userName
README
From the website for the L-BFGS-B code (from at
http://www.ece.northwestern.edu/~nocedal/lbfgsb.html):
"""
L-BFGS-B is a limited-memory quasi-Newton code for bound-constrained
optimization, i.e. for problems where the only constraints are of the
form l<= x <= u.
"""
This is a Python wrapper (using F2PY) written by David M. Cooke
and released as version 0.9 on April 9, 2004.
The wrapper was slightly modified by Joonas Paalasmaa for the 3.0 version
in March 2012.
License of L-BFGS-B (Fortran code)
==================================
The version included here (in lbfgsb.f) is 3.0 (released April 25, 2011). It was
written by Ciyou Zhu, Richard Byrd, and Jorge Nocedal . It
carries the following condition for use:
"""
This software is freely available, but we expect that all publications
describing work using this software, or all commercial products using it,
quote at least one of the references given below. This software is released
under the BSD License.
References
* R. H. Byrd, P. Lu and J. Nocedal. A Limited Memory Algorithm for Bound
Constrained Optimization, (1995), SIAM Journal on Scientific and
Statistical Computing, 16, 5, pp. 1190-1208.
* C. Zhu, R. H. Byrd and J. Nocedal. L-BFGS-B: Algorithm 778: L-BFGS-B,
FORTRAN routines for large scale bound constrained optimization (1997),
ACM Transactions on Mathematical Software, 23, 4, pp. 550 - 560.
* J.L. Morales and J. Nocedal. L-BFGS-B: Remark on Algorithm 778: L-BFGS-B,
FORTRAN routines for large scale bound constrained optimization (2011),
ACM Transactions on Mathematical Software, 38, 1.
"""
The Python wrapper
==================
This code uses F2PY (http://cens.ioc.ee/projects/f2py2e/) to generate
the wrapper around the Fortran code.
The Python code and wrapper are copyrighted 2004 by David M. Cooke
.
Installation
============
Make sure you have F2PY, scipy_distutils, and a BLAS library that
scipy_distutils can find. Then,
$ python setup.py build
$ python setup.py install
and you're done.
Example usage
=============
An example of the usage is given at the bottom of the lbfgsb.py file.
Run it with 'python lbfgsb.py'.
License for the Python wrapper
==============================
Copyright (c) 2004 David M. Cooke
Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the Software without restriction, including without limitation the rights to
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
of the Software, and to permit persons to whom the Software is furnished to do
so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
http://www.ece.northwestern.edu/~nocedal/lbfgsb.html):
"""
L-BFGS-B is a limited-memory quasi-Newton code for bound-constrained
optimization, i.e. for problems where the only constraints are of the
form l<= x <= u.
"""
This is a Python wrapper (using F2PY) written by David M. Cooke
and released as version 0.9 on April 9, 2004.
The wrapper was slightly modified by Joonas Paalasmaa for the 3.0 version
in March 2012.
License of L-BFGS-B (Fortran code)
==================================
The version included here (in lbfgsb.f) is 3.0 (released April 25, 2011). It was
written by Ciyou Zhu, Richard Byrd, and Jorge Nocedal . It
carries the following condition for use:
"""
This software is freely available, but we expect that all publications
describing work using this software, or all commercial products using it,
quote at least one of the references given below. This software is released
under the BSD License.
References
* R. H. Byrd, P. Lu and J. Nocedal. A Limited Memory Algorithm for Bound
Constrained Optimization, (1995), SIAM Journal on Scientific and
Statistical Computing, 16, 5, pp. 1190-1208.
* C. Zhu, R. H. Byrd and J. Nocedal. L-BFGS-B: Algorithm 778: L-BFGS-B,
FORTRAN routines for large scale bound constrained optimization (1997),
ACM Transactions on Mathematical Software, 23, 4, pp. 550 - 560.
* J.L. Morales and J. Nocedal. L-BFGS-B: Remark on Algorithm 778: L-BFGS-B,
FORTRAN routines for large scale bound constrained optimization (2011),
ACM Transactions on Mathematical Software, 38, 1.
"""
The Python wrapper
==================
This code uses F2PY (http://cens.ioc.ee/projects/f2py2e/) to generate
the wrapper around the Fortran code.
The Python code and wrapper are copyrighted 2004 by David M. Cooke
.
Installation
============
Make sure you have F2PY, scipy_distutils, and a BLAS library that
scipy_distutils can find. Then,
$ python setup.py build
$ python setup.py install
and you're done.
Example usage
=============
An example of the usage is given at the bottom of the lbfgsb.py file.
Run it with 'python lbfgsb.py'.
License for the Python wrapper
==============================
Copyright (c) 2004 David M. Cooke
Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the Software without restriction, including without limitation the rights to
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
of the Software, and to permit persons to whom the Software is furnished to do
so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.