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electric:Documentation generated on March 01, 2013 at 04:25 PM
fuerte:Documentation generated on January 02, 2014 at 11:37 AM
This is the official description of Minpack, from the original ReadMe file:
Minpack includes software for solving nonlinear equations and nonlinear
least squares problems. Five algorithmic paths each include a core
subroutine and an easy-to-use driver. The algorithms proceed either from an
analytic specification of the Jacobian matrix or directly from the problem
functions. The paths include facilities for systems of equations with a
banded Jacobian matrix, for least squares problems with a large amount of
data, and for checking the consistency of the Jacobian matrix with the
functions.
Minpack is probably the best open-source implementation of the
Levenberg-Marquardt algorithm (in fact, it is even better, since it adds to
L-M automatic variables scaling). There is another open-source L-M
implementation in C/C++, levmar by Manolis Lourakis, but unfortunately is is
released under the GPL, which restricts its inclusion in commercial
software. Minpack is licensed under a BSD-like license (available in the
distribution).
I took a dozen of hours to rework all these problems, and came out with a
pure C version of Minpack, with has standard (ISO C99) parameters passing,
is fully reentrant, multithread-safe, and has a full set of examples and
tests:
1. Input variables are now passed by value, output variables are passed by
reference. The keyword "const" is used as much as possible for constant
arrays. The return value of each function is now used to get the function
status (it was obtained via the IFLAG or INFO parameter in Minpack).
2. All non-const static variables were removed, and the code was tested
after that. Luckily, Minpack didn't use the nastiest feature in FORTRAN: all
local variables are static, so that a function can behave differently when
you call it several times.
3. The function to be minimized and all the Minpack functions now take
an extra "void*" argument, which can be used to pass any
pointer-to-struct or pointer-to-class, and you can put all you extra
parameters and datd in that struct. Just cast this pointer to the
appropriate pointer type in your function, and there they are! There
is no need for global variables anymore. Be careful if you access the
same object from different threads, though.
4. The Debian project did a C include file for Minpack. It still needed some
work (add consts and C++ compatibility), so I did this work, and used the
include file for the FORTRAN version as the base for my C/C++ version.
5. The Debian project also translated all the FORTRAN examples to C. I
worked from these to produce examples which also call my C/C++ version of
Minpack instead of the FORTRAN version. Also included in the distribution
are reference output files produced by the test runs (for comparison).
This is the official description of Minpack, from the original ReadMe file:
Minpack includes software for solving nonlinear equations and nonlinear
least squares problems. Five algorithmic paths each include a core
subroutine and an easy-to-use driver. The algorithms proceed either from an
analytic specification of the Jacobian matrix or directly from the problem
functions. The paths include facilities for systems of equations with a
banded Jacobian matrix, for least squares problems with a large amount of
data, and for checking the consistency of the Jacobian matrix with the
functions.
Minpack is probably the best open-source implementation of the
Levenberg-Marquardt algorithm (in fact, it is even better, since it adds to
L-M automatic variables scaling). There is another open-source L-M
implementation in C/C++, levmar by Manolis Lourakis, but unfortunately is is
released under the GPL, which restricts its inclusion in commercial
software. Minpack is licensed under a BSD-like license (available in the
distribution).
I took a dozen of hours to rework all these problems, and came out with a
pure C version of Minpack, with has standard (ISO C99) parameters passing,
is fully reentrant, multithread-safe, and has a full set of examples and
tests:
1. Input variables are now passed by value, output variables are passed by
reference. The keyword "const" is used as much as possible for constant
arrays. The return value of each function is now used to get the function
status (it was obtained via the IFLAG or INFO parameter in Minpack).
2. All non-const static variables were removed, and the code was tested
after that. Luckily, Minpack didn't use the nastiest feature in FORTRAN: all
local variables are static, so that a function can behave differently when
you call it several times.
3. The function to be minimized and all the Minpack functions now take
an extra "void*" argument, which can be used to pass any
pointer-to-struct or pointer-to-class, and you can put all you extra
parameters and datd in that struct. Just cast this pointer to the
appropriate pointer type in your function, and there they are! There
is no need for global variables anymore. Be careful if you access the
same object from different threads, though.
4. The Debian project did a C include file for Minpack. It still needed some
work (add consts and C++ compatibility), so I did this work, and used the
include file for the FORTRAN version as the base for my C/C++ version.
5. The Debian project also translated all the FORTRAN examples to C. I
worked from these to produce examples which also call my C/C++ version of
Minpack instead of the FORTRAN version. Also included in the distribution
are reference output files produced by the test runs (for comparison).
This is the official description of Minpack, from the original ReadMe file:
Minpack includes software for solving nonlinear equations and nonlinear
least squares problems. Five algorithmic paths each include a core
subroutine and an easy-to-use driver. The algorithms proceed either from an
analytic specification of the Jacobian matrix or directly from the problem
functions. The paths include facilities for systems of equations with a
banded Jacobian matrix, for least squares problems with a large amount of
data, and for checking the consistency of the Jacobian matrix with the
functions.
Minpack is probably the best open-source implementation of the
Levenberg-Marquardt algorithm (in fact, it is even better, since it adds to
L-M automatic variables scaling). There is another open-source L-M
implementation in C/C++, levmar by Manolis Lourakis, but unfortunately is is
released under the GPL, which restricts its inclusion in commercial
software. Minpack is licensed under a BSD-like license (available in the
distribution).
I took a dozen of hours to rework all these problems, and came out with a
pure C version of Minpack, with has standard (ISO C99) parameters passing,
is fully reentrant, multithread-safe, and has a full set of examples and
tests:
1. Input variables are now passed by value, output variables are passed by
reference. The keyword "const" is used as much as possible for constant
arrays. The return value of each function is now used to get the function
status (it was obtained via the IFLAG or INFO parameter in Minpack).
2. All non-const static variables were removed, and the code was tested
after that. Luckily, Minpack didn't use the nastiest feature in FORTRAN: all
local variables are static, so that a function can behave differently when
you call it several times.
3. The function to be minimized and all the Minpack functions now take
an extra "void*" argument, which can be used to pass any
pointer-to-struct or pointer-to-class, and you can put all you extra
parameters and datd in that struct. Just cast this pointer to the
appropriate pointer type in your function, and there they are! There
is no need for global variables anymore. Be careful if you access the
same object from different threads, though.
4. The Debian project did a C include file for Minpack. It still needed some
work (add consts and C++ compatibility), so I did this work, and used the
include file for the FORTRAN version as the base for my C/C++ version.
5. The Debian project also translated all the FORTRAN examples to C. I
worked from these to produce examples which also call my C/C++ version of
Minpack instead of the FORTRAN version. Also included in the distribution
are reference output files produced by the test runs (for comparison).
