Revision 5f4b66b247128720c6e7e8e9abfcecae4b518e41 authored by Miriam Cabero on 24 July 2017, 11:22:45 UTC, committed by Collin Capano on 24 July 2017, 11:22:45 UTC
* Fix Travis issues (hopefully)

* Rebase with master (for spherical harmonics) and fix documentation typos

* Change ringdown approximants' names

* Adapt pycbc_ringinj to new approximants and names

* Fix typos and remove unnecessary lines

* Adapt generator ringdown classes to new approximants

* Forgotten name-change in generator class

* Missing inclination
1 parent 0a8adfc
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INSTALL
PyCBC installation instructions
===============================

Prerequisites
-------------

* Python 2.6 or 2.7
  Should be provided by the distribution.

* python-decorator >= 3.3
  Should be available in the distribution.
  
* argparse >= 1.2.0
  Should be available in the distribution

* Numpy >= 1.4.1 and Scipy >= 0.7.2
  Should be installable either via the distribution packaging system,
  pip or easy_install. Numpy >= 1.5.1 is required for GPU acceleration
  via CUDA due to a bug in older versions.

* LALSuite
  See https://www.lsc-group.phys.uwm.edu/daswg/docs/howto/lal-install.html
  for installation instructions. LALSuite must be configured with the
  --enable-swig-python option.

Installing PyCBC
----------------

    git clone https://github.com/ligo-cbc/pycbc.git
    cd pycbc
    python setup.py build
    python setup.py install --user
    python setup.py test

For installing system-wide, replace the 'setup.py install' command with
    sudo python setup.py install


Installing CUDA Python modules
------------------------------

For GPU acceleration through CUDA:

* Nvidia CUDA >= 4.0 (driver and libraries).

* PyCUDA >= 2013.1.1 - http://mathema.tician.de/software/pycuda
  See next section for instructions.

* SciKits.cuda >= 0.041 - http://scikits.appspot.com/cuda
  See next section for instructions.

* Mako >= 0.7.2 - http://www.makotemplates.org
  See next section for instructions.

These packages may not be available via the distribution packaging system,
at least in the required versions. Although they should be generally
installable via pip or easy_install, this method is not always available
on LSC clusters. Therefore, we report general instructions for installing
from source on your ~/.local directory.

PyCUDA:
    git clone http://git.tiker.net/trees/pycuda.git
    cd pycuda
    git submodule init
    git submodule update
    ./configure.py
    python setup.py build
    python setup.py install --user

If your CUDA installation is in a non-standard location X,
pass --cuda-root=X to configure.py.

SciKits.cuda:
    Get the tarball (http://pypi.python.org/pypi/scikits.cuda) and unpack it.
    cd scikits.cuda*
    python setup.py install --user

Mako:
    Get the tarball (http://www.makotemplates.org/download.html) and unpack it.
    cd Mako*
    python setup.py install --user

To install system-wide rather than to ~/.local, change the 'setup.py install'
commands to
    sudo python setup.py install



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