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<li><a class="reference internal" href="#">Customizing matplotlib</a><ul>
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<li><a class="reference internal" href="#dynamic-rc-settings">Dynamic rc settings</a><ul>
<li><a class="reference internal" href="#a-sample-matplotlibrc-file">A sample matplotlibrc file</a></li>
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<div class="section" id="customizing-matplotlib">
<span id="id1"></span><h1>Customizing matplotlib<a class="headerlink" href="#customizing-matplotlib" title="Permalink to this headline">¶</a></h1>
<div class="section" id="the-matplotlibrc-file">
<span id="customizing-with-matplotlibrc-files"></span><h2>The <tt class="file docutils literal"><span class="pre">matplotlibrc</span></tt> file<a class="headerlink" href="#the-matplotlibrc-file" title="Permalink to this headline">¶</a></h2>
<p>matplotlib uses <tt class="file docutils literal"><span class="pre">matplotlibrc</span></tt> configuration files to customize all kinds
of properties, which we call <tt class="xref py py-obj docutils literal"><span class="pre">rc</span> <span class="pre">settings</span></tt> or <tt class="xref py py-obj docutils literal"><span class="pre">rc</span> <span class="pre">parameters</span></tt>. You can control
the defaults of almost every property in matplotlib: figure size and dpi, line
width, color and style, axes, axis and grid properties, text and font
properties and so on. matplotlib looks for <tt class="file docutils literal"><span class="pre">matplotlibrc</span></tt> in three
locations, in the following order:</p>
<ol class="arabic">
<li><p class="first"><tt class="file docutils literal"><span class="pre">matplotlibrc</span></tt> in the current working directory, usually used for
specific customizations that you do not want to apply elsewhere.</p>
</li>
<li><p class="first">It next looks in a user-specific place, depending on your platform:</p>
<ul class="simple">
<li>On Linux, it looks in <tt class="file docutils literal"><span class="pre">.config/matplotlib/matplotlibrc</span></tt> (or
<tt class="xref py py-obj docutils literal"><span class="pre">$XDG_CONFIG_HOME/matplotlib/matplotlibrc</span></tt>) if you’ve customized
your environment.</li>
<li>On other platforms, it looks in <tt class="file docutils literal"><span class="pre">.matplotlib/matplotlibrc</span></tt>.</li>
</ul>
<p>See <a class="reference internal" href="../faq/troubleshooting_faq.html#locating-matplotlib-config-dir"><em>.matplotlib directory location</em></a>.</p>
</li>
<li><p class="first"><tt class="file docutils literal"><em><span class="pre">INSTALL</span></em><span class="pre">/matplotlib/mpl-data/matplotlibrc</span></tt>, where
<tt class="file docutils literal"><em><span class="pre">INSTALL</span></em></tt> is something like
<tt class="file docutils literal"><span class="pre">/usr/lib/python2.5/site-packages</span></tt> on Linux, and maybe
<tt class="file docutils literal"><span class="pre">C:\Python25\Lib\site-packages</span></tt> on Windows. Every time you
install matplotlib, this file will be overwritten, so if you want
your customizations to be saved, please move this file to your
user-specific matplotlib directory.</p>
</li>
</ol>
<p>To display where the currently active <tt class="file docutils literal"><span class="pre">matplotlibrc</span></tt> file was
loaded from, one can do the following:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">matplotlib</span>
<span class="gp">>>> </span><span class="n">matplotlib</span><span class="o">.</span><span class="n">matplotlib_fname</span><span class="p">()</span>
<span class="go">'/home/foo/.config/matplotlib/matplotlibrc'</span>
</pre></div>
</div>
<p>See below for a sample <a class="reference internal" href="#matplotlibrc-sample"><em>matplotlibrc file</em></a>.</p>
</div>
<div class="section" id="dynamic-rc-settings">
<span id="customizing-with-dynamic-rc-settings"></span><h2>Dynamic rc settings<a class="headerlink" href="#dynamic-rc-settings" title="Permalink to this headline">¶</a></h2>
<p>You can also dynamically change the default rc settings in a python script or
interactively from the python shell. All of the rc settings are stored in a
dictionary-like variable called <a class="reference internal" href="../api/matplotlib_configuration_api.html#matplotlib.rcParams" title="matplotlib.rcParams"><tt class="xref py py-data docutils literal"><span class="pre">matplotlib.rcParams</span></tt></a>, which is global to
the matplotlib package. rcParams can be modified directly, for example:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="kn">import</span> <span class="nn">matplotlib</span> <span class="kn">as</span> <span class="nn">mpl</span>
<span class="n">mpl</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s">'lines.linewidth'</span><span class="p">]</span> <span class="o">=</span> <span class="mi">2</span>
<span class="n">mpl</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s">'lines.color'</span><span class="p">]</span> <span class="o">=</span> <span class="s">'r'</span>
</pre></div>
</div>
<p>Matplotlib also provides a couple of convenience functions for modifying rc
settings. The <a class="reference internal" href="../api/matplotlib_configuration_api.html#matplotlib.rc" title="matplotlib.rc"><tt class="xref py py-func docutils literal"><span class="pre">matplotlib.rc()</span></tt></a> command can be used to modify multiple
settings in a single group at once, using keyword arguments:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="kn">import</span> <span class="nn">matplotlib</span> <span class="kn">as</span> <span class="nn">mpl</span>
<span class="n">mpl</span><span class="o">.</span><span class="n">rc</span><span class="p">(</span><span class="s">'lines'</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s">'r'</span><span class="p">)</span>
</pre></div>
</div>
<p>The <tt class="xref py py-func docutils literal"><span class="pre">matplotlib.rcdefaults()</span></tt> command will restore the standard matplotlib
default settings.</p>
<p>There is some degree of validation when setting the values of rcParams, see
<tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.rcsetup</span></tt> for details.</p>
<div class="section" id="a-sample-matplotlibrc-file">
<span id="matplotlibrc-sample"></span><h3>A sample matplotlibrc file<a class="headerlink" href="#a-sample-matplotlibrc-file" title="Permalink to this headline">¶</a></h3>
<a class="reference external" href="../_static/matplotlibrc">(download)</a><div class="highlight-python"><div class="highlight"><pre>### 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, eg red,
# blue, darkslategray
#### CONFIGURATION BEGINS HERE
# the default backend; one of GTK GTKAgg GTKCairo GTK3Agg GTK3Cairo
# CocoaAgg MacOSX Qt4Agg 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 : qt4agg
# 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 : PyQt4 # 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
# 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, eg 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.color_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)
### 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, cursive
#font.fantasy : Comic Sans MS, Chicago, Charcoal, Impact, Western, 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://www.scipy.org/Wiki/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.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.color_cycle : b, g, r, c, m, y, k # 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.scatterpoints : 3 # number of scatter points
### FIGURE
# See http://matplotlib.org/api/figure_api.html#matplotlib.figure.Figure
#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
### CONTOUR PLOTS
#contour.negative_linestyle : dashed # dashed | solid
### 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, eg --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.writer : ffmpeg # MovieWriter 'backend' to use
#animation.codec : mp4 # 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.
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© Copyright 2002 - 2012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the matplotlib development team; 2012 - 2014 The matplotlib development team.
Last updated on Sep 02, 2014.
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