Fw: RedHat and Release Upgrade to Numpy 1.8.1 and Matplotlib 1.3.1 / Install from Source

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: claudef@…3779…**

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

From:
Benjamin Root <ben.root@…1304…>

To:
falbriard <claudef@…3729…79…>,

Cc:
Matplotlib Users matplotlib-users@lists.sourceforge.net

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.v.root@…287…


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, <claudef@…3779…> 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`](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`](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`](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`](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`](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](http://mathtext.tt/)
: monospace
#[mathtext.it](http://mathtext.it/)
: serif:italic
#[mathtext.bf](http://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`](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`](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`](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`](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: **claudef@…4509…

From: Benjamin
Root <ben.root@…1304…>

To:
falbriard <claudef@…3779…>,
Matplotlib Users matplotlib-users@lists.sourceforge.net,

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.v.root@…287…


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, <claudef@…3779…> 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: **claudef@…4509…

From: Benjamin
Root <ben.root@…1304…>

To: falbriard
<claudef@…3779…>,

Cc: Matplotlib
Users matplotlib-users@lists.sourceforge.net

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.v.root@…287…


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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