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# Customizing matplotlib

Tips for customizing the properties and default styles of matplotlib.

## Using style sheets

The `style` package adds support for easy-to-switch plotting “styles” with the same parameters as a matplotlibrc file (which is read at startup to configure matplotlib).

There are a number of pre-defined styles provided by matplotlib. For example, there’s a pre-defined style called “ggplot”, which emulates the aesthetics of ggplot (a popular plotting package for R). To use this style, just add:

    import numpy as np
    import matplotlib.pyplot as plt
    import matplotlib as mpl
    plt.style.use('ggplot')
    data = np.random.randn(50)

To list all available styles, use:

    print(plt.style.available)

Out:

    ['seaborn-deep', 'ggplot', 'seaborn-white', 'seaborn-pastel', 'seaborn-talk', 'bmh', 'seaborn-notebook', 'seaborn-muted', 'seaborn-darkgrid', 'dark_background', 'seaborn-paper', 'grayscale', 'seaborn-ticks', 'seaborn-poster', 'seaborn-dark', 'seaborn-dark-palette', 'seaborn-whitegrid', 'classic', 'seaborn-colorblind', '_classic_test', 'seaborn-bright', 'fivethirtyeight', 'seaborn']

## Defining your own style

You can create custom styles and use them by calling `style.use` with the path or URL to the style sheet. Additionally, if you add your `<style-name>.mplstyle` file to `mpl_configdir/stylelib`, you can reuse your custom style sheet with a call to `style.use(<style-name>)`. By default `mpl_configdir` should be `~/.config/matplotlib`, but you can check where yours is with `matplotlib.get_configdir()`; you may need to create this directory. You also can change the directory where matplotlib looks for the stylelib/ folder by setting the MPLCONFIGDIR environment variable, see matplotlib configuration and cache directory locations.

Note that a custom style sheet in `mpl_configdir/stylelib` will override a style sheet defined by matplotlib if the styles have the same name.

For example, you might want to create `mpl_configdir/stylelib/presentation.mplstyle` with the following:

    axes.titlesize : 24
    axes.labelsize : 20
    lines.linewidth : 3
    lines.markersize : 10
    xtick.labelsize : 16
    ytick.labelsize : 16

Then, when you want to adapt a plot designed for a paper to one that looks good in a presentation, you can just add:

    >>> import matplotlib.pyplot as plt
    >>> plt.style.use('presentation')

## Composing styles

Style sheets are designed to be composed together. So you can have a style sheet that customizes colors and a separate style sheet that alters element sizes for presentations. These styles can easily be combined by passing a list of styles:

    >>> import matplotlib.pyplot as plt
    >>> plt.style.use(['dark_background', 'presentation'])

Note that styles further to the right will overwrite values that are already defined by styles on the left.

## Temporary styling

If you only want to use a style for a specific block of code but don’t want to change the global styling, the style package provides a context manager for limiting your changes to a specific scope. To isolate your styling changes, you can write something like the following:

    with plt.style.context(('dark_background')):
        plt.plot(np.sin(np.linspace(0, 2 * np.pi)), 'r-o')
    plt.show()

# matplotlib rcParams

## Dynamic rc settings

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 `matplotlib.rcParams`, which is global to the matplotlib package. rcParams can be modified directly, for example:

    mpl.rcParams['lines.linewidth'] = 2
    mpl.rcParams['lines.color'] = 'r'
    plt.plot(data)

Matplotlib also provides a couple of convenience functions for modifying rc settings. The `matplotlib.rc()` command can be used to modify multiple settings in a single group at once, using keyword arguments:

    mpl.rc('lines', linewidth=4, color='g')
    plt.plot(data)

The `matplotlib.rcdefaults()` command will restore the standard matplotlib default settings.

There is some degree of validation when setting the values of rcParams, see `matplotlib.rcsetup` for details.

## The `matplotlibrc` file

matplotlib uses `matplotlibrc` configuration files to customize all kinds of properties, which we call `rc settings` or `rc parameters`. 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 `matplotlibrc` in four locations, in the following order:

1. `matplotlibrc` in the current working directory, usually used for specific customizations that you do not want to apply elsewhere.

2. `$MATPLOTLIBRC` if it is a file, else `$MATPLOTLIBRC/matplotlibrc`.

3. It next looks in a user-specific place, depending on your platform:

   - On Linux and FreeBSD, it looks in `.config/matplotlib/matplotlibrc` (or `$XDG_CONFIG_HOME/matplotlib/matplotlibrc`) if you’ve customized your environment.
   - On other platforms, it looks in `.matplotlib/matplotlibrc`.

   See matplotlib configuration and cache directory locations.

4. `INSTALL/matplotlib/mpl-data/matplotlibrc`, where `INSTALL` is something like `/usr/lib/python3.5/site-packages` on Linux, and maybe `C:\Python35\Lib\site-packages` 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.

Once a `matplotlibrc` file has been found, it will not search any of the other paths.

To display where the currently active `matplotlibrc` file was loaded from, one can do the following:

    >>> import matplotlib
    >>> matplotlib.matplotlib_fname()
    '/home/foo/.config/matplotlib/matplotlibrc'

See below for a sample matplotlibrc file. Although all parameters are optional, you should almost always set the `backend` or else matplotlib will choose `Agg`, a non-interactive backend. This can lead to unexpected behavior, since if you do not have a `matplotlibrc` file, it would normally fall back to `INSTALL/matplotlib/mpl-data/matplotlibrc`, which is often set to an interactive backend by the package maintainer.

### A sample matplotlibrc file

(download)

    ### 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 - 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
    # 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'.
    #
    # If you omit this parameter, it will always default to "Agg", which is a
    # non-interactive backend.
    backend      : qt5agg

    # 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

    # When True, the figures rendered in the nbagg backend are created with
    # a transparent background.
    # nbagg.transparent : False

    # 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   : 1.5     # line width in points
    #lines.linestyle   : -       # solid line
    #lines.color       : C0      # has no affect on plot(); see axes.prop_cycle
    #lines.marker      : None    # the default marker
    #lines.markeredgewidth  : 1.0     # 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 antialiased (no jaggies)

    # The three standard dash patterns.  These are scaled by the linewidth.
    #lines.dashed_pattern : 2.8, 1.2
    #lines.dashdot_pattern : 4.8, 1.2, 0.8, 1.2
    #lines.dotted_pattern : 1.1, 1.1
    #lines.scale_dashes : True

    #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        # edge width in points.
    #patch.facecolor        : C0
    #patch.edgecolor        : black   # if forced, or patch is not filled
    #patch.force_edgecolor  : False   # True to always use edgecolor
    #patch.antialiased      : True    # render patches in antialiased (no jaggies)

    ### HATCHES
    #hatch.color     : k
    #hatch.linewidth : 1.0

    ### Boxplot
    #boxplot.notch       : False
    #boxplot.vertical    : True
    #boxplot.whiskers    : 1.5
    #boxplot.bootstrap   : None
    #boxplot.patchartist : False
    #boxplot.showmeans   : False
    #boxplot.showcaps    : True
    #boxplot.showbox     : True
    #boxplot.showfliers  : True
    #boxplot.meanline    : False

    #boxplot.flierprops.color           : 'k'
    #boxplot.flierprops.marker          : 'o'
    #boxplot.flierprops.markerfacecolor : 'none'
    #boxplot.flierprops.markeredgecolor : 'k'
    #boxplot.flierprops.markersize      : 6
    #boxplot.flierprops.linestyle       : 'none'
    #boxplot.flierprops.linewidth       : 1.0

    #boxplot.boxprops.color     : 'k'
    #boxplot.boxprops.linewidth : 1.0
    #boxplot.boxprops.linestyle : '-'

    #boxplot.whiskerprops.color     : 'k'
    #boxplot.whiskerprops.linewidth : 1.0
    #boxplot.whiskerprops.linestyle : '-'

    #boxplot.capprops.color     : 'k'
    #boxplot.capprops.linewidth : 1.0
    #boxplot.capprops.linestyle : '-'

    #boxplot.medianprops.color     : 'C1'
    #boxplot.medianprops.linewidth : 1.0
    #boxplot.medianprops.linestyle : '-'

    #boxplot.meanprops.color           : 'C2'
    #boxplot.meanprops.marker          : '^'
    #boxplot.meanprops.markerfacecolor : 'C2'
    #boxplot.meanprops.markeredgecolor : 'C2'
    #boxplot.meanprops.markersize      :  6
    #boxplot.meanprops.linestyle       : 'none'
    #boxplot.meanprops.linewidth       : 1.0

    ### 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.
    # 10 pt 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           : 10.0
    #font.serif          : DejaVu 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     : DejaVu Sans, 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, xkcd, fantasy
    #font.monospace      : DejaVu Sans Mono, 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.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 : dejavusans # Should be 'dejavusans' (default),
                                   # 'dejavuserif', '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.facecolor      : white   # axes background color
    #axes.edgecolor      : black   # axes edge color
    #axes.linewidth      : 0.8     # edge linewidth
    #axes.grid           : False   # display grid or not
    #axes.titlesize      : large   # fontsize of the axes title
    #axes.titlepad       : 6.0     # pad between axes and title in points
    #axes.labelsize      : medium  # fontsize of the x any y labels
    #axes.labelpad       : 4.0     # space between label and axis
    #axes.labelweight    : normal  # weight of the x and y labels
    #axes.labelcolor     : black
    #axes.axisbelow      : 'line'  # draw axis gridlines and ticks below
                                   # patches (True); above patches but below
                                   # lines ('line'); or above all (False)

    #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.min_exponent: 0 # minimum exponent to format in 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
                                             # small compared to the minimum absolute
                                             # value of the data.
    #axes.formatter.offset_threshold : 4     # When useoffset is True, the offset
                                             # will be used when it can remove
                                             # at least this number of significant
                                             # digits from tick labels.

    # axes.spines.left   : True   # display axis spines
    # axes.spines.bottom : True
    # axes.spines.top    : True
    # axes.spines.right  : True

    #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',
    #                            ['1f77b4', 'ff7f0e', '2ca02c', 'd62728',
    #                              '9467bd', '8c564b', 'e377c2', '7f7f7f',
    #                              'bcbd22', '17becf'])
                                                # color cycle for plot lines
                                                # as list of string colorspecs:
                                                # single letter, long name, or
                                                # web-style hex
    #axes.autolimit_mode : data # How to scale axes limits to the data.
                                # Use "data" to use data limits, plus some margin
                                # Use "round_number" move to the nearest "round" number
    #axes.xmargin        : .05  # x margin.  See `axes.Axes.margins`
    #axes.ymargin        : .05  # y margin See `axes.Axes.margins`

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

    ### DATES
    # These control the default format strings used in AutoDateFormatter.
    # Any valid format datetime format string can be used (see the python
    # `datetime` for details).  For example using '%%x' will use the locale date representation
    # '%%X' will use the locale time representation and '%%c' will use the full locale datetime
    # representation.
    # These values map to the scales:
    #    {'year': 365, 'month': 30, 'day': 1, 'hour': 1/24, 'minute': 1 / (24 * 60)}

    # date.autoformatter.year     : %Y
    # date.autoformatter.month    : %Y-%m
    # date.autoformatter.day      : %Y-%m-%d
    # date.autoformatter.hour     : %m-%d %H
    # date.autoformatter.minute   : %d %H:%M
    # date.autoformatter.second   : %H:%M:%S
    # date.autoformatter.microsecond   : %M:%S.%f

    ### TICKS
    # see http://matplotlib.org/api/axis_api.html#matplotlib.axis.Tick
    #xtick.top            : False   # draw ticks on the top side
    #xtick.bottom         : True   # draw ticks on the bottom side
    #xtick.major.size     : 3.5      # major tick size in points
    #xtick.minor.size     : 2      # minor tick size in points
    #xtick.major.width    : 0.8    # major tick width in points
    #xtick.minor.width    : 0.6    # minor tick width in points
    #xtick.major.pad      : 3.5      # distance to major tick label in points
    #xtick.minor.pad      : 3.4      # 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      : out    # direction: in, out, or inout
    #xtick.minor.visible  : False  # visibility of minor ticks on x-axis
    #xtick.major.top      : True   # draw x axis top major ticks
    #xtick.major.bottom   : True   # draw x axis bottom major ticks
    #xtick.minor.top      : True   # draw x axis top minor ticks
    #xtick.minor.bottom   : True   # draw x axis bottom minor ticks

    #ytick.left           : True   # draw ticks on the left side
    #ytick.right          : False  # draw ticks on the right side
    #ytick.major.size     : 3.5      # major tick size in points
    #ytick.minor.size     : 2      # minor tick size in points
    #ytick.major.width    : 0.8    # major tick width in points
    #ytick.minor.width    : 0.6    # minor tick width in points
    #ytick.major.pad      : 3.5      # distance to major tick label in points
    #ytick.minor.pad      : 3.4      # 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      : out    # direction: in, out, or inout
    #ytick.minor.visible  : False  # visibility of minor ticks on y-axis
    #ytick.major.left     : True   # draw y axis left major ticks
    #ytick.major.right    : True   # draw y axis right major ticks
    #ytick.minor.left     : True   # draw y axis left minor ticks
    #ytick.minor.right    : True   # draw y axis right minor ticks

    ### GRIDS
    #grid.color       :   b0b0b0    # grid color
    #grid.linestyle   :   -         # solid
    #grid.linewidth   :   0.8       # in points
    #grid.alpha       :   1.0       # transparency, between 0.0 and 1.0

    ### Legend
    #legend.loc           : best
    #legend.frameon       : True     # if True, draw the legend on a background patch
    #legend.framealpha    : 0.8      # legend patch transparency
    #legend.facecolor     : inherit  # inherit from axes.facecolor; or color spec
    #legend.edgecolor     : 0.8      # background patch boundary color
    #legend.fancybox      : True     # if True, use a rounded box for the
                                     # legend background, else a rectangle
    #legend.shadow        : False    # if True, give background a shadow effect
    #legend.numpoints     : 1        # the number of marker points in the legend line
    #legend.scatterpoints : 1        # number of scatter points
    #legend.markerscale   : 1.0      # the relative size of legend markers vs. original
    #legend.fontsize      : medium
    # Dimensions as fraction of fontsize:
    #legend.borderpad     : 0.4      # border whitespace
    #legend.labelspacing  : 0.5      # the vertical space between the legend entries
    #legend.handlelength  : 2.0      # the length of the legend lines
    #legend.handleheight  : 0.7      # the height of the legend handle
    #legend.handletextpad : 0.8      # the space between the legend line and legend text
    #legend.borderaxespad : 0.5      # the border between the axes and legend edge
    #legend.columnspacing : 2.0      # column separation

    ### FIGURE
    # See http://matplotlib.org/api/figure_api.html#matplotlib.figure.Figure
    #figure.titlesize : large      # size of the figure title (Figure.suptitle())
    #figure.titleweight : normal   # weight of the figure title
    #figure.figsize   : 6.4, 4.8   # figure size in inches
    #figure.dpi       : 100      # figure dots per inch
    #figure.facecolor : white   # 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.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  : 0.11    # the bottom of the subplots of the figure
    #figure.subplot.top     : 0.88    # the top of the subplots of the figure
    #figure.subplot.wspace  : 0.2    # the amount of width reserved for blank space between subplots,
                                     # expressed as a fraction of the average axis width
    #figure.subplot.hspace  : 0.2    # the amount of height reserved for white space between subplots,
                                     # expressed as a fraction of the average axis height

    ### IMAGES
    #image.aspect : equal             # equal | auto | a number
    #image.interpolation  : nearest   # see help(imshow) for options
    #image.cmap   : viridis           # A colormap name, gray etc...
    #image.lut    : 256               # the size of the colormap lookup table
    #image.origin : upper             # lower | upper
    #image.resample  : True
    #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 # string or on-off ink sequence
    #contour.corner_mask        : True   # True | False | legacy

    ### ERRORBAR PLOTS
    #errorbar.capsize : 0             # length of end cap on error bars in pixels

    ### HISTOGRAM PLOTS
    #hist.bins : 10                   # The default number of histogram bins.
                                      # If Numpy 1.11 or later is
                                      # installed, may also be `auto`

    ### SCATTER PLOTS
    #scatter.marker : o               # The default marker type for scatter plots.

    ### 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         : figure   # figure dots per inch or 'figure'
    #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.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
    #svg.hashsalt : None           # if not None, use this string as hash salt
                                   # instead of uuid4

    # 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, ctrl+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 major grids in current axes
    #keymap.grid_minor : G               # switching on/off minor grids 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 : h264            # 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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