matplotlib Code

221 lines (197 with data), 10.2 kB

### MATPLOTLIBRC FORMAT 

# This is a sample matplotlib configuration file.  It should be placed
# in HOME/.matplotlib/matplotlibrc (unix/linux like systems)
#
# By default, the installer will overwrite the existing file in the
# install path, so if you want to preserve your's, please move it to
# your HOME dir and set the environment variable if necessary.
#
# 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  (no '#' symbol)
#  - a scalar grayscale intensity such as 0.75
#  - a legal html color name, eg red, blue, darkslategray

#### CONFIGURATION BEGINS HERE
backend      : GTKAgg    # the default backend
numerix      : Numeric   # Numeric or numarray
interactive  : False     # see http://matplotlib.sourceforge.net/interactive.html
toolbar      : toolbar2   # None | classic | toolbar2
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.sourceforge.net/matplotlib.lines.html for more
# information on line properties.  Note antialiased rendering looks
# better, but can be slower.  If you want fast antialiased rendering,
# use the Agg backend (or TkAgg, GTKAgg, WxAgg)
lines.linewidth   : 0.5     # line width in points
lines.linestyle   : -       # solid line
lines.color       : blue    
lines.marker      : None    # the default marker
lines.markerfacecolor  : blue
lines.markeredgecolor  : black
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)
lines.data_clipping : False      # Use data clipping in addition to viewport
                                 # clipping.  Useful if you plot long data
                                 # sets with only a fraction in the viewport

### Patches 
# Patches are graphical objects that fill 2D space, like polygons or
# circles.  See
# http://matplotlib.sourceforge.net/matplotlib.patches.html for more
# 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.sourceforge.net/matplotlib.font_manager.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.
# 
# 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 has 11 values: xx-small, x-small, small,
# medium, large, x-large, xx-large, larger, smaller, length (such as
# 12pt), and percentage.  larger and smaller are relative values.
# percentage is not yet implemented.
#
font.family         : sans-serif
font.style          : normal
font.variant        : normal
font.weight         : medium
font.stretch        : normal
font.size           : medium
font.serif          : New Century Schoolbook, Century Schoolbook L, Utopia, ITC Bookman, Bookman, Bitstream Vera Serif, Nimbus Roman No9 L, Times New Roman, Times, Palatino, Charter, serif
font.sans-serif     : Lucida Grande, Verdana, Geneva, Lucida, Bitstream Vera Sans, Arial, Helvetica, sans-serif
font.cursive        : Apple Chancery, Textile, Zapf Chancery, Sand, cursive
font.fantasy        : Comic Sans MS, Chicago, Charcoal, Impact, Western, fantasy
font.monospace      : Andale Mono, Bitstream Vera Sans Mono, Nimbus Mono L, Courier New, Courier, Fixed, Terminal, monospace
font.latex.package  : type1cm  # This must be an available LaTeX font
#package, like 'times' or 'pslatex' ; only applies if text.usetex is set

### TEXT
# text properties used by text.Text.  See
# http://matplotlib.sourceforge.net/matplotlib.text.html for more
# information on text properties
text.color          : black
text.usetex         : False  # use tex/latex for all text handling.  See http://matplotlib.sf.net/matplotlib.texmanager.html
text.tex.engine     : latex  # tex is faster, but latex is required to use special font packages

### AXES
# default face and edge color, default tick sizes,
# default fontsizes for ticklabels, and so on.  See
# http://matplotlib.sourceforge.net/matplotlib.axes.html#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      : 14      # fontsize of the axes title
axes.labelsize      : 12      # fontsize of the x any y labels
axes.labelcolor     : black

polaraxes.grid      : True    # display grid on polar axes

### TICKS
# see http://matplotlib.sourceforge.net/matplotlib.axis.html#Ticks
tick.major.size     : 4      # major tick size in points
tick.minor.size     : 2      # minor tick size in points
tick.major.pad      : 4      # distance to major tick label in points
tick.minor.pad      : 4      # distance to the minor tick label in points
tick.color          : k      # color of the tick labels 
tick.labelsize      : 12     # fontsize of the tick labels

### Grids
grid.color       :   black       # grid color
grid.linestyle   :   :       # dotted
grid.linewidth   :   0.5     # in points            

### FIGURE
# See http://matplotlib.sourceforge.net/matplotlib.figure.html#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

# The figure subplot parameters.  All dimensions are 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 : free              # free | preserve
image.interpolation  : bilinear  # see help(imshow) for options
image.cmap   : jet               # gray | jet
image.lut    : 256               # the size of the colormap lookup table
image.origin : upper             # lower | upper
 
### SAVING FIGURES
# the default savefig params can be different for the GUI backends.
# Eg, 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

# tk backend params
tk.window_focus   : False    # Maintain shell focus for TkAgg
tk.pythoninspect  : False    # tk sets PYTHONINSEPCT

# ps backend params
ps.papersize      : letter   # executive, letter, legal, ledger, A0-A10, B0-B6, C0-C6
ps.useafm         : False    # use of afm fonts -- breaks mathtext but results in small files
ps.usedistiller   : False    # Experimental: use ghostscript to distill ps output - may yield smaller files
ps.distiller.res  : 6000      # dpi

# Set the verbose flags.  This controls how much information
# matplotlib gives you at runtime and where it goes.  Ther verbosity
# levels are: silent, helpful, debug, debug-annoying.  Any level is
# inclusive of all the levels below it.  If you 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