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plot.py

+import argparse, pandas as pd, matplotlib
+matplotlib.use('Agg')
+import matplotlib.pyplot as plt, re, os
+
+def find_avg_row(df):
+    for idx, row in df.iterrows():
+        if any(isinstance(cell, str) and re.search(r'平均值|Average', str(cell)) for cell in row):
+            return idx
+    return df.index[-1]
+
+def extract_values(df):
+    idx = find_avg_row(df)
+    vals = [float(v) for v in df.iloc[idx].dropna().iloc[-4:] if str(v).replace('.', '').isdigit()]
+    if len(vals) != 4:
+        vals = [float(v) for v in df.iloc[-1].dropna().iloc[-4:] if str(v).replace('.', '').isdigit()]
+    if len(vals) != 4:
+        raise ValueError("无法提取4个百分比")
+    return {
+        "Total_throughput": vals[3],
+        "generate_throughput": vals[2],
+        "singel_road_generate_throughput": vals[1],
+        "generate_throughput_without_ttft": vals[0]
+    }
+
+def plot_summary(file_path, output_prefix):
+    xls = pd.ExcelFile(file_path)
+    summary = {}
+    for sheet in xls.sheet_names:
+        try:
+            df = pd.read_excel(xls, sheet_name=sheet, header=None)
+            summary[sheet] = extract_values(df)
+        except Exception:
+            continue
+
+    if not summary:
+        print("❌ 无数据可绘图")
+        return
+
+    labels = ["Total_throughput", "generate_throughput", 
+              "singel_road_generate_throughput", "generate_throughput_without_ttft"]
+    colors = ['#2E5984', '#FF8C42', '#4CB944', '#8C2F39']
+    models = list(summary.keys())
+    x = range(len(models))
+    bar_width = 0.18
+
+    plt.figure(figsize=(max(len(models)*1.2, 12), 8))
+    
+    # 绘制柱状图
+    for i, lab in enumerate(labels):
+        vals = [summary[m][lab] for m in models]
+        offset = (i - 1.5) * bar_width
+        bars = plt.bar([p + offset for p in x], vals, width=bar_width, label=lab, color=colors[i])
+        
+        # 添加带引导线的标注
+        for bar, v in zip(bars, vals):
+            height = bar.get_height()
+            # 引导线起点（柱顶中心）
+            line_start = (bar.get_x() + bar.get_width()/2, height)
+            # 文本位置（柱顶上方5%处）
+            text_pos = (line_start[0], height + max(vals)*0.05)
+            
+            # 绘制引导线
+            plt.plot([line_start[0], text_pos[0]], [line_start[1], text_pos[1]], 
+                    color='gray', linestyle='--', linewidth=0.8, alpha=0.7)
+            
+            # 添加带背景框的文本
+            plt.text(text_pos[0], text_pos[1], f"{v:.1f}%",
+                    ha='center', va='bottom',
+                    fontsize=6,
+                    rotation=60,
+                    bbox=dict(facecolor='white', edgecolor='gray', boxstyle='round,pad=0.2'))
+
+    plt.xticks(x, models, rotation=30, ha='right', fontsize=9)
+    plt.ylabel("Percentage", fontsize=10)
+    plt.title("Throughput Comparison", fontsize=12, pad=20)
+    
+    # 调整图例
+    plt.legend(
+        bbox_to_anchor=(1.02, 1),
+        loc='upper left',
+        fontsize=9,
+        frameon=False
+    )
+    
+    plt.subplots_adjust(right=0.8, bottom=0.15)
+
+    for ext in ['png', 'pdf']:
+        plt.savefig(f"{output_prefix}.{ext}", dpi=300 if ext == 'png' else None, bbox_inches='tight')
+    print(f"✅ 已保存：{output_prefix}.png / .pdf")
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("xlsx_path")
+    parser.add_argument("-o", "--output", default="summary_chart")
+    args = parser.parse_args()
+    plot_summary(args.xlsx_path, args.output)
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