[feel++] 02/04: remove from git these files that some clean target removes...
Mattia Rizzolo
mattia at debian.org
Wed Apr 20 06:54:19 UTC 2016
This is an automated email from the git hooks/post-receive script.
mattia pushed a commit to branch master
in repository feel++.
commit 781211770909541a9024627a51516fd9eea5f814
Author: Mattia Rizzolo <mattia at debian.org>
Date: Tue Apr 19 21:38:00 2016 +0000
remove from git these files that some clean target removes...
Gbp-Dch: Ignore
---
contrib/nlopt/bobyqa/README.orig | 60 --------------------------------
contrib/nlopt/cobyla/README.orig | 74 ----------------------------------------
contrib/nlopt/newuoa/README.orig | 40 ----------------------
3 files changed, 174 deletions(-)
diff --git a/contrib/nlopt/bobyqa/README.orig b/contrib/nlopt/bobyqa/README.orig
deleted file mode 100644
index 8a81d98..0000000
--- a/contrib/nlopt/bobyqa/README.orig
+++ /dev/null
@@ -1,60 +0,0 @@
-===========================================================================
-On 8/13/09 added the paper on BOBYQA
-===========================================================================
-
-For simplicity, the Makefi;e has been replaced by a one-line compile
-script "comp" which needs to be adjusted if the compiler name is not
-f77. All Fortran files are in bobyla.f. Compiling and running bobyqa
-should produce results similar to those in RESULTS.
- Hans Mittelmann, Jan 2009
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
- The Fortran version of BOBYQA is attached. Its purpose is to seek
-the least value of a function F of several variables, when derivatives
-are not available, where F is specified by the user through a subroutine
-called CALFUN. The name BOBYQA denotes Bound Approximation BY Quadratic
-Approximation, the constraints being lower and upper bounds on every
-variable, which can be set to huge values for unconstrained variables.
-The algorithm is intended to change the variables to values that are close
-to a local minimum of F. The user, however, should assume responsibility for
-finding out if the calculations are satisfactory, by considering carefully
-the values of F that occur. The BOBYQA software has been developed from the
-method of the paper "The NEWUOA software for unconstrained minimization
-without derivatives", in Large-Scale Nonlinear Optimization, editors G. Di
-Pillo and M. Roma, Springer (2006), pages 255-297. A report that describes
-the details of the development is going to be written soon.
-
- The attachments in sequence are a suitable Makefile, followed by a main
-program and a CALFUN routine for the "Invdist2" problem, in order to provide
-an example for testing. Then BOBYQA and its six auxiliary routines, namely
-BOBYQB, ALTMOV, PRELIM, RESCUE, TRSBOX and UPDATE, are given. Finally, the
-computed output that the author obtained for the Invdist2 problems is listed.
-
- In addition to providing CALFUN, an initial vector of variables and
-the lower and upper bounds, the user has to set the values of the parameters
-RHOBEG, RHOEND and NPT. After scaling the individual variables if necessary,
-so that the magnitudes of their expected changes are similar, RHOBEG is the
-initial steplength for changes to the variables, a reasonable choice being
-the mesh size of a coarse grid search. Further, RHOEND should be suitable for
-a search on a very fine grid. Typically, the software calculates a vector
-of variables that is within distance 10*RHOEND of a local minimum. Another
-consideration is that every trial vector of variables is forced to satisfy
-the lower and upper bounds, but there has to be room to make a search in all
-directions. Therefore an error return occurs if the difference between the
-bounds on any variable is less than 2*RHOBEG. The parameter NPT specifies
-the number of interpolation conditions on each quadratic model, the value
-NPT=2*N+1 being recommended for a start, where N is the number of variables.
-It is often worthwhile to try other choices too, but much larger values tend
-to be inefficient, because the amount of routine work of each iteration is
-of magnitude NPT**2, and because the achievement of adequate accuracy in some
-matrix calculations becomes more difficult. Some excellent numerical results
-have been found in the case NPT=N+6 even with more than 100 variables.
-
- The way of calling BOBYQA should be clear from the Invdist2 examples
-and from the comments near the beginning of SUBROUTINE BOBYQA. There are no
-restrictions on or charges for the use of the software. I hope that the time
-and effort I have spent on developing the package will be helpful to much
-research and to many applications.
-
-January 5th, 2009 M.J.D. Powell (mjdp at cam.ac.uk)
-
diff --git a/contrib/nlopt/cobyla/README.orig b/contrib/nlopt/cobyla/README.orig
deleted file mode 100644
index 09ead81..0000000
--- a/contrib/nlopt/cobyla/README.orig
+++ /dev/null
@@ -1,74 +0,0 @@
-# COBYLA : constrained optimization by linear approximation
-# Version 1.1
-# Copyright (c) 1992, Michael J. D. Powell (M.J.D.Powell at damtp.cam.ac.uk)
-# Copyright (c) 2004, J.S. Roy (js at jeannot.org)
-# See the LICENSE file for copyright information.
-# $Jeannot: README,v 1.7 2004/04/18 14:04:20 js Exp $
-
-This software is a C version of COBYLA2, a contrained optimization by linear
-approximation package developed by Michael J. D. Powell in Fortran.
-
-The original source code can be found at :
-http://plato.la.asu.edu/topics/problems/nlores.html
-
-Reference article for the method: Powell, J.M.D. (1992), "A Direct Search
-Optimization Method that Models the Objective and Constraint Functions by Linear
-Interpolation", DAMTP/NA5, Cambridge, England.
-
-This package was initially built by J.S. Roy to ease integration into SciPy.
-See: http://www.scipy.org/
-Many thanks to Michael J. D. Powell for allowing this to happen !
-
-This software, a derivative free non-linear optimizer, aims at minimizing the
-value of a nonlinear function subject to nonlinear constraints. It requires to
-be able to evaluate the function and the value of the constraints.
-
-COBYLA will try to make all the values of the constraints positive.
-So if you want to input a constraint j such as variable x[i] <= MAX, set:
- constraint[j] = MAX - x[i]
-
-See the comments in cobyla.c for more details.
-
-This software has been converted from the Fortran into C and provides the
-following modifications :
-- reentrancy, no global variables or functions ;
-- ability to pass a pointer to the function to be optimized (to provide
- access to constants) ;
-- ability to end the minimization at any time ;
-And other small changes.
-
-The last version (and other software) is avalaible at the URL :
-http://www.jeannot.org/~js/code/index.en.html
-
-A Python interface module is also provided.
-
-Contents :
-- cobyla.c : Source
-- cobyla.h : Header, and API documentation
-- LICENSE : License and copyright information
-- HISTORY : Release history
-- README : This file
-- example.c : A simple example
-- Makefile : Make file used to build the examples
-- moduleCobyla.c : the source of the python module
-- cobyla.py : the python module wrapper
-- example.py : an example for the python module
-- setup.py : the python installer
-
-Use is described in cobyla.h. For more information, see the example.
-The example can be built and executed by doing :
- make test
-
-You may need to adjust the Makefile before building cobyla.
-
-To install the module in the current directory, use:
- python setup.py build_ext --inplace
-To test it, execute:
- python cobyla.py
-To install it globaly, use:
- python setup.py install
-
-If you make use of this software, or if you make modifications to it (for a
-specific platform for example), you are encouraged to contact the author of
-this Fortran to C conversion at the following email : js at jeannot.org
-Thanks !
diff --git a/contrib/nlopt/newuoa/README.orig b/contrib/nlopt/newuoa/README.orig
deleted file mode 100644
index 23f7354..0000000
--- a/contrib/nlopt/newuoa/README.orig
+++ /dev/null
@@ -1,40 +0,0 @@
- This is the Fortran version of NEWUOA. Its purpose is to seek
-the least value of a function F of several variables, when derivatives
-are not available, where F is specified by the user through a subroutine
-called CALFUN. The algorithm is intended to change the variables to values
-that are close to a local minimum of F. The user, however, should assume
-responsibility for finding out if the calculations are satisfactory, by
-considering carefully the values of F that occur. The method is described
-in the report "The NEWUOA software for unconstrained optimization without
-derivatives", which is available on the web at www.damtp.cam.ac.uk, where
-you have to click on Numerical Analysis and then on Reports, the number
-of the report being NA2004/08. Let N be the number of variables. The main
-new feature of the method is that quadratic models are updated using only
-about NPT=2N+1 interpolation conditions, the remaining freedom being taken
-up by minimizing the Frobenius norm of the change to the second derivative
-matrix of the model.
-
- The new software was developed from UOBYQA, which also forms quadratic
-models from interpolation conditions. That method requires NPT=(N+1)(N+2)/2
-conditions, however, because they have to define all the parameters of the
-model. The least Frobenius norm updating procedure with NPT=2N+1 is usually
-much more efficient when N is large, because the work of each iteration is
-much less than before, and in some experiments the number of calculations
-of the objective function seems to be only of magnitude N.
-
- The attachments in sequence are a suitable Makefile, followed by a main
-program and a CALFUN routine for the Chebyquad problems, in order to provide
-an example for testing. Then NEWUOA and its five auxiliary routines, namely
-NEWUOB, BIGDEN, BIGLAG, TRSAPP and UPDATE, are given. Finally, the computed
-output that the author obtained for the Chebyquad problems is listed.
-
- The way of calling NEWUOA should be clear from the Chebyquad example
-and from the comments of that subroutine. It is hoped that the software will
-be helpful to much future research and to many applications. There are no
-restrictions on or charges for its use. If you wish to refer to it, please
-cite the DAMTP report that is mentioned above, which has been submitted for
-publication in the proceedings of the 40th Workshop on Large Scale Nonlinear
-Optimization (Erice, Italy, 2004).
-
-December 16th, 2004 M.J.D. Powell (mjdp at cam.ac.uk)
-
--
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