I've been working on the GUI event loop hooks in IPython, and while working on this issue, I realized that importing backend_inline will trigger matplotlib's "auto backend selection". In many systems, this results in selecting QtAgg and thus in IPython, this effectively calls %gui qt.

The issue is that 'qt' as far as GUI event loop hooks go implies "latest version of Qt", and once a version of Qt is imported in a session, you can't change it. So on a system with e.g. pyside6 and PyQt5 installed, starting IPython with --matplotlib=qt5 will result in an effective %gui qt call, which will import pyside6, followed by a %gui qt5 call, which will refuse to run because it cannot import PyQt5.

The culprit is this:

I believe that should instead call _get_backend_or_none(), i.e. you want to see if a backend is loaded, you don't want to cause the default to be loaded.

I prevented IPython from importing backend_inline where the problem starts (see here) and it seems to cause no difference in Jupyter notebook - so I'm not entirely sure what matplotlib-inline is supposed to be doing. It's quite likely I don't understand what I'm even testing here.

Hello,

I was taking a look at https://pypi.org/project/matplotlib-inline/ .

Is there any reason why as a source/homepage it points to a fork of @martinRenou instead of this repo? Isn't this the "official" repo? As of my understanding, Martin currently works for your organization so it is possible there was a mistake when publishing to Pypi?

To me it feels strange to have the official package source to be here (ipython/matplotlib-inline) but deployed/owned by Martin on Pypi (via martinRenou/matplotlib-inline, which clearly is shown by GitHub as a fork) .

Thanks for the clarification,

Cristian

While attempting to create a piano roll with librosa and matplotlib, like this:

def plot_piano_roll(pm, start_pitch, end_pitch, fs=100):
    # Use librosa's specshow function for displaying the piano roll
    librosa.display.specshow(pm.get_piano_roll(fs)[start_pitch:end_pitch],
                             hop_length=1, sr=fs, x_axis='time', y_axis='cqt_note',
                             fmin=pretty_midi.note_number_to_hz(start_pitch))

plt.figure(figsize=(8, 4))
plot_piano_roll(pm, 56, 70)

I encounter this error:

AttributeError                            Traceback (most recent call last)
File ~/anaconda3/lib/python3.9/site-packages/matplotlib_inline/backend_inline.py:100, in show(close, block)
     97 # only call close('all') if any to close
     98 # close triggers gc.collect, which can be slow
     99 if close and Gcf.get_all_fig_managers():
--> 100     matplotlib.pyplot.close('all')

File ~/anaconda3/lib/python3.9/site-packages/matplotlib/_api/__init__.py:226, in caching_module_getattr.<locals>.__getattr__(name)
    224 if name in props:
    225     return props[name].__get__(instance)
--> 226 raise AttributeError(
    227     f"module {cls.__module__!r} has no attribute {name!r}")

AttributeError: module 'matplotlib' has no attribute 'pyplot'

The error seems to be fixed if I explicitly declare import matplotlib.pyplot as plt at the start of the file and then use that to call it like this: plt.close('all'). If that alone is satisfactory, I would request to do a PR.

This package doesn't contain the figure formatters it uses, which are still all defined in IPython.core.pylabtools. Should they be here so that upgrading the matplotlib-inline package upgrades the inline-figure formatters?

@martinRenou ? Want to add ad from . import backend_inline in __init__.py ?

See ipython/ipython#13206 (comment)_

I found that in a fresh Jupyter kernel, the following snippet prevents further figures to be rendered:

# cell 1
import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter

with plt.style.context('seaborn'):
    fig, ax = plt.subplots(figsize=(5, 5))
    ax.xaxis.set_major_formatter(DateFormatter("%H:%M"))

This figure ("cell 1") is rendered, but new figures are not rendered any more in a notebook:

# cell 2
fig, ax = plt.subplots(figsize=(5, 5))  # not rendered

The issue does not appear in any of the following case:

• "cell 2" is run before "cell 1": all following figures are then properly rendered
• The %matplotlib inline instruction is explicitly added, before or after "cell 1"
• The context manager is not used (but it fails with any stylesheet)
• The DateFormatter is not applied

I have one notebook cell that creates a 3D axes, which I want to plot into in the next cell.

With the inline backend

we see that the "current plot" has been forgotten, and plt.gca() creates a new 2D plot.

With the notebook backend

The behaviour is different

and plt.gca() remembers the 3D plot across the cell boundaries.

Expected behaviour

The same in both cases, ideally the remembering the current plot across the cell boundary. I'm not sure which behaviour is "correct" but the difference is a problem when I'm running code in an ipython kernel from a client.

When using png and svg as the figure_format, I'd expect the displayed figures to be of the same size, but they are not:

Should they be the same size?

The last release of matplotlib-inline is 0.1.3 from 9 months ago (Sept. 2021).
There have been several code changes since.
Specifically I am interested in commit a433a89 from May 12/13th which includes dropping some Matplotlib rcParams overrides that were specific to ipython notebooks.
I would like to know if any schedule is currently in place for this commit to be published.
Thanks.

See matplotlib/matplotlib#14171, especially matplotlib/matplotlib#14171 (comment)

IPYthon docs lead me here -
https://ipython.readthedocs.io/en/stable/api/generated/IPython.display.html#IPython.display.set_matplotlib_formats

they suggest:

"deprecated since version 7.23: use matplotlib_inline.backend_inline.set_matplotlib_formats()"

It's not entirely clear how to call this API.

This is what I"m doing

from IPython import get_ipython
get_ipython().run_line_magic("matplotlib", "inline")
import matplotlib_inline.backend_inline
matplotlib_inline.backend_inline.set_matplotlib_formats()

Is this the correct convention for using this API via python?

Cheers, thanks for the great library.

Just find it a bit weird that mpl isn't listed in install_requires.

Using plt.interactive(False) or plt.ioff() in Jupyter (Lab and classic notebook) does not seem to prevent automatic figure generation, unless the magic %matplotlib inline in run first, even though the inline backend is the default.

Example

import matplotlib.pyplot as plt

plt.ioff()

fig, ax = plt.subplots()
a = 0

The figure still appears automatically under the cell.

Note that

Explicitly running %matplotlib inline blocks figure creation (even though inline is the default activated backend in Jupyter):

Originally posted in matplotlib/matplotlib#23766

The removal of the Matplotlib RC overrides in #14 by @fperez has given me hope to one day get good defaults for inline plots.

What about setting the default output format to SVG (instead of the current PNG)?

This would provide the correct plot size in notebooks and I guess it would also improve the perceived plot quality in most cases.

I've used SVG for years via local settings, but it would be great to have it as the default.

A possible objection would be that SVG plots can become quite large if there is a lot of data to plot, but I think in this case rasterization should be recommended.

Bug summary

plt.scatter gives UnicodeDecodeError: 'utf-8' codec can't decode byte 0x89 in position 0: invalid start byte error with notebook running python3 ipykernel, matplotlib-3.4.3, backend: module://matplotlib_inline.backend_inline.

Works fine when kernel is switched to python2, matplotlib-2.2.3, backend: module://ipykernel.pylab.backend_inline .

Code for reproduction

import matplotlib.pyplot as plt

X = [590,540,740,130,810,300,320,230,470,620,770,250]
Y = [32,36,39,52,61,72,77,75,68,57,48,48]
print(X)
print(Y)

plt.scatter(X,Y)

Actual outcome

[590, 540, 740, 130, 810, 300, 320, 230, 470, 620, 770, 250]
[32, 36, 39, 52, 61, 72, 77, 75, 68, 57, 48, 48]
<matplotlib.collections.PathCollection at 0x7fd16a4d8390>
---------------------------------------------------------------------------
UnicodeDecodeError                        Traceback (most recent call last)
~/.local/lib/python3.7/site-packages/matplotlib_inline/backend_inline.py in show(close, block)
     41             display(
     42                 figure_manager.canvas.figure,
---> 43                 metadata=_fetch_figure_metadata(figure_manager.canvas.figure)
     44             )
     45     finally:

~/.local/lib/python3.7/site-packages/IPython/core/display.py in display(include, exclude, metadata, transient, display_id, *objs, **kwargs)
    325                 # kwarg-specified metadata gets precedence
    326                 _merge(md_dict, metadata)
--> 327             publish_display_data(data=format_dict, metadata=md_dict, **kwargs)
    328     if display_id:
    329         return DisplayHandle(display_id)

~/.local/lib/python3.7/site-packages/IPython/core/display.py in publish_display_data(data, metadata, source, transient, **kwargs)
    120         data=data,
    121         metadata=metadata,
--> 122         **kwargs
    123     )
    124 

~/.local/lib/python3.7/site-packages/ipykernel/zmqshell.py in publish(self, data, metadata, transient, update)
    137 
    138         self.session.send(
--> 139             self.pub_socket, msg, ident=self.topic,
    140         )
    141 

~/.local/lib/python3.7/site-packages/jupyter_client/session.py in send(self, stream, msg_or_type, content, parent, ident, buffers, track, header, metadata)
    828         if self.adapt_version:
    829             msg = adapt(msg, self.adapt_version)
--> 830         to_send = self.serialize(msg, ident)
    831         to_send.extend(buffers)
    832         longest = max([len(s) for s in to_send])

~/.local/lib/python3.7/site-packages/jupyter_client/session.py in serialize(self, msg, ident)
    702             content = self.none
    703         elif isinstance(content, dict):
--> 704             content = self.pack(content)
    705         elif isinstance(content, bytes):
    706             # content is already packed, as in a relayed message

~/.local/lib/python3.7/site-packages/jupyter_client/session.py in json_packer(obj)
     97         default=json_default,
     98         ensure_ascii=False,
---> 99         allow_nan=False,
    100     )
    101 

/usr/lib/python3/dist-packages/zmq/utils/jsonapi.py in dumps(o, **kwargs)
     38         kwargs['separators'] = (',', ':')
     39 
---> 40     s = jsonmod.dumps(o, **kwargs)
     41 
     42     if isinstance(s, unicode):

/usr/lib/python3/dist-packages/simplejson/__init__.py in dumps(obj, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, encoding, default, use_decimal, namedtuple_as_object, tuple_as_array, bigint_as_string, sort_keys, item_sort_key, for_json, ignore_nan, int_as_string_bitcount, iterable_as_array, **kw)
    397         ignore_nan=ignore_nan,
    398         int_as_string_bitcount=int_as_string_bitcount,
--> 399         **kw).encode(obj)
    400 
    401 

/usr/lib/python3/dist-packages/simplejson/encoder.py in encode(self, o)
    294         # exceptions aren't as detailed.  The list call should be roughly
    295         # equivalent to the PySequence_Fast that ''.join() would do.
--> 296         chunks = self.iterencode(o, _one_shot=True)
    297         if not isinstance(chunks, (list, tuple)):
    298             chunks = list(chunks)

/usr/lib/python3/dist-packages/simplejson/encoder.py in iterencode(self, o, _one_shot)
    376                 self.iterable_as_array, Decimal=decimal.Decimal)
    377         try:
--> 378             return _iterencode(o, 0)
    379         finally:
    380             key_memo.clear()

/usr/lib/python3/dist-packages/simplejson/encoder.py in encode_basestring(s, _PY3, _q)
     42     if _PY3:
     43         if isinstance(s, bytes):
---> 44             s = str(s, 'utf-8')
     45         elif type(s) is not str:
     46             # convert an str subclass instance to exact str

UnicodeDecodeError: 'utf-8' codec can't decode byte 0x89 in position 0: invalid start byte

Expected outcome

plt.show() right after this should give an image of the plot.

Operating system

Debian 10 (Skolelinux)

Matplotlib Version

3.4.3

Matplotlib Backend

module://matplotlib_inline.backend_inline

Python version

3.7.3

Jupyter version

5.7.8

Other libraries

No response

Installation

pip

Conda channel

No response

I often work with complex matplotlib figures with millions of points, which I've been displaying in my notebooks using the ipython magic %config InlineBackend.figure_format = 'retina'. Unfortunately, these inline images are quite large in terms of file size.

I'm looking for general suggestions on how to reduce the size of my ipynb files, which can grow into the 10s or even hundreds of MB in size and become a bit unwieldy.

One thought I had was to switch to generating jpegs, but while it looks like I can meaningfully reduce the file size by switching the backend to jpeg and increasing the dpi to 2x:

from matplotlib import rcParams
%config InlineBackend.figure_format = 'jpeg'
rcParams['figure.dpi'] = 200

From this repo, it looks like I can dial in jpeg compression values, which should help reduce file size. However, I can't figure out how to size the jpegs appropriately for a retina display (they're twice as large as they should be, and slightly blurry). Is there a way to display jpegs in jupyter notebooks at similar resolution and size to the defaults provided by 'retina' mode?

See also:
Matplotlib issue
Stackoverflow question

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!