Matplotlib无法在同一画布绘制三条曲线的问题求助

在Jupyter Notebook中运行以下代码，目标是在同一张图中绘制三条曲线：FedAvg折线、两条水平参考线，但目前仅显示两条水平参考线。单独绘制FedAvg折线时可以正常显示。

代码如下：

import matplotlib.pyplot as plt
from pathlib import Path
def plot_metric_from_history() -> None:

    metric_dict = {'accuracy': [('0', '98.82'),
                                ('1', '98.87'),
                                ('2', '98.9'),
                                ('3', '98.91'),
                                ('4', '98.98'),
                                ('5', '98.89'),
                                ('6', '98.99'),
                                ('7', '99.05'),
                                ('8', '99.0'),
                                ('9', '99.03')]}
    expected_maximum = "0.9924"
    
    # Convert values to float 
    metric_dict['accuracy'] = ([(int(round_num), float(accuracy_val)) for round_num, accuracy_val in
                                      metric_dict['accuracy']])
    
    rounds, values = zip(*metric_dict["accuracy"])
    
    fig = plt.figure()
    axis = fig.add_subplot(111)
    plt.plot(rounds, values, label="FedAvg")
    
    # Set the apect ratio to 1.0
    xleft, xright = axis.get_xlim()
    ybottom, ytop = axis.get_ylim()
    axis.set_aspect(abs((xright - xleft) / (ybottom - ytop)) * 1.0)

    # Set expected graph for data
    plt.axhline(
        y=float(expected_maximum),
        color="r",
        linestyle="--",
        label=f"Paper's best result @{expected_maximum}",
    )
    
    # Set paper's results
    plt.axhline(
        y=0.99,
        color="silver",
        label="Paper's baseline @0.9900",
    )
    
    plt.ylim([0.97, 1])
    plt.title(f"Validation - MNIST")
    plt.xlabel("Rounds")
    plt.ylabel("Accuracy")
    plt.legend(loc="lower right")
    

    # Set the apect ratio to 1.0
    xleft, xright = axis.get_xlim()
    ybottom, ytop = axis.get_ylim()
    axis.set_aspect(abs((xright - xleft) / (ybottom - ytop)) * 1.0)

    plt.show()

plot_metric_from_history()

问题原因 #

1. 数值转换错误：metric_dict中的准确率是百分比格式（如98.82代表98.82%），但代码直接转成float后得到98.82，而后续设置的y轴范围是[0.97, 1]（对应97%到100%），导致FedAvg折线的y值远超出可视范围，自然无法显示。
2. 重复设置纵横比：在绘制折线后和设置完所有元素后两次设置纵横比，干扰了坐标轴的自动调整逻辑，进一步加剧显示问题。

修复方案 #

1. 将百分比格式的准确率数值除以100，转换为小数格式（如98.82转为0.9882）。
2. 只在所有绘图元素设置完成后统一设置纵横比，避免重复调整干扰。

修复后的代码 #

import matplotlib.pyplot as plt
from pathlib import Path
def plot_metric_from_history() -> None:

    metric_dict = {'accuracy': [('0', '98.82'),
                                ('1', '98.87'),
                                ('2', '98.9'),
                                ('3', '98.91'),
                                ('4', '98.98'),
                                ('5', '98.89'),
                                ('6', '98.99'),
                                ('7', '99.05'),
                                ('8', '99.0'),
                                ('9', '99.03')]}
    expected_maximum = "0.9924"
    
    # 修正：将百分比转换为小数
    metric_dict['accuracy'] = ([(int(round_num), float(accuracy_val)/100) for round_num, accuracy_val in
                                      metric_dict['accuracy']])
    
    rounds, values = zip(*metric_dict["accuracy"])
    
    fig = plt.figure()
    axis = fig.add_subplot(111)
    plt.plot(rounds, values, label="FedAvg")

    # 绘制水平参考线
    plt.axhline(
        y=float(expected_maximum),
        color="r",
        linestyle="--",
        label=f"Paper's best result @{expected_maximum}",
    )
    
    plt.axhline(
        y=0.99,
        color="silver",
        label="Paper's baseline @0.9900",
    )
    
    # 设置坐标轴范围和标签
    plt.ylim([0.97, 1])
    plt.title(f"Validation - MNIST")
    plt.xlabel("Rounds")
    plt.ylabel("Accuracy")
    plt.legend(loc="lower right")
    
    # 统一设置纵横比（放在最后）
    xleft, xright = axis.get_xlim()
    ybottom, ytop = axis.get_ylim()
    axis.set_aspect(abs((xright - xleft) / (ybottom - ytop)) * 1.0)

    plt.show()

plot_metric_from_history()

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