newtr.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 "newtr.h"
#include "libmatlbm.h"

static mxChar _array1_[27] = { 'N', 'o', 't', ' ', 'e', 'n', 'o', 'u', 'g',
                               'h', ' ', 'i', 'n', 'p', 'u', 't', ' ', 'a',
                               'r', 'g', 'u', 'm', 'e', 'n', 't', 's', '.' };
static mxArray * _mxarray0_;
static mxArray * _mxarray2_;
static mxArray * _mxarray3_;
static double _ieee_nan_;
static mxArray * _mxarray4_;
static mxArray * _mxarray5_;

static mxChar _array7_[3] = { 't', 'r', '.' };
static mxArray * _mxarray6_;

static mxChar _array9_[7] = { '=', 'b', 'l', 'a', 'n', 'k', ';' };
static mxArray * _mxarray8_;

void InitializeModule_newtr(void) {
    _mxarray0_ = mclInitializeString(27, _array1_);
    _mxarray2_ = mclInitializeDouble(0.0);
    _mxarray3_ = mclInitializeDouble(1.0);
    _ieee_nan_ = mclGetNaN();
    _mxarray4_ = mclInitializeDouble(_ieee_nan_);
    _mxarray5_ = mclInitializeDoubleVector(0, 0, (double *)NULL);
    _mxarray6_ = mclInitializeString(3, _array7_);
    _mxarray8_ = mclInitializeString(7, _array9_);
}

void TerminateModule_newtr(void) {
    mxDestroyArray(_mxarray8_);
    mxDestroyArray(_mxarray6_);
    mxDestroyArray(_mxarray5_);
    mxDestroyArray(_mxarray4_);
    mxDestroyArray(_mxarray3_);
    mxDestroyArray(_mxarray2_);
    mxDestroyArray(_mxarray0_);
}

static mxArray * Mnewtr(int nargout_, mxArray * epochs, mxArray * varargin);

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

/*
 * The function "mlfNewtr" contains the normal interface for the "newtr"
 * M-function from file "d:\matlab6p5\toolbox\nnet\nnutils\newtr.m" (lines
 * 1-27). This function processes any input arguments and passes them to the
 * implementation version of the function, appearing above.
 */
mxArray * mlfNewtr(mxArray * epochs, ...) {
    mxArray * varargin = NULL;
    int nargout = 1;
    mxArray * tr = NULL;
    mlfVarargin(&varargin, epochs, 0);
    mlfEnterNewContext(0, -2, epochs, varargin);
    tr = Mnewtr(nargout, epochs, varargin);
    mlfRestorePreviousContext(0, 1, epochs);
    mxDestroyArray(varargin);
    return mlfReturnValue(tr);
}

/*
 * The function "mlxNewtr" contains the feval interface for the "newtr"
 * M-function from file "d:\matlab6p5\toolbox\nnet\nnutils\newtr.m" (lines
 * 1-27). The feval function calls the implementation version of newtr through
 * this function. This function processes any input arguments and passes them
 * to the implementation version of the function, appearing above.
 */
void mlxNewtr(int nlhs, mxArray * plhs[], int nrhs, mxArray * prhs[]) {
    mxArray * mprhs[2];
    mxArray * mplhs[1];
    int i;
    if (nlhs > 1) {
        mlfError(
          mxCreateString(
            "Run-time Error: File: newtr Line: 1 Column: 1 The function \"newtr"
            "\" was called with more than the declared number of outputs (1)."),
          NULL);
    }
    for (i = 0; i < 1; ++i) {
        mplhs[i] = NULL;
    }
    for (i = 0; i < 1 && i < nrhs; ++i) {
        mprhs[i] = prhs[i];
    }
    for (; i < 1; ++i) {
        mprhs[i] = NULL;
    }
    mlfEnterNewContext(0, 1, mprhs[0]);
    mprhs[1] = NULL;
    mlfAssign(&mprhs[1], mclCreateVararginCell(nrhs - 1, prhs + 1));
    mplhs[0] = Mnewtr(nlhs, mprhs[0], mprhs[1]);
    mlfRestorePreviousContext(0, 1, mprhs[0]);
    plhs[0] = mplhs[0];
    mxDestroyArray(mprhs[1]);
}

/*
 * The function "Mnewtr" is the implementation version of the "newtr"
 * M-function from file "d:\matlab6p5\toolbox\nnet\nnutils\newtr.m" (lines
 * 1-27). 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 tr=newtr(epochs,varargin)
 */
static mxArray * Mnewtr(int nargout_, mxArray * epochs, mxArray * varargin) {
    mexLocalFunctionTable save_local_function_table_
      = mclSetCurrentLocalFunctionTable(&_local_function_table_newtr);
    int nargin_ = mclNargin(-2, epochs, varargin, NULL);
    mxArray * tr = NULL;
    mxArray * i = NULL;
    mxArray * blank = NULL;
    mxArray * names = NULL;
    mxArray * ans = NULL;
    mclCopyArray(&epochs);
    mclCopyArray(&varargin);
    /*
     * %NEWTR New training record with any number of optional fields.
     * %
     * %  Syntax
     * %
     * %    tr = newtr(epochs,'fieldname1','fieldname2',...)
     * %    tr = newtr([firstEpoch epochs],'fieldname1','fieldname2',...)
     * %
     * %  Warning!!
     * %
     * %    This function may be altered or removed in future
     * %    releases of the Neural Network Toolbox. We recommend
     * %    you do not write code which calls this function.
     * 
     * % Mark Beale, 11-31-97
     * % Copyright 1992-2002 The MathWorks, Inc.
     * % $Revision: 1.9 $ $Date: 2002/03/25 16:55:00 $
     * 
     * if nargin < 1,error('Not enough input arguments.'),end
     */
    if (nargin_ < 1) {
        mlfError(_mxarray0_, NULL);
    }
    /*
     * 
     * names = varargin;
     */
    mlfAssign(&names, mclVa(varargin, "varargin"));
    /*
     * tr.epoch = 0:epochs;
     */
    mlfIndexAssign(
      &tr, ".epoch", mlfColon(_mxarray2_, mclVa(epochs, "epochs"), NULL));
    /*
     * blank = zeros(1,epochs+1)+NaN;
     */
    mlfAssign(
      &blank,
      mclPlus(
        mlfZeros(
          _mxarray3_, mclPlus(mclVa(epochs, "epochs"), _mxarray3_), NULL),
        _mxarray4_));
    /*
     * for i=1:length(names)
     */
    {
        int v_ = mclForIntStart(1);
        int e_ = mclLengthInt(mclVv(names, "names"));
        if (v_ > e_) {
            mlfAssign(&i, _mxarray5_);
        } else {
            /*
             * eval(['tr.' names{i} '=blank;']);
             * end
             */
            for (; ; ) {
                mclAssignAns(
                  &ans,
                  mlfEval(
                    mclAnsVarargout(),
                    mlfHorzcat(
                      _mxarray6_,
                      mlfIndexRef(mclVv(names, "names"), "{?}", mlfScalar(v_)),
                      _mxarray8_,
                      NULL),
                    NULL));
                if (v_ == e_) {
                    break;
                }
                ++v_;
            }
            mlfAssign(&i, mlfScalar(v_));
        }
    }
    mclValidateOutput(tr, 1, nargout_, "tr", "newtr");
    mxDestroyArray(ans);
    mxDestroyArray(names);
    mxDestroyArray(blank);
    mxDestroyArray(i);
    mxDestroyArray(varargin);
    mxDestroyArray(epochs);
    mclSetCurrentLocalFunctionTable(save_local_function_table_);
    return tr;
}