I installed PETSc and libMesh in my user directory, since I have a single-user workstation.

Installing PETSc for use with libMesh

First, ensure that OpenMPI is installed and the system paths have been configured correctly.  You will need to add the directory containing OpenMPI binaries to your $PATH, and the directory containing OpenMPI libraries to $LD_LIBRARY_PATH.  CentOS does not do this automatically!  Type mpicc on the command line to make sure the shell can find the binary.  If mpicc and mpif77 run, then you should not need to use the comnand-line flags to the configure script for PETSc.

If you are going to use libMesh with PETSc, you need to enable C++ with a command-line option to the configure script.  Here is the process I used (it might be a good idea to set PETSC_ARCH and PETSC_DIR in your .bashrc so they are consistent for all builds).

tar xfz petsc-3.2-p6.tar.gz
cd petsc-3.2-p6
export PETSC_DIR=$PWD
./configure --with-clanguage=c++
make PETSC_ARCH=arch-linux2-c-debug all
make PETSC_ARCH=arch-linux2-c-debug test

Installing libMesh

You must have compiled PETSc with C++ support, as detailed above, to install libMesh successfully.  Also, the environment variables PETSC_ARCH and PETSC_DIR in the libMesh build environment must have the same values used to build PETSc.  Once PETSc is built correctly, libMesh is easy to build:

 cd libmesh-0.7.2/libmesh
./configure
make
make run_examples

That’s it!  Please comment below if you have a different experience.

What if you want Paraview to appear in the Applications menu in your desktop environment?  Most modern desktops (I use XFCE4) construct the Applications menu “on the fly” based upon the files in a standard directory (/usr/share/applications on CentOS).  The Free Desktop Project has created a standard for desktop entry files.  You may also find this summary of the standard to be helpful.  To add Paraview to the menu, you simply need to create a new file in the standard location.  If you installed Paraview in your user directory, you may want to place the desktop file in $HOME/.local/applications.  Here are the contents of a file I called paraview.desktop:

[Desktop Entry]
Type=Application
Name=Paraview
Categories=Graphics;3DGraphics;Science;Engineering
Comment=3D visualization tool
Exec=paraview
Icon=paraview.svg

I found Paraview menu icons here.  Save the SVG icon to /usr/share/icons (there may be an equivalent location in your user directory but I don’t know what it is).  Now, when you bring up the Applications menu in your desktop environment the entry should appear (no need to restart or anything).

Screenshot of Paraview

If you find this post helpful, please check out the Sage Beginner’s Guide at Packt Publishing.  Since I don’t use Sage every day, I actually refer to my own book on a regular basis!

Download

Since CentOS is designed to be binary compatible with Red Hat Enterprise Linux, the correct binary to download is
sage-4.7.2-linux-64bit-red_hat_enterprise_linux_server_release_5.6_tikanga-x86_64-Linux.tar.gz

Install

Uncompress the file with tar xfz <filename>  The result is a huge directory (3.1Gb) with a self-contained version of Sage that can be run right where you uncompressed it.  As root, I moved the directory to /opt, changed ownership to root, and changed the name to sage-4.7.2.  I then edited the script /opt/sage-4.7.2/sage so that the variable SAGE_ROOT contains the correct path:

SAGE_ROOT="/opt/sage-4.7.2"

Run sage once as root to set the paths correctly.

User Access

To make it easier to run Sage,  I created a symbolic link to the Sage run script in /usr/bin/:

cd /usr/bin
ln -s /opt/sage-4.7.2/sage sage

Since this directory is on every user’s default path, a user can now start Sage by simply typing sage in a terminal.

Notebook Interface

When you first start Sage you will get a comnand-line interface in a terminal, which is very similar to iPython.  If you want to use a more graphical interface, type notebook() at the Sage command prompt:

Launching Sage Notebook

You will have to create an admin password, as shown above.  Follow the advice and create a secure password.  If a new browser tab or window doesn’t automatically open, open one manually and paste http://localhost:8000 into the address field.  You are now logged in as a user called admin, so I suggest creating a separate user account for yourself (for the same reason that you should only use the root account for system administration on a Linux system).  From the links at the top of the screen choose Settings->Manage Users->Add User.  After entering a user name, you will be given a temporary password.  Copy the temporary password, log out, and log in with your new user name and temporary password.  I suggest that you go to Settings and change your password to something easier to remember.

Formatting a floating-point number

"{0:.4f}".format(0.1234567890)

The result is the following string:

'0.1235'

Explanation

Braces { } are used to enclose the “replacement field”
0 indicates the first argument to method format
: indicates the start of the format specifier
.4 indicates four decimal places
f indicates a floating-point number

Scientific Notation

"{0:.4e}".format(0.1234567890)

Output:

'1.2346e-01'

Multiple Arguments

In Python 2.6 you can include multiple arguments like this:

"sin({0:.4f}) = {1:.4e}".format(0.1234567890, sin(0.123456789))

'sin(0.1235) = 1.2314e-01'

In Python 2.7 and later, you may omit the first integer from each replacement field, and the arguments to format will be taken in order:

"sin({:.4f}) = {:.4e}".format(0.1234567890, sin(0.123456789))

'sin(0.1235) = 1.2314e-01'

Gentoo Kernel 3.1 Config

For reasons unknown, a TeX Live package is not available for Red Hat Enterprise Linux/Centos 5 from the major repositories (EPEL or DAG).  I consider this to be a glaring omission, since TeXLive is a great improvement upon teTeX.  Since I don’t have time right now to package it myself, I installed TeX Live manually in my user directory and it’s working fine.  I used the network install process, which starts with downloading a command-line installer and then following the detailed installation instructions with the base path set to $HOME/texlive/2011.

Asymptote

The binary version of Asymptote installed with TeX Live didn’t run on my system, so I installed the Asymptote vector graphics language manually.  As root, I used yum to install the gc and gc-devel packages to provide the Boehm garbage collector that Asymptote uses.  I also had to install the package texinfo-tex from the CentOS base repo to provide the texindex utility that Asymptote uses to build its documentation.  Once the dependencies were in place, I downloaded the Asymptote source archive and unpacked it.  I used the following commands to build Asymptote in my user directory:

./configure --prefix=$HOME/asymptote
make
make install

Finally, I set up up the path environment variable in my .bashrc so that the copy of Asymptote I just built will run instead of the binary that comes with TeX Live and my locally installed TeX Live will run instead of the system installation of teTeX:

export PATH=~/asymptote/bin:~/texlive/2011/bin/x86_64-linux:$PATH

If you are doing this from scratch, you should check whether there is a away to prevent the TeX Live installer from installing Asymptote.

Technically, I could remove the system installation of teTeX at this point, but the LyX package depends on teTeX and I’ll have to see if there’s a way to tell yum to keep LyX and get rid of teTeX.

NOTE: I had to go through some trial and error to get this working.  I tried to summarize only the necessary steps, but I can’t guarantee I got it completely right until I try a fresh install on another system which does not have any of the dependencies already installed.  Please leave a comment if you encounter any problems.

As a superuser, use yum to install octave.  You need octave-devel and ncurses-devel in order to install any Octave packages.  You will need to have the EPEL repository enabled:

yum install octave octave-devel ncurses-devel

As a superuser, use yum to install ffmpeg and ffmpeg-devel from the rpmforge repo.  The video package for octave uses the ffmpeg libraries (avilib) to perform the actual video processing.  You will need the ffmpeg-devel package, because Octave builds the video package from source.

1. Since ffmpeg and ffmpeg-devel are only available from DAG/rpmforge, I suggest disabling EPEL before installing these packages.  This will ensure that all the dependencies are installed from rpmforge, instead of mixing packages from EPEL and rpmforge.  Mixing dependencies from different repositories might lead to incompatibilities and bugs that can be hard to trace.
2. yum install ffmpeg ffmpeg-devel

Install the video package for Octave.  I prefer to do this as an ordinary user (not root) so that the packages will be installed in my home directory (I have a “rule” that only the package manager is allowed to put files into system locations).  You will need to set the CXX flags environment variable to work around a bug in the C++ headers for the ffmpeg libraries.  If you are going to build other packages that link to ffmpeg’s libraries, you should probably set CXXFLAGS in your .bashrc.  I think this bug was fixed in later versions of ffmpeg, but they haven’t made it into EPEL or rpmforge yet.

1. Download video package
2. Unpack the archive: tar xfz video-1.0.2.tar.gz
3. Change to the unpacked directory: cd video-1.0.2
4. Temporarily set C++ flags and configure: CXXFLAGS=-D__STDC_CONSTANT_MACROS ./configure
5. Temporarily set C++ flags and build: CXXFLAGS=-D__STDC_CONSTANT_MACROS make
6. Install: make install

If you don’t set the C++ flags this way, you will get an error like this:

/usr/include/libavutil/common.h: In function ‘int32_t av_clipl_int32(int64_t)’:
/usr/include/libavutil/common.h:154: error: ‘UINT64_C’ was not declared in this scope

EDIT 2: you should use the –prefix=/home/yourusername instead of –user.  The prefix option places packages in the standard location: /home/yourusername/lib/python2.7/site-packages.  The –user option places the packages in /home/yourusername/.local/lib/python2.7/site-packages which I think is screwed up!

I use CentoOS5 because I want enterprise-class stability, as well as binary compatibility with a commercial application that is built for RHEL5.  I need to use some “bleeding edge” packages, such as the latest version of SciPy, but I don’t want to affect the base stability of the system.  Here is how I did it.  First, with superuser privileges, use yum to install the following packages.  You may need to set up epel as an alternate repository:

• readline-devel
• python-devel
• blas
• lapack
• atlas
• blas-devel
• lapack-devel
• atlas-devel

If you are going to install iPython (which I highly recommend) you will also need to install:

• sqlite-devel

Installing the “-devel” packages is critical!  The basic packages install libraries that end in *.so.3, which cannot be used to link newly built applications.  The -devel packages include libraries that end in *.so that are required for building Scipy.

Now, without superuser privileges, download Python 2.7.2, NumPy 1.6.1, and SciPy 0.9.0 to your home directory.

Building Python 2.7

cd Python-2.7.2
LDFLAGS='-L/usr/lib64' ./configure --prefix=/home/cfinch --enable-shared
make
make install

The LDFLAGS variable tells configure where to find libraries like sqlite, which will be needed if you want to build iPython.  A Python binary should now be installed in /home/yourname/bin/python2.7.  You have to type python2.7 to use the new one; if you just type python you will get the system-wide Python 2.4 interpreter.  You don’t want to change the default to 2.7 unless you really know what your are doing, because important system tools depend on having 2.4 as the default.  Finally, set your LD_LIBRARY_PATH environment variable to include /home/cfinch/lib:

export LD_LIBRARY_PATH='/home/cfinch/lib':$LD_LIBRARY_PATH

Building NumPy

tar xfz numpy-1.6.1.tar.gz
cd numpy-1.6.1

Now, copy the file site.cfg.example to site.cfg and make the following changes:

[DEFAULT]
#library_dirs = /usr/local/lib
#include_dirs = /usr/local/include
library_dirs=/usr/lib64/atlas

This tells the installation process where to find the library files for BLAS, LAPACK, and ATLAS. Now, we can install NumPy with:

python2.7 setup.py install --prefix=/home/cfinch

Building SciPy

tar xfz scipy-0.9.0.tar.gz
cd scipy-9.0.0
python2.7 setup.py install --prefix=/home/cfinch

Finally, download, build, and install iPython per the instructions. It won’t work unless you built Python with sqlite support, as described above.

matplotlib plot without a y axis

The full example is available on github.

First, we construct a figure and an axes object:

fig1 = plt.figure(facecolor='white')
ax1 = plt.axes(frameon=False)

The Axes object is a container that holds the axes, the ticks, the labels, the plot, the legend, etc.  You will always have an Axes object, even if the axes are not visible! The keyword argument frameon=False turns the frame off. An alternative method is:

ax1.set_frame_on(False)

We’ll disable the drawing of ticks at the top of the plot:

ax1.get_xaxis().tick_bottom()

Now, we’ll turn off the y axis:

ax1.axes.get_yaxis().set_visible(False)

Replace get_yaxis with get_xaxis to access the x axis.  The problem is that now the x axis doesn’t have a line, so we’ll have to add one ourselves.  Let’s assumed we’ve plotted some stuff.  To add the x axis line:

xmin, xmax = ax1.get_xaxis().get_view_interval()
ymin, ymax = ax1.get_yaxis().get_view_interval()
ax1.add_artist(Line2D((xmin, xmax), (ymin, ymin), color='black', linewidth=2))

First, we obtain the limits of the current view. Then, we use these limits to define the length of the x axis line. This approach allows the line to dynamically adapt if the user changes the view limits in the plot window. Note that we have to use a linewidth of 2 to get a visible linewidth of 1, because the lower half of the lower half of the line is clipped.  We use the add_artist method to add the line to the Axes object.   This method is better than just plotting a line on the Axes, because we don’t want the axis to show up in the legend!
Get the full example on github.

An alternate approach is to use the AxesGrid Toolkit, which comes with versions of Matplotlib 0.99 or higher.  Here is an example of how AxesGrid can display only the left and bottom axes.