validation checks that produce the visuals.
+- Do NOT output new narrative paragraphs for the paper (captions are allowed only as a separate manifest field).
+
+INPUTS (use only the uploaded files + user-provided data paths):
+A) “Required diagrams list” markdown: defines the figure lineup and intent for Fig 1–15.
+B) Current model/paper markdown: defines variables and equations (z, v_p, T_b, S, w; L, C, N, Ψ, T_a; power mapping; CPL closure; etc.).
+C) Any existing workflow/flowchart markdown (e.g., Mermaid) if provided.
+D) Simulation outputs / datasets: YOU MUST NOT invent filenames. Instead, you must require a user-editable config file to provide file paths.
+
+DETERMINISM REQUIREMENTS:
+- Fix all random seeds (one global seed constant).
+- No dependence on system time.
+- All figures must be reproducible bitwise given identical inputs.
+- Use explicit figure sizes, DPI, font sizes, line widths, and layout parameters.
+- Avoid any “automatic styling” that can vary by environment.
+
+VISUAL QUALITY REQUIREMENTS (O-Prize standard):
+- Export BOTH vector and raster:
+  - Vector: PDF (preferred) or SVG for diagrams.
+  - Raster: PNG at 300+ DPI for embedding.
+- Consistent typography and sizing:
+  - Use a serif family (Times-like), mathtext enabled.
+  - Axis labels with units, readable ticks, uncluttered legends.
+- No chartjunk: remove unnecessary spines, avoid overcrowding, use consistent margins.
+- Every figure must have a clear “message” aligned with the diagram spec.
+
+ALLOWED TOOLS / LIBS (Python):
+- matplotlib (primary plotting)
+- numpy, pandas
+- scipy (curve fitting if needed)
+- graphviz (preferred for flowcharts/diagrams via DOT)
+- (Optional) matplotlib 3D for surfaces; must remain deterministic
+
+OUTPUTS YOU MUST PRODUCE (exact order):
+1) FIGURE_MANIFEST_v1 (JSON)
+2) CODE_PACKAGE_v1 (multiple code files; each in its own code fence with file path header)
+3) RUN_INSTRUCTIONS_v1 (plain text; exact commands)
+4) VALIDATION_REPORT_v1 (JSON schema + what each check prints)
+
+────────────────────────────────────────────────────────
+METHODOLOGY (follow exactly)
+────────────────────────────────────────────────────────
+
+STEP 1 — Parse the required figure specification
+- Read the “required diagrams list” markdown and extract Fig 1–15.
+For each figure, store:
+  - fig_id (1..15)
+  - title (verbatim)
+  - intended location/section (if provided)
+  - required chart type (flowchart, 3D surface, stacked area, heatmap, etc.)
+  - required axes/annotations (e.g., ΔTTE arrow, R² > 0.99 display, “95% Confidence TTE” marker)
+Do NOT add or remove figures.
+
+STEP 2 — Define a strict data contract via a user-editable config
+Because you cannot assume filenames, you MUST implement:
+- config/figure_config.yaml
+This YAML must specify input paths for each figure, such as:
+- ocv_samples_csv
+- scenario_trajectories: mapping scenario_name -> csv_path
+- mc_trajectories_path or mc_summary_csv (TTE samples)
+- sensitivity_results_csv or parameter_sweep_csv
+- heatmap_grid_csv (T_a, Ψ, TTE)
+- aging_lifecycle_csv (cycle, SOH, TTE_full)
+- radar_scores_csv (mode, metrics...)
+Each figure script MUST read only its declared inputs from this config.
+
+STEP 3 — Enforce a common plotting style module (single source of truth)
+Create scripts/plot_style.py that:
+- Sets matplotlib rcParams (font family, font size, mathtext, line width, figure dpi for save)
+- Defines helper utilities:
+  - save_figure(fig, out_basepath): writes .pdf and .png (png at >=300 dpi)
+  - format_axes(ax): consistent grid/ticks/spines
+All figure scripts MUST import and use plot_style.py.
+
+STEP 4 — Implement one script per figure (Fig 01 … Fig 15)
+Folder: scripts/figures/
+Naming:
+- fig01_macro_logic_flowchart.py
+- fig02_system_interaction_diagram.py
+...
+- fig15_radar_user_guide.py
+
+Each figure script MUST:
+- Define a single public function: make_figure(config: dict) -> dict
+- Return a dict containing:
+  - output_files: list[str]
+  - computed_metrics: dict (e.g., R², quantiles)
+  - validation_flags: dict[str,bool]
+- Save outputs under figures/ with fixed filenames:
+  figures/Fig01.pdf, figures/Fig01.png, ... figures/Fig15.*
+
+STEP 5 — Required figure-by-figure implementation details
+You MUST implement all figures listed below exactly as specified.
+
+FIG 1 (Macro-Logic Flowchart)
+- Type: diagram/flowchart
+- Tool: Graphviz DOT (preferred) + python wrapper to render
+- Nodes: Data Processing → Core Modeling → Application (must match spec wording)
+- Output: Fig01.pdf + Fig01.png
+
+FIG 2 (System Interaction Diagram)
+- Type: diagram
+- Must show inputs around system: L, C, N, G (GPS proxy), T_a; outputs: TTE, SOH
+- Use Graphviz DOT with clusters: Inputs / Internal Modules / Outputs
+- Output: Fig02.*
+
+FIG 3 (OCV Curve Fitting)
+- Inputs: ocv_samples_csv with columns: z, V_oc_meas
+- Method: Fit to the paper’s chosen OCV form (use the exact OCV function from the paper markdown)
+- Plot: scatter of data + fitted curve line
+- Display: R² in the plot (must meet threshold in validation)
+- Output: Fig03.*
+
+FIG 4 (Internal Resistance Surface)
+- Inputs: either (a) parameterized function R0(T_b,z or S) OR (b) a grid csv with columns (T_b, z, R0)
+- Plot: 3D surface with labeled axes and units
+- Output: Fig04.*
+
+FIG 5 (Tail Energy Illustration)
+- Inputs (preferred): a trajectory csv containing time, N(t), w(t), P_net(t) OR a small synthetic pulse-definition in config
+- Plot: two-panel figure:
+  - Top: data burst indicator (N or packet events)
+  - Bottom: power state persistence (P_net or tail component k_tail*w)
+- Must visually demonstrate “short burst → long tail”
+- Output: Fig05.*
+
+FIG 6 (CPL Avalanche Loop)
+- Type: causal loop diagram
+- Must show: V↓ → I↑ → Loss↑ → V↓↓ (exact concept)
+- Use Graphviz DOT with arrow labels
+- Output: Fig06.*
+
+FIG 7 (Baseline Validation 2×2)
+- Inputs: baseline trajectory csv with columns (t, z, V_term, I, T_b)
+- Plot: 2×2 subplots: SOC, Voltage, Current, Temperature vs time
+- Must visually confirm CPL signature: as V_term declines, I increases (include a note/annotation)
+- Output: Fig07.*
+
+FIG 8 (Power Breakdown Stacked Area)
+- Inputs: baseline trajectory csv with columns (t, P_bg, P_scr, P_cpu, P_net, [P_gps if present])
+- Plot: stacked area of power components vs time
+- Output: Fig08.*
+
+FIG 9 (Scenario Comparison & GPS Impact)
+- Inputs: multiple scenario csvs with columns (t, z) and TTE summary values
+- Plot: overlay 3–4 SOC curves (baseline, video, gaming, navigation)
+- Must annotate ΔTTE due to GPS/navigation with a double-arrow and numeric label
+- Output: Fig09.*
+
+FIG 10 (Tornado Diagram)
+- Inputs: sensitivity_results_csv with columns: parameter_name, low_TTE, base_TTE, high_TTE (or delta)
+- Plot: horizontal tornado bars sorted by absolute impact
+- Must include GPS, signal quality, temperature, brightness (as available)
+- Output: Fig10.*
+
+FIG 11 (Two-Parameter Heatmap)
+- Inputs: heatmap_grid_csv with columns: T_a, Psi, TTE
+- Plot: heatmap (T_a on x, Psi on y) colored by TTE (hours)
+- Output: Fig11.*
+
+FIG 12 (Monte Carlo Spaghetti Plot)
+- Inputs: mc_trajectories file(s) OR a single tidy csv: run_id, t, z
+- Plot: many thin SOC curves + one thick mean curve
+- Use fixed seed only for any sampling/downselection
+- Output: Fig12.*
+
+FIG 13 (Reliability / Survival Curve)
+- Inputs: tte_samples_csv with column: TTE
+- Plot: empirical survival S(t)=P(TTE>t) as a step function
+- Must mark “95% Confidence TTE” = 5th percentile (or specify explicitly) with a vertical line + label
+- Output: Fig13.*
+
+FIG 14 (Lifecycle Degradation)
+- Inputs: aging_lifecycle_csv with columns: cycle_index, SOH, TTE_full
+- Plot: dual-axis (SOH vs cycle, TTE_full vs cycle) with clear legends and units
+- Output: Fig14.*
+
+FIG 15 (User Guide Radar Chart)
+- Inputs: radar_scores_csv with columns: mode, screen, cpu, location, network, experience (or exact metrics listed)
+- Plot: radar comparing “power-saving mode” vs “high-performance mode”
+- Output: Fig15.*
+
+STEP 6 — Add a run-all pipeline
+Create run_all_figures.py that:
+- Loads config/figure_config.yaml
+- Calls each make_figure in numerical order
+- Writes a single artifacts/figure_build_report.json with metrics + flags
+- Exits with non-zero code if any validation fails
+
+STEP 7 — Validation (must be implemented, not just described)
+Each figure must have at least one deterministic validation check:
+- Fig03: R² >= 0.99 (configurable threshold but default 0.99)
+- Fig07: correlation check showing CPL tendency (e.g., corr(V_term, I) < 0 under baseline)
+- Fig09: ΔTTE annotation value matches computed TTE difference within tolerance
+- Fig12: M >= 100 runs unless user sets otherwise
+- Fig13: survival curve starts at 1 and ends near 0; 95% marker equals empirical percentile
+- All plots: output files exist and are non-empty; axis labels present
+
+────────────────────────────────────────────────────────
+DELIVERABLE FORMATS (STRICT)
+────────────────────────────────────────────────────────
+
+1) FIGURE_MANIFEST_v1 (JSON only)
+Schema:
+{
+  "global": {
+    "seed": 12345,
+    "output_dir": "figures",
+    "formats": ["pdf","png"],
+    "dpi_png": 300
+  },
+  "figures": [
+    {
+      "fig_id": 1,
+      "title": "...",
+      "script": "scripts/figures/fig01_....py",
+      "inputs_from_config": ["..."],
+      "outputs": ["figures/Fig01.pdf","figures/Fig01.png"],
+      "caption_suggestion": "..."
+    },
+    ...
+  ]
+}
+
+2) CODE_PACKAGE_v1
+- Output multiple code fences.
+- Each code fence MUST start with a single line comment containing the file path, e.g.:
+  # scripts/plot_style.py
+- Include at minimum:
+  - config/figure_config.yaml (template with placeholders)
+  - scripts/plot_style.py
+  - scripts/config_io.py (loads yaml)
+  - scripts/validation.py (shared checks)
+  - scripts/figures/fig01_*.py … scripts/figures/fig15_*.py
+  - run_all_figures.py
+  - requirements.txt
+
+3) RUN_INSTRUCTIONS_v1 (plain text)
+Must include exact commands:
+- pip install -r requirements.txt
+- python run_all_figures.py
+
+4) VALIDATION_REPORT_v1 (JSON only)
+Schema:
+{
+  "status": "PASS" or "FAIL",
+  "failed_figures": [ ... ],
+  "details": {
+    "Fig03": {"R2": 0.995, "pass": true},
+    ...
+  }
+}
+
+FORBIDDEN:
+- Do NOT modify paper text.
+- Do NOT invent data. If a required input path is missing in config, raise a clear error message and stop.
+- Do NOT output partial scripts; every file must be complete and runnable.
+- Do NOT output any additional commentary outside the four deliverables.
+
+NOW EXECUTE: produce the four deliverables exactly.

A题/图像/论文图表规划与建议.md

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+抱歉，之前的建议虽然精简，但对于追求 **O奖（Outstanding Winner）** 的顶级论文来说，确实还可以进一步丰富，特别是为了展现**建模的每一个细节**和**多维度的分析**。
+
+仔细研读你的《论文结构2.md》后，我为你重新规划了一份 **14-15 张图表** 的完整清单。这份清单的逻辑是：**“每一个关键数学假设都有图验证，每一个关键结论都有图支撑”**。
+
+以下是根据你论文章节顺序排列的详细图表列表：
+
+### ---
+
+**第一部分：模型背景与架构 (Section 1-2)**
+
+*目的：用视觉语言让评委在进入复杂公式前先看懂你的逻辑。*
+
+**Fig 1: The "Macro-Logic" Flowchart (总体思维导图)**
+
+* **位置：** Section 1 (Introduction) 或 Section 2 (Overview)  
+* **内容：** 这是一个大图，展示解决问题的三步走：  
+  1. **Data Processing:** (OCV拟合, 参数提取)  
+  2. **Core Modeling:** (Power Map $\\to$ CPL Feedback $\\to$ Thermal $\\to$ Battery State)  
+  3. **Application:** (Scenario Analysis, UQ, Aging)  
+* **为何需要：** 评委第一眼需要看到你的“作战地图”。
+
+**Fig 2: System Interaction Diagram (系统边界与变量图)**
+
+* **位置：** Section 2 (Assumptions & Notations)  
+* **内容：** 中间是手机（电池），周围环绕着 5 个输入变量 ($L, C, N, G, T\_a$)。箭头指向内部模块，再从内部指由输出 ($TTE, SOH$)。  
+* **为何需要：** 直观展示你的 $u(t)$ 和 $x(t)$ 向量包含什么，特别是高亮你新增的 GPS 模块。
+
+### ---
+
+**第二部分：模型建立细节 (Section 3-5)**
+
+*目的：展示你的模型不是凭空捏造的，而是基于物理和数据的。这是之前版本主要缺失的部分。*
+
+**Fig 3: OCV Curve Fitting (开路电压拟合验证图)**
+
+* **位置：** Section 3 (Battery Model) 或 Section 5 (Parameter Estimation)  
+* **内容：**  
+  * 散点：实验数据点 (Reference Data Points)。  
+  * 实线：你拟合的函数曲线 $V\_{oc}(z) \= \\alpha \+ \\beta z \+ ...$。  
+  * **重点：** 展示拟合的 $R^2 \> 0.99$。  
+* **为何需要：** **这是O奖论文的硬通货。** 证明你的电压模型极其准确，不是随便写个线性公式。
+
+**Fig 4: Internal Resistance Surface (内阻 $R\_0$ 三维曲面图)**
+
+* **位置：** Section 3 (Battery Model)  
+* **内容：** 3D Surface Plot。  
+  * X轴：温度 ($T\_b$)  
+  * Y轴：SOC ($z$)  
+  * Z轴：内阻 ($R\_0$)  
+* **趋势：** 展示低温下内阻急剧升高，低电量下内阻升高。  
+* **为何需要：** 二维图太普通，三维图能瞬间提升模型的“物理复杂度”观感。
+
+**Fig 5: The "Tail Energy" Illustration (网络尾流效应示意图)**
+
+* **位置：** Section 3.1 (Power Mapping \- Network)  
+* **内容：** 时间轴上的脉冲图。  
+  * 上图：数据包传输 (Data Burst) —— 只有一瞬间。  
+  * 下图：功率状态 (Power State) —— 传输完后维持 High Power 一段时间，再降到 Idle。  
+* **为何需要：** 你的模型里提到了 $w(t)$ (Radio tail)，如果不画图，评委很难理解这个微分方程的精妙之处。
+
+**Fig 6: CPL "Avalanche" Loop (恒功率负载反馈机制图)**
+
+* **位置：** Section 3.3 (CPL Closure)  
+* **内容：** 之前提到的闭环反馈图 ($V\\downarrow \\to I\\uparrow \\to Loss\\uparrow \\to V\\downarrow\\downarrow$)。  
+* **为何需要：** 解释为什么最后 10% 电量掉得特别快，这是物理核心。
+
+### ---
+
+**第三部分：仿真与结果分析 (Section 6-8)**
+
+*目的：展示模型运行结果，证明其符合现实规律。*
+
+**Fig 7: Baseline Validation (基准动力学四联图)**
+
+* **位置：** Section 7 (Baseline Results)  
+* **内容：** 2x2 子图 (SOC, Voltage, Current, Temp)。  
+* **细节：** 必须清晰展示 Current 随 Voltage 下降而上升的曲线（CPL特征）。  
+* **为何需要：** 证明模型运行正常，符合基本物理定律。
+
+**Fig 8: Power Breakdown Stacked Area Plot (功率成分堆叠图)**
+
+* **位置：** Section 7 (Baseline Results)  
+* **内容：** 堆叠面积图。
+  * X轴：时间 (0 到 TTE)。
+  * Y轴：功率 (Watts)。
+  * 颜色层：最底层是 $P\_{bg}$，上面是 $P\_{screen}$，再上面是 $P\_{cpu}$。
+* **为何需要：** 让评委直观看到“到底电都去哪儿了”。
+
+**Fig 9: Scenario Comparison & GPS Impact (多场景 TTE 对比图)**
+
+* **位置：** Section 8 (Scenario Analysis)  
+* **内容：** 3-4 条 SOC 下降曲线（基准、视频、游戏、**导航**）。  
+* **标注：** 用双箭头标注出 **GPS 导致的 $\\Delta TTE$**。  
+* **为何需要：** 直接回答题目关于“不同活动影响”的问题。
+
+### ---
+
+**第四部分：高级分析与灵敏度 (Section 9-11)**
+
+*目的：这是拿 O 奖的关键，展示数学深度和不确定性处理。*
+
+**Fig 10: Tornado Diagram (龙卷风图 \- 灵敏度排名)**
+
+* **位置：** Section 9 (Sensitivity Analysis)  
+* **内容：** 横向条形图，展示各参数（屏幕、信号、温度、GPS）对 TTE 的影响幅度。  
+* **为何需要：** 决策者最爱看这种图，一眼看出关键因子。
+
+**Fig 11: Two-Parameter Heatmap (双变量热力图)**
+
+* **位置：** Section 9 (Sensitivity Analysis)  
+* **内容：** 颜色方块图。  
+  * X轴：环境温度 ($T\_a$)，从 \-10°C 到 40°C。  
+  * Y轴：信号质量 ($\\Psi$)，从 0 到 1。  
+  * 颜色：TTE (小时)。  
+* **结论：** 颜色最深区域（低温+弱信号）就是“电池杀手区”。  
+* **为何需要：** 展示变量之间的**耦合效应 (Interaction Effect)**，比单变量分析高级。
+
+**Fig 12: Monte Carlo "Spaghetti Plot" (蒙特卡洛随机路径图)**
+
+* **位置：** Section 10 (Uncertainty Quantification)  
+* **内容：** 100 条灰色的 SOC 曲线叠加，中间有一条加粗的均值线。  
+* **为何需要：** 视觉化展示“不可预测性”，说明你的模型能处理随机波动。
+
+**Fig 13: Reliability / Survival Curve (生存曲线图)**
+
+* **位置：** Section 10 (Uncertainty Quantification)  
+* **内容：** 概率 $P(TTE \> t)$ 随时间下降的阶梯图。  
+* **标注：** 标出 "95% Confidence TTE"。  
+* **为何需要：** 将不确定性转化为**可靠性指标**，回答题目隐含的“用户想知道到底能用多久”的需求。
+
+### ---
+
+**第五部分：长期影响 (Section 11-13)**
+
+*目的：展示时间维度的拓展。*
+
+**Fig 14: Lifecycle Degradation (全生命周期老化图)**
+
+* **位置：** Section 11 (Aging)  
+* **内容：**  
+  * 左轴：SOH (健康度) 随循环次数下降。  
+  * 右轴：满电 TTE 随循环次数下降。  
+* **为何需要：** 证明你的模型不仅能看“一天”，还能看“一年”。
+
+**Fig 15: "User Guide" Radar Chart (用户建议雷达图 \- Optional but Recommended)**
+
+* **位置：** Section 12 (Recommendations)  
+* **内容：** 一个五边形雷达图，对比“省电模式”vs“高性能模式”在不同维度（屏幕、CPU、位置、网络、体验）的得分。  
+* **为何需要：** 将复杂的数学结论转化为给非技术用户的直观建议，非常加分。
+
+### ---
+
+**总结**
+
+现在你有 **15 张图**。
+
+* **逻辑/原理图：** 4 张 (Fig 1, 2, 5, 6\) —— *用 Visio 画*  
+* **物理/拟合图：** 2 张 (Fig 3, 4\) —— *用 Python 画*  
+* **结果/分析图：** 9 张 (Fig 7-15) —— *用 Python 画*
+
+这完全符合一篇 25 页 O 奖论文的体量，图文比例非常完美。你需要我为你生成其中哪些数据图的代码？