matplotlib-users Mailing List for matplotlib (Page 2)

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Dear colleagues, 

Took a while to fix it here. 

 I've chosen the qt package downloading and installing it manually 
together with the sip package as well as the pyqy4 package and qt-devel 
package. 

The pyqy4 configure process showed a dependency from the module "qmake" 
which I fixed with the install command:  python configure.py -q 
/usr/lib64/qt4/bin/qmake -g 
Further I've updated the matplotlibrc file pointing the entry to:  backend 
: QT4Agg. 

Numpy 1.8.1 and Matplotlib 1.3.1 is executing now the 3dScatter diagram, 
all working nicely, latest versions of Matplotlib and Numpy are running on 
the RedHat 6.4. 

Thanks Ben for your guidance and support. Problem solved. 

Regards, 
Claude 

Claude Falbriard 
Certified IT Specialist L2 - Middleware
AMS Hortolândia / SP - Brazil
phone:    +55 13 9 9760 0453
cell:         +55 13 9 8117 3316
e-mail:    cl...@br...

----- Forwarded by Claude Falbriard/Brazil/IBM on 27/03/2014 21:20 -----

From:   Benjamin Root <ben...@ou...>
To:     falbriard <cl...@br...>, 
Cc:     Matplotlib Users <mat...@li...>
Date:   27/03/2014 17:16
Subject:        Re: [Matplotlib-users] RedHat and Release Upgrade to Numpy 
1.8.1 and Matplotlib 1.3.1 / Install from Source
Sent by:        ben...@gm...

Claude,

Just noticed your matplotlibrc file has "agg" listed for the backend. That 
usually happens when the build process for matplotlib does not find any 
development files for a particular backend to be available. See this page: 
http://matplotlib.org/faq/installing_faq.html#install-from-git

Essentially, just having the "devel" packages for one or more of the 
various toolkits is sufficient. Once you have that installed, clean the 
build and rebuild.

Cheers!
Ben Root

On Thu, Mar 27, 2014 at 4:08 PM, <cl...@br...> wrote:
Dear Ben, 

I've also repeated the install using pip unistall and install of 
matplotlib, both completed successfully but the issue remains, no 
graphical display at the RedHat Linux, as well as very fast and silent 
exit from the program code. 

The source used for my test is the 3D Scatter Sample form the Gallery: 

from mpl_toolkits.mplot3d import Axes3D 
import numpy as np 
import matplotlib.pyplot as plt 

fig = plt.figure() 
ax = fig.gca(projection='3d') 

x = np.linspace(0, 1, 100) 
y = np.sin(x * 2 * np.pi) / 2 + 0.5 
ax.plot(x, y, zs=0, zdir='z', label='zs=0, zdir=z') 

colors = ('r', 'g', 'b', 'k') 
for c in colors: 
    x = np.random.sample(20) 
    y = np.random.sample(20) 
    ax.scatter(x, y, 0, zdir='y', c=c) 

ax.legend() 
ax.set_xlim3d(0, 1) 
ax.set_ylim3d(0, 1) 
ax.set_zlim3d(0, 1) 

plt.show() 

The maplotlibrc 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 HOME/.matplotlib/matplotlibrc (unix/linux 
# like systems) and C:\Documents and Settings\yourname\.matplotlib 
# (win32 systems). 
# 
# 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      : agg 

# 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.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'. 
#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 

# 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 

Hope this helps to isolate the error. 

Regards, 
Claude 

Claude Falbriard 
Certified IT Specialist L2 - Middleware
AMS Hortolândia / SP - Brazil
phone:    +55 13 9 9760 0453
cell:         +55 13 9 8117 3316
e-mail:    cl...@br...

From:        Benjamin Root <ben...@ou...> 
To:        falbriard <cl...@br...>, Matplotlib Users <
mat...@li...>, 
Date:        27/03/2014 16:20 
Subject:        Re: [Matplotlib-users] RedHat and Release Upgrade to Numpy 
1.8.1 and Matplotlib 1.3.1 / Install from Source 
Sent by:        ben...@gm... 

Claude, it would be helpful to know exactly what code you executed. Some 
example code assumes interactive modes, while others simply save files 
without ever showing them to the screen.

Also, please include a copy of your matplotlibrc file.

Ben Root

On Thu, Mar 27, 2014 at 1:47 PM, <cl...@br...> wrote: 
Dear Ben, 

The execution of any of the Matplotlib sample code start quickly and and 
exits immediately with no error message displayed  at the screen. The 
process runs instantly, so there is no wait in the process. 
Looks more like a missing setup option, matplotlib does not find a valid 
graphical screen display environment. What do you think is causing this 
error in RedHat Linux? 

Regards, 
Claude 

Claude Falbriard 
Certified IT Specialist L2 - Middleware
AMS Hortolândia / SP - Brazil
phone:    +55 13 9 9760 0453
cell:         +55 13 9 8117 3316
e-mail:    cl...@br...

From:        Benjamin Root <ben...@ou...> 
To:        falbriard <cl...@br...>, 
Cc:        Matplotlib Users <mat...@li...> 
Date:        27/03/2014 14:32 
Subject:        Re: [Matplotlib-users] RedHat and Release Upgrade to Numpy 
1.8.1 and Matplotlib 1.3.1 / Install from Source 
Sent by:        ben...@gm... 

How long did you wait? Do allow approximately one minute for the first 
execution to allow for the font.cache to be built. It can appear that the 
process has "hung" because it is waiting for "fc-list" subprocess to 
complete. 

Cheers!
Ben Root 

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