Optimize the Rendering of Inline Formulas, Subscripts and Superscripts, Bubble Charts, and Horizontal Bars
This commit is contained in:
马一丁
@@ -160,6 +160,19 @@ class ChartToSVGConverter:
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if props.get('type'):
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chart_type = props['type']
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# Chart.js v4已移除horizontalBar类型，这里自动降级为bar并设置横向坐标
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horizontal_bar = False
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if chart_type and str(chart_type).lower() == 'horizontalbar':
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chart_type = 'bar'
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horizontal_bar = True
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# 支持通过indexAxis: 'y' 强制横向柱状图
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if isinstance(props, dict):
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options = props.get('options') or {}
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index_axis = (options.get('indexAxis') or props.get('indexAxis') or '').lower()
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if index_axis == 'y':
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horizontal_bar = True
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# 提取数据
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data = widget_data.get('data', {})
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if not data:
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@@ -172,10 +185,16 @@ class ChartToSVGConverter:
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logger.debug("检测到词云图表，跳过chart_to_svg转换")
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return None
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render_method = getattr(self, f'_render_{chart_type}', None)
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if not render_method:
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logger.warning(f"不支持的图表类型: {chart_type}")
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return None
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# 分派渲染方法，特殊处理横向柱状图
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if chart_type == 'bar':
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return self._render_bar(data, props, width, height, dpi, horizontal=horizontal_bar)
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elif chart_type == 'bubble':
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return self._render_bubble(data, props, width, height, dpi)
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else:
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render_method = getattr(self, f'_render_{chart_type}', None)
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if not render_method:
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logger.warning(f"不支持的图表类型: {chart_type}")
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return None
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# 创建图表并转换为SVG
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return render_method(data, props, width, height, dpi)
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@@ -687,9 +706,10 @@ class ChartToSVGConverter:
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props: Dict[str, Any],
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width: int,
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height: int,
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dpi: int
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dpi: int,
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horizontal: bool = False
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) -> Optional[str]:
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"""渲染柱状图"""
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"""渲染柱状图（支持横向barh）"""
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try:
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labels = data.get('labels', [])
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datasets = data.get('datasets', [])
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@@ -703,44 +723,147 @@ class ChartToSVGConverter:
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colors = self._get_colors(datasets)
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# 计算柱子位置
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x = np.arange(len(labels))
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positions = np.arange(len(labels))
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width_bar = 0.8 / len(datasets) if len(datasets) > 1 else 0.6
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# 绘制每个数据系列
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# 横向/纵向绘制
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for i, dataset in enumerate(datasets):
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dataset_data = dataset.get('data', [])
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label = dataset.get('label', f'系列{i+1}')
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color = colors[i]
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offset = (i - len(datasets)/2 + 0.5) * width_bar
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ax.bar(
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x + offset,
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dataset_data,
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width_bar,
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label=label,
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color=color,
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alpha=0.8,
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edgecolor='white',
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linewidth=0.5
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)
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# 设置x轴标签
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ax.set_xticks(x)
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ax.set_xticklabels(labels, rotation=45, ha='right')
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if horizontal:
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ax.barh(
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positions + offset,
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dataset_data,
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height=width_bar,
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label=label,
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color=color,
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alpha=0.8,
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edgecolor='white',
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linewidth=0.5
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)
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else:
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ax.bar(
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positions + offset,
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dataset_data,
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width_bar,
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label=label,
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color=color,
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alpha=0.8,
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edgecolor='white',
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linewidth=0.5
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)
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# 轴标签/网格
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if horizontal:
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ax.set_yticks(positions)
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ax.set_yticklabels(labels)
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ax.invert_yaxis() # 与Chart.js横向排列保持一致
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ax.grid(True, alpha=0.3, linestyle='--', axis='x')
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else:
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ax.set_xticks(positions)
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ax.set_xticklabels(labels, rotation=45, ha='right')
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ax.grid(True, alpha=0.3, linestyle='--', axis='y')
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# 显示图例
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if len(datasets) > 1:
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ax.legend(loc='best', framealpha=0.9)
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# 网格
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ax.grid(True, alpha=0.3, linestyle='--', axis='y')
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return self._figure_to_svg(fig)
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except Exception as e:
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logger.error(f"渲染柱状图失败: {e}")
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return None
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def _render_bubble(
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self,
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data: Dict[str, Any],
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props: Dict[str, Any],
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width: int,
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height: int,
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dpi: int
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) -> Optional[str]:
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"""渲染气泡图"""
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try:
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datasets = data.get('datasets', [])
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if not datasets:
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return None
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title = props.get('title')
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fig, ax = self._create_figure(width, height, dpi, title)
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colors = self._get_colors(datasets)
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def _safe_radius(raw) -> float:
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try:
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val = float(raw)
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return max(val, 0.5)
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except Exception:
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return 1.0
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all_x: list[float] = []
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all_y: list[float] = []
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max_r: float = 0.0
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for i, dataset in enumerate(datasets):
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points = dataset.get('data', [])
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label = dataset.get('label', f'系列{i+1}')
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color = colors[i]
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if points and isinstance(points[0], dict):
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xs = [p.get('x', 0) for p in points]
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ys = [p.get('y', 0) for p in points]
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rs = [_safe_radius(p.get('r', 1)) for p in points]
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else:
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xs = list(range(len(points)))
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ys = points
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rs = [1.0 for _ in points]
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all_x.extend(xs)
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all_y.extend(ys)
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if rs:
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max_r = max(max_r, max(rs))
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# 适度放大半径，近似Chart.js像素尺寸（动态尺度，避免过大遮挡）
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size_scale = 8.0 if max_r <= 20 else 6.5
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sizes = [(r * size_scale) ** 2 for r in rs]
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ax.scatter(
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xs,
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ys,
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s=sizes,
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label=label,
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color=color,
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alpha=0.45,
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edgecolors='white',
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linewidth=0.6
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)
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if len(datasets) > 1:
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ax.legend(loc='best', framealpha=0.9)
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# 适度留白，避免大气泡被裁切
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if all_x and all_y:
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x_min, x_max = min(all_x), max(all_x)
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y_min, y_max = min(all_y), max(all_y)
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x_span = max(x_max - x_min, 1e-6)
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y_span = max(y_max - y_min, 1e-6)
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pad_x = max(x_span * 0.12, max_r * 1.2)
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pad_y = max(y_span * 0.12, max_r * 1.2)
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ax.set_xlim(x_min - pad_x, x_max + pad_x)
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ax.set_ylim(y_min - pad_y, y_max + pad_y)
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# 额外安全边距
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ax.margins(x=0.05, y=0.05)
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ax.grid(True, alpha=0.3, linestyle='--')
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return self._figure_to_svg(fig)
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except Exception as e:
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logger.error(f"渲染气泡图失败: {e}", exc_info=True)
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return None
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def _render_pie(
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self,
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data: Dict[str, Any],
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