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Only released in EOL distros:  

perception_pcl: cminpack | flann | pcl | pcl_android | pcl_ros

Package Summary

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).

perception_pcl: cminpack | flann | pcl | pcl_ros

Package Summary

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).

perception_pcl_fuerte_unstable: cminpack | flann | pcl16 | pcl16_ros | python_msg_conversions

Package Summary

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).

ExternalDocumentation

This is a third party package with external documentation.


2019-07-13 12:32