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📄 estpab.cpp

📁 计算两个离散时间序列变量间的信息熵和互信息
💻 CPP
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//=========================================================////This is a prog in the MutualInfo 0.9 package written by// Hanchuan Peng.////Disclaimer: The author of program is Hanchuan Peng//      at <penghanchuan@yahoo.com> and <phc@cbmv.jhu.edu>.////The CopyRight is reserved by the author.////Last modification: April/19/2002////========================================================//// estpab.cpp// Calculate the joint histgram/probability of two vectors/images// By Hanchuan Peng// Dec/2000// April/8/2002#include "miinclude.h"//return the number of statestemplate <class T> void copyvecdata(T * srcdata, long len, int * desdata, int& nstate);template <class T> void copyvecdata(T * srcdata, long len, int * desdata, int& nstate){  if(!srcdata || !desdata)  {    printf("NULL points in copyvecdata()!\n");    return;  }   long i;  //note: originally I added 0.5 before rounding, however seems the negative numbers and   //      positive numbers are all rounded towarded 0; hence int(-1+0.5)=0 and int(1+0.5)=1;  //      This is unwanted because I need the above to be -1 and 1.  // for this reason I just round with 0.5 adjustment for positive and negative differently  //copy data  int minn,maxx;  if (srcdata[0]>0)    maxx = minn = int(srcdata[0]+0.5);  else    maxx = minn = int(srcdata[0]-0.5);  int tmp;  double tmp1;  for (i=0;i<len;i++)  {    tmp1 = double(srcdata[i]);    tmp = (tmp1>0)?(int)(tmp1+0.5):(int)(tmp1-0.5);//round to integers    minn = (minn<tmp)?minn:tmp;    maxx = (maxx>tmp)?maxx:tmp;    desdata[i] = tmp;    //    printf("%i ",desdata[i]);  }  //printf("\n");  //make the vector data begin from 0 (i.e. 1st state)  for (i=0;i<len;i++)  {    desdata[i] -= minn;  }  //return the #state  nstate = (maxx-minn+1);  return;}void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[]){  // check the arguments  if(nrhs != 3 && nrhs !=2 && nrhs!=4)    mexErrMsgTxt("Usage [jointprob_table, marginprob_1, marginprob2] = progname(vector1, vector2, maxstatenum, b_returnprob). \n(Both vectors can be images). Max range handled: INT type of the OS");  if(nlhs > 3)    mexErrMsgTxt("Too many output argument <jointprob_table>.");  if (!mxIsInt8(prhs[0]) && !mxIsUint8(prhs[0]) && !mxIsDouble(prhs[0]) )     mexErrMsgTxt("The first input argument must be types of INT8 or UINT8 or DOUBLE.");  if (!mxIsInt8(prhs[1]) && !mxIsUint8(prhs[1]) && !mxIsDouble(prhs[1]) )     mexErrMsgTxt("The second input argument must be types of INT8 or UINT8 or DOUBLE.");  //get and check size information  long i,j;  void *img1 = (void *)mxGetData(prhs[0]);  long len1 = mxGetNumberOfElements(prhs[0]);  mxClassID type1 = mxGetClassID(prhs[0]);  void *img2 = (void *)mxGetData(prhs[1]);  long len2 = mxGetNumberOfElements(prhs[1]);  mxClassID type2 = mxGetClassID(prhs[1]);	  if (!img1 || !img2 || !len1 || !len2)    mexErrMsgTxt("At least one of the input vectors is invalid.");  if (len1!=len2)    mexErrMsgTxt("The two vectors/images should have the same length.");  int b_findstatenum = 1;  int nstate1 = 0, nstate2 = 0;  if (nrhs>=3)  {    b_findstatenum = 0;    long MaxGrayLevel = (long) mxGetScalar(prhs[2]);    nstate1 = nstate2 = MaxGrayLevel;    if (MaxGrayLevel<=1)    {      printf("The argument #state is invalid. This program will decide #state itself.\n");      b_findstatenum = 1;    }  }  int b_returnprob = 1;  if (nrhs>=4)  {    b_returnprob = (mxGetScalar(prhs[3])!=0);  }  //copy data into new INT type array (hence quantization) and then reange them begin from 0 (i.e. state1)  int * vec1 = new int[len1];  int * vec2 = new int[len2];  int nrealstate1=0, nrealstate2=0;  switch(type1)  {    case mxINT8_CLASS: copyvecdata((char *)img1,len1,vec1,nrealstate1); break;    case mxUINT8_CLASS: copyvecdata((unsigned char *)img1,len1,vec1,nrealstate1); break;    case mxDOUBLE_CLASS: copyvecdata((double *)img1,len1,vec1,nrealstate1); break;  }    switch(type2)  {    case mxINT8_CLASS: copyvecdata((char *)img2,len2,vec2,nrealstate2); break;    case mxUINT8_CLASS: copyvecdata((unsigned char *)img2,len2,vec2,nrealstate2); break;    case mxDOUBLE_CLASS: copyvecdata((double *)img2,len2,vec2,nrealstate2); break;  }    //update the #state when necessary  if (nstate1<nrealstate1)  {    nstate1 = nrealstate1;    // printf("First vector #state = %i\n",nrealstate1);  }  if (nstate2<nrealstate2)  {    nstate2 = nrealstate2;    // printf("Second vector #state = %i\n",nrealstate2);  }  //generate the joint-distribution table  plhs[0] = mxCreateDoubleMatrix(nstate1,nstate2,mxREAL);  double *hab = (double *) mxGetPr(plhs[0]);  double **hab2d = new double * [nstate2];  for(j=0;j<nstate2;j++)    hab2d[j] = hab + (long)j*nstate1;  for (i=0; i<nstate1;i++)  for (j=0; j<nstate2;j++)  {    hab2d[j][i] = 0;  }    for (i=0;i<len1;i++)  {    //old method -- slow    //     indx = (long)(vec2[i]) * nstate1 + vec1[i];    //     hab[indx] += 1;    //new method -- fast    hab2d[vec2[i]][vec1[i]] += 1;  }    //return the probabilities, otherwise return count numbers  if(b_returnprob)  {    for (i=0; i<nstate1;i++)    for (j=0; j<nstate2;j++)    {      hab2d[j][i] /= len1;    }  }  //for nlhs>=2  if (nlhs>=2)  {    plhs[1] = mxCreateDoubleMatrix(nstate1,1,mxREAL);    double *ha = (double *)mxGetPr(plhs[1]);    for (i=0;i<nstate1;i++) {ha[i] = 0;}    for (i=0;i<nstate1;i++)    for (j=0;j<nstate2;j++)    {      ha[i] += hab2d[j][i];    }  }    if (nlhs>=3)  {    plhs[2] = mxCreateDoubleMatrix(nstate2,1,mxREAL);    double *hb = (double *)mxGetPr(plhs[2]);    for (j=0;j<nstate2;j++) {hb[j] = 0;}    for (i=0;i<nstate1;i++)    for (j=0;j<nstate2;j++)    {      hb[j] += hab2d[j][i];    }  }  //finish  if (hab2d) {delete []hab2d;}  if (vec1) delete []vec1;  if (vec2) delete []vec2;  return;}

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