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plt.bar with nan input fails rendering in notebook using 3.3.0rc1 #17868
Description
Bug report
Bug summary
A previously-working code (that gets to plot well using other backends or matplotlib==3.2.2) fails to render a plot on Jupyter notebook when using matplotlib==3.3.0rc1. This has to do with np.nan input to plt.bar.
Code for reproduction
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
%matplotlib inline
x = range(2)
heights = np.asarray([np.nan, 4])
plt.bar(x, heights)Actual outcome
<BarContainer object of 2 artists>
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
~/.local/lib/python3.8/site-packages/IPython/core/formatters.py in __call__(self, obj)
339 pass
340 else:
--> 341 return printer(obj)
342 # Finally look for special method names
343 method = get_real_method(obj, self.print_method)
~/.local/lib/python3.8/site-packages/IPython/core/pylabtools.py in <lambda>(fig)
246
247 if 'png' in formats:
--> 248 png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
249 if 'retina' in formats or 'png2x' in formats:
250 png_formatter.for_type(Figure, lambda fig: retina_figure(fig, **kwargs))
~/.local/lib/python3.8/site-packages/IPython/core/pylabtools.py in print_figure(fig, fmt, bbox_inches, **kwargs)
130 FigureCanvasBase(fig)
131
--> 132 fig.canvas.print_figure(bytes_io, **kw)
133 data = bytes_io.getvalue()
134 if fmt == 'svg':
~/miniconda/envs/seaborn_devenv/lib/python3.8/site-packages/matplotlib/backend_bases.py in print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)
2186 self.figure.draw(renderer)
2187
-> 2188 bbox_inches = self.figure.get_tightbbox(
2189 renderer, bbox_extra_artists=bbox_extra_artists)
2190 if pad_inches is None:
~/miniconda/envs/seaborn_devenv/lib/python3.8/site-packages/matplotlib/figure.py in get_tightbbox(self, renderer, bbox_extra_artists)
2500
2501 for a in artists:
-> 2502 bbox = a.get_tightbbox(renderer)
2503 if bbox is not None and (bbox.width != 0 or bbox.height != 0):
2504 bb.append(bbox)
~/miniconda/envs/seaborn_devenv/lib/python3.8/site-packages/matplotlib/artist.py in get_tightbbox(self, renderer)
276 The enclosing bounding box (in figure pixel coordinates).
277 """
--> 278 bbox = self.get_window_extent(renderer)
279 if self.get_clip_on():
280 clip_box = self.get_clip_box()
~/miniconda/envs/seaborn_devenv/lib/python3.8/site-packages/matplotlib/patches.py in get_window_extent(self, renderer)
596
597 def get_window_extent(self, renderer=None):
--> 598 return self.get_path().get_extents(self.get_transform())
599
600 def _convert_xy_units(self, xy):
~/miniconda/envs/seaborn_devenv/lib/python3.8/site-packages/matplotlib/path.py in get_extents(self, transform, **kwargs)
590 self = transform.transform_path(self)
591 bbox = Bbox.null()
--> 592 for curve, code in self.iter_bezier(**kwargs):
593 # places where the derivative is zero can be extrema
594 _, dzeros = curve.axis_aligned_extrema()
~/miniconda/envs/seaborn_devenv/lib/python3.8/site-packages/matplotlib/path.py in iter_bezier(self, **kwargs)
442 if first_vert is None:
443 if code != Path.MOVETO:
--> 444 raise ValueError("Malformed path, must start with MOVETO.")
445 if code == Path.MOVETO: # a point is like "CURVE1"
446 first_vert = verts
ValueError: Malformed path, must start with MOVETO.
<Figure size 432x288 with 1 Axes>
Expected outcome
3.2.2:
Matplotlib version
- Operating system: macOS
- Matplotlib version: 3.3.0rc1
- Matplotlib backend (
print(matplotlib.get_backend())): 'module://ipykernel.pylab.backend_inline' - Python version: 3.8.3
- Jupyter version (if applicable): notebook 6.0.3, IPython 7.15.0
- Other libraries:
matplotlib installed using pip
python installed from conda-forge
Activity
dstansby commentedon Jul 9, 2020
I can reproduce this with the current master branch in a jupyter notebook.
dstansby commentedon Jul 9, 2020
Bisects to 95a530c
dstansby commentedon Jul 9, 2020
Some more digging, and I think the changes in #16832 are exposing a pre-existing bug in
_path.cleanup_path. The code path to this error includes_path.cleanup_pathbeing called withremove_nans=Trueonand it is returning
which is odd, I would expect it to return something empty since the input was all NaNs. This then propagates to a point where matplotlib complains, because this path does not start with a
MOVETO(ie.1) code.QuLogic commentedon Jul 9, 2020
cc @brunobeltran
brunobeltran commentedon Jul 10, 2020
This appears to simply be a missed corner case in my rewrite of
get_extents(tbh, I thought I checked the all-NaN's case, sorry...). I'll push a fix with a new test in a minute!brunobeltran commentedon Jul 11, 2020
After some digging: in
_path.h, thecleanup_pathfunction removes NaN's using the algorithm inPathNanRemover's constructor. When this function encounters a NaN, it replaces that BezierSegment in the Path by a MOVETO (no-op) whose vertex is taken from the first control point of the next BezierSegment in the Path.However, due to the way that
PathNanRemover's logic is arranged,CLOSEPOLYcommands are always passed thru as-is regardless of whether or non they are NaN (except in corner cases where there should not have been aCLOSEPOLYthere in the first place, likecoces=[1, 3, 79, 0])Our C++ implementation of
update_path_extentsdoesn't mind this, because it doesn't actually deal correctly with Path's that contain curves, so it can just go through the control points one by one and if it finds aCLOSEPOLY, it knows that by definition it has already seen that control point before, so it can just ignore it:However, the new
Path.get_extentsdoes correctly deal with arbitrary Paths, but to do so it relies onPath.cleanedto return a valid Path, (which it currently does not, per the above).As pointed out by David, this is definitely a bug in
Path.cleaned. I initially was tempted to just patchPath.iter_bezierto look out forCLOSEPOLYcommands that contain aNaNexplicitly and just skip them (hence my comment above), but I think the correct solution is to just fixPathNanRemover. Thankfully, the algorithm it uses is very straightforward so this shouldn't be too hard....