import matplotlib.pyplot as pltfrom matplotlib.patches import Wedge, FancyArrowPatchimport numpy as npimport pandas as pdimport random# ================= 从CSV导入数据 =================def load_data_from_csv(top_labels_file, bottom_labels_file, connections_file):    """    从CSV文件加载数据    top_labels.csv 格式: 一列，每行一个标签    bottom_labels.csv 格式: 一列，每行一个标签    connections.csv 格式: start_idx,end_idx,weight,direction    """    # 读取标签    top_df = pd.read_csv(top_labels_file, header=None)    bottom_df = pd.read_csv(bottom_labels_file, header=None)    top_labels = top_df[0].tolist()    bottom_labels = bottom_df[0].tolist()    # 读取连接数据    conn_df = pd.read_csv(connections_file)    # 检查必要的列    required_cols = ['start_idx', 'end_idx', 'weight', 'direction']    if not all(col in conn_df.columns for col in required_cols):        raise ValueError(f"CSV文件必须包含以下列: {required_cols}")    connections = conn_df[required_cols].values.tolist()    return top_labels, bottom_labels, connections# ================= 绘图函数 =================def create_circular_plot(top_labels, bottom_labels, connections,                          top_colors=None, bottom_colors=None,                         R_in=3.0, R_out=4.5, gap=4,                         num_arrows=None, figsize=(14, 14),                         outer_top_label="Characteristics of the airborne plastisphere",                         outer_bottom_label="Planetary health threats"):    """    创建环形连接图    """    # 自动生成颜色（如果未提供）    if top_colors is None:        top_colors = plt.cm.Blues(np.linspace(0.3, 0.9, len(top_labels)))    if bottom_colors is None:        bottom_colors = plt.cm.Reds(np.linspace(0.3, 0.9, len(bottom_labels)))    # 确保颜色数量匹配    if len(top_colors) != len(top_labels):        raise ValueError(f"top_colors长度({len(top_colors)})与top_labels长度({len(top_labels)})不匹配")    if len(bottom_colors) != len(bottom_labels):        raise ValueError(f"bottom_colors长度({len(bottom_colors)})与bottom_labels长度({len(bottom_labels)})不匹配")    # 计算角度    top_start, top_end = gap / 2, 180 - gap / 2    bot_start, bot_end = 180 + gap / 2, 360 - gap / 2    top_angles = np.linspace(top_start, top_end, len(top_labels) + 1)    bot_angles = np.linspace(bot_start, bot_end, len(bottom_labels) + 1)    # 创建图表    fig, ax = plt.subplots(figsize=figsize, dpi=120)    ax.set_aspect('equal')    ax.axis('off')    # 绘制扇区和收集中心角度    top_centers = draw_wedges(ax, top_labels, top_angles, top_colors, True, R_in, R_out)    bot_centers = draw_wedges(ax, bottom_labels, bot_angles, bottom_colors, False, R_in, R_out)    # 绘制外层环标签    draw_outer_rings(ax, top_start, top_end, bot_start, bot_end,                     R_out, outer_top_label, outer_bottom_label)    # 绘制连接    draw_connections(ax, top_centers, bot_centers, connections, R_in, num_arrows)    # 设置坐标轴范围    R_outer_ring_out = R_out + 0.45    ax.set_xlim(-R_outer_ring_out - 0.8, R_outer_ring_out + 0.8)    ax.set_ylim(-R_outer_ring_out - 0.8, R_outer_ring_out + 0.8)    plt.tight_layout()    return fig, axdef draw_wedges(ax, labels, angles, colors, is_top, R_in, R_out):    """绘制扇形区块"""    centers = []    for i in range(len(labels)):        theta1, theta2 = angles[i], angles[i + 1]        mid_theta = (theta1 + theta2) / 2        centers.append(mid_theta)        # 绘制扇区        w = Wedge((0, 0), R_out, theta1, theta2, width=R_out - R_in,                  facecolor=colors[i], edgecolor='white', linewidth=2.5)        ax.add_patch(w)        # 文字放置        mid_rad = np.deg2rad(mid_theta)        rot = mid_theta        if 90 < rot <= 270:            rot += 180        # 自动判断文字颜色        if isinstance(colors[i], str):            # 如果是颜色字符串，简单判断亮度            text_color = 'white' if i >= len(labels) - 2 else 'black'        else:            text_color = 'white' if (is_top and i >= 6) or (not is_top and i >= 5) else 'black'        r_text = (R_in + R_out) / 2        x = r_text * np.cos(mid_rad)        y = r_text * np.sin(mid_rad)        ax.text(x, y, labels[i], ha='center', va='center', rotation=rot - 90,                fontsize=14, color=text_color, fontweight='bold')    return centersdef draw_outer_rings(ax, top_start, top_end, bot_start, bot_end, R_out,                      top_label, bottom_label):    """绘制外层环和标签"""    R_outer_ring_in = R_out + 0.15    R_outer_ring_out = R_out + 0.45    # 上半部分外层环    w_top_outer = Wedge((0, 0), R_outer_ring_out, top_start, top_end,                        width=R_outer_ring_out - R_outer_ring_in,                         facecolor='#A9B1C1', edgecolor='none')    ax.add_patch(w_top_outer)    ax.text(0, R_outer_ring_out + 0.25, top_label,            ha='center', va='bottom', fontsize=14, color='black', fontweight='bold')    # 下半部分外层环    w_bot_outer = Wedge((0, 0), R_outer_ring_out, bot_start, bot_end,                        width=R_outer_ring_out - R_outer_ring_in,                         facecolor='#E39496', edgecolor='none')    ax.add_patch(w_bot_outer)    ax.text(0, -(R_outer_ring_out + 0.25), bottom_label,            ha='center', va='top', fontsize=14, color='black', fontweight='bold')def draw_connections(ax, top_centers, bot_centers, connections, R_in, num_arrows=None):    """根据连接数据绘制箭头"""    # 如果指定了箭头总数，根据权重生成多个箭头    if num_arrows is not None:        # 计算总权重        total_weight = sum(conn[2] for conn in connections)        if total_weight == 0:            return        # 根据权重分配箭头数量        all_arrows = []        for start_idx, end_idx, weight, direction in connections:            n_arrows = max(1, int(num_arrows * weight / total_weight))            for _ in range(n_arrows):                all_arrows.append([start_idx, end_idx, direction])        # 打乱顺序        random.shuffle(all_arrows)        connections_to_draw = all_arrows    else:        # 直接使用connections中的每条记录画一个箭头        connections_to_draw = [[c[0], c[1], c[3]] for c in connections]    # 绘制每个箭头    for start_idx, end_idx, direction in connections_to_draw:        try:            # 获取角度            if direction == 'top_to_bottom':                start_theta = top_centers[start_idx]                end_theta = bot_centers[end_idx]            elif direction == 'top_to_top':                start_theta = top_centers[start_idx]                end_theta = top_centers[end_idx]            elif direction == 'bottom_to_bottom':                start_theta = bot_centers[start_idx]                end_theta = bot_centers[end_idx]            elif direction == 'bottom_to_top':                start_theta = bot_centers[start_idx]                end_theta = top_centers[end_idx]            else:                print(f"警告: 未知的方向 '{direction}'，跳过")                continue        except IndexError as e:            print(f"警告: 索引超出范围 - {e}，跳过")            continue        # 添加随机偏移避免完全重合        start_theta += random.uniform(-3, 3)        end_theta += random.uniform(-3, 3)        start_rad = np.deg2rad(start_theta)        end_rad = np.deg2rad(end_theta)        r_arrow = R_in - 0.05        start_pt = (r_arrow * np.cos(start_rad), r_arrow * np.sin(start_rad))        end_pt = (r_arrow * np.cos(end_rad), r_arrow * np.sin(end_rad))        # 曲线弧度        dist = np.sqrt((start_pt[0] - end_pt[0]) ** 2 + (start_pt[1] - end_pt[1]) ** 2)        rad_curve = 0.2 if dist > 4 else 0.5        arrow = FancyArrowPatch(posA=start_pt, posB=end_pt,                                connectionstyle=f"arc3,rad={rad_curve}",                                color='#4A6572', alpha=0.8, lw=2.5,                                arrowstyle='-|>,head_length=6,head_width=4')        ax.add_patch(arrow)# ================= 主程序 =================# 设置随机种子（可选，用于复现）random.seed(42)# 从CSV文件加载数据top_labels_file = 'top_labels.csv'bottom_labels_file = 'bottom_labels.csv'connections_file = 'connections.csv'try:    top_labels, bottom_labels, connections = load_data_from_csv(        top_labels_file, bottom_labels_file, connections_file    )    print(f"成功加载数据:")    print(f"  - 顶部标签: {len(top_labels)} 个")    print(f"  - 底部标签: {len(bottom_labels)} 个")    print(f"  - 连接关系: {len(connections)} 条")    # 创建图表    fig, ax = create_circular_plot(        top_labels=top_labels,        bottom_labels=bottom_labels,        connections=connections,        num_arrows=35,  # 总箭头数量（可选）        figsize=(14, 14),        outer_top_label="Characteristics of the airborne plastisphere",        outer_bottom_label="Planetary health threats"    )    # 保存图表（可选）    # plt.savefig('circular_plot.png', dpi=300, bbox_inches='tight')    plt.show()except FileNotFoundError as e:    print(f"错误: 找不到文件 - {e}")    print("请确保以下CSV文件存在于当前目录:")    print("  - top_labels.csv")    print("  - bottom_labels.csv")    print("  - connections.csv")except Exception as e:    print(f"错误: {e}")