label_font = { 'weight': 'bold', 'size': 22, 'family': 'SimSun' } colorbar_label_font_C = { 'weight': 'bold', 'size': 18, 'family': 'SimSun' } colorbar_label_font_E = { 'weight': 'bold', 'size': 18, 'family': 'Times New Roman' }

这段代码定义了三个字体样式的字典，别是`label_font``colorbar_label_font`和`colorbar_label_font_E`。每个字典包含了字体的粗细（weight）、大小（size）和字体族（family）等属性。其中，`label_font`使用宋体（SimSun）字体，大小为22，粗细为粗体；`colorbar_label_font_C`和`colorbar_label_font_E`分别使用宋体和Times New Roman字体，大小为18，粗细为粗体。这些字体样式可以在绘图过程中应用于相应的标签或文本。

相关问题

我要把feature_type_mean放在横轴其他位置，请增加代码，#这种初始化操作可以用来创建一个空的数据结构，用于后续存储和填充数据。在这种情况下，DataFrame的所有元素被初始化为0，准备接收进一步的数据填充。 filter_features = pd.DataFrame(0, index=filter_names, columns=feature_type_names, ) for key in c: for filter_name in filter_names: for feature_type_name in feature_type_names: if filter_name in key and feature_type_name in key: # print(filter_name, feature_type_name, key, c[key]) filter_features.loc[filter_name, feature_type_name] += c[key] filter_features['filter_mean'] = filter_features.mean(axis = 1) filter_features.loc['feature_type_mean'] = filter_features.mean(axis = 0) # %% plt.figure(figsize=(8, 12), dpi=300) sns.set_style('white', {'font.sans-serif': ['simsun', 'Times New Roman'], "size": 6}) ax = sns.heatmap(filter_features, # .apply(np.log1p), #vmin=5, vmax=17, fmt=".3f", annot=False, cmap="YlOrBr",#"vlag",#"YlOrBr", # cmap="RdBu_r", annot_kws={"size": 6}, square=True ) # label_y = ax.get_yticklabels() # plt.setp(label_y, rotation=45) # label_x = ax.get_xticklabels() # plt.setp(label_x, rotation=45) # plt.tick_params(labelsize=6) plt.show()

To move the 'feature_type_mean' column to a different position in the DataFrame, you can use the `reindex` method of pandas DataFrame. Here's the modified code:

filter_features = pd.DataFrame(0, index=filter_names, columns=feature_type_names)
for key in c:
    for filter_name in filter_names:
        for feature_type_name in feature_type_names:
            if filter_name in key and feature_type_name in key:
                filter_features.loc[filter_name, feature_type_name] += c[key]

filter_features['filter_mean'] = filter_features.mean(axis=1)

# Calculate the mean of each column and store it in a new DataFrame
feature_type_mean = filter_features.mean(axis=0)
feature_type_mean_df = pd.DataFrame(feature_type_mean, columns=['feature_type_mean'])

# Reorder the columns in the DataFrame
filter_features = pd.concat([feature_type_mean_df, filter_features.drop(columns=['feature_type_mean'])], axis=1)

plt.figure(figsize=(8, 12), dpi=300)
sns.set_style('white', {'font.sans-serif': ['simsun', 'Times New Roman'], "size": 6})
ax = sns.heatmap(filter_features, fmt=".3f", annot=False, cmap="YlOrBr", annot_kws={"size": 6}, square=True)

plt.show()

In this modified code, the `feature_type_mean` column is calculated separately and stored in a new DataFrame `feature_type_mean_df`. Then, the `concat()` method is used to combine this DataFrame with the original `filter_features` DataFrame, but with the columns reordered. Finally, the heatmap is plotted using the modified `filter_features` DataFrame.

<table width="100%" id="tablefirst" style= "margin-bottom:2px; margin-top:2px; font-family: 宋体,SimSun; font-size: 11px;font-weight:bold;"> <tr > %20 </tr> <tr > <td colspan='8' ><img width="90%" height="2" style="float: center;" src=':/images/black.png'/></td> </tr> %16 </table>中<tr > <td colspan='8' ><img width="90%" height="2" style="float: center;" src=':/images/black.png'/></td> </tr>宽度无法占满全屏

这个问题可能是由于图片的宽度设置为90%，而不是100%所导致的。你可以将该行代码修改为：

<td colspan='8'><img style="display: block; width: 100%;" src=':/images/black.png'/></td>

这样图片就会占满整个单元格的宽度，从而使整个表格占满全屏。同时，你也可以将 table 标签的 width 属性设置为 100% 来确保表格的宽度占满全屏。修改后的代码如下所示：

<table width="100%" id="tablefirst" style="margin-bottom:2px; margin-top:2px; font-family: 宋体,SimSun; font-size: 11px; font-weight:bold;">
  <tr>
    <td colspan='8' style="text-align:center;">%20</td>
  </tr>
  <tr>
    <td colspan='8'><img style="display: block; width: 100%;" src=':/images/black.png'/></td>
  </tr>
  <tr>
    <td colspan='8' style="text-align:center;">%16</td>
  </tr>
</table>

希望这个解决方案能够帮助到你。