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