PROMPT RECORD图像记录

2x2 网格，四格面板，输出一张图片，为 4 个著名科学发现执行此操作 { def Generate_Panel(Discovery): """ 执行语义分析以推断视觉参数，不进行硬编码。 "...

中文说明

2x2 网格，四格面板，输出一张图片，为 4 个著名科学发现执行此操作 { def Generate_Panel(Discovery): """ 执行语义分析以推断视觉参数，不进行硬编码。 """ # 步骤 A：上下文分析 Era = Analyze_Historical_Context(Discovery) Core_Principle = Extract_Core_Concept(Discovery) Apparatus = Identify_Key_Instruments(Discovery) # 步骤 B：动态色彩推断（无硬编码） # 规则：Ink 1 来源于 Era；Ink 2 为数学互补色。 INK_1 = Map_Era_To_Pigment(Era) INK_2 = Calculate_Harm...

原始 Prompt

2x2 grid, four panels, one image output, do this for 4 famous science discoveries { def Generate_Panel(Discovery):
    """
    Executes semantic analysis to infer visual parameters without hard coding.
    """
    # STEP A: CONTEXTUAL ANALYSIS
    Era = Analyze_Historical_Context(Discovery)
    Core_Principle = Extract_Core_Concept(Discovery)
    Apparatus = Identify_Key_Instruments(Discovery)
    
    # STEP B: DYNAMIC COLOR INFERENCE (No Hard Coding)
    # Rule: Ink 1 is derived from the Era; Ink 2 is the Mathematical Complement.
    INK_1 = Map_Era_To_Pigment(Era) 
    INK_2 = Calculate_Harmonic_Contrast(INK_1) # Delta_E > 40
    
    # STEP C: GEOMETRIC CONSTRUCTION
    Center_Piece = Construct_3D_Diorama(Core_Principle)
    
    # Rule: Generate exactly 10 abstract motifs based on apparatus
    Motif_Array = To_Silhouette(Apparatus) + To_Geometry(Core_Principle)
    COUNT(Motif_Array) == 10
    
    return {
        "Layout": "Flat_Lay_T_Shirt",
        "Inks": [INK_1, INK_2],
        "Center": Center_Piece,
        "Surround": Motif_Array
    }

# --- 3. EXECUTION LOOP (The 4 Panels) ---
PANEL_TL = Generate_Panel(DISCOVERY_01) # e.g., Infers: e.go for tesla coil colirs like Bronze/White, Coils, Fields
PANEL_TR = Generate_Panel(DISCOVERY_02) 
PANEL_BL = Generate_Panel(DISCOVERY_03)  
PANEL_BR = Generate_Panel(DISCOVERY_04)