python - 使用 sharex=True 绘制日期会导致 ValueError : ordinal must be >= 1

Question

在进行一些分析时，我偶然发现了一个 ValueError，我可以将其归结为以下可以重现我遇到的错误的简单示例:

import numpy as np
import matplotlib.pyplot as plt
import datetime as dt

x = np.array([dt.datetime(2012, 10, 19, 10, 0, 0),
              dt.datetime(2012, 10, 19, 10, 0, 1),
              dt.datetime(2012, 10, 19, 10, 0, 2),
              dt.datetime(2012, 10, 19, 10, 0, 3)])

y = np.array([1, 3, 4, 2])

当尝试绘制这个简单的 x 和 y 数组时，我没有遇到以下问题:

fig, ax = plt.subplots()
ax.plot(x, y)

或

fig, (ax1, ax2) = plt.subplots(nrows=2)
ax1.plot(x, y)

但是在添加 sharex=True 时，出现错误:

fig, (ax1, ax2) = plt.subplots(nrows=2, sharex=True)
ax1.plot(x, y)

错误信息:

Traceback (most recent call last):
  File "C:\Python27\lib\site-packages\matplotlib\backend_bases.py", line 2445, in home
    self._update_view()
  File "C:\Python27\lib\site-packages\matplotlib\backend_bases.py", line 2818, in _update_view
    self.draw()
  File "C:\Python27\lib\site-packages\matplotlib\backend_bases.py", line 2796, in draw
    loc.refresh()
  File "C:\Python27\lib\site-packages\matplotlib\dates.py", line 758, in refresh
    dmin, dmax = self.viewlim_to_dt()
  File "C:\Python27\lib\site-packages\matplotlib\dates.py", line 530, in viewlim_to_dt
    return num2date(vmin, self.tz), num2date(vmax, self.tz)
  File "C:\Python27\lib\site-packages\matplotlib\dates.py", line 289, in num2date
    if not cbook.iterable(x): return _from_ordinalf(x, tz)
  File "C:\Python27\lib\site-packages\matplotlib\dates.py", line 203, in _from_ordinalf
    dt = datetime.datetime.fromordinal(ix)
ValueError: ordinal must be >= 1

我从 matplotlib ( https://github.com/matplotlib/matplotlib/issues/162 ) 中发现了一个关于使用 twinx 和日期给出相同错误的问题。这是同一个错误吗？这似乎是一个早就知道的错误，但尚未解决。

Answer 1

如果您在第二个轴上绘制某些内容，则可以避免该错误:

import matplotlib.pyplot as plt
import numpy as np
import datetime as dt

x = np.array([dt.datetime(2012, 10, 19, 10, 0, 0),
              dt.datetime(2012, 10, 19, 10, 0, 1),
              dt.datetime(2012, 10, 19, 10, 0, 2),
              dt.datetime(2012, 10, 19, 10, 0, 3)])

y = np.array([1, 3, 4, 2])

fig, (ax1, ax2) = plt.subplots(nrows = 2, sharex = True)
ax1.plot(x, y, 'b-')
ax2.plot(x, 1.0/y, 'r-')
plt.show()