Hoffman2:Software Tools: Difference between revisions

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===CMake===
===CMake===
===CPACK===
===CPACK===
===MPI Kmeans===
See this website for how to cite using the MPI Kmeans tool.
[http://mloss.org/software/view/48/]
===Python2.7===
===Python2.7===
====Packages====
====Packages====

Revision as of 03:01, 18 April 2012

Back to all things Hoffman2

There is an FMRI usergroup on Hoffman2 which is maintained for groups doing Neuroimaging work at UCLA. Tools like FSL, FreeSurfer, AFNI and Nibabel are maintained for this group separate from normal Hoffman2 programs. In order to take advantage of these tools, you need to setup your account properly.

Setting Up Your Account to Access the Tools

NOTE: If you've never used a *NIX text editor, please read a bit about some of them here before proceeding.

In order to access all the great software packages that have been installed on Hoffman2 for the FMRI usergroup (list below), you need to edit your Bash Profile on the cluster. Follow these easy steps:

  1. SSH into Hoffman2 and make sure you are in your home directory (type the command cd and press enter).
  2. Open the file .bash_profile for editing. With VIM you would type
    With VIM you would type
    $ vim .bash_profile
    With Emacs you would type
    $ emacs .bash_profile
  3. Paste in the lines
    source /u/home/FMRI/apps/etc/profile
    umask 007
  4. Save and close out the file
    With VIM you would type
    ESC + ":wq" + ENTER
    With Emacs you would type
    CTRL+x, CTRL+c
  5. Logout of Hoffman2. The next time you log in, extra login messages will appear and you will have access to the FMRI usergroup software packages.


List of Tools

Under Construction...

GCC

LAPACK

BLAS

GLIB

C++

CMake

CPACK

MPI Kmeans

See this website for how to cite using the MPI Kmeans tool. [1]

Python2.7

Packages

CVXOPT
Cython
Gnuplot
IPython
matplotlib
nibabel
nifti
nimfa
Non-negative Matrix Factorization
http://nimfa.biolab.si/
nipype
nose
numpy
(p)lsa
(probabilistic) Latent Semantic Analysis. Failed its tests.py though.
http://www.mblondel.org/journal/2010/06/13/lsa-and-plsa-in-python/
pydicom
pygments
PyMF
Python Matrix Factorization Module. Failed its tests though.
http://pymf.googlecode.com
pypr
PyQt4
pytz
pywt
pyximport
scikits
scipy
sklearn
sparsesvd
Singular Value Decomposition. Passed both tests.
http://pypi.python.org/pypi/sparsesvd
sphinx
sympy
traits
virtualenv
xcbgen