Skip to content

[Bug]: Figure manager is gone - AttributeError: 'NoneType' object has no attribute 'canvas' #18

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom
Closed
1kastner opened this issue Aug 17, 2022 · 6 comments · Fixed by #19
Closed

[Bug]: Figure manager is gone - AttributeError: 'NoneType' object has no attribute 'canvas' #18

1kastner opened this issue Aug 17, 2022 · 6 comments · Fixed by #19

Comments

@1kastner
Copy link
Contributor

Inside my Jupyter Notebooks, I want to create several plots with matplotlib. Since the release of v0.1.5, my CI for my docs and unittests is failing now.

The error message goes like this:

 File ~/work/conflowgen/conflowgen/conflowgen/analyses/inbound_and_outbound_vehicle_capacity_analysis_report.py:77, in InboundAndOutboundVehicleCapacityAnalysisReport.get_report_as_graph(self, **kwargs)
     71 df = pd.DataFrame({
     72     "inbound volume (in TEU)": inbound_capacities,
     73     "outbound volume (in TEU)": outbound_actual_capacities,
     74     "outbound maximum capacity": outbound_maximum_capacities
     75 })
     76 df.index = [str(i).replace("_", " ") for i in df.index]
---> 77 ax = df.plot.barh()
     78 ax.set_xlabel("Capacity (in TEU)")
     79 ax.set_title("Inbound and outbound vehicle capacity analysis")

File ~/.local/lib/python3.8/site-packages/pandas/plotting/_core.py:1217, in PlotAccessor.barh(self, x, y, **kwargs)
   1133 @Appender(
   1134     """
   1135     See Also
   (...)
   1206 @Appender(_bar_or_line_doc)
   1207 def barh(self, x=None, y=None, **kwargs):
   1208     """
   1209     Make a horizontal bar plot.
   1210 
   (...)
   1215     other axis represents a measured value.
   1216     """
-> 1217     return self(kind="barh", x=x, y=y, **kwargs)

File ~/.local/lib/python3.8/site-packages/pandas/plotting/_core.py:972, in PlotAccessor.__call__(self, *args, **kwargs)
    969             label_name = label_kw or data.columns
    970             data.columns = label_name
--> 972 return plot_backend.plot(data, kind=kind, **kwargs)

File ~/.local/lib/python3.8/site-packages/pandas/plotting/_matplotlib/__init__.py:71, in plot(data, kind, **kwargs)
     69         kwargs["ax"] = getattr(ax, "left_ax", ax)
     70 plot_obj = PLOT_CLASSES[kind](data, **kwargs)
---> 71 plot_obj.generate()
     72 plot_obj.draw()
     73 return plot_obj.result

File ~/.local/lib/python3.8/site-packages/pandas/plotting/_matplotlib/core.py:328, in MPLPlot.generate(self)
    326 self._args_adjust()
    327 self._compute_plot_data()
--> 328 self._setup_subplots()
    329 self._make_plot()
    330 self._add_table()

File ~/.local/lib/python3.8/site-packages/pandas/plotting/_matplotlib/core.py:386, in MPLPlot._setup_subplots(self)
    384 else:
    385     if self.ax is None:
--> 386         fig = self.plt.figure(figsize=self.figsize)
    387         axes = fig.add_subplot(111)
    388     else:

File ~/.local/lib/python3.8/site-packages/matplotlib/pyplot.py:810, in figure(num, figsize, dpi, facecolor, edgecolor, frameon, FigureClass, clear, **kwargs)
    798     _api.warn_external(
    799         f"More than {max_open_warning} figures have been opened. "
    800         f"Figures created through the pyplot interface "
   (...)
    803         f"warning, see the rcParam `figure.max_open_warning`).",
    804         RuntimeWarning)
    806 manager = new_figure_manager(
    807     num, figsize=figsize, dpi=dpi,
    808     facecolor=facecolor, edgecolor=edgecolor, frameon=frameon,
    809     FigureClass=FigureClass, **kwargs)
--> 810 fig = manager.canvas.figure
    811 if fig_label:
    812     fig.set_label(fig_label)

AttributeError: 'NoneType' object has no attribute 'canvas'
AttributeError: 'NoneType' object has no attribute 'canvas'

I have checked the changes with git blame and saw that there is this line where the figure manager can turn None:
https://github.com/ipython/matplotlib-inline/blob/master/matplotlib_inline/backend_inline.py#L55 which has changed with commit 6380cd9.
Is it possible that this causes my issue? In my unittests, I use nbformat/nbconvert and for the docs I use nbsphinx. I am no expert in these tools myself but in each case just image files are generated and included in the output. They are in that sense not interactive. However, I still need the figure manager not to be None! A bit of discussion regarding this can be found at matplotlib/matplotlib#23648. There, it was mentioned that when the figure manager is None, something fishy is going on.

I am no expert in either tool. My first guess work, however, is that in 6380cd9 and later commits possibly some edge cases were not covered? I would love if you could have a look! Thank you!
@jklymak jklymak mentioned this issue Aug 17, 2022
Closed
@anntzer
Copy link
Contributor

anntzer commented Aug 17, 2022

Sorry, that return should have been a return manager, I think. Not in front of my computer right now so feel free to make a pr out of the suggestion, or I'll do one when I can.

1kastner added a commit to 1kastner/matplotlib-inline that referenced this issue Aug 17, 2022
@1kastner
Return manager instead of None
023bc08 
Fixes ipython#18
@1kastner 1kastner mentioned this issue Aug 17, 2022
Merged
@1kastner
Copy link
Contributor Author

Thanks a lot, I have done as you have proposed!

@fperez fperez mentioned this issue Aug 18, 2022
Merged
fperez added a commit that referenced this issue Aug 18, 2022
@fperez
Merge pull request #19 from 1kastner/patch-1
6bc258f 
Return manager instead of None - fixes #18.

Will release quickly a 0.1.6 with this fix.
fperez added a commit that referenced this issue Aug 18, 2022
@fperez
Release 0.1.6 to fix #18.
fbf0ab8
@fperez
Copy link
Member

fperez commented Aug 18, 2022

Thx @1kastner for the fix! I just pushed 0.1.6 with this fix to PyPI, should be up on conda-forge soon.

Sorry @sryza for the hassles and thx for the prompt report.

@1kastner
Copy link
Contributor Author

@fperez thanks for the fast reaction and no worries. I just checked the repository and I was wondering whether there are any automated checks in place for the code? For example, unittests or Python type hints in combination with code linting might have helped to spot such an issue before release. I am just saying this because many, many people rely on this package.

1kastner added a commit to 1kastner/conflowgen that referenced this issue Aug 18, 2022
@1kastner
Drop explicit installation of matplotlib-inline
e3c3282 
The issues should eb solved in ipython/matplotlib-inline#18
@1kastner 1kastner mentioned this issue Aug 18, 2022
Merged
1kastner added a commit to 1kastner/conflowgen that referenced this issue Aug 18, 2022
@1kastner
Drop explicit installation of matplotlib-inline (#141)
7350ddc 
The issues has been solved in ipython/matplotlib-inline#18
@fperez
Copy link
Member

fperez commented Aug 18, 2022

No, there aren't - yesterday I was very pressed for time and basically had to decide "do I spend the window I have adding some CI/tests to this, or do I finish this release quickly so the manual fix is out?" And I went for the latter, but given all my preaching about good testing, I felt bad about it :)

This package is tiny and moves very rarely, so in the past it hasn't been too terrible, but I 100% agree we should. Even putting in a few high-level tests in a notebook would be useful.

I'll try to find the time for that now that 0.1.6 is out and we're back where we needed to, but feel free to beat me to it!

@1kastner
Copy link
Contributor Author

1kastner commented Aug 19, 2022 •
edited
Loading

I completely feel you! Some aspects can be tested better, such as "does this throw an exception in situations it should not", and some worse, such as "does it look beautiful". I have seen projects where they started a pixel-wise comparison of the expected and intended output. I believe humans are better in that task and it might be over the top for this project. But it is one important step to make the decision where to draw the line. I guess unittesting might be helpful but time-consuming as well.

If there is some testing infrastructure in place that the leading maintainers are all happy with, I could add one or two automated tests as well - probably some nbconvert invocations or something similar.

@QuLogic QuLogic mentioned this issue Nov 30, 2022
Closed
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
None yet
Projects
None yet
Milestone
No milestone
Development

Successfully merging a pull request may close this issue.

Return manager instead of None 1kastner/matplotlib-inline
3 participants
@fperez @anntzer @1kastner