Cannot manually close matplotlib plot window in Mac OS X Yosemite

[Auerilas]

I'm running Python v2.7 and matplotlib v1.5.0 on Mac OS X Yosemite. Up to recently, I was able to run my script in the interactive interpreter, show a plot, and then manually kill the window. For example

import numpy as np
x = np.arange(1,10)
y = np.arange(1,10)
plt.plot(x,y)
plt.show()

This used to work fine. The window would close and I'd return to the prompt. However, now when I hit the red X to close the window, the window remains open. My command prompt returns and works fine, but the window is stuck and I see the spinning beach ball over it.

It's not until I run the script a second time that the first window closes, but then I'm stuck with a second open plot with the same problem. I'm a bit confused because this only happened recently. Up till now, the window would close fine.

It's not a huge issue, because Python still runs and I can still make new plots, but I'm curious as to why the window would all of a sudden stick open.

[tacaswell]

attn @mdehoon

@Auerilas Thanks for moving this over from SO

[mdehoon]

@Auerilas I have not been able to replicate this bug. Can you post the exact script that you are using, and also your matplotlibrc file (which you can find in $HOME/.matplotlib/matplotlibrc)? Then I can try and reproduce this.

[Auerilas]

Sure. Before I do though, I’ve learned a little bit more. It appears that this is a conflict with the ete2 module for working with phylogenetic trees. If I don’t import ete2 (comment out the line), the MacOSX backend works fine. If I do import it, the window hangs. The CocoaAgg backend leads to a hanging window, regardless of whether or not ete2 is imported.

Alternatively, I can use the TkAgg backend which sometimes (not always) leads to this error:

called Tcl_FindHashEntry on deleted table
Abort trap: 6

This appears to be related to TK but I don’t know what it means.

So for now I’m using the Qt4Agg backend, which for now appears to the most stable, although I prefer MacOSX or TkAgg.

Here’s the script:

import matplotlib.pyplot as plt
import numpy as np
#import ete2 as ete
import seaborn as sns
sns.set(context='talk', style='ticks', font_scale=1.2, rc={'figure.figsize': (6.5, 5.5), 'xtick.direction': 'in', 'ytick.direction': 'in'})
x = np.arange(1,10)
plt.plot(x, x)
plt.show()

And here’s the matplotlibrc file:

MATPLOTLIBRC FORMAT

This is a sample matplotlib configuration file - you can find a copy

of it on your system in

site-packages/matplotlib/mpl-data/matplotlibrc. If you edit it

there, please note that it will be overwritten in your next install.

If you want to keep a permanent local copy that will not be

overwritten, place it in the following location:

unix/linux:

$HOME/.config/matplotlib/matplotlibrc or

$XDG_CONFIG_HOME/matplotlib/matplotlibrc (if $XDG_CONFIG_HOME is set)

other platforms:

$HOME/.matplotlib/matplotlibrc

See http://matplotlib.org/users/customizing.html#the-matplotlibrc-file for

more details on the paths which are checked for the configuration file.

This file is best viewed in a editor which supports python mode

syntax highlighting. Blank lines, or lines starting with a comment

symbol, are ignored, as are trailing comments. Other lines must

have the format

key : val # optional comment

Colors: for the color values below, you can either use - a

matplotlib color string, such as r, k, or b - an rgb tuple, such as

(1.0, 0.5, 0.0) - a hex string, such as ff00ff or #ff00ff - a scalar

grayscale intensity such as 0.75 - a legal html color name, e.g., red,

blue, darkslategray

CONFIGURATION BEGINS HERE

The default backend; one of GTK GTKAgg GTKCairo GTK3Agg GTK3Cairo

CocoaAgg MacOSX Qt4Agg Qt5Agg TkAgg WX WXAgg Agg Cairo GDK PS PDF SVG

Template.

You can also deploy your own backend outside of matplotlib by

referring to the module name (which must be in the PYTHONPATH) as

'module://my_backend'.

backend : MacOSX

If you are using the Qt4Agg backend, you can choose here

to use the PyQt4 bindings or the newer PySide bindings to

the underlying Qt4 toolkit.

#backend.qt4 : PySide # PyQt4 | PySide

Note that this can be overridden by the environment variable

QT_API used by Enthought Tool Suite (ETS); valid values are

"pyqt" and "pyside". The "pyqt" setting has the side effect of

forcing the use of Version 2 API for QString and QVariant.

The port to use for the web server in the WebAgg backend.

webagg.port : 8888

If webagg.port is unavailable, a number of other random ports will

be tried until one that is available is found.

webagg.port_retries : 50

When True, open the webbrowser to the plot that is shown

webagg.open_in_browser : True

When True, the figures rendered in the nbagg backend are created with

a transparent background.

nbagg.transparent : True

if you are running pyplot inside a GUI and your backend choice

conflicts, we will automatically try to find a compatible one for

you if backend_fallback is True

#backend_fallback: True

#interactive : False
#toolbar : toolbar2 # None | toolbar2 ("classic" is deprecated)
#timezone : UTC # a pytz timezone string, e.g., US/Central or Europe/Paris

Where your matplotlib data lives if you installed to a non-default

location. This is where the matplotlib fonts, bitmaps, etc reside

#datapath : /home/jdhunter/mpldata

LINES

See http://matplotlib.org/api/artist_api.html#module-matplotlib.lines for more

information on line properties.

#lines.linewidth : 1.0 # line width in points
#lines.linestyle : - # solid line
#lines.color : blue # has no affect on plot(); see axes.prop_cycle
#lines.marker : None # the default marker
#lines.markeredgewidth : 0.5 # the line width around the marker symbol
#lines.markersize : 6 # markersize, in points
#lines.dash_joinstyle : miter # miter|round|bevel
#lines.dash_capstyle : butt # butt|round|projecting
#lines.solid_joinstyle : miter # miter|round|bevel
#lines.solid_capstyle : projecting # butt|round|projecting
#lines.antialiased : True # render lines in antialised (no jaggies)

#markers.fillstyle: full # full|left|right|bottom|top|none

PATCHES

Patches are graphical objects that fill 2D space, like polygons or

circles. See

http://matplotlib.org/api/artist_api.html#module-matplotlib.patches

information on patch properties

#patch.linewidth : 1.0 # edge width in points
#patch.facecolor : blue
#patch.edgecolor : black
#patch.antialiased : True # render patches in antialised (no jaggies)

FONT

font properties used by text.Text. See

http://matplotlib.org/api/font_manager_api.html for more

information on font properties. The 6 font properties used for font

matching are given below with their default values.

The font.family property has five values: 'serif' (e.g., Times),

'sans-serif' (e.g., Helvetica), 'cursive' (e.g., Zapf-Chancery),

'fantasy' (e.g., Western), and 'monospace' (e.g., Courier). Each of

these font families has a default list of font names in decreasing

order of priority associated with them. When text.usetex is False,

font.family may also be one or more concrete font names.

The font.style property has three values: normal (or roman), italic

or oblique. The oblique style will be used for italic, if it is not

present.

The font.variant property has two values: normal or small-caps. For

TrueType fonts, which are scalable fonts, small-caps is equivalent

to using a font size of 'smaller', or about 83% of the current font

size.

The font.weight property has effectively 13 values: normal, bold,

bolder, lighter, 100, 200, 300, ..., 900. Normal is the same as

400, and bold is 700. bolder and lighter are relative values with

respect to the current weight.

The font.stretch property has 11 values: ultra-condensed,

extra-condensed, condensed, semi-condensed, normal, semi-expanded,

expanded, extra-expanded, ultra-expanded, wider, and narrower. This

property is not currently implemented.

The font.size property is the default font size for text, given in pts.

12pt is the standard value.

#font.family : sans-serif
#font.style : normal
#font.variant : normal
#font.weight : medium
#font.stretch : normal

note that font.size controls default text sizes. To configure

special text sizes tick labels, axes, labels, title, etc, see the rc

settings for axes and ticks. Special text sizes can be defined

relative to font.size, using the following values: xx-small, x-small,

small, medium, large, x-large, xx-large, larger, or smaller

#font.size : 12.0
#font.serif : Bitstream Vera Serif, New Century Schoolbook, Century Schoolbook L, Utopia, ITC Bookman, Bookman, Nimbus Roman No9 L, Times New Roman, Times, Palatino, Charter, serif
#font.sans-serif : Bitstream Vera Sans, Lucida Grande, Verdana, Geneva, Lucid, Arial, Helvetica, Avant Garde, sans-serif
#font.cursive : Apple Chancery, Textile, Zapf Chancery, Sand, Script MT, Felipa, cursive
#font.fantasy : Comic Sans MS, Chicago, Charcoal, Impact, Western, Humor Sans, fantasy
#font.monospace : Bitstream Vera Sans Mono, Andale Mono, Nimbus Mono L, Courier New, Courier, Fixed, Terminal, monospace

TEXT

text properties used by text.Text. See

http://matplotlib.org/api/artist_api.html#module-matplotlib.text for more

information on text properties

#text.color : black

LaTeX customizations. See http://wiki.scipy.org/Cookbook/Matplotlib/UsingTex

#text.usetex : False # use latex for all text handling. The following fonts
# are supported through the usual rc parameter settings:
# new century schoolbook, bookman, times, palatino,
# zapf chancery, charter, serif, sans-serif, helvetica,
# avant garde, courier, monospace, computer modern roman,
# computer modern sans serif, computer modern typewriter
# If another font is desired which can loaded using the
# LaTeX \usepackage command, please inquire at the
# matplotlib mailing list
#text.latex.unicode : False # use "ucs" and "inputenc" LaTeX packages for handling
# unicode strings.
#text.latex.preamble : # IMPROPER USE OF THIS FEATURE WILL LEAD TO LATEX FAILURES
# AND IS THEREFORE UNSUPPORTED. PLEASE DO NOT ASK FOR HELP
# IF THIS FEATURE DOES NOT DO WHAT YOU EXPECT IT TO.
# preamble is a comma separated list of LaTeX statements
# that are included in the LaTeX document preamble.
# An example:
# text.latex.preamble : \usepackage{bm},\usepackage{euler}
# The following packages are always loaded with usetex, so
# beware of package collisions: color, geometry, graphicx,
# type1cm, textcomp. Adobe Postscript (PSSNFS) font packages
# may also be loaded, depending on your font settings

#text.dvipnghack : None # some versions of dvipng don't handle alpha
# channel properly. Use True to correct
# and flush ~/.matplotlib/tex.cache
# before testing and False to force
# correction off. None will try and
# guess based on your dvipng version

#text.hinting : auto # May be one of the following:
# 'none': Perform no hinting
# 'auto': Use freetype's autohinter
# 'native': Use the hinting information in the
# font file, if available, and if your
# freetype library supports it
# 'either': Use the native hinting information,
# or the autohinter if none is available.
# For backward compatibility, this value may also be
# True === 'auto' or False === 'none'.
#text.hinting_factor : 8 # Specifies the amount of softness for hinting in the
# horizontal direction. A value of 1 will hint to full
# pixels. A value of 2 will hint to half pixels etc.

#text.antialiased : True # If True (default), the text will be antialiased.
# This only affects the Agg backend.

The following settings allow you to select the fonts in math mode.

They map from a TeX font name to a fontconfig font pattern.

These settings are only used if mathtext.fontset is 'custom'.

Note that this "custom" mode is unsupported and may go away in the

future.

#mathtext.cal : cursive
#mathtext.rm : serif
#mathtext.tt : monospace
#mathtext.it : serif:italic
#mathtext.bf : serif:bold
#mathtext.sf : sans
#mathtext.fontset : cm # Should be 'cm' (Computer Modern), 'stix',
# 'stixsans' or 'custom'
#mathtext.fallback_to_cm : True # When True, use symbols from the Computer Modern
# fonts when a symbol can not be found in one of
# the custom math fonts.

#mathtext.default : it # The default font to use for math.
# Can be any of the LaTeX font names, including
# the special name "regular" for the same font
# used in regular text.

AXES

default face and edge color, default tick sizes,

default fontsizes for ticklabels, and so on. See

http://matplotlib.org/api/axes_api.html#module-matplotlib.axes

#axes.hold : True # whether to clear the axes by default on
#axes.facecolor : white # axes background color
#axes.edgecolor : black # axes edge color
#axes.linewidth : 1.0 # edge linewidth
#axes.grid : False # display grid or not
#axes.titlesize : large # fontsize of the axes title
#axes.labelsize : medium # fontsize of the x any y labels
#axes.labelpad : 5.0 # space between label and axis
#axes.labelweight : normal # weight of the x and y labels
#axes.labelcolor : black
#axes.axisbelow : False # whether axis gridlines and ticks are below
# the axes elements (lines, text, etc)

#axes.formatter.limits : -7, 7 # use scientific notation if log10
# of the axis range is smaller than the
# first or larger than the second
#axes.formatter.use_locale : False # When True, format tick labels
# according to the user's locale.
# For example, use ',' as a decimal
# separator in the fr_FR locale.
#axes.formatter.use_mathtext : False # When True, use mathtext for scientific
# notation.
#axes.formatter.useoffset : True # If True, the tick label formatter
# will default to labeling ticks relative
# to an offset when the data range is very
# small compared to the minimum absolute
# value of the data.

#axes.unicode_minus : True # use unicode for the minus symbol
# rather than hyphen. See
# http://en.wikipedia.org/wiki/Plus_and_minus_signs#Character_codes
#axes.prop_cycle : cycler('color', 'bgrcmyk')
# color cycle for plot lines
# as list of string colorspecs:
# single letter, long name, or
# web-style hex
#axes.xmargin : 0 # x margin. See axes.Axes.margins
#axes.ymargin : 0 # y margin See axes.Axes.margins

#polaraxes.grid : True # display grid on polar axes
#axes3d.grid : True # display grid on 3d axes

TICKS

see http://matplotlib.org/api/axis_api.html#matplotlib.axis.Tick

#xtick.major.size : 4 # major tick size in points
#xtick.minor.size : 2 # minor tick size in points
#xtick.major.width : 0.5 # major tick width in points
#xtick.minor.width : 0.5 # minor tick width in points
#xtick.major.pad : 4 # distance to major tick label in points
#xtick.minor.pad : 4 # distance to the minor tick label in points
#xtick.color : k # color of the tick labels
#xtick.labelsize : medium # fontsize of the tick labels
#xtick.direction : in # direction: in, out, or inout

#ytick.major.size : 4 # major tick size in points
#ytick.minor.size : 2 # minor tick size in points
#ytick.major.width : 0.5 # major tick width in points
#ytick.minor.width : 0.5 # minor tick width in points
#ytick.major.pad : 4 # distance to major tick label in points
#ytick.minor.pad : 4 # distance to the minor tick label in points
#ytick.color : k # color of the tick labels
#ytick.labelsize : medium # fontsize of the tick labels
#ytick.direction : in # direction: in, out, or inout

GRIDS

#grid.color : black # grid color
#grid.linestyle : : # dotted
#grid.linewidth : 0.5 # in points
#grid.alpha : 1.0 # transparency, between 0.0 and 1.0

Legend

#legend.fancybox : False # if True, use a rounded box for the
# legend, else a rectangle
#legend.isaxes : True
#legend.numpoints : 2 # the number of points in the legend line
#legend.fontsize : large
#legend.borderpad : 0.5 # border whitespace in fontsize units
#legend.markerscale : 1.0 # the relative size of legend markers vs. original

the following dimensions are in axes coords

#legend.labelspacing : 0.5 # the vertical space between the legend entries in fraction of fontsize
#legend.handlelength : 2. # the length of the legend lines in fraction of fontsize
#legend.handleheight : 0.7 # the height of the legend handle in fraction of fontsize
#legend.handletextpad : 0.8 # the space between the legend line and legend text in fraction of fontsize
#legend.borderaxespad : 0.5 # the border between the axes and legend edge in fraction of fontsize
#legend.columnspacing : 2. # the border between the axes and legend edge in fraction of fontsize
#legend.shadow : False
#legend.frameon : True # whether or not to draw a frame around legend
#legend.framealpha : None # opacity of of legend frame
#legend.scatterpoints : 3 # number of scatter points

FIGURE

See http://matplotlib.org/api/figure_api.html#matplotlib.figure.Figure

#figure.titlesize : medium # size of the figure title
#figure.titleweight : normal # weight of the figure title
#figure.figsize : 8, 6 # figure size in inches
#figure.dpi : 80 # figure dots per inch
#figure.facecolor : 0.75 # figure facecolor; 0.75 is scalar gray
#figure.edgecolor : white # figure edgecolor
#figure.autolayout : False # When True, automatically adjust subplot
# parameters to make the plot fit the figure
#figure.max_open_warning : 20 # The maximum number of figures to open through
# the pyplot interface before emitting a warning.
# If less than one this feature is disabled.

The figure subplot parameters. All dimensions are a fraction of the

figure width or height

#figure.subplot.left : 0.125 # the left side of the subplots of the figure
#figure.subplot.right : 0.9 # the right side of the subplots of the figure
#figure.subplot.bottom : 0.1 # the bottom of the subplots of the figure
#figure.subplot.top : 0.9 # the top of the subplots of the figure
#figure.subplot.wspace : 0.2 # the amount of width reserved for blank space between subplots
#figure.subplot.hspace : 0.2 # the amount of height reserved for white space between subplots

IMAGES

#image.aspect : equal # equal | auto | a number
#image.interpolation : bilinear # see help(imshow) for options
#image.cmap : jet # gray | jet etc...
#image.lut : 256 # the size of the colormap lookup table
#image.origin : upper # lower | upper
#image.resample : False
#image.composite_image : True # When True, all the images on a set of axes are
# combined into a single composite image before
# saving a figure as a vector graphics file,
# such as a PDF.

CONTOUR PLOTS

#contour.negative_linestyle : dashed # dashed | solid
#contour.corner_mask : True # True | False | legacy

ERRORBAR PLOTS

#errorbar.capsize : 3 # length of end cap on error bars in pixels

Agg rendering

Warning: experimental, 2008/10/10

#agg.path.chunksize : 0 # 0 to disable; values in the range
# 10000 to 100000 can improve speed slightly
# and prevent an Agg rendering failure
# when plotting very large data sets,
# especially if they are very gappy.
# It may cause minor artifacts, though.
# A value of 20000 is probably a good
# starting point.

SAVING FIGURES

#path.simplify : True # When True, simplify paths by removing "invisible"
# points to reduce file size and increase rendering
# speed
#path.simplify_threshold : 0.1 # The threshold of similarity below which
# vertices will be removed in the simplification
# process
#path.snap : True # When True, rectilinear axis-aligned paths will be snapped to
# the nearest pixel when certain criteria are met. When False,
# paths will never be snapped.
#path.sketch : None # May be none, or a 3-tuple of the form (scale, length,
# randomness).
# scale is the amplitude of the wiggle
# perpendicular to the line (in pixels). length
# is the length of the wiggle along the line (in
# pixels). randomness is the factor by which
# the length is randomly scaled.

the default savefig params can be different from the display params

e.g., you may want a higher resolution, or to make the figure

background white

#savefig.dpi : 100 # figure dots per inch
#savefig.facecolor : white # figure facecolor when saving
#savefig.edgecolor : white # figure edgecolor when saving
#savefig.format : png # png, ps, pdf, svg
#savefig.bbox : standard # 'tight' or 'standard'.
# 'tight' is incompatible with pipe-based animation
# backends but will workd with temporary file based ones:
# e.g. setting animation.writer to ffmpeg will not work,
# use ffmpeg_file instead
#savefig.pad_inches : 0.1 # Padding to be used when bbox is set to 'tight'
#savefig.jpeg_quality: 95 # when a jpeg is saved, the default quality parameter.
#savefig.directory : ~ # default directory in savefig dialog box,
# leave empty to always use current working directory
#savefig.transparent : False # setting that controls whether figures are saved with a
# transparent background by default

tk backend params

#tk.window_focus : False # Maintain shell focus for TkAgg

ps backend params

#ps.papersize : letter # auto, letter, legal, ledger, A0-A10, B0-B10
#ps.useafm : False # use of afm fonts, results in small files
#ps.usedistiller : False # can be: None, ghostscript or xpdf
# Experimental: may produce smaller files.
# xpdf intended for production of publication quality files,
# but requires ghostscript, xpdf and ps2eps
#ps.distiller.res : 6000 # dpi
#ps.fonttype : 3 # Output Type 3 (Type3) or Type 42 (TrueType)

pdf backend params

#pdf.compression : 6 # integer from 0 to 9
# 0 disables compression (good for debugging)
#pdf.fonttype : 3 # Output Type 3 (Type3) or Type 42 (TrueType)

svg backend params

#svg.image_inline : True # write raster image data directly into the svg file
#svg.image_noscale : False # suppress scaling of raster data embedded in SVG
#svg.fonttype : 'path' # How to handle SVG fonts:

'none': Assume fonts are installed on the machine where the SVG will be viewed.

'path': Embed characters as paths -- supported by most SVG renderers

'svgfont': Embed characters as SVG fonts -- supported only by Chrome,

Opera and Safari

docstring params

#docstring.hardcopy = False # set this when you want to generate hardcopy docstring

Set the verbose flags. This controls how much information

matplotlib gives you at runtime and where it goes. The verbosity

levels are: silent, helpful, debug, debug-annoying. Any level is

inclusive of all the levels below it. If your setting is "debug",

you'll get all the debug and helpful messages. When submitting

problems to the mailing-list, please set verbose to "helpful" or "debug"

and paste the output into your report.

The "fileo" gives the destination for any calls to verbose.report.

These objects can a filename, or a filehandle like sys.stdout.

You can override the rc default verbosity from the command line by

giving the flags --verbose-LEVEL where LEVEL is one of the legal

levels, e.g., --verbose-helpful.

You can access the verbose instance in your code

from matplotlib import verbose.

#verbose.level : silent # one of silent, helpful, debug, debug-annoying
#verbose.fileo : sys.stdout # a log filename, sys.stdout or sys.stderr

Event keys to interact with figures/plots via keyboard.

Customize these settings according to your needs.

Leave the field(s) empty if you don't need a key-map. (i.e., fullscreen : '')

#keymap.fullscreen : f # toggling
#keymap.home : h, r, home # home or reset mnemonic
#keymap.back : left, c, backspace # forward / backward keys to enable
#keymap.forward : right, v # left handed quick navigation
#keymap.pan : p # pan mnemonic
#keymap.zoom : o # zoom mnemonic
#keymap.save : s # saving current figure
#keymap.quit : ctrl+w, cmd+w # close the current figure
#keymap.grid : g # switching on/off a grid in current axes
#keymap.yscale : l # toggle scaling of y-axes ('log'/'linear')
#keymap.xscale : L, k # toggle scaling of x-axes ('log'/'linear')
#keymap.all_axes : a # enable all axes

Control location of examples data files

#examples.directory : '' # directory to look in for custom installation

###ANIMATION settings
#animation.html : 'none' # How to display the animation as HTML in
# the IPython notebook. 'html5' uses
# HTML5 video tag.
#animation.writer : ffmpeg # MovieWriter 'backend' to use
#animation.codec : mpeg4 # Codec to use for writing movie
#animation.bitrate: -1 # Controls size/quality tradeoff for movie.
# -1 implies let utility auto-determine
#animation.frame_format: 'png' # Controls frame format used by temp files
#animation.ffmpeg_path: 'ffmpeg' # Path to ffmpeg binary. Without full path
# $PATH is searched
#animation.ffmpeg_args: '' # Additional arguments to pass to ffmpeg
#animation.avconv_path: 'avconv' # Path to avconv binary. Without full path
# $PATH is searched
#animation.avconv_args: '' # Additional arguments to pass to avconv
#animation.mencoder_path: 'mencoder'
# Path to mencoder binary. Without full path
# $PATH is searched
#animation.mencoder_args: '' # Additional arguments to pass to mencoder
#animation.convert_path: 'convert' # Path to ImageMagick's convert binary.
# On Windows use the full path since convert
# is also the name of a system tool.

On Dec 6, 2015, at 4:26 AM, mdehoon notifications@github.com wrote:

@Auerilas https://github.com/Auerilas I have not been able to replicate this bug. Can you post the exact script that you are using, and also your matplotlibrc file (which you can find in $HOME/.matplotlib/matplotlibrc)? Then I can try and reproduce this.

—
Reply to this email directly or view it on GitHub #5624 (comment).

[mdehoon]

@Auerilas Does the bug also appear if you don't import seaborn?

[mdehoon]

Actually, ete2 import PyQt4, which has its own event loop. I expect that when you import PyQt4, its event loop starts to run, and the event loop in Tkinter or the MacOSX backend will stop. If so, there is not much you can do about it, other than to use PyQt4 in matplotlib as well.

[Auerilas]

That would explain why the MacOSX and TK backends fail when I’m importing ete2. Thanks!

For the record, this bug still appears for the CocoaAgg backend regardless of whether or not both seaborn or ete2 are imported.

On Dec 7, 2015, at 1:02 AM, mdehoon notifications@github.com wrote:

Actually, ete2 import PyQt4, which has its own event loop. I expect that when you import PyQt4, its event loop starts to run, and the event loop in Tkinter or the MacOSX backend will stop. If so, there is not much you can do about it, other than to use PyQt4 in matplotlib as well.

—
Reply to this email directly or view it on GitHub #5624 (comment).

[mdehoon]

Can you try to import PyQt4 (after importing matplotlib) to verify that that is sufficient to trigger the bug?

[Auerilas]

This did not trigger the bug.

import matplotlib.pyplot as plt
import PyQt4
import numpy as np
import seaborn as sns
sns.set(context='talk', style='ticks', font_scale=1.2, rc={'figure.figsize': (6.5, 5.5), 'xtick.direction': 'in', 'ytick.direction': 'in'})
x = np.arange(1,10)
plt.plot(x, x)
plt.show()

I also tried it without seaborn as well.

On Dec 7, 2015, at 8:05 PM, mdehoon notifications@github.com wrote:

Can you try to import PyQt4 (after importing matplotlib) to verify that that is sufficient to trigger the bug?

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Reply to this email directly or view it on GitHub #5624 (comment).

[mdehoon]

But

import matplotlib.pyplot as plt
import numpy as np
import ete2 as ete
x = np.arange(1,10)
plt.plot(x, x)
plt.show()

gives you the bug? If so, can you find out which part of ete2 is causing this? I am seeing many imports like

from PyQt4 import QtCore, QtGui

in ete2; this may be the source of the bug.

[Auerilas]

This:

import matplotlib.pyplot as plt
import PyQt4
import numpy as np
import seaborn as sns
sns.set(context='talk', style='ticks', font_scale=1.2, rc={'figure.figsize': (6.5, 5.5), 'xtick.direction': 'in', 'ytick.direction': 'in'})
x = np.arange(1,10)
plt.plot(x, x)
plt.show()

does not give me the bug as noted earlier.

This:

import matplotlib.pyplot as plt
from PyQt4 import QtCore, QtGui
import numpy as np
import seaborn as sns
sns.set(context='talk', style='ticks', font_scale=1.2, rc={'figure.figsize': (6.5, 5.5), 'xtick.direction': 'in', 'ytick.direction': 'in'})
x = np.arange(1,10)
plt.plot(x, x)
plt.show()

does, however. To narrow it down, I tried isolating QtCore and QtGui.

Importing QtGui results in the bug:

import matplotlib.pyplot as plt
from PyQt4 import QtGui
import numpy as np
import seaborn as sns
sns.set(context='talk', style='ticks', font_scale=1.2, rc={'figure.figsize': (6.5, 5.5), 'xtick.direction': 'in', 'ytick.direction': 'in'})
x = np.arange(1,10)
plt.plot(x, x)
plt.show()

Importing QtCore also results in the bug.

import matplotlib.pyplot as plt
from PyQt4 import QtCore
import numpy as np
import seaborn as sns
sns.set(context='talk', style='ticks', font_scale=1.2, rc={'figure.figsize': (6.5, 5.5), 'xtick.direction': 'in', 'ytick.direction': 'in'})
x = np.arange(1,10)
plt.plot(x, x)
plt.show()

Importing QtSvg also results in the bug.

import matplotlib.pyplot as plt
from PyQt4 import QtSvg
import numpy as np
import seaborn as sns
sns.set(context='talk', style='ticks', font_scale=1.2, rc={'figure.figsize': (6.5, 5.5), 'xtick.direction': 'in', 'ytick.direction': 'in'})
x = np.arange(1,10)
plt.plot(x, x)
plt.show()

So the bug doesn’t appear until I import specific modules within PyQt4.

On Dec 7, 2015, at 10:05 PM, mdehoon notifications@github.com wrote:

But

import matplotlib.pyplot as plt
import numpy as np
import ete2 as ete
x = np.arange(1,10)
plt.plot(x, x)
plt.show()
gives you the bug? If so, can you find out which part of ete2 is causing this? I am seeing many imports like

from PyQt4 import QtCore, QtGui
in ete2; this may be the source of the bug.

—
Reply to this email directly or view it on GitHub #5624 (comment).

[tacaswell]

The top-level of PyQt4 is a no-op place holder to make the set of *.so files that are the actual wrappers. Importing the wrappers auto-registers the input hook. The way py_osinputhook is implemented in cpython, like highlanders, there can be only one; hence importing pyqt4.* will break mpl with any other gui framework.

There is nothing we can do and this should maybe reported as a bug to ete.

[mdehoon]

@Auerilas Thank you. I would suggest to report this as a bug to PyQt4. If PyQt4 tries to set PyOS_InputHook and finds that it is already in use, it should raise an Exception or at least print a warning.

[Auerilas]

Thanks. Will do.

On Dec 8, 2015, at 4:58 PM, mdehoon notifications@github.com wrote:

@Auerilas https://github.com/Auerilas Thank you. I would suggest to report this as a bug to PyQt4. If PyQt4 tries to set PyOS_InputHook and finds that it is already in use, it should raise an Exception or at least print a warning.

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[flipdazed]

I have had the same problem withinipython 5.0.0 and matplotlib 1.5.1 but notably it is only causing issues with ipython and not the regular python console - nevertheless the similar issue might give insight

I am using OS X El Capitan Version 10.11.6. This problem has also affected everyone I work with that updated to these currently latest matplotlib, ipython and OS X versions.

The simplest reproduction is trying to manually close the window after

import matplotlib.pyplot as plt
plt.plot()

even worse is attempting plt.close() which disables the three native osx window buttons.
The most convenient workaround to force the window to acknowledge the close command is via the shortcut for closing ipython and then cancelling the exit

^+d
Do you really want to exit ([y]/n)? n

[afvincent]

@flipdazed I guess the behavior you are describing is similar to the one reported in #6838 . You may want to try the %matplotlib magic command in your IPython session (or launch IPython with the --matplotlib command) if you don't already do.

[flipdazed]

I have tried both cases of %matplotlib and ipython --matplotlib without success so I think it's different to #6838. It does indeed seem more related to ipython though so I won't further comment here.

I have opened a StackOverflow post on the issue instead http://stackoverflow.com/questions/38801285/matplotlib-window-freezing-hanging-on-close-in-ipython-with-os-x

[jenshnielsen]

I can reproduce this but I think it is a bug on the IPython side part of ipython/ipython#9659

This is as far as I know only an issue with the Mac OSX backend and caused by the OSX backend event loop integration in IPython not being updated to work with the new IPython based on prompt-toolkit. @flipdazed Would you mind opening a new issue for this since it's not really the same as this issue but an entirely new one caused by changes in IPython

[Auerilas]

I had issues with this as well. I don’t remember how I resolved it, though. I know that’s not helpful, but I did want to mention that I was having the same problem.

On Aug 6, 2016, at 3:44 AM, Jens Hedegaard Nielsen notifications@github.com wrote:

I can reproduce this but I think it is a bug on the IPython side part of ipython/ipython#9659 ipython/ipython#9659
This is as far as I know only an issue with the Mac OSX backend and caused by the OSX backend event look integration in IPython not being updated to work with the new IPython based on prompt-toolkit. @flipdazed https://github.com/flipdazed Would you mind opening a new issue for this since it's not really the same as this issue but an entirely new one caused by changes in IPython

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[jeffheaton]

Also having this issue.

[jenshnielsen]

@jeffheaton The original issue behind this has been fixed for a long time you are likely seeing a related issue. It is probably better to open a new issue and describe what you are seeing in more detail and which versions you are using