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Abstract: RLaB is an interactive, interpreted scientific programming environment for fast numerical prototyping and program development. rlabplus provides the third release of the environment for 32- and 64-bit linux systems on Intel and ARM/RaspberryPi architectures. The environment integrates large number of numerical solvers and functions from various sources, most notably from the Gnu Scientific Library (GSL) and from the netlib. In addition, it is possible to visualize data using gnuplot, xmgrace, and pgplot or plplot; get data using uniform resource locator implementing HDF5 or world wide web; control serial, GPIB or TCP/IP connection, to mention a few. RLaB was created by Ian Searle and collaborators. rlabplus is being actively developed by Marijan Kostrun. 

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 What is RLaB ? 

" .. RLaB is an interactive, interpreted scientific programming environment. RLaB is a very high level language intended to provide fast prototyping and program development, as well as easy data-visualization, and processing. RLaB is not a clone of languages such as those used by tools like Matlab or Matrix-X/Xmath. However, as RLaB focuses on creating a good experimental environment (or laboratory) in which to do matrix math, it can be called ``Matlab-like''; since the programming language possesses similar operators and concepts.

RLaB does not try to be a Matlab clone. Instead, it borrows what I believe are the best features of the Matlab language and provides improved language syntax and semantics. The syntax has been improved to allow users more expression and reduce ambiguities. The variable scoping rules have been improved to facilitate creation of larger programs and program libraries. A heterogeneous associative array has been added to allow users to create and operate on arbitrary data structures. The fundamental data type is a floating point matrix (either real or complex), though RLaB also includes string matrices, and sparse numerical matrices (both real and complex) .."
Ian Searle   

RLaB2 Rel. 1 (rlab-2.1.05) is no longer maintained. It is still available for download from the web site

Features of   or   RLaB2 Rel.3

  1. Built-in solvers:

    1. Advanced numerical methods and algorithms from the GNU Scientific Library (GSL) and  netlib /gams;
      1. cubic spline toolkit;
      2. root finding in one and multi-dimensions using MINPACK/GSL and HOMPACK (multidimensions), single parameter curve tracking with CONTIN and HOMPACK;
      3. numerical integration of a real function of a real scalar (QUADPACK/GSL) and a real vector variable over hypercube (GENZPAK and Monte Carlo) and simplex domains (GENZPAK);
      4. Tchebyshev polynomial toolkit, numerical differentiation of a real scalar and vector function in one and multi-dimensions, numerical div operator;
      5. Minimization of real vector functions of real vector variable with MINPACK/GSL, CONMAX and Proximal Bundle (TOMS 811), NEWUOA and differential evolution ;
      6. Fitting and modeling : least-squares and orthogonal distance regression solvers provided by ODRPACK and the GSL;
      7. Statistics toolkit, permutations, combinations, outliers;
      8. Ordinary differential equations toolkit with solvers for:
        • Initial value problems: rk2, rk4, rkf45, rkck45, rk8pd, rk2imp, rk4imp, gear1, gear2, bsimp (from the GSL), adams method (from netlib), blended implicite method (BiM) and the backward difference method as implemented in the package dvode (also from netlib) ;
        • Two-point boundary value problems:  ACDC/TWPBVP (stiff), COLDAE/COLSYS (mildly stiff) and MIRKDC (non-stiff);
        • Differential algebraic equations initial value problem: MEBDFI, DDASKR and BIM (all stiff solvers);
        • Sturm-Liouville eigenvalue/eigenfunction boundary value problem: SLEIGN2.
      9. Special functions (from AiryAi to Zeta, total of more than 65 new functions);
      10. Random number generators: integer, discrete, continuous, and histogrammatic in 1- and 2-D; and their respective probability distribution functions. Shuffling, choosing and sampling;
      11. Simulated annealing: basic (the GSL) and advanced (ASA code);
      12. Partial Differential Equations in 1-D:
      13. Chaos and Signal Processing toolkit, based-on or inspired-by the Time-Series Analysis Package ( TISEAN ) and recognized sources from netlib and gams:  False nearest neighbors, average mutual information; Recurrent maps, autocorrelation, running average;
      14. Generalized cross-validating spline smoothing (GCVSPL) for noisy data; piece-wise line interpolation (STL2) of noisy data, and generic b-spline fit in 1- and 2-D (DIERCKX).
      15. The Gnu Linear Programming Kit (GLPK): load/save data in different formats (MPS, CPLEX LP, GnuMath), and solvers (simplex, interior point, mixed integer). Uses sparse matrix storage for constraint matrix, can work with both dense and sparse constraint matrices.
      16. Sparse matrices functionality: integrated solvers SuperLU , UMFPack and SPARSKIT v.2, which provide efficient (memory and speed-wise) built-in sparse matrix functions solve, spsolve and det.
      17. Linear algebra functionality: ARPACK which provides eigs function for calculation of smaller number of eigenvalues/eigenvectors for dense and sparse matrices. It offers 4 general purpose iterative routines, integrated with UMFPACK (complex sparse matrices), SuperLU (real sparse matrices) and LAPACK (dense matrices).
      18. Integer data type which allows bit-wise logical operations on integers (and, or, not). Seamlessly incorporated in readb/writeb binary I/O operations.
      19. Elements of the C Clustering Library that are combined with such from the (now extinct and vanished) SPRANNLIB.

    2. General purpose libraries:  String toolkit: access to ascii table, creation of a string matrix, conversion of a real matrix to string matrix, gawk-type manipulations on string matrices.

    3. Dedicated lists mks and const with conversion factors between MKSA (SI) units and others, and the mathematical constants (different from unity), respectively.

  2. Data visualisation and input/output:
    1. Grace toolkit for visualization of the RLaB data arrays: custom colors, stacked graphs, etc. See jpegs of grace graphs created using rlabplus : example 1, example 2, and example 3;
    2. Pgplot fully integrated for fast data plots (e.g., during iterative solving). Gnuplot fully supported through pipe, or files: Predefined terminal options implemented for eps/ps, and gdlib (png/gif/jpeg) and xterm/wxt.
    3. Standard input/output functions: access to shell commands, editing or viewing of data arrays, stderr console etc.
    4. Handling of input/output using Uniform Resource Locator (URL) protocol://address. Supports protocols file, HDF5, serial, http/https/ftp and tcp.
      HDF5 input/output is supported for all data structures specific to RLaB (dense and sparse matrices, lists).
    5. GPIB add-on (shared object library. loader and scripted library) based on the project linux-gpib.
      Here, GPIB stands for General Purpose Interface Bus, and is a communication hardware and protocol used for scientific instrumentation, e.g., to communicate with oscilloscopes, power supplies, source meters, and so forth.
      I wrote support libraries for bunch of instruments. Let me know what you need.
    6. Export data to openoffice.org and matrix market (NIST) format.

  3. Embedded interpreters (virtual machines) and special solvers - all are disabled by default:
      1. Python
        (requires  ./configure --with-python).
        Initializes/kills interpreter, executes commands, and sets and reads python variables.
      2. Java Virtual Machnine
        (requires ./configure --with-jvm=/location/of/your/libjvm.so)
        Initializes the interpreter, calls different java methods from their jar files, and sets or reads jvm variables.
      3. ngspice
        (requires ./configure --with-spice, requires ngspice-25 or later built as a shared library)
        Initializes/kills the interpreter, passes commands to spice, runs spice scripts and files, and retrieves node values from processed spice circuits. Irrespectively, it can start ngspice processes, and read raw spice output files.

  4. Documentation: A first draft of a manual containing some 330 pages is available for download (size 2MB). Test codes demonstrating new features are available for download, as well. See a screenshoot of RLaB in action.

    On-line help is also available from the site Project Rosetta Code.

Installation Notes

rlabplus provides RLaB2 for 32- and 64-bit linux systems. Each comes in two archives, binaries only, and as source code. The source code archive contains a number of rconfigure scripts that set recommended features, e.g.:
All shared libraries require their development packages (library, e.g., libopenblas_barcelonap-r0.2.9.rc1.so; library soft link, e.g., libopenblas_barcelonap-r0.2.9.rc1.so -> libblas.so, and its header files in system wide directory /usr/include). Some libraries are mandatory, while the others are optional, where
  1. Mandatory libraries are:
    • math/io: BLAS, LAPACK,GSL, HDF, curl, X (if one chooses accompanying pgplot package for plotting)
    • system: termcap, readline, gnulib, f2c, gcc, ncurses, gfortran

  2. Optional libraries are
    • math: ARPACK (linear algebra), GLPK (linear programming), superlu/suitesparse (linear systems based on sparse matrices);
    • plot: plplot;
    • image/camera: gphoto2, imagemagick.

    All libraries except   ng-spice  are available from the installation media of any major linux distribution.

    I recommend using processor/cache optimized version library openblas, or libgoto2, in place of BLAS, because it significantly speeds up matrix computations.

  3. Optional libraries for embedded interpreters are
    • python (tested on 2.7);
    • java virtual machine; and,
    • ngspice 25 or later (tested and working for ngspice configured through, may require openmpi libraries)
       root/of/ngspice> \
             ./configure --with-ngshared --with-pic --with-gnu-ld --libdir=/usr/lib64 --enable-nobypass --enable-xspice --enable-cider
             --enable-pss --enable-ndev --enable-openmp --enable-gc

  4. Installation from archived source,
    1. Download rlab-2.x.y.z.src.tgz
    2. > tar xvfz rlab-2.x.y.z.src.tgz
    3. > cd rlab-2.x.y-gcc
    4. > ./configure  [--with-ngspice] [--with-jvm=/whereis/your/libjvm.so] [--with-python]
        [--with-arpack] [--with-superlu] [--with-im] [--with-gphoto2] [--with-plplot] [--enable-glpk] [--with-suitesparse]
    5. > make [scanner] gc flibs clibs rlab
    6. > sudo make install
      The last step will
      - executable and accompanying libraries in /usr/local/lib{64}/rlab{64}-2.x.y-gcc{n}.{l}.{m};
      - RLaB headers necessary for development of local shared object libraries in /usr/local/include/rlab.
      (accessible through #include <rlab/.....h> in your shared library source (c.f. libgpib).
    7. > sudo make uninstall
      also works, and it will remove RLaB - might be used to remove prior installations (I don't use it, as different versions of rlab, designation y above, can peacefully coexist on single machine).
      > make clean
      is recommended before building from the source code.

  5. Installation from archived binary,
    1. Download rlab-2.x.y.z.bin.tgz
    2. > tar xvfz rlab-2.x.y.z.bin.tgz
    3. > cd rlab-2.x.y
    4. Start an installation script in the directory, which will
      • copy the binaries and the needed libraries in the
      • copy the start script in /usr/local/bin/rlab2.
During building from sources, the flags CFLAGS and FFLAGS are consulted. The binary version was built using FFLAGS=CFLAGS=-O3 -fPIC .

Known Compilation Issues

rlabplus is built and tested on Linux distributions opensuse 11.1, 12.1, 12.3, 13.1, on processors ranging from Intel Pentium IV (32-bit), to AMD 64-bit Opterons, and ARM (RaspberryPi). I hear through the grape wine, it compiles without a problem of debian, ubuntu and fedora. Please report any problems with building rlabplus.

The known compilation issues are:
  1. ncurses library has to be fixed on opensuse 11.1 and prior installations. The two are provided, /usr/lib/libncurses.so.4 and /lib/ncurses.so.5. The .so.5 is required because of readline.
    cd /usr/lib{64]; ln -s ../../lib/libncurses.so.5 ./libncurses.so
    to fix it.
  2. termcap library has to be fixed on opensuse: The library is located in /usr/lib{64]/termcap.
    cd /usr/lib{64}; ln -s termcap/libtermcap.so ./; .
  3. The garbage collector gc (version 7.2) is part of the source tree, and is built through
             ./configure --disable-threads
    Use  make gc  to build it from the source root directory.
  4. Warning! RLaB parser is contained in the file lex.yy.c, which is created by FLEX, version 2.5.35 and fixed by hand.
    If there are problems with the parser file (it suddenly disappeared from source root directory),
            make scanner
    should fix it.

About the author

Marijan Kostrun, Ph.D. Physics (2002), University of Connecticut. Past gigs include UConn, ITAMP, and Wesleyan University. Currently researching on how to make the world a better place one photon at a time, albeit with as few electrons as possible.

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© 2004-2014, Marijan Kostrun.
Last updated on April 12, 2014.
Please e-mail all questions or comments to me !
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