First, copy the file site.cfg.example to site.cfg and open it in an editor like vim. The commented lines in the file give some explanation of how it works. You only need to add the following lines:

[mkl]
mkl_libs =  mkl_intel_lp64, mkl_intel_thread, mkl_core, guide
lapack_libs = mkl_lapack
include_dirs = /opt/intel/mkl/10.0.1.014/include
library_dirs = /opt/intel/mkl/10.0.1.014/lib/em64t

Notes:

• mkl_intel_thread and guide are only required if you want NumPy to use multi-threaded numerical libraries using OpenMP. If you use these two options, you must also pass the -openmp option to the Fortran compiler (see below).
• The [fftw] section appears to be obsolete. According to the SciPy wiki, support for FFTW was dropped for NumPy >= 1.2. If you need a faster FFT than the fftpack that is now included with NumPy, you may want to check out this project to build FFTW wrappers for Python.

Once you have fixed the config file, the following commands can be used to build NumPy:

LDFLAGS="" FFLAGS="-openmp" python2.7 setup.py build --fcompiler=intelem > stdout.txt 2> stderr.txt
python2.7 setup.py install --prefix=/apps/Python/Python-2.7.3/

Notes:

• I set LDFLAGS=”" to make sure that the LDFLAGS set in my .bashrc weren’t used in this build.
• Set FFLAGS=”-openmp” if you specify the libraries mkl_intel_thread and guide in site.cfg
• I like to redirect the standard error and standard output to files that I can view later.

Your configuration is successful if the first few lines of stdout look like this:

F2PY Version 2
blas_opt_info:
blas_mkl_info:
  FOUND:
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'guide', 'pthread']
    library_dirs = ['/opt/intel/mkl/10.0.1.014/lib/em64t']
    define_macros = [('SCIPY_MKL_H', None)]
    include_dirs = ['/opt/intel/mkl/10.0.1.014/include']

  FOUND:
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'guide', 'pthread']
    library_dirs = ['/opt/intel/mkl/10.0.1.014/lib/em64t']
    define_macros = [('SCIPY_MKL_H', None)]
    include_dirs = ['/opt/intel/mkl/10.0.1.014/include']

lapack_opt_info:
lapack_mkl_info:
mkl_info:
  FOUND:
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'guide', 'pthread']
    library_dirs = ['/opt/intel/mkl/10.0.1.014/lib/em64t']
    define_macros = [('SCIPY_MKL_H', None)]
    include_dirs = ['/opt/intel/mkl/10.0.1.014/include']

  FOUND:
    libraries = ['mkl_lapack', 'mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'guide'
, 'pthread']
    library_dirs = ['/opt/intel/mkl/10.0.1.014/lib/em64t']
    define_macros = [('SCIPY_MKL_H', None)]
    include_dirs = ['/opt/intel/mkl/10.0.1.014/include']

  FOUND:
    libraries = ['mkl_lapack', 'mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'guide'
, 'pthread']
    library_dirs = ['/opt/intel/mkl/10.0.1.014/lib/em64t']
    define_macros = [('SCIPY_MKL_H', None)]
    include_dirs = ['/opt/intel/mkl/10.0.1.014/include']

Next step: run some benchmarks!

var('x y')
function('test', x, y)
show(test(x, y))
show(diff(test(x, y), x))
show(diff(test(x, y), x, 2))
show(diff(test(x, y), y))
show(diff(test(x, y), y, 2))

I defined a function of two variables called test.  When you run this in the notebook interface, you get:

test(x,y)
D[0](test)(x,y)
D[0,0](test)(x,y)
D[1](test)(x,y)
D[1,1](test)(x,y)

The capital D denotes a derivative. The numbers in brackets indicate which variable the derivative is with respect to. In this example, 0 denotes x and 1 denotes y. The number of times a number is repeated indicates the order of the derivative. D[0] is the first derivative with respect to x, D[1] is the first derivative with respect to y, D[0,0] is the second derivative with respect to x and D[1,1] is the second derivative with respect to y.  Sage uses the same notation when typesetting equations in LaTeX, so you will have to do some manual typsetting if you want traditional partial derivative notation.

Why does Sage do it this way instead of using traditional notation?  The reason is that test is defined as a function of two variables, but Sage doesn’t know in advance what these variables will be.  test may be a function of two other functions, in which the chain rule would have to be used to display the derivatives correctly.  The extensive discussion that went into this design decision is archived in this thread.

If you’re new to Sage, I suggest you check out my Sage Beginner’s Guide.

1. Create and format the chart correctly in Excel.  It’s better to insert a “floating” chart in an existing worksheet, as shown below, rather than creating a new worksheet that contains only the chart.  Set the size of the chart by right-clicking near the edge of the chart and selecting Format Chart Area.  Then select Size and set the actual size and aspect ratio that you want (try 3 inches by 4 inches).  If you want a set of plots to have consistent formatting, it is very important that they are the exact same size in Excel!  If the finished plots must be different sizes but have the same formatting, make the outer dimensions for all the charts big enough to accommodate the largest plot.  Then shrink the plot within the frame, leaving whitespace which will be cropped out at a later step.  Also set correct font sizes, line widths, colors, etc.

2. Select the chart and print.  This will print the chart, by itself, on its own page.  When the Excel print dialog opens, select “Bullzip PDF Printer” instead of your normal printer and press Print. The Bullzip dialog will open and allow you to choose options for printing to a file. Choose a TIFF file in the General tab and set the output file name.  Then go to the Image tab, select tiff24nc (24-bit RGB) and set the resolution to at least 600dpi.  I have not gotten the other TIFF formats to work correctly.  Press the Save button when finished.  The resulting file will be quite large because it is uncompressed.

3. Open the saved file in an image editor such as the GIMP.  You will see that the chart has been printed on a large white page.  Use the crop tool to eliminate the extra whitespace around the chart.  Then choose “Save As” to save the image.  After you choose a file name, another dialog will appear to select TIFF options.  Choose “LZW” compression–it’s lossless, which is good for plots and line art.

Here is a link to the finished TIFF image.  This method is much more reliable and consistent than copying and pasting plots from Excel into Word or Powerpoint.

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.