tlm1.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 16:47:40 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 "tlm1.h"
#include "learnlm.h"
#include "libmatlbm.h"
#include "libmmfile.h"
#include "nncpyd.h"
#include "nncpyi.h"
#include "nndef.h"
#include "nntobsf.h"
#include "ploterr.h"
#include "plotfa.h"
#include "simuff.h"
#include "sumsqr.h"

static mxChar _array1_[4] = { 't', 'l', 'm', '1' };
static mxArray * _mxarray0_;

static mxChar _array3_[54] = { 'U', 's', 'e', ' ', 'N', 'N', 'T', '2', 'F',
                               'F', ' ', 'a', 'n', 'd', ' ', 'T', 'R', 'A',
                               'I', 'N', ' ', 't', 'o', ' ', 'u', 'p', 'd',
                               'a', 't', 'e', ' ', 'a', 'n', 'd', ' ', 't',
                               'r', 'a', 'i', 'n', ' ', '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 double _array8_[8] = { 25.0, 1000.0, .02, .0001, .001, 10.0, .1, 1e+10 };
static mxArray * _mxarray7_;

static mxChar _array10_[5] = { 'd', 'e', 'l', 't', 'a' };
static mxArray * _mxarray9_;
static mxArray * _mxarray11_;

static mxChar _array13_[46] = { 'T', 'R', 'A', 'I', 'N', 'L', 'M', ':',
                                ' ', '%', '%', 'g', '/', '%', 'g', ' ',
                                'e', 'p', 'o', 'c', 'h', 's', ',', ' ',
                                'm', 'u', ' ', '=', ' ', '%', '%', 'g',
                                ',', ' ', 'S', 'S', 'E', ' ', '=', ' ',
                                '%', '%', 'g', '.', 0x005c, 'n' };
static mxArray * _mxarray12_;
static mxArray * _mxarray14_;
static mxArray * _mxarray15_;

static mxChar _array17_[1] = { 'm' };
static mxArray * _mxarray16_;

static mxChar _array19_[1] = { ' ' };
static mxArray * _mxarray18_;

static mxChar _array21_[58] = { 'T', 'R', 'A', 'I', 'N', 'L', 'M', ':', ' ',
                                'E', 'r', 'r', 'o', 'r', ' ', 'g', 'r', 'a',
                                'd', 'i', 'e', 'n', 't', ' ', 'i', 's', ' ',
                                't', 'o', 'o', ' ', 's', 'm', 'a', 'l', 'l',
                                ' ', 't', 'o', ' ', 'c', 'o', 'n', 't', 'i',
                                'n', 'u', 'e', ' ', 'l', 'e', 'a', 'r', 'n',
                                'i', 'n', 'g', '.' };
static mxArray * _mxarray20_;

static mxChar _array23_[52] = { 'T', 'R', 'A', 'I', 'N', 'L', 'M', ':', ' ',
                                'N', 'e', 't', 'w', 'o', 'r', 'k', ' ', 'e',
                                'r', 'r', 'o', 'r', ' ', 'd', 'i', 'd', ' ',
                                'n', 'o', 't', ' ', 'r', 'e', 'a', 'c', 'h',
                                ' ', 't', 'h', 'e', ' ', 'e', 'r', 'r', 'o',
                                'r', ' ', 'g', 'o', 'a', 'l', '.' };
static mxArray * _mxarray22_;

static mxChar _array25_[53] = { ' ', ' ', 'F', 'u', 'r', 't', 'h', 'e', 'r',
                                ' ', 't', 'r', 'a', 'i', 'n', 'i', 'n', 'g',
                                ' ', 'm', 'a', 'y', ' ', 'b', 'e', ' ', 'n',
                                'e', 'c', 'e', 's', 's', 'a', 'r', 'y', ',',
                                ' ', 'o', 'r', ' ', 't', 'r', 'y', ' ', 'd',
                                'i', 'f', 'f', 'e', 'r', 'e', 'n', 't' };
static mxArray * _mxarray24_;

static mxChar _array27_[55] = { ' ', ' ', 'i', 'n', 'i', 't', 'i', 'a',
                                'l', ' ', 'w', 'e', 'i', 'g', 'h', 't',
                                's', ' ', 'a', 'n', 'd', ' ', 'b', 'i',
                                'a', 's', 'e', 's', ' ', 'a', 'n', 'd',
                                '/', 'o', 'r', ' ', 'm', 'o', 'r', 'e',
                                ' ', 'h', 'i', 'd', 'd', 'e', 'n', ' ',
                                'l', 'a', 'y', 'e', 'r', 's', '.' };
static mxArray * _mxarray26_;

void InitializeModule_tlm1(void) {
    _mxarray0_ = mclInitializeString(4, _array1_);
    _mxarray2_ = mclInitializeString(54, _array3_);
    _mxarray4_ = mclInitializeString(21, _array5_);
    _mxarray6_ = mclInitializeDoubleVector(0, 0, (double *)NULL);
    _mxarray7_ = mclInitializeDoubleVector(1, 8, _array8_);
    _mxarray9_ = mclInitializeString(5, _array10_);
    _mxarray11_ = mclInitializeDouble(1.0);
    _mxarray12_ = mclInitializeString(46, _array13_);
    _mxarray14_ = mclInitializeDouble(0.0);
    _mxarray15_ = mclInitializeDouble(6.0);
    _mxarray16_ = mclInitializeString(1, _array17_);
    _mxarray18_ = mclInitializeString(1, _array19_);
    _mxarray20_ = mclInitializeString(58, _array21_);
    _mxarray22_ = mclInitializeString(52, _array23_);
    _mxarray24_ = mclInitializeString(53, _array25_);
    _mxarray26_ = mclInitializeString(55, _array27_);
}

void TerminateModule_tlm1(void) {
    mxDestroyArray(_mxarray26_);
    mxDestroyArray(_mxarray24_);
    mxDestroyArray(_mxarray22_);
    mxDestroyArray(_mxarray20_);
    mxDestroyArray(_mxarray18_);
    mxDestroyArray(_mxarray16_);
    mxDestroyArray(_mxarray15_);
    mxDestroyArray(_mxarray14_);
    mxDestroyArray(_mxarray12_);
    mxDestroyArray(_mxarray11_);
    mxDestroyArray(_mxarray9_);
    mxDestroyArray(_mxarray7_);
    mxDestroyArray(_mxarray6_);
    mxDestroyArray(_mxarray4_);
    mxDestroyArray(_mxarray2_);
    mxDestroyArray(_mxarray0_);
}

static mxArray * Mtlm1(mxArray * * b1,
                       mxArray * * i,
                       mxArray * * tr,
                       int nargout_,
                       mxArray * w1_in,
                       mxArray * b1_in,
                       mxArray * f1,
                       mxArray * p,
                       mxArray * t,
                       mxArray * tp);

_mexLocalFunctionTable _local_function_table_tlm1
  = { 0, (mexFunctionTableEntry *)NULL };

/*
 * The function "mlfTlm1" contains the normal interface for the "tlm1"
 * M-function from file "d:\matlab6p5\toolbox\nnet\nnobsolete\tlm1.m" (lines
 * 1-163). This function processes any input arguments and passes them to the
 * implementation version of the function, appearing above.
 */
mxArray * mlfTlm1(mxArray * * b1,
                  mxArray * * i,
                  mxArray * * tr,
                  mxArray * w1_in,
                  mxArray * b1_in,
                  mxArray * f1,
                  mxArray * p,
                  mxArray * t,
                  mxArray * tp) {
    int nargout = 1;
    mxArray * w1 = NULL;
    mxArray * b1__ = NULL;
    mxArray * i__ = NULL;
    mxArray * tr__ = NULL;
    mlfEnterNewContext(3, 6, b1, i, tr, w1_in, b1_in, f1, p, t, tp);
    if (b1 != NULL) {
        ++nargout;
    }
    if (i != NULL) {
        ++nargout;
    }
    if (tr != NULL) {
        ++nargout;
    }
    w1 = Mtlm1(&b1__, &i__, &tr__, nargout, w1_in, b1_in, f1, p, t, tp);
    mlfRestorePreviousContext(3, 6, b1, i, tr, w1_in, b1_in, f1, p, t, tp);
    if (b1 != NULL) {
        mclCopyOutputArg(b1, b1__);
    } else {
        mxDestroyArray(b1__);
    }
    if (i != NULL) {
        mclCopyOutputArg(i, i__);
    } else {
        mxDestroyArray(i__);
    }
    if (tr != NULL) {
        mclCopyOutputArg(tr, tr__);
    } else {
        mxDestroyArray(tr__);
    }
    return mlfReturnValue(w1);
}

/*
 * The function "mlxTlm1" contains the feval interface for the "tlm1"
 * M-function from file "d:\matlab6p5\toolbox\nnet\nnobsolete\tlm1.m" (lines
 * 1-163). The feval function calls the implementation version of tlm1 through
 * this function. This function processes any input arguments and passes them
 * to the implementation version of the function, appearing above.
 */
void mlxTlm1(int nlhs, mxArray * plhs[], int nrhs, mxArray * prhs[]) {
    mxArray * mprhs[6];
    mxArray * mplhs[4];
    int i;
    if (nlhs > 4) {
        mlfError(
          mxCreateString(
            "Run-time Error: File: tlm1 Line: 1 Column: 1 The function \"tlm1\""
            " was called with more than the declared number of outputs (4)."),
          NULL);
    }
    if (nrhs > 6) {
        mlfError(
          mxCreateString(
            "Run-time Error: File: tlm1 Line: 1 Column: 1 The function \"tlm1"
            "\" was called with more than the declared number of inputs (6)."),
          NULL);
    }
    for (i = 0; i < 4; ++i) {
        mplhs[i] = NULL;
    }
    for (i = 0; i < 6 && i < nrhs; ++i) {
        mprhs[i] = prhs[i];
    }
    for (; i < 6; ++i) {
        mprhs[i] = NULL;
    }
    mlfEnterNewContext(
      0, 6, mprhs[0], mprhs[1], mprhs[2], mprhs[3], mprhs[4], mprhs[5]);
    mplhs[0]
      = Mtlm1(
          &mplhs[1],
          &mplhs[2],
          &mplhs[3],
          nlhs,
          mprhs[0],
          mprhs[1],
          mprhs[2],
          mprhs[3],
          mprhs[4],
          mprhs[5]);
    mlfRestorePreviousContext(
      0, 6, mprhs[0], mprhs[1], mprhs[2], mprhs[3], mprhs[4], mprhs[5]);
    plhs[0] = mplhs[0];
    for (i = 1; i < 4 && i < nlhs; ++i) {
        plhs[i] = mplhs[i];
    }
    for (; i < 4; ++i) {
        mxDestroyArray(mplhs[i]);
    }
}

/*
 * The function "Mtlm1" is the implementation version of the "tlm1" M-function
 * from file "d:\matlab6p5\toolbox\nnet\nnobsolete\tlm1.m" (lines 1-163). 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 [w1,b1,i,tr] = tlm1(w1,b1,f1,p,t,tp)
 */
static mxArray * Mtlm1(mxArray * * b1,
                       mxArray * * i,
                       mxArray * * tr,
                       int nargout_,
                       mxArray * w1_in,
                       mxArray * b1_in,
                       mxArray * f1,
                       mxArray * p,
                       mxArray * t,
                       mxArray * tp) {
    mexLocalFunctionTable save_local_function_table_
      = mclSetCurrentLocalFunctionTable(&_local_function_table_tlm1);
    int nargin_ = mclNargin(6, w1_in, b1_in, f1, p, t, tp, NULL);
    mxArray * w1 = NULL;
    mxArray * new_SSE = NULL;
    mxArray * new_e = NULL;
    mxArray * new_b1 = NULL;
    mxArray * new_w1 = NULL;
    mxArray * dx = NULL;
    mxArray * jj = NULL;
    mxArray * grad = NULL;
    mxArray * je = NULL;
    mxArray * j = NULL;
    mxArray * j1 = NULL;
    mxArray * ext_d1 = NULL;
    mxArray * d1 = NULL;
    mxArray * mu = NULL;
    mxArray * h = NULL;
    mxArray * message = NULL;
    mxArray * plottype = NULL;
    mxArray * SSE = NULL;
    mxArray * e = NULL;
    mxArray * a1 = NULL;
    mxArray * ext_p = NULL;
    mxArray * db1 = NULL;
    mxArray * dw1 = NULL;
    mxArray * ii = NULL;
    mxArray * b1_ind = NULL;
    mxArray * w1_ind = NULL;
    mxArray * r = NULL;
    mxArray * s1 = NULL;
    mxArray * df1 = NULL;
    mxArray * mu_max = NULL;
    mxArray * mu_dec = NULL;
    mxArray * mu_inc = NULL;
    mxArray * mu_init = NULL;
    mxArray * grad_min = NULL;
    mxArray * eg = NULL;
    mxArray * me = NULL;
    mxArray * df = NULL;
    mxArray * ans = NULL;
    mclCopyInputArg(&w1, w1_in);
    mclCopyInputArg(b1, b1_in);
    mclCopyArray(&f1);
    mclCopyArray(&p);
    mclCopyArray(&t);
    mclCopyArray(&tp);
    /*
     * %TLM1 Train 1-layer feed-forward network w/Levenberg-Marquardt.
     * %
     * %  This function is obselete.
     * %  Use NNT2FF and TRAIN to update and train your network.
     * 
     * nntobsf('tlm1','Use NNT2FF and TRAIN to update and train your network.')
     */
    mlfNntobsf(_mxarray0_, _mxarray2_, NULL);
    /*
     * 
     * %  [W,B,TE,TR] = TLM1(W,B,'F1',P,T)
     * %    W  - Weight matrix.
     * %    B  - Bias vector.
     * %    F  - Transfer function (string).
     * %    P  - RxQ matrix of input vectors.
     * %    T  - S1xQ matrix of target vectors.
     * %    TP - Training parameters (optional).
     * %  Returns:
     * %    Wi - new weights.
     * %    Bi - new biases.
     * %    TE - the actual number of epochs trained.
     * %    TR - training record: [row of errors]
     * %
     * %  Training parameters are:
     * %    TP(1) - Epochs between updating display, default = 25.
     * %    TP(2) - Maximum number of epochs to train, default = 1000.
     * %    TP(3) - Sum-squared error goal, default = 0.02.
     * %    TP(4) - Minimum gradient, default = 0.0001.
     * %    TP(5) - Initial value for MU, default = 0.001.
     * %    TP(6) - Multiplier for increasing MU, default = 10.
     * %    TP(7) - Multiplier for decreasing MU, default = 0.1.
     * %    TP(8) - Maximum value for MU, default = 1e10.
     * %  Missing parameters and NaN's are replaced with defaults.
     * 
     * % Mark Beale, 12-15-93
     * % Copyright 1992-2002 The MathWorks, Inc.
     * % $Revision: 1.11 $  $Date: 2002/03/25 16:54:22 $
     * 
     * if nargin < 5,error('Not enough arguments.'),end
     */
    if (nargin_ < 5) {
        mlfError(_mxarray4_, NULL);
    }
    /*
     * 
     * % TRAINING PARAMETERS
     * if nargin == 5, tp = []; end
     */
    if (nargin_ == 5) {
        mlfAssign(&tp, _mxarray6_);
    }
    /*
     * tp = nndef(tp,[25 1000 0.02 0.0001 0.001 10 0.1 1e10]);
     */
    mlfAssign(&tp, mlfNndef(mclVa(tp, "tp"), _mxarray7_));
    /*
     * df = tp(1);
     */
    mlfAssign(&df, mclIntArrayRef1(mclVa(tp, "tp"), 1));
    /*
     * me = tp(2);
     */
    mlfAssign(&me, mclIntArrayRef1(mclVa(tp, "tp"), 2));
    /*
     * eg = tp(3);
     */
    mlfAssign(&eg, mclIntArrayRef1(mclVa(tp, "tp"), 3));
    /*
     * grad_min = tp(4);
     */
    mlfAssign(&grad_min, mclIntArrayRef1(mclVa(tp, "tp"), 4));
    /*
     * mu_init = tp(5);
     */
    mlfAssign(&mu_init, mclIntArrayRef1(mclVa(tp, "tp"), 5));
    /*
     * mu_inc = tp(6);
     */
    mlfAssign(&mu_inc, mclIntArrayRef1(mclVa(tp, "tp"), 6));
    /*
     * mu_dec = tp(7);
     */
    mlfAssign(&mu_dec, mclIntArrayRef1(mclVa(tp, "tp"), 7));
    /*
     * mu_max = tp(8);
     */
    mlfAssign(&mu_max, mclIntArrayRef1(mclVa(tp, "tp"), 8));
    /*
     * df1 = feval(f1,'delta');
     */
    mlfAssign(
      &df1, mlfFeval(mclValueVarargout(), mclVa(f1, "f1"), _mxarray9_, NULL));
    /*
     * 
     * % DEFINE SIZES
     * [s1,r] = size(w1);
     */
    mlfSize(mlfVarargout(&s1, &r, NULL), mclVa(w1, "w1"), NULL);
    /*
     * w1_ind = [1:(s1*r)];
     */
    mlfAssign(
      &w1_ind,
      mlfColon(_mxarray11_, mclMtimes(mclVv(s1, "s1"), mclVv(r, "r")), NULL));
    /*
     * b1_ind = [1:s1] + w1_ind(length(w1_ind));
     */
    mlfAssign(
      &b1_ind,
      mclPlus(
        mlfColon(_mxarray11_, mclVv(s1, "s1"), NULL),
        mclIntArrayRef1(
          mclVv(w1_ind, "w1_ind"), mclLengthInt(mclVv(w1_ind, "w1_ind")))));
    /*
     * ii = eye(b1_ind(length(b1_ind)));
     */
    mlfAssign(
      &ii,
      mlfEye(
        mclIntArrayRef1(
          mclVv(b1_ind, "b1_ind"), mclLengthInt(mclVv(b1_ind, "b1_ind"))),
        NULL));
    /*
     * dw1 = w1; db1 = b1;
     */
    mlfAssign(&dw1, mclVa(w1, "w1"));
    mlfAssign(&db1, mclVa(*b1, "b1"));
    /*
     * ext_p = nncpyi(p,s1);
     */
    mlfAssign(&ext_p, mlfNncpyi(mclVa(p, "p"), mclVv(s1, "s1")));