matplotlib中的分层轴标记(Python)

Question

假设我正在看一个nxn网格,并且在每个轴上我都有标记,比如动物.但我也有兴趣研究这些动物的群体,小组等之间的关系.因此,例如,我可能有脊椎动物和无脊椎动物,在脊椎动物中我可能有哺乳动物和爬行动物等等.(如果重要的话,我对相关矩阵特别感兴趣,实际上是通过seaborn使用热图......)

我想在matplotlib中绘制它,但沿轴有层次标记.因此,使用上面的例子,我会有像狗,猫,马,蜥蜴,鳄鱼等标签,然后第一组通过马的狗将有一个哺乳动物的标签和第二组蜥蜴,鳄鱼等将有爬行动物,这两个一起会有更多的脊椎动物标签......

我该怎么做？

Answer 1

这是@Vadim 答案的稍微更新版本，因为我找到了一种无需 SubplotHost 即可完成此操作的方法。然后，即使您不创建子图（例如在使用 seaborn 图形级函数时），您也可以执行此操作。

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker

fig1, ax1 = plt.subplots(1)
# Some data
x = np.arange(1,6)
y = np.random.random(len(x))

# First X-axis
ax1.plot(x, y)
ax1.set_xticks(x)
ax1.set_xticklabels(['dog', 'cat', 'horse', 'lizard', 'crocodile'])
ax1.yaxis.set_label_text("Sample data")

# Second X-axis
ax2 = ax1.twiny()

ax2.spines["bottom"].set_position(("axes", -0.10))
ax2.tick_params('both', length=0, width=0, which='minor')
ax2.tick_params('both', direction='in', which='major')
ax2.xaxis.set_ticks_position("bottom")
ax2.xaxis.set_label_position("bottom")

ax2.set_xticks([0.0, 0.6, 1.0])
ax2.xaxis.set_major_formatter(ticker.NullFormatter())
ax2.xaxis.set_minor_locator(ticker.FixedLocator([0.3, 0.8]))
ax2.xaxis.set_minor_formatter(ticker.FixedFormatter(['mammal', 'reptiles']))

# Third X-axis
ax3 = ax1.twiny()

ax3.spines["bottom"].set_position(("axes", -0.20))
ax3.tick_params('both', length=0, width=0, which='minor')
ax3.tick_params('both', direction='in', which='major')
ax3.xaxis.set_ticks_position("bottom")
ax3.xaxis.set_label_position("bottom")

ax3.set_xticks([0.0, 1.0])
ax3.xaxis.set_major_formatter(ticker.NullFormatter())
ax3.xaxis.set_minor_locator(ticker.FixedLocator([0.5]))
ax3.xaxis.set_minor_formatter(ticker.FixedFormatter(['vertebrates']))

ax1.grid(True)
plt.show()

Answer 2

不幸的是我无法弄清楚如何禁用次要滴答:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
from mpl_toolkits.axes_grid.parasite_axes import SubplotHost

fig1 = plt.figure()
ax1 = SubplotHost(fig1, 111)
fig1.add_subplot(ax1)

# Some data
x = np.arange(1,6)
y = np.random.random(len(x))

# First X-axis
ax1.plot(x, y)
ax1.set_xticks(x)
ax1.set_xticklabels(['dog', 'cat', 'horse', 'lizard', 'crocodile'])
#ax1.xaxis.set_label_text('First X-axis') # Uncomment to label axis
ax1.yaxis.set_label_text("Sample data")

# Second X-axis
ax2 = ax1.twiny()
offset = 0, -25 # Position of the second axis
new_axisline = ax2.get_grid_helper().new_fixed_axis
ax2.axis["bottom"] = new_axisline(loc="bottom", axes=ax2, offset=offset)
ax2.axis["top"].set_visible(False)

ax2.set_xticks([0.0, 0.6, 1.0])
ax2.xaxis.set_major_formatter(ticker.NullFormatter())
ax2.xaxis.set_minor_locator(ticker.FixedLocator([0.3, 0.8]))
ax2.xaxis.set_minor_formatter(ticker.FixedFormatter(['mammal', 'reptiles']))

# Third X-axis
ax3 = ax1.twiny()
offset = 0, -50
new_axisline = ax3.get_grid_helper().new_fixed_axis
ax3.axis["bottom"] = new_axisline(loc="bottom", axes=ax3, offset=offset)
ax3.axis["top"].set_visible(False)

ax3.set_xticks([0.0, 1.0])
ax3.xaxis.set_major_formatter(ticker.NullFormatter())
ax3.xaxis.set_minor_locator(ticker.FixedLocator([0.5]))
ax3.xaxis.set_minor_formatter(ticker.FixedFormatter(['vertebrates']))

ax1.grid(1)
plt.show()