我喜欢用Plotly来可视化一切，我正在尝试用Plotly来可视化一个混淆矩阵，我的代码如下：

def plot_confusion_matrix(y_true, y_pred, class_names):    confusion_matrix = metrics.confusion_matrix(y_true, y_pred)    confusion_matrix = confusion_matrix.astype(int)    layout = {        "title": "Confusion Matrix",         "xaxis": {"title": "预测值"},         "yaxis": {"title": "实际值"}    }    fig = go.Figure(data=go.Heatmap(z=confusion_matrix,                                    x=class_names,                                    y=class_names,                                    hoverongaps=False),                    layout=layout)    fig.show()

结果是

如何在每个单元格内显示数字，而不是悬停时显示，像这样

回答：

你可以使用带注释的热图ff.create_annotated_heatmap()来实现这个效果：

完整代码：

import plotly.figure_factory as ffz = [[0.1, 0.3, 0.5, 0.2],     [1.0, 0.8, 0.6, 0.1],     [0.1, 0.3, 0.6, 0.9],     [0.6, 0.4, 0.2, 0.2]]x = ['healthy', 'multiple diseases', 'rust', 'scab']y =  ['healthy', 'multiple diseases', 'rust', 'scab']# 将z的每个元素转换为字符串以便注释z_text = [[str(y) for y in x] for x in z]# 设置图形fig = ff.create_annotated_heatmap(z, x=x, y=y, annotation_text=z_text, colorscale='Viridis')# 添加标题fig.update_layout(title_text='<i><b>混淆矩阵</b></i>',                  #xaxis = dict(title='x'),                  #yaxis = dict(title='x')                 )# 添加自定义x轴标题fig.add_annotation(dict(font=dict(color="black",size=14),                        x=0.5,                        y=-0.15,                        showarrow=False,                        text="预测值",                        xref="paper",                        yref="paper"))# 添加自定义y轴标题fig.add_annotation(dict(font=dict(color="black",size=14),                        x=-0.35,                        y=0.5,                        showarrow=False,                        text="实际值",                        textangle=-90,                        xref="paper",                        yref="paper"))# 调整边距以便为y轴标题留出空间fig.update_layout(margin=dict(t=50, l=200))# 添加颜色条fig['data'][0]['showscale'] = Truefig.show()