在混淆矩阵的各个方面绘制标签
Plot labels from all sides in confusion matrix
我需要绘制从各个方面注释的混淆矩阵。我在右侧有问题,我想在底部打印相同的标签([...类 names..., 'Total samples', 'Accuracy' 'mIoU']) .此外,顶部刻度似乎与底部刻度不对齐。
这是我尝试过的:
fig, ax1 = get_new_fig('Conf matrix default', figsize)
ax = sn.heatmap(df_cm, annot=annot, annot_kws={"size": fz}, linewidths=lw, ax=ax1,
cbar=cbar, cmap=cmap, linecolor='w', fmt=fmt)
ax_new = ax.twinx().twiny()
labels = ['' for _ in range(len(ax.get_xticklabels()))]
labels[-3] = 'Total samples'
labels[-2] = 'Accuracy'
labels[-1] = 'mIoU'
ticks = [tick for tick in ax.get_xticks()]
ax_new.set_xticks(ticks)
ax_new.set_yticks(ticks)
ax_new.yaxis.set_label_position('right')
ax_new.set_xticklabels([text.get_text() for text in ax.get_xticklabels()], fontsize=10, rotation=-45) # top
ax_new.set_yticklabels(labels, fontsize=10, rotation=-25) # right
# set ticklabels
ax.set_xticklabels(labels, rotation=45, fontsize=10) # bottom
ax.set_yticklabels(ax.get_yticklabels(), rotation=25, fontsize=10) # left
非常感谢任何帮助,因为我不知道我是否遗漏了代码中的某些内容或其他内容。
提前致谢。
问题在于新 ax
的限制。这些需要等于原始 ax
的限制。尤其是原来 ax
的 y 轴被颠倒了,导致新的 y 轴没有可见的刻度标签。不同的限制也阻止了 x 轴刻度的对齐。
ax_new.set_xlim(ax.get_xlim())
和 ax_new.set_ylim(ax.get_ylim())
应该可以解决问题。 plt.tight_layout()
可以帮助在周围的图中很好地定位所有标签。
右y刻度标签的旋转问题似乎有点难。下面的代码通过将 twinx
和 twiny
轴分开来解决它:
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
fig, ax1 = plt.subplots()
ax1.set_title('Conf matrix default')
df_cm = pd.DataFrame(np.random.rand(9, 9), columns=range(1, 10), index=range(1, 10))
ax = sns.heatmap(df_cm, annot=True, annot_kws={"size": 12}, linewidths=2, ax=ax1,
cbar=False, linecolor='w', fmt='.2f')
ax_new1 = ax.twinx()
ax_new2 = ax_new1.twiny()
labels = ['' for _ in range(len(ax.get_xticklabels()))]
labels[-3] = 'Total samples'
labels[-2] = 'Accuracy'
labels[-1] = 'mIoU'
ticks = [tick for tick in ax.get_xticks()]
ax_new2.set_xticks(ticks)
ax_new1.set_yticks(ticks)
ax_new1.yaxis.set_label_position('right')
ax_new2.set_xticklabels([text.get_text() for text in ax.get_xticklabels()], fontsize=10, rotation=-45) # top
ax_new1.set_yticklabels(labels, fontsize=10, rotation=-45) # right
# set ticklabels
ax.set_xticklabels(labels, rotation=45, fontsize=10) # bottom
ax.set_yticklabels(ax.get_yticklabels(), rotation=25, fontsize=10) # left
ax_new2.set_xlim(ax.get_xlim())
ax_new1.set_ylim(ax.get_ylim())
plt.tight_layout()
plt.show()
我需要绘制从各个方面注释的混淆矩阵。我在右侧有问题,我想在底部打印相同的标签([...类 names..., 'Total samples', 'Accuracy' 'mIoU']) .此外,顶部刻度似乎与底部刻度不对齐。
这是我尝试过的:
fig, ax1 = get_new_fig('Conf matrix default', figsize)
ax = sn.heatmap(df_cm, annot=annot, annot_kws={"size": fz}, linewidths=lw, ax=ax1,
cbar=cbar, cmap=cmap, linecolor='w', fmt=fmt)
ax_new = ax.twinx().twiny()
labels = ['' for _ in range(len(ax.get_xticklabels()))]
labels[-3] = 'Total samples'
labels[-2] = 'Accuracy'
labels[-1] = 'mIoU'
ticks = [tick for tick in ax.get_xticks()]
ax_new.set_xticks(ticks)
ax_new.set_yticks(ticks)
ax_new.yaxis.set_label_position('right')
ax_new.set_xticklabels([text.get_text() for text in ax.get_xticklabels()], fontsize=10, rotation=-45) # top
ax_new.set_yticklabels(labels, fontsize=10, rotation=-25) # right
# set ticklabels
ax.set_xticklabels(labels, rotation=45, fontsize=10) # bottom
ax.set_yticklabels(ax.get_yticklabels(), rotation=25, fontsize=10) # left
非常感谢任何帮助,因为我不知道我是否遗漏了代码中的某些内容或其他内容。
提前致谢。
问题在于新 ax
的限制。这些需要等于原始 ax
的限制。尤其是原来 ax
的 y 轴被颠倒了,导致新的 y 轴没有可见的刻度标签。不同的限制也阻止了 x 轴刻度的对齐。
ax_new.set_xlim(ax.get_xlim())
和 ax_new.set_ylim(ax.get_ylim())
应该可以解决问题。 plt.tight_layout()
可以帮助在周围的图中很好地定位所有标签。
右y刻度标签的旋转问题似乎有点难。下面的代码通过将 twinx
和 twiny
轴分开来解决它:
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
fig, ax1 = plt.subplots()
ax1.set_title('Conf matrix default')
df_cm = pd.DataFrame(np.random.rand(9, 9), columns=range(1, 10), index=range(1, 10))
ax = sns.heatmap(df_cm, annot=True, annot_kws={"size": 12}, linewidths=2, ax=ax1,
cbar=False, linecolor='w', fmt='.2f')
ax_new1 = ax.twinx()
ax_new2 = ax_new1.twiny()
labels = ['' for _ in range(len(ax.get_xticklabels()))]
labels[-3] = 'Total samples'
labels[-2] = 'Accuracy'
labels[-1] = 'mIoU'
ticks = [tick for tick in ax.get_xticks()]
ax_new2.set_xticks(ticks)
ax_new1.set_yticks(ticks)
ax_new1.yaxis.set_label_position('right')
ax_new2.set_xticklabels([text.get_text() for text in ax.get_xticklabels()], fontsize=10, rotation=-45) # top
ax_new1.set_yticklabels(labels, fontsize=10, rotation=-45) # right
# set ticklabels
ax.set_xticklabels(labels, rotation=45, fontsize=10) # bottom
ax.set_yticklabels(ax.get_yticklabels(), rotation=25, fontsize=10) # left
ax_new2.set_xlim(ax.get_xlim())
ax_new1.set_ylim(ax.get_ylim())
plt.tight_layout()
plt.show()