基于matplotlib的饼图绘制

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import numpy as np
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import pandas as pd
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from glob import glob
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import matplotlib.pyplot as plt
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import seaborn as sns
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%matplotlib inline
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%config InlineBackend.figure_format='svg'
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fps = glob("out/*.xlsx")
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for fp in fps:
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    df = pd.read_excel(fp, index_col=0)
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    # 将 Frame 转换为 ns
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    df['Time_ns'] = df['Frame'] * 0.1
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    # --- 数据准备：折线图所需数据 ---
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    bin_size_frame = 100
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    df['bin'] = (df['Frame'] // bin_size_frame) * bin_size_frame
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    bin_summary = df.groupby('bin')['inside'].agg(['sum', 'count']).reset_index()
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    bin_summary.rename(columns={'sum': 'true_count', 'count': 'total_count'}, inplace=True)
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    bin_summary['proportion_true'] = bin_summary['true_count'] / bin_summary['total_count']
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    bin_summary['Time_ns'] = bin_summary['bin'] * 0.1
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    # --- 数据准备：饼图所需数据 ---
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    # 筛选 Time_ns >= 100 的数据
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    df_filtered = df[df['Time_ns'] >= 100].copy()
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    if not df_filtered.empty:
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        # 计算 inside 为 True 和 False 的数量
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        inside_counts = df_filtered['inside'].value_counts()
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        # 使用 reindex 确保 'True' 和 'False' 都在索引中，如果缺失则填充 0
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        # 这是解决 KeyError 的关键
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        inside_counts = inside_counts.reindex([True, False], fill_value=0)
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        # 准备圆饼图的数据
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        labels = ['Inside', 'Not Inside']
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        sizes = [inside_counts[True], inside_counts[False]]
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        colors = ["#17e135", "#e14141"] # 可以自定义颜色
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    else:
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        print("没有 Time_ns >= 100 ns 的数据，饼图将为空或显示错误。")
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        labels = []
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        sizes = []
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        colors = []
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    # --- 合并绘图 ---
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    # 创建一个 1 行 2 列的子图布局
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    fig, axes = plt.subplots(1, 2, figsize=(12, 4)) # 调整整体 figure 大小以容纳两个图
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    # 左侧子图：折线图
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    sns.lineplot(data=bin_summary, x='Time_ns', y='proportion_true', marker='o', ax=axes[0])
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    axes[0].set_title(f'Proportion of "inside" over Time (bin size = {bin_size_frame * 0.1} ns)')
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    axes[0].set_xlabel('Time (ns)')
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    axes[0].set_ylabel('Proportion of "inside"')
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    axes[0].set_ylim(-.1, 1.1)
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    axes[0].grid(True, linestyle='--', alpha=0.7)
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    # 右侧子图：饼图
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    if not df_filtered.empty: # 只有在有数据时才绘制饼图
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        axes[1].pie(sizes, labels=labels, colors=colors, autopct='%1.1f%%', startangle=90, explode=(0.05, 0))
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        axes[1].set_title('Proportion of "inside" for Time >= 100 ns')
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        axes[1].axis('equal') # 确保饼图是圆形
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    else:
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        axes[1].text(0.5, 0.5, "No data for Time >= 100 ns", horizontalalignment='center', verticalalignment='center', transform=axes[1].transAxes)
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        axes[1].set_xticks([])
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        axes[1].set_yticks([])
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        axes[1].set_title('Proportion of "inside" for Time >= 100 ns')
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    plt.suptitle(fp.split(".xlsx")[0].split("\\")[1].replace("_results", ""))
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    plt.tight_layout() # 自动调整子图参数，使之紧密地排列在图的区域内
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    plt.show()