Bug report

Bug summary
Cannot plot a fully masked array agaisnt an array of datetimes. A ValueError is raised for a seemingly unrelated reason. Surprisingly, matplotlib has no problem plotting a fully masked array by itself.

Code for reproduction

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

x = np.array([
    datetime(2017, 1, 1), 
    datetime(2017, 1, 2), 
    datetime(2017, 1, 3),
    datetime(2017, 1, 4),
    datetime(2017, 1, 5)
])

y = np.array([1,2,3,4,5])
m = np.ma.masked_greater(y, 0)

fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x, m)
plt.show()

Actual outcome

[super big traceback, only showing the most recent to save space...]
/usr/lib64/python3.5/dist-packages/matplotlib/dates.py in _from_ordinalf(x, tz)
    258 
    259     ix = int(x)
--> 260     dt = datetime.datetime.fromordinal(ix).replace(tzinfo=UTC)
    261 
    262     remainder = float(x) - ix
ValueError: ordinal must be >= 1

Expected outcome
An empty graph. If you comment out x and don't plot against it, then matplotlib has no problem displaying an empty graph. It is only when you plot against a datetime array this is an issue.

Matplotlib version

• Operating system: GNU/Linux
• Matplotlib version: 2.1.1
• Matplotlib backend (print(matplotlib.get_backend())): module://ipykernel.pylab.backend_inline
• Python version: 3.5.5
• Jupyter version (if applicable): 4.3.0
• Other libraries: numpy, datetime