点击matplotlib/plotly阶梯图子图点显示标注报Line2D无get_offsets错误如何解决？

错误原因 #

• plot() 方法返回的是 Line2D 类型对象，get_offsets() 是散点图返回的 PathCollection 对象的方法，二者接口不通用，直接调用必然触发 AttributeError。
• 循环绘制子图时反复覆盖了 steps、y_gage、annot 变量，交互逻辑仅绑定了最后一个子图的配置，前面子图的点击逻辑完全失效。
• 循环内重复创建了大量冗余的标注对象，无意义占用资源。

修改说明 #

1. 改用 Line2D 的 get_xdata()、get_ydata() 方法获取点位坐标
2. 提前定义全局唯一的可复用标注对象，初始设置为隐藏
3. 用列表存储每个子图对应的线对象、Gage值列表，点击时判断当前触发的子图，匹配对应数据
4. 修正交互逻辑，支持所有子图的点击触发，标注内容直接显示对应点位的Gage值

完整可运行代码 #

import pandas as pd
import numpy as np
import matplotlib as mtpl
from matplotlib import pyplot as plt
import matplotlib.ticker as ticker

data = {
    'Name': ['Lamp_D_Rq', 'Status', 'Status', 'HMI', 'Lck_D_RqDrv3', 'Lck_D_RqDrv3', 'Lck_D_RqDrv3', 'Lck_D_RqDrv3', 'Lamp_D_Rq', 'Lamp_D_Rq', 'Lamp_D_Rq', 'Lamp_D_Rq'],
    'Value': [0, 4, 4, 2, 1, 1, 2, 2, 1, 1, 3, 3],
    'Gage': ['F1', 'H1', 'H3', 'H3', 'H3', 'F1', 'H3', 'F1', 'F1', 'H3', 'F1', 'H3'],
    'Id_Par': [0, 0, 0, 11, 0, 0, 0, 0, 0, 0, 0, 0]
    }

signals_df = pd.DataFrame(data)


def plot_signals(signals_df):
    print(signals_df)
    # Count signals by parallel
    signals_df['Count'] = signals_df.groupby('Id_Par').cumcount().add(1).mask(signals_df['Id_Par'].eq(0), 0)
    # Subtract Parallel values from the index column
    signals_df['Sub'] = signals_df.index - signals_df['Count']
    id_par_prev = signals_df['Id_Par'].unique()
    id_par = np.delete(id_par_prev, 0)
    signals_df['Prev'] = [1 if x in id_par else 0 for x in signals_df['Id_Par']]
    signals_df['Final'] = signals_df['Prev'] + signals_df['Sub']
    # Convert and set Subtract to index
    signals_df.set_index('Final', inplace=True)

    # Get individual names and variables for the chart
    names_list = [name for name in signals_df['Name'].unique()]
    num_names_list = len(names_list)
    num_axisx = len(signals_df["Name"])

    # Matplotlib's categorical feature to convert x-axis values to string
    x_values = [-1, ]
    x_values += (list(set(signals_df.index)))
    x_values = [str(i) for i in sorted(x_values)]

    # Creation Graphics
    fig, ax = plt.subplots(nrows=num_names_list, figsize=(10, 10), sharex=True)
    plt.xticks(np.arange(0, num_axisx), color='SteelBlue', fontweight='bold')

    # 存储每个子图对应的线对象、Gage值列表
    line_list = []
    gage_list = []
    ax_list = ax.flatten()

    # 全局唯一标注，初始隐藏
    annot = mtpl.text.Annotation("", xy=(0,0), xytext=(-20, 20), textcoords="offset points",
                                bbox=dict(boxstyle="round", fc="w"),
                                arrowprops=dict(arrowstyle="->"))
    annot.set_visible(False)
    fig.add_artist(annot)

    # Loop to build the different graphs
    for pos, name in enumerate(names_list):
        # Creating a dummy plot and then remove it
        dummy, = ax[pos].plot(x_values, np.zeros_like(x_values))
        dummy.remove()

        # Get names by values and gage data
        data = signals_df[signals_df["Name"] == name]["Value"]
        data_gage = signals_df[signals_df["Name"] == name]["Gage"]

        # Get values axis-x and axis-y
        x_ = np.hstack([-1, data.index.values, len(signals_df) - 1])
        y_ = np.hstack([0, data.values, data.iloc[-1]])
        y_gage = np.hstack(["", "-", data_gage.values])

        # Plotting the data by position
        steps = ax[pos].plot(x_.astype('str'), y_, drawstyle='steps-post', marker='*', markersize=8, color='k', linewidth=2)
        ax[pos].set_ylabel(name, fontsize=8, fontweight='bold', color='SteelBlue', rotation=30, labelpad=35)
        ax[pos].yaxis.set_major_formatter(ticker.FormatStrFormatter('%0.1f'))
        ax[pos].yaxis.set_tick_params(labelsize=6)
        ax[pos].grid(alpha=0.4, color='SteelBlue')
        
        # 存储当前子图的线对象和Gage值
        line_list.append(steps[0])
        gage_list.append(y_gage)

        # 显示点位数值
        xy_temp = []
        for i in range(len(y_)):
            if i == 0:
                xy = [x_[0].astype('str'), y_[0]]
                xy_temp.append(xy)
            else:
                xy = [x_[i - 1].astype('str'), y_[i - 1]]
                xy_temp.append(xy)
            ax[pos].text(x=xy[0], y=xy[1], s=str(xy[1]), color='k', fontweight='bold', fontsize=12)

    # Function for storing and showing the clicked values
    def update_annot(line, gage_data, ind):
        x = line.get_xdata()[ind["ind"][0]]
        y = line.get_ydata()[ind["ind"][0]]
        annot.xy = (x, y)
        text = gage_data[ind["ind"][0]]
        annot.set_text(text)
        annot.get_bbox_patch().set_alpha(0.4)

    def on_click(event):
        vis = annot.get_visible()
        # 遍历所有子图判断点击位置
        for ax_idx, current_ax in enumerate(ax_list):
            if event.inaxes == current_ax:
                line = line_list[ax_idx]
                gage_data = gage_list[ax_idx]
                cont, ind = line.contains(event)
                if cont:
                    update_annot(line, gage_data, ind)
                    annot.set_visible(True)
                    fig.canvas.draw_idle()
                    return
        # 点击点位外隐藏标注
        if vis:
            annot.set_visible(False)
            fig.canvas.draw_idle()

    fig.canvas.mpl_connect("button_press_event",on_click)
    plt.show()

plot_signals(signals_df)

内容的提问来源于stack exchange，提问作者MayEncoding