Matplotlib：pandas MultiIndex DataFrame 的自定义代码

我有一个想要绘制的大熊猫 MultiIndex DataFrame。一个最小的例子看起来像：

import pandas as pd

years = range(2015, 2018)
fields = range(4)
days = range(4)
bands = ['R', 'G', 'B']

index = pd.MultiIndex.from_product(
    [years, fields], names=['year', 'field'])
columns = pd.MultiIndex.from_product(
    [days, bands], names=['day', 'band'])

df = pd.DataFrame(0, index=index, columns=columns)

df.loc[(2015,), (0,)] = 1
df.loc[(2016,), (1,)] = 1
df.loc[(2017,), (2,)] = 1

如果我使用 绘制此图plt.spy，我会得到：

但是，刻度位置和标签不太理想。我希望刻度完全忽略 MultiIndex 的第二级。使用IndexLocatorand IndexFormatter，我可以执行以下操作：

from matplotlib.ticker import IndexFormatter, IndexLocator

import matplotlib.pyplot as plt

ax = plt.gca()
plt.spy(df)

xbase = len(bands)
xoffset = xbase / 2
xlabels = df.columns.get_level_values('day')
ax.xaxis.set_major_locator(IndexLocator(base=xbase, offset=xoffset))
ax.xaxis.set_major_formatter(IndexFormatter(xlabels))
plt.xlabel('Day')
ax.xaxis.tick_bottom()

ybase = len(fields)
yoffset = ybase / 2
ylabels = df.index.get_level_values('year')
ax.yaxis.set_major_locator(IndexLocator(base=ybase, offset=yoffset))
ax.yaxis.set_major_formatter(IndexFormatter(ylabels))
plt.ylabel('Year')

plt.show()

这正是我想要的：

But here's the problem. My actual DataFrame has 15 years, 4,000 fields, 365 days, and 7 bands. If I actually label every single day, the labels would be illegible. I could place a tick every 50 days, but I would like the ticks to be dynamic so that when I zoom in, the ticks become more fine-grained. Basically what I'm looking for is a custom MultiIndexLocator that combines the placement of IndexLocator with the dynamism of MaxNLocator.

Bonus: My data is really nice in the sense that there are always the same number of fields for every year and the same number of bands for every day. But what if this was not the case? I would love to contribute a generic MultiIndexLocator and MultiIndexFormatter to matplotlib that works for any MultiIndex DataFrame.