"""主题配置 — 配色、字体、间距、结构几何""" # ── 新增 tokens 的默认值（供旧主题/自定义主题 fallback） ────────────── _LAYOUT_DEFAULTS = { # 字号层级 "cover_title_size": 36, "page_title_size": 16, "chart_subtitle_size": 11, "footer_size": 8, # 幻灯片尺寸 (inches) "slide_w": 13.333, # 16:9 default "slide_h": 7.5, # 结构几何 (inches) "header_y": 0.25, "divider_y": 0.80, "divider_h": 0.015, "content_y": 1.00, "content_h": 5.80, "footer_y": 7.10, # content_w 由 _theme() 自动计算: slide_w - 2 * margin # 表格样式 "table_header_bg": "1F4E79", "table_zebra_even": "F8FAFC", "table_zebra_odd": "FFFFFF", # 图表默认 "chart_default_scheme": "default", } def _theme(base: dict) -> dict: """合并 layout defaults，保证每个 theme 都有完整 tokens""" merged = {**_LAYOUT_DEFAULTS, **base} # table_header_bg 默认跟随 primary if "table_header_bg" not in base: merged["table_header_bg"] = base.get("primary", _LAYOUT_DEFAULTS["table_header_bg"]) # content_w = slide_w - 2 * margin（自动派生） if "content_w" not in base: merged["content_w"] = merged["slide_w"] - 2 * merged.get("margin", 0.6) return merged THEMES = { "midnight": _theme({ "name": "Midnight Executive", "primary": "1E2761", "secondary": "CADCFC", "accent": "E8B931", "bg_dark": "1E2761", "bg_light": "F5F7FA", "card_bg": "FFFFFF", "text_dark": "1E2761", "text_light": "FFFFFF", "text_muted": "8896AB", "border": "E2E8F0", "positive": "10B981", "negative": "EF4444", "header_font": "微软雅黑", "body_font": "微软雅黑", "margin": 0.6, "title_size": 28, "subtitle_size": 18, "body_size": 14, "caption_size": 10, "kpi_size": 44, "chart_default_scheme": "midnight", }), "charcoal": _theme({ "name": "Charcoal Minimal", "primary": "36454F", "secondary": "F2F2F2", "accent": "E8B931", "bg_dark": "36454F", "bg_light": "F8F8F8", "card_bg": "FFFFFF", "text_dark": "212121", "text_light": "FFFFFF", "text_muted": "808080", "border": "E0E0E0", "positive": "10B981", "negative": "EF4444", "header_font": "微软雅黑", "body_font": "微软雅黑", "margin": 0.6, "title_size": 28, "subtitle_size": 18, "body_size": 14, "caption_size": 10, "kpi_size": 44, "chart_default_scheme": "charcoal", }), # ── 新主题（设计源自投行级研报分析 + 行业报告研究） ────────────── "jp_finance": _theme({ "name": "IB Finance", "primary": "1B3D6E", "secondary": "00A5BD", "accent": "C9A84C", "bg_dark": "0F2340", "bg_light": "F4F6FA", "card_bg": "FFFFFF", "text_dark": "1A2744", "text_light": "FFFFFF", "text_muted": "6B7C93", "border": "C8D6E5", "positive": "0B7B3E", "negative": "C0392B", "header_font": "微软雅黑", "body_font": "微软雅黑", "margin": 0.6, "title_size": 28, "subtitle_size": 18, "body_size": 12, "caption_size": 9, "kpi_size": 44, # IB-specific overrides "table_header_bg": "1B3D6E", "chart_default_scheme": "jp_finance", }), "pension_warm": _theme({ "name": "Pension Warm", "primary": "2E5FA3", "secondary": "7BA7BC", "accent": "D4903F", "bg_dark": "1C3557", "bg_light": "F7F4F0", "card_bg": "FDFAF7", "text_dark": "2C3E50", "text_light": "FAFAFA", "text_muted": "7F8C8D", "border": "D5C9B8", "positive": "27AE60", "negative": "E74C3C", "header_font": "微软雅黑", "body_font": "微软雅黑", "margin": 0.6, "title_size": 28, "subtitle_size": 18, "body_size": 12, "caption_size": 9, "kpi_size": 44, "chart_default_scheme": "pension_warm", }), "tech_blue": _theme({ "name": "Tech Blue", "primary": "1565C0", "secondary": "29B6F6", "accent": "00BFA5", "bg_dark": "0A1628", "bg_light": "F0F4FF", "card_bg": "FFFFFF", "text_dark": "102040", "text_light": "E8F1FF", "text_muted": "7A8CA8", "border": "C0D0E8", "positive": "00C896", "negative": "FF4B5C", "header_font": "微软雅黑", "body_font": "微软雅黑", "margin": 0.6, "title_size": 28, "subtitle_size": 18, "body_size": 12, "caption_size": 9, "kpi_size": 44, "chart_default_scheme": "tech_blue", }), "state_red": _theme({ "name": "State Red", "primary": "8B0000", "secondary": "B8860B", "accent": "DAA520", "bg_dark": "5C0000", "bg_light": "FDF8F0", "card_bg": "FFFFFF", "text_dark": "2C1810", "text_light": "FFF8E7", "text_muted": "8C7B6B", "border": "E0CFAA", "positive": "2E6B30", "negative": "8B0000", "header_font": "微软雅黑", "body_font": "微软雅黑", "margin": 0.6, "title_size": 28, "subtitle_size": 18, "body_size": 12, "caption_size": 9, "kpi_size": 44, "chart_default_scheme": "state_red", }), "esg_green": _theme({ "name": "ESG Green", "primary": "1A5C2A", "secondary": "4CAF50", "accent": "8BC34A", "bg_dark": "0D3318", "bg_light": "F1F8F2", "card_bg": "FFFFFF", "text_dark": "1B2B1C", "text_light": "E8F5E9", "text_muted": "5C7A5E", "border": "B8D8BA", "positive": "2E7D32", "negative": "C62828", "header_font": "微软雅黑", "body_font": "微软雅黑", "margin": 0.6, "title_size": 28, "subtitle_size": 18, "body_size": 12, "caption_size": 9, "kpi_size": 44, "chart_default_scheme": "esg_green", }), # ── 研究级主题（Morningstar / 宏观研究风格） ────────────────────── "morningstar": _theme({ "name": "Morningstar Research", "primary": "1D2B3A", # 深石板灰 "secondary": "5A9BD5", # 中蓝 "accent": "E67E22", # 暖橙 "bg_dark": "1A1A2E", "bg_light": "FAFBFC", "card_bg": "FFFFFF", "text_dark": "2C3E50", "text_light": "F8F9FA", "text_muted": "7B8794", "border": "DEE2E6", "positive": "28A745", "negative": "DC3545", "header_font": "微软雅黑", "body_font": "微软雅黑", "margin": 0.6, "title_size": 28, "subtitle_size": 18, "body_size": 11, "caption_size": 9, "kpi_size": 36, "chart_default_scheme": "morningstar", }), "macro_research": _theme({ "name": "Macro Research", "primary": "2C3E50", # 深藏蓝灰 "secondary": "3498DB", # 净蓝 "accent": "95A5A6", # 中性灰（低调） "bg_dark": "1A252F", "bg_light": "F7F9FB", "card_bg": "FFFFFF", "text_dark": "2C3E50", "text_light": "ECF0F1", "text_muted": "95A5A6", "border": "D5D8DC", "positive": "27AE60", "negative": "E74C3C", "header_font": "微软雅黑", "body_font": "微软雅黑", "margin": 0.6, "title_size": 28, "subtitle_size": 18, "body_size": 11, "caption_size": 9, "kpi_size": 36, "chart_default_scheme": "macro_research", }), "dark_pro": _theme({ "name": "Dark Pro", "primary": "00BFFF", "secondary": "7B68EE", "accent": "FFD700", "bg_dark": "080808", "bg_light": "141820", "card_bg": "1E2430", "text_dark": "E0E8F0", "text_light": "FFFFFF", "text_muted": "6880A0", "border": "2A3848", "positive": "00E676", "negative": "FF1744", "header_font": "微软雅黑", "body_font": "微软雅黑", "margin": 0.6, "title_size": 30, "subtitle_size": 20, "body_size": 13, "caption_size": 10, "kpi_size": 48, "chart_default_scheme": "dark_pro", }), } DEFAULT_THEME = THEMES["midnight"] # ── 比例预设 ────────────────────────────────────────────────────────── ASPECT_4_3 = {"slide_w": 10.0, "slide_h": 7.5} ASPECT_16_9 = {"slide_w": 13.333, "slide_h": 7.5} def resolve_theme(theme, aspect_ratio=None) -> dict: """解析主题参数，确保所有 tokens 都有值 Args: theme: 主题名称(str) 或主题字典(dict) 或 None aspect_ratio: 可选比例 "4:3" 或 "16:9" Returns: 完整的主题字典（包含所有 layout tokens） """ if isinstance(theme, str): result = dict(THEMES.get(theme, DEFAULT_THEME)) elif isinstance(theme, dict): result = {**DEFAULT_THEME, **theme} else: result = dict(DEFAULT_THEME) if aspect_ratio == "4:3": result.update(ASPECT_4_3) result["content_w"] = result["slide_w"] - 2 * result.get("margin", 0.6) return result