[Bug]: Rendering inconsistency between matplotlib-inline `plt.show()` and `fig.savefig(...)` #24281

posita · 2022-10-26T21:41:28Z

Bug summary

This originally came up in jupyterlite/jupyterlite#850, but I'm pretty sure the root cause is here. I'll reproduce the most helpful comment from that thread here. The following is a pretty good demonstration of how savefig clips (e.g.) the title of a pie chart.

Possibly related issues:

Code for reproduction

Run the following in Jupyter Lab to reproduce the attached images.

import matplotlib.pyplot
import base64, io
from enum import Enum
from ipywidgets import widgets
from fractions import Fraction
from itertools import chain

data = {3: Fraction(1, 216), 4: Fraction(1, 72), 5: Fraction(1, 36), 6: Fraction(5, 108), 7: Fraction(5, 72), 8: Fraction(7, 72), 9: Fraction(25, 216), 10: Fraction(1, 8), 11: Fraction(1, 8), 12: Fraction(25, 216), 13: Fraction(7, 72), 14: Fraction(5, 72), 15: Fraction(5, 108), 16: Fraction(1, 36), 17: Fraction(1, 72), 18: Fraction(1, 216)}

class Format(str, Enum):
    NATIVE = "native"
    PNG = "png"
    SVG = "svg"

class PngImage:
    def __init__(self, data):
        self.data = data

    def _repr_png_(self):
        return base64.b64encode(self.data).decode()

class SvgImage:
    def __init__(self, data):
        self.data = data

    def _repr_svg_(self):
        return self.data.decode()

@widgets.interact
def show(output_to_format = Format, use_subplots: bool = True):
    with matplotlib.style.context("bmh"):
        if use_subplots:
            _, ax = matplotlib.pyplot.subplots()
        else:
            fig = matplotlib.pyplot.figure()
            xmin, ymin, dx, dy = 0.1, 0.1, 0.9, 0.9
            ax = fig.add_axes((xmin, ymin, dx, dy))
        unique_outcomes = sorted(data.keys())
        ax.set_title(
            "Super duper duper long title that will probably exceed the width of the pie chart",
            fontdict={"fontweight": "bold",},
        )
        outcomes, values = zip(*((outcome, float(value)) for outcome, value in data.items()))
        ax.pie(outcomes, values)
        if output_to_format is Format.NATIVE:
            matplotlib.pyplot.show()
        else:
            buf = io.BytesIO()
            matplotlib.pyplot.savefig(buf, format=output_to_format)
            if output_to_format is Format.PNG:
                display(PngImage(buf.getvalue()))
            elif output_to_format is Format.SVG:
                display(SvgImage(buf.getvalue()))
            else:
                assert False, "should never be here"
            matplotlib.pyplot.clf()

print(matplotlib.__version__)

Actual outcome

Output method	Using `subplots`	Using `add_axes`
`show()`
`savefig(..., format="png")`
`savefig(..., format="svg")`

Expected outcome

I expected all backends to produce at least similar results (i.e., not ones where titles were clipped or missing entirely).

Additional information

No response

Operating system

No response

Matplotlib Version

3.5.2, 3.6.1

Matplotlib Backend

module://matplotlib_inline.backend_inline

Python version

3.10.6

Jupyter version

Lab 3.4.8

Installation

No response

The text was updated successfully, but these errors were encountered:

jklymak · 2022-10-26T21:52:07Z

It looks like the widget is doing the equivalent of matplotlib.pyplot.savefig(buf, format=output_to_format, bbox_inches='tight') which will clip the figure to whatever artists are in it. That is the choice the inline backend makes as well. I don't think this is a bug, or actionable on our part.

posita · 2022-10-26T21:59:17Z

It looks like the widget is doing the equivalent of matplotlib.pyplot.savefig(buf, format=output_to_format, bbox_inches='tight') which will clip the figure to whatever artists are in it. That is the choice the inline backend makes as well. I don't think this is a bug, or actionable on our part.

Why would that yield a different result from, say matplotlib.pyplot.tight_layout() ; matplotlib.pyplot.show()?

posita · 2022-10-26T22:06:44Z

@jklymak, how would one go about getting similar results for both matplotlib.pyplot.show() and matplotlib.pyplot.savefig(...) then? Or are you saying this is an ipywidgets issue and should be filed against that project?

jklymak · 2022-10-26T22:12:38Z

It looks like the widget is doing the equivalent of matplotlib.pyplot.savefig(buf, format=output_to_format, bbox_inches='tight') which will clip the figure to whatever artists are in it. That is the choice the inline backend makes as well. I don't think this is a bug, or actionable on our part.

Why would that yield a different result from, say matplotlib.pyplot.tight_layout() ; matplotlib.pyplot.show()?

Because bbox_inches='tight' clips the figure to the artists as draw, plt.tight_layout adjusts the size of the axes so the artists fit in the figure, but doesn't change the size of the figure.

@jklymak, how would one go about getting similar results for both matplotlib.pyplot.show() and matplotlib.pyplot.savefig(...) then?

To get similar results, you pass bbox_inches='tight' to savefig. I think there is also a configuration option to change ipython to not do bbox_inches='tight', but forget what it is.

QuLogic · 2022-10-26T22:47:41Z

ipywidgets uses the inline backend to display plots. That defaults to a tight bbox.

It can be disabled by overriding their save options.

Going to close as not our bug.

posita · 2022-10-26T22:47:53Z

Thanks for the insight! That actually led me to finding jupyter/notebook#2640, including jupyter/notebook#2640 (comment) , which offers a way to bring parity.

UPDATE: Hah! Beat me to it, @QuLogic!

tacaswell · 2022-10-26T22:48:35Z

To be very clear here, there are a bunch of moving parts:

matplotlib
matplotlib.pyplot (the stateful MATLAB-like plotting application we provide)
malptolib-inline (the backend you are using that is externally maintained)
ipywidgets (which is involved in the example but not responsible for any of the problems)

that have become a bit tangled. I just want to make sure we are not talking past each other.

The inline backend (which used to be part of IPython and is now its own package) partially replicates the desktop interactive backends by dropping a static png into the output cells of the notebook when it would have normally poped up a GUI window. The png is embeded in the notebook as a data URL with the base64 encoded binary and the png data is rendered using (effectively) fig.savefig(buf, bbox_inches='tight'). The use of bbox_inches='tight' is the key detail as it clips the figure size to exactly fit the artists in the Figure. The somewhat surprising behavior of this clipping is that in addition to making the Figure smaller (trimming whitespace), it also can make the figure effectively bigger.

A minimal example to reproduce this behavior:

import matplotlib.pyplot
from fractions import Fraction


import matplotlib.pyplot as plt

data = {
    3: Fraction(1, 216),
    4: Fraction(1, 72),
    5: Fraction(1, 36),
    6: Fraction(5, 108),
    7: Fraction(5, 72),
    8: Fraction(7, 72),
    9: Fraction(25, 216),
    10: Fraction(1, 8),
    11: Fraction(1, 8),
    12: Fraction(25, 216),
    13: Fraction(7, 72),
    14: Fraction(5, 72),
    15: Fraction(5, 108),
    16: Fraction(1, 36),
    17: Fraction(1, 72),
    18: Fraction(1, 216),
}

fig, ax = matplotlib.pyplot.subplots(figsize=(4, 4))
unique_outcomes = sorted(data.keys())
ax.set_title(
    "Super duper duper long title that will probably exceed the width of the pie chart",
    fontdict={
        "fontweight": "bold",
    },
)
outcomes, values = zip(*((outcome, float(value)) for outcome, value in data.items()))
ax.pie(outcomes, values)
# this will clip the title, but will be the size you asked for
fig.savefig('test1.png')                       
# this will include the full title, but it is bigger than you asked for and not square
fig.savefig('test2.png', bbox_inches='tight')

There is no chance that we will change the default behavior of savefig to do this resizing (targeting fixed-sized figures is a major part of what we do) and I think it is also far too late for matplotlib-inline to change their default (the wave of bug reports of people who implicitly depended on this would be huge!).

I think you option are either to pass bbox_inches='tight' when you save or configure the inline backend to not pass it (I think

%config InlineBackend.print_figure_kwargs = {'bbox_inches':None}

will work interactively and there is a way to put this in your profile configuration files).

https://stackoverflow.com/questions/37864735/matplotlib-and-ipython-notebook-displaying-exactly-the-figure-that-will-be-save

I took the liberty of updating the title to include matplotlib-inline.

posita · 2022-10-29T01:12:42Z

Thanks @tacaswell! That is a great breakdown and very helpful not only for me in understanding the layers, but hopefully for folks developing JupyterLite or anyone else who stumbles across this issue. I really appreciate you taking the time to lay it all out in such a way that even a stranger to these technologies (like me) can easily understand. It am especially grateful for the layout of possible options and explanations of why some were off the table. I feel much more aware of things now.

Many, many thanks again! 🙇

tacaswell · 2022-10-29T19:30:12Z

@posita Your welcome!

posita mentioned this issue Oct 26, 2022

matplotib margins/padding are not consistent with (and sometimes radically different from) Jupyter Lab jupyterlite/jupyterlite#850

Closed

jklymak added the status: needs clarification Issues that need more information to resolve. label Oct 26, 2022

tacaswell changed the title ~~[Bug]: Rendering inconsistency between plt.show() and fig.savefig(...)~~ [Bug]: Rendering inconsistency between matplotlib-inline plt.show() and fig.savefig(...) Oct 26, 2022

QuLogic closed this as not planned Won't fix, can't repro, duplicate, stale Oct 26, 2022

posita closed this as completed Oct 26, 2022

posita closed this as not planned Won't fix, can't repro, duplicate, stale Oct 26, 2022

posita mentioned this issue Oct 29, 2022

JupyterLite 8000 needs default consistent with %config InlineBackend.print_figure_kwargs = {'bbox_inches':'tight'} jupyterlite/jupyterlite#856

Closed

jklymak mentioned this issue Nov 21, 2022

[Bug]: Custom backend stopped working in 3.6.2 #24524

Closed

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[Bug]: Rendering inconsistency between matplotlib-inline `plt.show()` and `fig.savefig(...)` #24281

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[Bug]: Rendering inconsistency between matplotlib-inline `plt.show()` and `fig.savefig(...)` #24281

[Bug]: Rendering inconsistency between matplotlib-inline `plt.show()` and `fig.savefig(...)` #24281