Datetime plot fails with 'Agg' backend in interactive mode #15409
Description
Bug report
Bug summary
I try to plot the time series data, and the X-axis represents the datetime. The code succeeds when use the 'Qt5Agg' backend, but fails when use the 'Agg' backend
Code for reproduction
The example code based on the matplotlib tutorials(https://matplotlib.org/3.1.1/gallery/ticks_and_spines/date_concise_formatter.html).
When use the 'Qt5Agg' backend, the code works well.(To show my issue, I use the python instead of ipython, because the ipython will use 'Qt5Agg' backend as default in my ENV)
Python 3.6.8 (default, Oct 7 2019, 12:59:55)
[GCC 8.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import datetime
>>> import matplotlib.pyplot as plt
>>> import matplotlib.dates as mdates
>>> import numpy as np
>>> base = datetime.datetime(2005, 2, 1)
>>> dates = np.array([base + datetime.timedelta(hours=(2 * i)) for i in range(732)])
>>> np.random.seed(19680801)
>>> N = len(dates)
>>> y = np.cumsum(np.random.randn(N))
>>> import matplotlib
>>> matplotlib.get_backend()
'Qt5Agg'
>>> plt.plot(dates,y)
[<matplotlib.lines.Line2D object at 0x7f621c039828>]And I get the expected figure.
But when I use 'Agg' backend, the code fails.
Python 3.6.8 (default, Oct 7 2019, 12:59:55)
[GCC 8.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import matplotlib
>>> matplotlib.use('Agg')
>>> matplotlib.get_backend()
'agg'
>>> import datetime
>>> import matplotlib.pyplot as plt
>>> import matplotlib.dates as mdates
>>> import numpy as np
>>> base = datetime.datetime(2005, 2, 1)
>>> dates = np.array([base + datetime.timedelta(hours=(2 * i)) for i in range(732)])
>>> N = len(dates)
>>> np.random.seed(19680801)
>>> y = np.cumsum(np.random.randn(N))
>>> plt.plot(dates,y)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/pyplot.py", line 2795, in plot
is not None else {}), **kwargs)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/axes/_axes.py", line 1666, in plot
lines = [*self._get_lines(*args, data=data, **kwargs)]
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/axes/_base.py", line 225, in __call__
yield from self._plot_args(this, kwargs)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/axes/_base.py", line 391, in _plot_args
x, y = self._xy_from_xy(x, y)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/axes/_base.py", line 243, in _xy_from_xy
bx = self.axes.xaxis.update_units(x)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/axis.py", line 1498, in update_units
self._update_axisinfo()
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/axis.py", line 1516, in _update_axisinfo
self.set_major_locator(info.majloc)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/axis.py", line 1651, in set_major_locator
self.stale = True
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/artist.py", line 230, in stale
self.stale_callback(self, val)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/artist.py", line 51, in _stale_axes_callback
self.axes.stale = val
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/artist.py", line 230, in stale
self.stale_callback(self, val)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/figure.py", line 51, in _stale_figure_callback
self.figure.stale = val
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/artist.py", line 230, in stale
self.stale_callback(self, val)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/pyplot.py", line 589, in _auto_draw_if_interactive
fig.canvas.draw_idle()
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/backend_bases.py", line 1907, in draw_idle
self.draw(*args, **kwargs)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py", line 388, in draw
self.figure.draw(self.renderer)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/artist.py", line 38, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/figure.py", line 1709, in draw
renderer, self, artists, self.suppressComposite)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/image.py", line 135, in _draw_list_compositing_images
a.draw(renderer)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/artist.py", line 38, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/axes/_base.py", line 2647, in draw
mimage._draw_list_compositing_images(renderer, self, artists)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/image.py", line 135, in _draw_list_compositing_images
a.draw(renderer)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/artist.py", line 38, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/axis.py", line 1203, in draw
ticks_to_draw = self._update_ticks()
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/axis.py", line 1079, in _update_ticks
major_locs = self.get_majorticklocs()
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/axis.py", line 1324, in get_majorticklocs
return self.major.locator()
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/dates.py", line 1431, in __call__
self.refresh()
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/dates.py", line 1451, in refresh
dmin, dmax = self.viewlim_to_dt()
File "/home/fanxp/.local/lib/python3.6/site-packages/matplotlib/dates.py", line 1202, in viewlim_to_dt
.format(vmin))
ValueError: view limit minimum 0.0 is less than 1 and is an invalid Matplotlib date value. This often happens if you pass a non-datetime value to an axis that has datetime units
>>>So, how can I resolve this issue? Thanks!
Matplotlib version
- Operating system: ubuntu 18.04
- Matplotlib version: 3.1.1
- Matplotlib backend (
print(matplotlib.get_backend())): agg - Python version: 3.6.8
- Jupyter version (if applicable):
- Other libraries: numpy 1.17.2
I use pip to install numpy and matplotlib, and I use the system's python3