plotsm.c

nnToolKit 神经网络工具包是基于 MATLAB 神经网络工具箱自行开发的一组神经网络算法函数库

/*
 * MATLAB Compiler: 3.0
 * Date: Sun May 13 16:47:41 2007
 * Arguments: "-B" "macro_default" "-O" "all" "-O" "fold_scalar_mxarrays:on"
 * "-O" "fold_non_scalar_mxarrays:on" "-O" "optimize_integer_for_loops:on" "-O"
 * "array_indexing:on" "-O" "optimize_conditionals:on" "-M" "-silentsetup" "-d"
 * "d:/MATLAB6p5/work/nnToolKit/src" "-B" "csglcom:nnToolKit,nnToolKit,2.0"
 * "-B" "sgl" "-m" "-W" "main" "-L" "C" "-t" "-T" "link:exe" "-h"
 * "libmmfile.mlib" "-W" "mainhg" "libmwsglm.mlib" "-t" "-W"
 * "comhg:nnToolKit,nnToolKit,2.0" "-T" "link:lib" "-h" "libmmfile.mlib" "-i"
 * "-i" "D:/MATLAB6p5/work/nnToolKit/lmnet/LmSimu.m"
 * "D:/MATLAB6p5/work/nnToolKit/lmnet/LmTrain.m"
 * "D:/MATLAB6p5/work/nnToolKit/sofm/SofmSimu.m"
 * "D:/MATLAB6p5/work/nnToolKit/sofm/SofmTrain.m" 
 */
#include "plotsm.h"
#include "libmatlbm.h"
#include "libmmfile.h"
#include "nntobsf.h"
#include "xlabel.h"
#include "ylabel.h"

static mxChar _array1_[7] = { 'a', 'd', 'a', 'p', 't', 'w', 'h' };
static mxArray * _mxarray0_;

static mxChar _array3_[55] = { 'U', 's', 'e', ' ', 'N', 'N', 'T', '2', 'L', 'I',
                               'N', ' ', 'a', 'n', 'd', ' ', 'A', 'D', 'A', 'P',
                               'T', ' ', 't', 'o', ' ', 'u', 'p', 'd', 'a', 't',
                               'e', ' ', 'a', 'n', 'd', ' ', 'a', 'd', 'a', 'p',
                               't', ' ', 'y', 'o', 'u', 'r', ' ', 'n', 'e', 't',
                               'w', 'o', 'r', 'k', '.' };
static mxArray * _mxarray2_;

static mxChar _array5_[21] = { 'N', 'o', 't', ' ', 'e', 'n', 'o',
                               'u', 'g', 'h', ' ', 'a', 'r', 'g',
                               'u', 'm', 'e', 'n', 't', 's', '.' };
static mxArray * _mxarray4_;
static mxArray * _mxarray6_;

static mxChar _array8_[33] = { 'W', ' ', 'm', 'u', 's', 't', ' ', 'h', 'a',
                               'v', 'e', ' ', 'a', 't', ' ', 'l', 'e', 'a',
                               's', 't', ' ', 't', 'w', 'o', ' ', 'c', 'o',
                               'l', 'u', 'm', 'n', 's', '.' };
static mxArray * _mxarray7_;

static mxChar _array10_[3] = { 'b', 'o', 'x' };
static mxArray * _mxarray9_;

static mxChar _array12_[2] = { 'o', 'n' };
static mxArray * _mxarray11_;

static mxChar _array14_[6] = { 'W', '(', 'i', ',', '1', ')' };
static mxArray * _mxarray13_;

static mxChar _array16_[6] = { 'W', '(', 'i', ',', '2', ')' };
static mxArray * _mxarray15_;
static mxArray * _mxarray17_;
static mxArray * _mxarray18_;
static mxArray * _mxarray19_;

static mxChar _array21_[1] = { 'b' };
static mxArray * _mxarray20_;

static mxChar _array23_[2] = { '.', 'r' };
static mxArray * _mxarray22_;

static mxChar _array25_[10] = { 'm', 'a', 'r', 'k', 'e',
                                'r', 's', 'i', 'z', 'e' };
static mxArray * _mxarray24_;
static mxArray * _mxarray26_;

static mxChar _array28_[3] = { 'o', 'f', 'f' };
static mxArray * _mxarray27_;

void InitializeModule_plotsm(void) {
    _mxarray0_ = mclInitializeString(7, _array1_);
    _mxarray2_ = mclInitializeString(55, _array3_);
    _mxarray4_ = mclInitializeString(21, _array5_);
    _mxarray6_ = mclInitializeDouble(2.0);
    _mxarray7_ = mclInitializeString(33, _array8_);
    _mxarray9_ = mclInitializeString(3, _array10_);
    _mxarray11_ = mclInitializeString(2, _array12_);
    _mxarray13_ = mclInitializeString(6, _array14_);
    _mxarray15_ = mclInitializeString(6, _array16_);
    _mxarray17_ = mclInitializeDoubleVector(0, 0, (double *)NULL);
    _mxarray18_ = mclInitializeDouble(1.1);
    _mxarray19_ = mclInitializeDouble(1.0);
    _mxarray20_ = mclInitializeString(1, _array21_);
    _mxarray22_ = mclInitializeString(2, _array23_);
    _mxarray24_ = mclInitializeString(10, _array25_);
    _mxarray26_ = mclInitializeDouble(20.0);
    _mxarray27_ = mclInitializeString(3, _array28_);
}

void TerminateModule_plotsm(void) {
    mxDestroyArray(_mxarray27_);
    mxDestroyArray(_mxarray26_);
    mxDestroyArray(_mxarray24_);
    mxDestroyArray(_mxarray22_);
    mxDestroyArray(_mxarray20_);
    mxDestroyArray(_mxarray19_);
    mxDestroyArray(_mxarray18_);
    mxDestroyArray(_mxarray17_);
    mxDestroyArray(_mxarray15_);
    mxDestroyArray(_mxarray13_);
    mxDestroyArray(_mxarray11_);
    mxDestroyArray(_mxarray9_);
    mxDestroyArray(_mxarray7_);
    mxDestroyArray(_mxarray6_);
    mxDestroyArray(_mxarray4_);
    mxDestroyArray(_mxarray2_);
    mxDestroyArray(_mxarray0_);
}

static void Mplotsm(mxArray * w, mxArray * m);

_mexLocalFunctionTable _local_function_table_plotsm
  = { 0, (mexFunctionTableEntry *)NULL };

/*
 * The function "mlfPlotsm" contains the normal interface for the "plotsm"
 * M-function from file "d:\matlab6p5\toolbox\nnet\nnobsolete\plotsm.m" (lines
 * 1-55). This function processes any input arguments and passes them to the
 * implementation version of the function, appearing above.
 */
void mlfPlotsm(mxArray * w, mxArray * m) {
    mlfEnterNewContext(0, 2, w, m);
    Mplotsm(w, m);
    mlfRestorePreviousContext(0, 2, w, m);
}

/*
 * The function "mlxPlotsm" contains the feval interface for the "plotsm"
 * M-function from file "d:\matlab6p5\toolbox\nnet\nnobsolete\plotsm.m" (lines
 * 1-55). The feval function calls the implementation version of plotsm through
 * this function. This function processes any input arguments and passes them
 * to the implementation version of the function, appearing above.
 */
void mlxPlotsm(int nlhs, mxArray * plhs[], int nrhs, mxArray * prhs[]) {
    mxArray * mprhs[2];
    int i;
    if (nlhs > 0) {
        mlfError(
          mxCreateString(
            "Run-time Error: File: plotsm Line: 1 Column: "
            "1 The function \"plotsm\" was called with mor"
            "e than the declared number of outputs (0)."),
          NULL);
    }
    if (nrhs > 2) {
        mlfError(
          mxCreateString(
            "Run-time Error: File: plotsm Line: 1 Column: "
            "1 The function \"plotsm\" was called with mor"
            "e than the declared number of inputs (2)."),
          NULL);
    }
    for (i = 0; i < 2 && i < nrhs; ++i) {
        mprhs[i] = prhs[i];
    }
    for (; i < 2; ++i) {
        mprhs[i] = NULL;
    }
    mlfEnterNewContext(0, 2, mprhs[0], mprhs[1]);
    Mplotsm(mprhs[0], mprhs[1]);
    mlfRestorePreviousContext(0, 2, mprhs[0], mprhs[1]);
}

/*
 * The function "Mplotsm" is the implementation version of the "plotsm"
 * M-function from file "d:\matlab6p5\toolbox\nnet\nnobsolete\plotsm.m" (lines
 * 1-55). It contains the actual compiled code for that M-function. It is a
 * static function and must only be called from one of the interface functions,
 * appearing below.
 */
/*
 * function plotsm(w,m)
 */
static void Mplotsm(mxArray * w, mxArray * m) {
    mexLocalFunctionTable save_local_function_table_
      = mclSetCurrentLocalFunctionTable(&_local_function_table_plotsm);
    int nargin_ = mclNargin(2, w, m, NULL);
    mxArray * len = NULL;
    mxArray * ind = NULL;
    mxArray * j = NULL;
    mxArray * i = NULL;
    mxArray * R = NULL;
    mxArray * S = NULL;
    mxArray * ans = NULL;
    mclCopyArray(&w);
    mclCopyArray(&m);
    /*
     * %PLOTSM Plot weights vectors of self-organizing map.
     * %  
     * %
     * %  This function is obselete.
     * %  Use PLOTSOM to plot a self-organizing map.
     * 
     * nntobsf('adaptwh','Use NNT2LIN and ADAPT to update and adapt your network.')
     */
    mlfNntobsf(_mxarray0_, _mxarray2_, NULL);
    /*
     * 
     * %  PLOTSM(W,M)
     * %    W - RxS matrix of weight vectors.
     * %    M - Neighborhood matrix.
     * %  Plots each neurons weight vector as a dot, and connects
     * %    neighboring neurons weight vectors with lines.
     * %  
     * %  EXAMPLES: W = rands(12,2);
     * %            M = nbman(3,4);
     * %            plotsm(W,M)
     * %  
     * %            [x,y] = meshgrid(1:5,1:6);
     * %            W = [x(:) y(:)];
     * %            M = nbman(5,6);
     * %            plotsm(W,M)
     * %  
     * %  See also NBGRID, NBMAN, NBDIST.
     * 
     * % Mark Beale, 12-15-93
     * % Copyright 1992-2002 The MathWorks, Inc.
     * % $Revision: 1.11 $  $Date: 2002/03/25 16:54:08 $
     * 
     * if nargin < 2, error('Not enough arguments.'),end
     */
    if (nargin_ < 2) {
        mlfError(_mxarray4_, NULL);
    }
    /*
     * 
     * [S,R] = size(w);
     */
    mlfSize(mlfVarargout(&S, &R, NULL), mclVa(w, "w"), NULL);
    /*
     * if R < 2,error('W must have at least two columns.'),end
     */
    if (mclLtBool(mclVv(R, "R"), _mxarray6_)) {
        mlfError(_mxarray7_, NULL);
    }
    /*
     * 
     * newplot;
     */
    mclAssignAns(&ans, mlfNNewplot(0, NULL));
    /*
     * set(gca,'box','on')
     */
    mclPrintAns(&ans, mlfNSet(0, mlfGca(NULL), _mxarray9_, _mxarray11_, NULL));
    /*
     * hold on
     */
    mlfHold(_mxarray11_);
    /*
     * xlabel('W(i,1)');
     */
    mclAssignAns(&ans, mlfNXlabel(0, _mxarray13_, NULL));
    /*
     * ylabel('W(i,2)');
     */
    mclAssignAns(&ans, mlfNYlabel(0, _mxarray15_, NULL));
    /*
     * 
     * % CONNECT WEIGHT VECTORS
     * for i=1:(S-1)
     */
    {
        int v_ = mclForIntStart(1);
        int e_ = mclForIntEnd(mclMinus(mclVv(S, "S"), _mxarray19_));
        if (v_ > e_) {
            mlfAssign(&i, _mxarray17_);
        } else {
            /*
             * j=(i+1):S;
             * ind = find(m(i,j) <= 1.1);
             * j = j(ind);
             * len = length(j);
             * plot([ones(len,1)*w(i,1) w(j,1)]',[ones(len,1)*w(i,2)' w(j,2)]','b');
             * end
             */
            for (; ; ) {
                mlfAssign(&j, mlfColon(mlfScalar(v_ + 1), mclVv(S, "S"), NULL));
                mlfAssign(
                  &ind,
                  mlfFind(
                    NULL,
                    NULL,
                    mclLe(
                      mclArrayRef2(mclVa(m, "m"), mlfScalar(v_), mclVv(j, "j")),
                      _mxarray18_)));
                mlfAssign(&j, mclArrayRef1(mclVv(j, "j"), mclVv(ind, "ind")));
                mlfAssign(&len, mlfScalar(mclLengthInt(mclVv(j, "j"))));
                mclAssignAns(
                  &ans,
                  mlfNPlot(
                    0,
                    mlfCtranspose(
                      mlfHorzcat(
                        mclMtimes(
                          mlfOnes(mclVv(len, "len"), _mxarray19_, NULL),
                          mclIntArrayRef2(mclVa(w, "w"), v_, 1)),
                        mclArrayRef2(mclVa(w, "w"), mclVv(j, "j"), _mxarray19_),
                        NULL)),
                    mlfCtranspose(
                      mlfHorzcat(
                        mlf_times_transpose(
                          mlfOnes(mclVv(len, "len"), _mxarray19_, NULL),
                          mclIntArrayRef2(mclVa(w, "w"), v_, 2),
                          _mxarray6_),
                        mclArrayRef2(mclVa(w, "w"), mclVv(j, "j"), _mxarray6_),
                        NULL)),
                    _mxarray20_,
                    NULL));
                if (v_ == e_) {
                    break;
                }
                ++v_;
            }
            mlfAssign(&i, mlfScalar(v_));
        }
    }
    /*
     * 
     * % PLOT WEIGHT VECTORS
     * plot(w(:,1),w(:,2),'.r','markersize',20)
     */
    mclPrintAns(
      &ans,
      mlfNPlot(
        0,
        mclArrayRef2(mclVa(w, "w"), mlfCreateColonIndex(), _mxarray19_),
        mclArrayRef2(mclVa(w, "w"), mlfCreateColonIndex(), _mxarray6_),
        _mxarray22_,
        _mxarray24_,
        _mxarray26_,
        NULL));
    /*
     * hold off
     */
    mlfHold(_mxarray27_);
    /*
     * drawnow
     */
    mlfDrawnow(NULL);
    mxDestroyArray(ans);
    mxDestroyArray(S);
    mxDestroyArray(R);
    mxDestroyArray(i);
    mxDestroyArray(j);
    mxDestroyArray(ind);
    mxDestroyArray(len);
    mxDestroyArray(m);
    mxDestroyArray(w);
    mclSetCurrentLocalFunctionTable(save_local_function_table_);
}