However, the gnuplot function seems has a problem. I've tested your IVM C++ Gaussian Process tool (IVMCPP0p12 version). Below I suggest using the highest verbosity options -v 3 in each of the examples so that you can track the iterations.
The first oil example runs in a couple of minutes. Help can be obtained by writingĪll the tutorial optimisations are suggested take less than 1/2 hour to run on my less than 2GHz Pentium IV machine. The way the software operates is through the command line.
Much of the work to convert the code (which included ironing out several bugs) was done by William V.
Detailed instructions on how to compile are in the readme.msvc file. The compilation makes use of f2c versions of the FORTRAN code and the C version of LAPACK/BLAS, CLAPACK. A project file is provided in the current release in the directory MSVC/ivm. Microsoft Visual C++Īs of Release 0.101 the code compiles under Microsoft Visual Studio 7.1. Note that these pre-compiled versions are not optimised for the specific architecture and therefore do not give the speed up you would hope for from using lapack and blas. However you will need version s of the lapack and blas libraries available (see This can take some time to compile, and in the absence of any pre-compiled versions on the web I've provided some pre-compiled versions you may want to make use of (see the cygwin directory).
Cygwinįor Windows users the code compiles under cygwin.
These options may vary for particular machines. The file make.atlas includes options for compiling the ATLAS optimised versions of lapack and blas that are available on a server I have access to. One of the advantages of interfacing to the LAPACK and BLAS libraries is that they are often optimised for particular architectures. Rename the file with the relevant architecture to make.inc for it to be included. Architecture specific options are included in the make.ARCHITECTURE files. The code base makes fairly extensive use of FORTRAN so you need to have g77 installed.Īt the command line. Part of the reason for using gcc is the ease of interoperability with FORTRAN. The software was written with gcc on ubuntu. The software is mainly written in C++ but relies for some functions on FORTRAN code by other authors and the LAPACK and BLAS libraries.Īs well as the C++ code some utilities are supplied in the corresponding MATLAB code for visualising the results. This was difficult to do in MATLAB as users who have tried version 1 (which was fast but inflexible) and version 2 (which was flexible but slow) of the MATLAB software will appreciate. The software is written in C++ to try and get a degree of flexibility in the models that can be used without a serious performance hit. Release InformationĬurrent release is 0.001. This page describes how to compile and gives some examples of use of the C++ Gaussian Process code. Gaussian process code in C++ including some implementations of GP-LVM and IVM.