From a4388f1e8b73ce2f627360ce004da28255aaef7e Mon Sep 17 00:00:00 2001
From: ziejd2
Date: Tue, 2 Mar 2021 11:17:26 -0600
Subject: Delete sourcecodes/localscore directory

---
 sourcecodes/localscore/network_score.c | 1441 --------------------------------
 1 file changed, 1441 deletions(-)
 delete mode 100644 sourcecodes/localscore/network_score.c

(limited to 'sourcecodes/localscore/network_score.c')

diff --git a/sourcecodes/localscore/network_score.c b/sourcecodes/localscore/network_score.c
deleted file mode 100644
index c50a520e..00000000
--- a/sourcecodes/localscore/network_score.c
+++ /dev/null
@@ -1,1441 +0,0 @@
-#include<stdio.h>
-#include <stdlib.h>
-#include<string.h>
-#define MATHLIB_STANDALONE 1
-#include "matrix.h"
-#include "postc0.c"
-#include "modified_postc.c" // only line that has been changed in this code
-//#define OUT_DIR "./Result/"  //WHERE BENE READ DATA FOR STRUCTURE LEARNING //change it to #define OUT_DIR "/var/www/html/compbio/BNW/bene-0.9-4/example/resdir/" for server. Also change   from sprintf(line+9,"%d",i);  to sprintf(line+52,"%d",i);
-
-struct white{
-int n;
-int *list;
-};
-
-struct ban{
-int n;
-int *list;
-};
-
-struct ndata{
-int idx,type,score_i;
-char **ddata;
-char **label;              //for descrete node
-int lindex;
-double *prob,*cdata,*post_alpha;	
-double score_zeroparent;
-double *score;
-struct white wlist;
-struct ban blist;
-};
-
-
-struct nd{
-int num,nd,*discrete,nc,*continuous,row;
-double score;
-struct ndata *node;
-};
-
-void get_next_seq(int *,int *,int);
-void  learn_node(struct nd *);
-double learn_parent(struct nd  *,int,int);
-
-double run_strtof (const char * input)  //Convert string to double
-{
-    double output;
-    char * end;
-    output = strtod (input, & end);
-    if (end == input) {
-     return 0.0;    
-    }
-    else {
-        return output;
-    }
-}
-
- 
-char* itoa(int val, int base){  //convert number to string
-	
-	static char buf[32] = {0};
-	
-	int i = 30;
-	
-	for(; val && i ; --i, val /= base)
-	
-		buf[i] = "0123456789abcdef"[val % base];
-	
-	return &buf[i+1];
-	
-}
-
-double standarizedata(double val,double mean,double std)
-{
-  return (val-mean)/std;
-
-}
-
-double mean(double *a,int l)
-{
-int i;
-double m;
-m=0;
-for(i=0;i<l;i++)
-{
-	m+=a[i];
-}
-m=m/l;
-return m;
-}
-
-
-double stdev(double *a,int l,double m)
-{
-int i;
-double sqsum=0.0;
-
-for(i=0;i<l;i++)
-{
-   sqsum+=(a[i]-m)*(a[i]-m);
- 
-}
-
-return sqrt(sqsum/(l-1));
-}
-
-
-main(int argc, char *argv[])
-{
- FILE * pFile,*banf,*whitef;
- int i,s_i,j,k,l,m,id,ic,c,row,imatch,flag,bit,bit_count,ccount,maxccount;
- int n = 0,ban_flag,white_flag,white_flag_all;
- char line[2500],nf[250],nt[250],*file_name;
- char **name;  //name of variables
- double tc,tcm,score_val;
- struct nd network;
- int MAX_PARENT;
- FILE **inputFiles;
- 
-
- double min_score; 
- 
-
- if(argc<=5)
- {
-   printf("Use 5 arguments: 1. input data file name. 2. ban list file name. 3. white list file name. 4. integer value of the maximum number of parents are allowed and 5. output file directory\n");
-   return; 
- } 
-
- 
- 
- pFile=fopen (argv[1],"r");
-
-  
- if (pFile==NULL) perror ("Error opening file");
- else
- {//reading data from input file
-    
-
-    	row=0;
-    	do{   row++;
-    	} while (fgets (line,2500,pFile)!=NULL);  
-  
-    	row-=3;  
-    	network.row=row;
-    	fclose(pFile);
-   	pFile=fopen (argv[1],"r");
-       ccount=0;  
-       maxccount=0;
-   	do {
-      		c = fgetc (pFile);
-      		if (c == '\t') 
-              {     
-                   n++;
-                   if(maxccount<ccount)
-                      maxccount=ccount;
-                   ccount=0;
-              }
-              else
-                  ccount++;
-               
-
-    	} while (c != '\n');
-    
-
-    	network.num=n+1;
-    	network.discrete=(int *)malloc(sizeof(int)*network.num);
-    	network.continuous=(int *)malloc(sizeof(int)*network.num); 
-    	network.node=(struct ndata *)malloc(sizeof(struct ndata)*network.num);
-
-       MAX_PARENT=atoi(argv[4]);  //maximum number of parents for each node
-       if(MAX_PARENT==0)  //no restriction on parents
-           MAX_PARENT=network.num+1;
-
-       name=(char **)malloc(sizeof(char *)*network.num);
-
-    	for(i=0;i<network.num;i++)
-           name[i]=(char *)malloc(sizeof(char)*(maxccount+1));
-
-
-    
- 	id=0;
-       ic=0; 
-    	for(i=0;i<=n;i++)
-     	{
-	  	fscanf(pFile,"%d",&c);
-	  	network.node[i].idx=i;
-	  	network.node[i].type=c;
-	  	if(c==1)
-	  	{
-	    		network.continuous[ic]=i;
-	    		ic++;	
-	    		network.node[i].prob=(double *)malloc(sizeof(double)*2); //probability array of size 2 for continuous node
-	    		network.node[i].prob[0]=0.0;  //initialization
-	    		network.node[i].prob[1]=0.0; 
-	    	       network.node[i].cdata=(double *)malloc(sizeof(double)*row); //data matrix for continuous node
-	  	}
-	  	else
-	  	{
-	  		network.discrete[id]=i; 
-              	network.node[i].post_alpha=(double *)calloc(network.node[i].type,sizeof(double));  //prepare total count of each discrete data lebel initialize with zero by calloc which is used in learnnode
-			id++;
-	    		network.node[i].prob=(double *)malloc(sizeof(double)*c); //probability array of size equals to number of levels for discrete node 
-	    		network.node[i].ddata=(char **)malloc(sizeof(char *)*row); //data matrix for continuous node
-	    		network.node[i].label=(char **)malloc(sizeof(char *)*c);  //label array
-	    		for(j=0;j<c;j++)
-			   network.node[i].prob[j]=1.0/c;
-	  	}
-    	 }
-	 network.nd=id;  network.nc=ic; 
-        j=0;
-   	 
-        do{  //calculate average and prob for each node
-     	 	for(i=0;i<=n;i++) //n is nimber of column in the data matrix
-     		{
-     			if(network.node[i].type==1)   //if continuous
-     			{
-     	         		fscanf(pFile,"%s",line);
-     	         		tc=run_strtof(line);
-		  		//network.node[i].prob[1]+=tc;   //summation for average
-		  		network.node[i].cdata[j]=tc;  // data values in data column vector
-     			}
-     			else   //discrete
-     	 	       {
-				fscanf(pFile,"%s",line);
-				network.node[i].ddata[j]=(char *)malloc(sizeof(char)*strlen(line));
-				if(j==0)    //first iteration of do while
-				{ 
-	    	         		network.node[i].lindex=0;
-		   	  		network.node[i].label[0]=(char *)malloc(sizeof(char)*strlen(line));
-		   	  		strcpy(network.node[i].label[0],line);  //new label assigned to label list
-		   	  		network.node[i].post_alpha[0]=1;
-		   	
-				}
-				else  //store different label for discrete node also count number of ocarance of each label for calculation of post alpha score
-				{
-		   	 		imatch=0;
-		   	 		for(k=0;k<=network.node[i].lindex;k++)
-		   	 		{
-		   	   	 		if(strcmp(network.node[i].label[k],line)==0)
-		   	   	 		{
-		   	   	    			imatch=1; 
-							network.node[i].post_alpha[k]+=1;	
-		   	   	    			break; 	
-		   	   	 		}
-		   	   		}
-		   	 		if(imatch==0)
-		   	 		{
-		   	       		network.node[i].lindex++;
-		   	       		k=network.node[i].lindex;
-		   	       		network.node[i].label[k]=(char *)malloc(sizeof(char)*strlen(line));
-		   	       		strcpy(network.node[i].label[k],line);  //new label assigned to label list
-						network.node[i].post_alpha[k]+=1;
-		   	 		}
-				}
-				strcpy(network.node[i].ddata[j],line);
-     	 		}
-     	
-     		}
-      		j++;  
-    	} while (fgets (line,250,pFile)!=NULL);  //end of do while to read the input file  
-     
-       //////////////normalize continuous data/////////////
-       for(i=0;i<=n;i++)
-   	{
-     		if(network.node[i].type==1)  
-     		{    	  		
-
-                     tcm=mean(network.node[i].cdata,row);
-                     tc=stdev(network.node[i].cdata,row,tcm);
-          	  	for(j=0;j<row;j++)
-		  	{
-			    network.node[i].cdata[j]=standarizedata(network.node[i].cdata[j],tcm,tc); //dataval.data mean, standard deviation
-			}
-     		}
-	 } 
-     
-       //////////////////adjust average and prob for normalized data
-     	for(i=0;i<=n;i++)
-   	{
-     		if(network.node[i].type==1)  //claculate average and prob for continuous nodes
-     		{
-     	  		network.node[i].prob[1]=mean(network.node[i].cdata,row);
-	
-          	  	for(j=0;j<row;j++)
-		  	{
-			    network.node[i].prob[0]+=(network.node[i].cdata[j]-network.node[i].prob[1])*(network.node[i].cdata[j]-network.node[i].prob[1]);
-			}
-       	  	network.node[i].prob[0]*=1.0/(double)(row-1);	
-		  	network.node[i].prob[0]*=(double)(row-1.0)/(double)row;                    
-
-     		}
-	 } 
-
-  fclose (pFile);
-  }//end of else part for open input file
-
-  pFile=fopen (argv[1],"r");
-
-  for(i=0;i<network.num;i++)
-      fscanf(pFile,"%s",name[i]);
-
-  fclose(pFile);
-
-  learn_node(&network);    //call function to learn network and get local score whell 0 parent for all nodes
-
-
-
-  //printf("%.2lf\n",learn_parent(&network,6,176));
-  // printf("%.2lf\n",learn_parent(&network,6,47));
-  // printf("%.2lf\n",learn_parent(&network,6,18));
-  //printf("%.2lf\n",learn_parent(&network,7,80));
-  ////////printing trylist to a file////////////////////////////////
-
-  //fprintf(outfile,"Number of nodes\n%d\n",network.num);
-  //fprintf(outfile,"Possible sets of parents per node\n");
-  j=(int)pow(2.0,network.nd-1);  //possible number of parents for discrete node
-  k=(int)pow(2.0,network.num-1); //possible number of parents for continuous nodes
-
-
-  for(i=0;i<network.num;i++)
-  {
-     network.node[i].score=(double *)malloc(sizeof(double)*(k+1));
-     network.node[i].score_i=0;
-
- 
-     network.node[i].wlist.n=0;
-     network.node[i].blist.n=0;
-     network.node[i].blist.list=(int *)malloc(sizeof(int)*network.num);
-     network.node[i].wlist.list=(int *)malloc(sizeof(int)*network.num);
-    // if(network.node[i].type>1)  //discrete
-      //     fprintf(outfile,"%d\t",j);
-     //else   //continuous
-       //    fprintf(outfile,"%d\t",k);
-  }
-
-  banf=fopen (argv[2],"r");  //ban list file name
-  whitef=fopen (argv[3],"r");  //white list file name
-
-  //read banlist
-//  fgets (line,2500,banf); //header
-
-
-strcpy(nf,"");
-strcpy(nt,"");
-
-while (fgets (line,2500,banf)!=NULL){  
-  
-   fscanf(banf,"%s",nf);  //node from
-   fscanf(banf,"%s",nt);  //node to
-   
-   for(i=0;i<network.num;i++)
-   {
-       if(strcmp(name[i],nt)==0)
-       {
-              j=network.node[i].blist.n;
-              for(l=0;l<network.num;l++)
-   		{
-                    if(strcmp(name[l],nf)==0)
-                    {
-                        ban_flag=0;
-                        for(k=0;k<network.node[i].blist.n;k++)
-                             {    
-                                 if(network.node[i].blist.list[k]==l)
-                                  {           		   
-                       		         ban_flag=1;
-                          		         break;
-                                  }
-                             }
-                        if(ban_flag==0) 
-                        {
-                             network.node[i].blist.list[j]=l;
-                             j++;
-                             network.node[i].blist.n=j;
-                        }
-                        
-                    } 
-              }
-       }   
-  }
-
-}   
-
-
-
-//read whitelist
-//fgets (line,2500,whitef); //header
-
-strcpy(nf,"");
-strcpy(nt,"");
-
-while (fgets (line,2500,whitef)!=NULL){  
-
-fscanf(whitef,"%s",nf);  //node from
-fscanf(whitef,"%s",nt);  //node to
-
-for(i=0;i<network.num;i++)
-  {
-       if(strcmp(name[i],nt)==0)
-       {
-              j=network.node[i].wlist.n;
-              for(l=0;l<network.num;l++)
-   		{
-                    if(strcmp(name[l],nf)==0)
-                    {
-                        white_flag=0;
-                        for(k=0;k<network.node[i].wlist.n;k++)
-                             {    
-                                 if(network.node[i].wlist.list[k]==l)
-                                  {           		   
-                       		         white_flag=1;
-                          		         break;
-                                  }
-                             }
-                             if(white_flag==0) 
-                             {
-
-                                 network.node[i].wlist.list[j]=l;
-                                 j++;
-                                 network.node[i].wlist.n=j;
-                             }
- 
-                    } 
-              }
-       }   
-  }
-
-}   
-
-  //fprintf(outfile,"\nChild	Parents	Score\n");
-
-  m=(int)pow(2.0,network.num)-1; //number of combinations of parents
-  min_score=1.0;
-  for(i=0;i<network.num;i++)
-  {
- 
-    if(network.node[i].wlist.n==0)
-    {
-            network.node[i].score[0]=network.node[i].score_zeroparent;
-            if(min_score>network.node[i].score_zeroparent)
-                min_score=network.node[i].score_zeroparent;
-
-            //fprintf(outfile,"%d\t0\t%lf\n",i+1,network.node[i].score_zeroparent);  //printing score for zero parent 
-    }
-    else
-    {
-          network.node[i].score[0]=1.0;
-          //fprintf(outfile,"%d\t0\t0.0\n",i+1);
-          
-     }
-    network.node[i].score_i=1;
-
-
-     for(j=0;j<m;j++)
-     {   
-
-         ban_flag=0;
-         
-         bit= (j+1 >> i) & 1;
-
-         if(bit!=1)  //check if the child itself is present in parent list
-         { 
-
-          		bit_count=0;
-               	//fprintf(outfile,"%d\t",i+1);
-      			for(l=0;l<network.num;l++)
-                     {
-                       		bit= (j+1 >> l) & 1;
-                           		if(bit==1)
-                           		{
-                                         	//fprintf(outfile,"%d",l+1);
-                   				bit_count++;
- 	            				
-                                   }  
-
-                     }
-
-
-    	             	if(network.node[i].type>1)  //if discrete node checck if any continuous node is included in the parent list
-              	{     
-                  		flag=0;
-                            ban_flag=0;
-                  		for(l=0;l<network.num;l++)
-                  		{
-                        		bit= (j+1 >> l) & 1;
-                        
-	  	          		if(bit==1 && network.node[l].type==1) //check if continuous is parent of discrete
- 	   	           		{   
-                             		 flag=1;
-                             		 break;
-                         		}
-	  	          		if(bit==1)
-                                   { 
-                                           for(k=0;k<network.node[i].blist.n;k++)
-                                           {    
-                                               if(network.node[i].blist.list[k]==l)
-                                                {           		   
-                             		         ban_flag=1;
-                             		         break;
-                                                }
-                                           }
-
-
-                                           if(ban_flag==1)
-                                              break;
-                         		}
-
-
-
-                   		}
-                   		if(flag==0)  //if no continuous parent for discrete node then learn the network with the list of parents  
-                   		{
-
-					if(bit_count>MAX_PARENT)
-                                   {
-                                              //fprintf(outfile,"\t0.0\n");   
-
-                                              s_i=network.node[i].score_i;
-                                              network.node[i].score[s_i]=1.0;
-                                              network.node[i].score_i=s_i+1;
-
-
-
-                                   }
-                                   else if(ban_flag==1)
-                                    {        
-                                              //fprintf(outfile,"\t0.0\n");   
-                                              s_i=network.node[i].score_i;
-                                              network.node[i].score[s_i]=1.0;
-                                              network.node[i].score_i=s_i+1;
-                                    }
-                                   else  // calculate score if white list check get satisfied
-                         		{
-                                          if(network.node[i].wlist.n==0)
-                                           {  
-                                              score_val=learn_parent(&network,i,j);
-
-            					    if(min_score>score_val)
-					                min_score=score_val;
-
-
-
-                                              //fprintf(outfile,"\t%lf\n",score_val);   
-                                              s_i=network.node[i].score_i;
-                                              network.node[i].score[s_i]=score_val;
-                                              network.node[i].score_i=s_i+1;
-                                           }                                                 
-                                          else if(bit_count<network.node[i].wlist.n)  //white list is greater than list of parents
-                                          {
-						    //fprintf(outfile,"\tfor white\t0.0\n"); 
-                                              s_i=network.node[i].score_i;
-                                              network.node[i].score[s_i]=1.0;
-                                              network.node[i].score_i=s_i+1;
-                                          }
-                                          else
-                                          {
-                                                white_flag=0;  
-                                                white_flag_all=0;  
-
-     			                          for(l=0;l<network.num;l++)
-                        		            {
-                            	          	  bit= (j+1 >> l) & 1;
-
-                            		         if(bit==1)
-                                		         {
-                                                        for(k=0;k<network.node[i].wlist.n;k++)
-                                                        {     
-                                                               if(network.node[i].wlist.list[k]==l)
-                                                               {           		   
-                             		                        white_flag++;
-                                                                  //changed from white_flag=1;  
-                             		                        break;
-                                                               }
-                                                        }
-                                                        if(white_flag>=network.node[i].wlist.n)
-                                                        {    //!=1
-                                                              white_flag_all=1;
-                                                              break; 
-
-                                          	        }  
-                        
-                                    	           }
-                                                }
-                                                if(white_flag_all==1)
-                                       	      {
-                                                      score_val=learn_parent(&network,i,j);
-	             					     if(min_score>score_val)
-					                        min_score=score_val;
-
-                                                      //fprintf(outfile,"\t%lf\n",score_val);   
-                                                      s_i=network.node[i].score_i;
-                                                      network.node[i].score[s_i]=score_val;
-                                                      network.node[i].score_i=s_i+1;
-                                                }
-                                                else
-                                                { 
-                                                     //fprintf(outfile,"\t0.0\n");  
-	                                              s_i=network.node[i].score_i;
-	                                              network.node[i].score[s_i]=1.0;
-	                                              network.node[i].score_i=s_i+1;
-							}
-
-                                           } 
-                                   }
-
-                   		}
-                            else  //fill up data when continuous is parent of discrete
-                            {
-					//fprintf(outfile,"\t0.0\n"); 
-                                   s_i=network.node[i].score_i;
-                                   network.node[i].score[s_i]=1.0;
-                                   network.node[i].score_i=s_i+1;
-
-                             }  
-               	}
-               	else  //if continuous node then learn the network with the parent set
-               	{
-
-                            ban_flag=0;
-
-       
-                   		for(l=0;l<network.num;l++)
-                   		{
-                       		bit= (j+1 >> l) & 1;
-                       		if(bit==1)
-                            	{
-
-                                           for(k=0;k<network.node[i].blist.n;k++)
-                                           {    
-                                               if(network.node[i].blist.list[k]==l)
-                                                {           		   
-                             		         ban_flag=1;
-                             		         break;
-                                                }
-                                           }
-                                           if(ban_flag==1)
-                                              break;
-                         		}
-
-
-                   		}
-				if(bit_count>MAX_PARENT)
-                            {
-                                   //fprintf(outfile,"\t0.0\n"); 
-                                   s_i=network.node[i].score_i;
-                                   network.node[i].score[s_i]=1.0;
-                                   network.node[i].score_i=s_i+1;
-                            } 
-                            else if(ban_flag==1)
-                            {
-					//fprintf(outfile,"\t0.0\n"); 
-                                   s_i=network.node[i].score_i;
-                                   network.node[i].score[s_i]=1.0;
-                                   network.node[i].score_i=s_i+1;
-				}				
-                            else
-                            {
-                                          if(network.node[i].wlist.n==0)
-                                      	 {
-                                                      score_val=learn_parent(&network,i,j);
-       	      					     if(min_score>score_val)
-						                min_score=score_val;
-
-                                                      //fprintf(outfile,"\t%lf\n",score_val);   
-                                                      s_i=network.node[i].score_i;
-                                                      network.node[i].score[s_i]=score_val;
-                                                      network.node[i].score_i=s_i+1;
-                                            }
-                                          else if(bit_count<network.node[i].wlist.n)  //white list is greater than list of parents
-                                          {
-                                                     //fprintf(outfile,"\t0.0\n"); 
-                                                     s_i=network.node[i].score_i;
-                                                     network.node[i].score[s_i]=1.0;
-                                                     network.node[i].score_i=s_i+1;
-                                           } 
-                                          else
-                                          {
-                                                white_flag=0;  
-                                                white_flag_all=0;  
-
-     			                          for(l=0;l<network.num;l++)
-                        		            {
-                            	          	  bit= (j+1 >> l) & 1;
-
-                            		         if(bit==1)
-                                		         {
-                                                        for(k=0;k<network.node[i].wlist.n;k++)
-                                                        {     
-                                                               if(network.node[i].wlist.list[k]==l)
-                                                               {           		   
-                             		                        white_flag++;
-                             		                        break;
-                                                               }
-                                                        }
-                                                        if(white_flag>=network.node[i].wlist.n)
-                                                        {    //!=1
-                                                              white_flag_all=1;
-                                                              break; 
-
-                                          	        }  
-                        
-                                    	           }
-                                                }
-                                                if(white_flag_all==1)
-                                      	      {
-                                                      score_val=learn_parent(&network,i,j);
-            					            if(min_score>score_val)
-					                       min_score=score_val;
-
-                                                      //fprintf(outfile,"\t%lf\n",score_val);   
-                                                      s_i=network.node[i].score_i;
-                                                      network.node[i].score[s_i]=score_val;
-                                                      network.node[i].score_i=s_i+1;
-                                                }
-                                                else
-                                                {
-       						    // fprintf(outfile,"\t0.0\n");  
-                                              	     s_i=network.node[i].score_i;
-	                                               network.node[i].score[s_i]=1.0;
-	                                               network.node[i].score_i=s_i+1;
-							}
-
-                                           } 
-                              }
-
-
-                	}
-
-
-           }  
-       }
-  }  
-
-
-//print scores to separate files
-
-min_score*=10;
-inputFiles= (FILE **) malloc(network.num * sizeof(FILE*));
-
-printf("%s\n",argv[5]);
-
-for(i=0;i<network.num;i++)
-{
-  strcpy(line,argv[5]);
-  sprintf(line+10,"/%d",i);  //sprintf(line+52,"%d",i);
-
- // strcat(line,".txt");
-
-  inputFiles[i] = fopen(line, "wb");
-
-  //print content  
-  for(j=0;j<network.node[i].score_i;j++)
-  {      
-          if(network.node[i].score[j]<1.0)
-            fwrite(&network.node[i].score[j],sizeof(double),1,inputFiles[i]); 
-// fprintf(inputFiles[i],"%lf\n",network.node[i].score[j]);
-          else 
-            fwrite(&min_score,sizeof(double),1,inputFiles[i]); 
-//fprintf(inputFiles[i],"%lf\n",min_score);
-  }  
-
-  fclose(inputFiles[i]);
-}
-
-
-
-
-
-
-fclose(banf);
-fclose(whitef);
-
-
-// printf("Time elapsed: %f\n", ((double)clock() - start) / CLOCKS_PER_SEC);
-
-}
-
-
-/* learn the network for zero parent */
-
-void  learn_node(struct nd  *net)
-{
-  int i,j,k,nk,l,m,i1,j1;
-  long num,temp;
-  double n,N,s2;
-  struct nd network=*net; //create a local copy
-  double *alpha,nu,rho,mu,phi,tau;
-  double post_nu,post_rho,post_mu,post_phi,post_tau;
-  double loglik,post_loglik;
- 
-  num=network.num;
-
-  nk=1;
-  
-  for(i=0;i<num;i++)
-  {
-     if(network.node[i].type>1)
-        nk*=network.node[i].type;
-  }
-  
-  	   
-
-
-  for(i=0;i<num;i++)
-  {	   
-     if(network.node[i].type>1)
-     {
-	      	
-	  alpha=(double *)malloc(sizeof(double)*network.node[i].type);
-	  k=1;
-			  
-	   for(j=0;j<num;j++)
-          {
-          	  if(i!=j && network.node[j].type>1)
-                 k*=network.node[j].type;
-		          	
-          }
-          N=0.0; n=0.0;
-	   for(j=0;j<network.node[i].type;j++)
-          {
-              alpha[j]=2.0*k;
-              network.node[i].post_alpha[j]+=alpha[j];
-          ////////update loglik from udisclik
-              n+=alpha[j]; 
-              N+=network.node[i].post_alpha[j];
-          }
-     
-	  
-         loglik=0.0;
-         post_loglik=0.0;
-  
-     	  for(j=0;j<network.node[i].type;j++)
-             post_loglik+=lgammafn(network.node[i].post_alpha[j])-lgammafn(alpha[j]);
-
-          post_loglik+=lgammafn(n);
-          post_loglik-=lgammafn(N);
- 
-     
-	}
-	else
-	{
-	    	nu=nk*2.0;
-	    	tau=nu;
-	    	rho=nk*2.0;	
-		mu=network.node[i].prob[1];
-		phi=network.node[i].prob[0]*nk;
-		loglik=0.0;
-              post_mu=mu;
-              post_tau=tau;
-              post_rho=rho;
-              post_phi=phi;
-	       post_loglik=loglik; 
-
-              postc0(&post_mu,&post_tau,&post_rho,&post_phi,&post_loglik,network.node[i].cdata,&network.row);
-
-     		    	
-	}
-      network.node[i].score_zeroparent=post_loglik; // store the zero parent score 
-		  
-   }
-    	
-   if(nk!=1)
-     free(alpha);
-
-   *net=network;  //coppied back to original	
-}
-
-
-/*
-learn node for a list of parents
-*/
-
-double learn_parent(struct nd  *net,int child,int p)
-{
-  int i,j,jj,k,nk,l,m,i1,j1,k1,k2,cn_send;
-  long num,temp;
-  double n,N,s2;
-  struct nd network=*net; //create a local copy
-  int cn,ds,bit,*discrete,*continuous;
-  double alpha,*postalpha,alpha_parent,*postalpha_parent,nu,rho,mu,phi,tau;
-  double post_nu,post_rho,*post_mu,post_phi,post_tau;
-  double loglik,post_loglik=0,post_loglik_parent=0;
-  double *mu_mat,**tau_mat,tau11,tau12,tau22,div,phiinv;
-  char **label; 
-  int *a,*l_list,flag,y_count,z_count;
-  double *y,mu_p,phi_p,*tau_send,*z_send,loglik_sum;
-
-
-
-  num=network.num;
-
-  continuous=(int *)malloc(sizeof(int)*network.nc);
-  discrete=(int *)malloc(sizeof(int)*network.nd); 
-
-  nk=1;
-  for(i=0;i<num;i++)
-  {
-	if(network.node[i].type>1)
-	    nk*=network.node[i].type;
-  }
-	   
-//list of discrete snd continuous parents
-  cn=0;
-  ds=0;
-  alpha_parent=0;
-  alpha=2;
- 
-  k1=network.node[child].type;
-  k2=1;
- 
- //printf("%d\n",child);
-  for(j=0;j<network.num;j++)   //list the continuous parents and discrete parents
-	 {
-	  	bit= (p+1 >> j) & 1;
-              
-              
-	  	if(bit==1 && j!=child)
-	  	{   
-                 
-	  	   if(network.node[j].type>1)
-	  	    {
-			   discrete[ds]=j;
-                        //printf("discrete parent=%d\n",j);
-                        k1*=network.node[j].type;
-                        k2*=network.node[j].type;
-     			   ds++;
-	  	    }
-	   	    else
-	  	    {
-			   continuous[cn]=j; 
-                        //printf("continuous parent=%d\n",j);
-			   cn++;
-	  	    }	
-	  	}
-              else if(j!=child)
-              {
-                 alpha*=network.node[j].type;
-              }  
-	 }
-    
-       if(network.nd<=2)
-          alpha=2; 
-
-       i=child;   //i is the node with changes in its parrent nodes 
-         
-       if(network.node[i].type>1 && cn==0)  // no continuous node  //prepare alpha and post alpha and then calculate local score
-	{   
-         
-	   k=k1;
-      	   postalpha=(double *)calloc(network.node[i].type,sizeof(double));
-  
-          label=(char **)malloc(sizeof(char *)*(ds+1)); //label array
-  	   a=(int *)calloc((ds+1),sizeof(int));
-          l_list=(int *)malloc(sizeof(int)*(ds+1));
-
-          for(j=0;j<=ds;j++)
-              label[j]=(char *)malloc(sizeof(char)*100);
-       	   
-          for(j=0;j<ds;j++)
-          {
-               l=discrete[j];
-               l_list[j]=network.node[l].type; 
-              
-          }
-          l_list[ds]=network.node[i].type;
-                   
-          for(j=0;j<k;j++)                
-          {
- 	     
-	             get_next_seq(a,l_list,ds+1);   // prepare a new combination of labels for parent
-       	      for(i1=0;i1<ds;i1++)
-             		{
-                 		j1=a[i1];
-                 		l=discrete[i1];
-                 		strcpy(label[i1],network.node[l].label[j1]); 
-                     }  
-                     
-             		j1=a[i1];
-                     strcpy(label[i1],network.node[child].label[j1]); 
-                     for(i1=0;i1<network.node[i].type;i1++)
-               		postalpha[i1]=0;
-             		for(i1=0;i1<network.row;i1++)  // search through parents data and count how many number of matches for current label list. prepare post alpha from count+alpha
-             		{
-                     	flag=0;
-                     	for(m=0;m<ds;m++)
-                     	{
-                        		j1=a[m];
-                       		 l=discrete[m];
-                        		if(strcmp(label[m],network.node[l].ddata[i1])!=0)
-                        		{
-                          			flag=1;
-                        		}      
-                     	}  
-                    		j1=a[m];
-                    		if(strcmp(label[m],network.node[child].ddata[i1])!=0)
-                        	{
-                          		flag=1;
-                        	}     
-                   		if(flag==0)
-                   		{
-                        		j1=a[ds];
-                        		postalpha[j1]+=1;
-
-                   		}
-             		}
-             		for(m=0;m<network.node[i].type;m++)
-                     {   
-                             if(postalpha[m]!=0)
-                             {
-  	                        	postalpha[m]+=alpha;
-                                   post_loglik+=lgammafn(postalpha[m])-lgammafn(alpha);
-                             }
-                     } 
-          }
-
-	
-          k=k2;   // repeat the last step of preparing alpha and post alpha for only parent set. this time exclude the child node label from computation. prepare alpha_parent and post_alphaparent
-	   l=discrete[ds-1];       
-	   postalpha_parent=(double *)calloc(network.node[l].type,sizeof(double));
-
-	   for(j=0;j<ds;j++)
-	   {
-	  	    l=discrete[j];
-	      	    l_list[j]=network.node[l].type;
-	           a[j]=0; 
-
-	    }
-           for(j=0;j<k1/k2;j++)
-                 alpha_parent+=alpha; 
-	    for(j=0;j<k;j++)
-	    {
-		    	get_next_seq(a,l_list,ds);
-
-	      		for(i1=0;i1<ds;i1++)
-			{
-		  		j1=a[i1];
-		  		l=discrete[i1];
-		  		strcpy(label[i1],network.node[l].label[j1]);
-                            
-			}
-
-	      		l=discrete[ds-1]; 
-	      		for(i1=0;i1<network.node[l].type;i1++)
-				postalpha_parent[i1]=0;
-             
-			for(i1=0;i1<network.row;i1++)
-			{
-		  		flag=0;
-		  		for(m=0;m<ds;m++)
-		    		{
-		      			j1=a[m];
-		      			l=discrete[m];
-		      			if(strcmp(label[m],network.node[l].ddata[i1])!=0)
-                        		{
-                          			flag=1;
-                        		}
-		    		}
-                    
-		  		if(flag==0)
-		    		{
-		      			j1=a[ds-1];
-		       		postalpha_parent[j1]+=1;
-
-		    		}
-			}
-	      		l=discrete[ds-1];
-	      		for(m=0;m<network.node[l].type;m++)
-			{ 
-                             if(postalpha_parent[m]!=0)
-                              {  
-                                    postalpha_parent[m]+=alpha_parent;
-       	                      post_loglik_parent+=lgammafn(postalpha_parent[m])-lgammafn(alpha_parent);
-                              }
-			}
-	    }
-
-      
-         loglik=post_loglik-post_loglik_parent;
-	  free(postalpha);
-         free(postalpha_parent);
-         for(j=0;j<=ds;j++)
-             free(label[j]);
-	  free(label);
- 	  free(a);
- 	  free(l_list);
-
-	}
-       else if(network.node[i].type==1 && ds==0)  // no discrete node  //prepare continuous parameter set
-	{
-           z_count=0;
-           tau_mat=(double **)malloc(sizeof(double *)*(cn+1));
-
-           z_send=(double *)malloc(sizeof(double)*(cn+1)*network.row);
-           tau_send=(double *)malloc(sizeof(double)*(cn+1)*(cn+1));
-  
-	    mu_mat=(double *)malloc(sizeof(double)*(cn+1));
-           nu=nk*2.0;  rho=nk*2.0+cn; 
-           mu_mat[0]=network.node[i].prob[1];
-           for(j=0;j<cn;j++)
-           {
-              mu_mat[j+1]=0;
-              tau_mat[j]=(double *)malloc(sizeof(double)*(cn+1));
- 
-           } 
-         
-           tau_mat[j]=(double *)malloc(sizeof(double)*(cn+1));
-
-           for(j=0;j<network.row;j++)
-           {
-               z_send[z_count]=1;
-               z_count++;
-               for(j1=0;j1<cn;j1++)
-               {
-                  l=continuous[j1];
-                  z_send[z_count]=network.node[l].cdata[j];   
-                  z_count++;                                            
-               }
-                  
-           }
-           
-             phi=network.node[i].prob[0]*nk;	
-               
-             //preparing tau
-      
-             //**tau_mat
-               for(j=0;j<=cn;j++)
-                     for(m=0;m<=cn;m++)
-                     {
-                      tau_mat[j][m]=1.0;
-                     }
-              
-              for(j=0;j<cn;j++)
-              {
-                 l=continuous[j];
-                 mu_p=network.node[l].prob[1];
-                 phi_p=network.node[l].prob[0]*nk;
-                 phiinv=1/phi_p; 
-                 tau11 = 1/nu + mu_p*phiinv*mu_p;
-                 tau22 = phiinv;
-                 tau12 = -mu_p*phiinv;
-                 div=tau11*tau22-tau12*tau12;
-                 if(j==0) 
-                    tau_mat[0][0]=tau22/div;
-                 tau_mat[0][j+1]=-tau12/div;
-                 tau_mat[j+1][0]=tau_mat[0][j+1];
-                 tau_mat[j+1][j+1]=tau11/div;
-              }
-
-               for(j=0;j<=cn;j++)
-                     for(m=0;m<=cn;m++)
-                     {
-                       if(tau_mat[j][m]==1.0)
-                          { 
-                                tau_mat[j][m]=tau_mat[0][j]*(tau_mat[0][m]/tau_mat[0][0]);
-                               
-                          }
-                       j1=j*(cn+1)+m;
-                       tau_send[j1]=tau_mat[j][m];
-                      
-                     }
-                      
-              loglik=0.0;
-              
-              cn_send=cn+1; 
-              
-              postc(mu_mat,tau_send,&rho,&phi,&loglik,network.node[i].cdata,z_send,&network.row,&cn_send);
-             
- 	
- 		free(z_send);
- 		free(tau_send);
-              for(j=0;j<=cn;j++)
-                 free(tau_mat[j]);
-  		free(tau_mat);
- 		free(mu_mat);
- 		    	
-	}
-       else  //hybrid cases
-       {
-              if(cn==0)   //if parents are all discrete and child is continuous
-              { 
-   
-                     ///////////////////prepare y array and run c code////////////////////////////////
-              	loglik_sum=0;
-              	k=k2;
-      	       	y=(double *)calloc(network.row,sizeof(double));
-              	label=(char **)malloc(sizeof(char *)*(ds));  //label array
-  	       	a=(int *)calloc((ds+1),sizeof(int));
-              	l_list=(int *)malloc(sizeof(int)*(ds));
-
-          		for(j=0;j<ds;j++)
-              		label[j]=(char *)malloc(sizeof(char)*100);
-       	   
-          		for(j=0;j<ds;j++)
-          		{
-              		l=discrete[j];
-               		l_list[j]=network.node[l].type; 
-              
-          		}
-
-                   
-          		for(j=0;j<k;j++)                
-              	{
-
-                     	nu=(nk*2.0)/k2;
-	    			tau=nu;
-	    			rho=nu;	
-				mu=network.node[i].prob[1];
-				phi=network.node[i].prob[0]*nu/2;
-				loglik=0.0;
-
- 	               	get_next_seq(a,l_list,ds);   // prepare a new combination of labels for parent
-       	      		for(i1=0;i1<ds;i1++)
-             			{
-                 			j1=a[i1];
-                 			l=discrete[i1];
-                 			strcpy(label[i1],network.node[l].label[j1]); 
-                     	}  
-             	       	y_count=0; 	
-             			for(i1=0;i1<network.row;i1++)  // search through parents data and count how many number of matches for current label list. prepare post alpha from count+alpha
-             			{
-                     		flag=0;
-                     		for(m=0;m<ds;m++)
-                     		{
-                        		
-                       			l=discrete[m];
-                        			if(strcmp(label[m],network.node[l].ddata[i1])!=0)
-                        			{
-                          				flag=1;
-                        			}      
-                     		}  
-                    		     
-                   			if(flag==0)
-                   			{
-                        			y[y_count]=network.node[i].cdata[i1];
-                        			y_count++;
-             
-                   			}
-             			}
-          
-             			postc0(&mu,&tau,&rho,&phi,&loglik,y,&y_count);
-                     	loglik_sum+=loglik;
-          
-
-              	}
-
-              	loglik=loglik_sum;
-                      
-                     free(y);
-                     for(j=0;j<ds;j++)
-                         free(label[j]);
-			free(label);
-			free(a);
-			free(l_list);
-          
- 
-              }//end of continuous node discrete parent check
-              else //all the other hybrid cases when parents are both continuous and discrete 
-              {
-                     
-                   
-          	      tau_mat=(double **)malloc(sizeof(double *)*(cn+1));
-		      z_send=(double *)malloc(sizeof(double)*(cn+1)*network.row);
-         	      tau_send=(double *)malloc(sizeof(double)*(cn+1)*(cn+1));
-	    	      mu_mat=(double *)malloc(sizeof(double)*(cn+1));
-           	      
-           	       for(j=0;j<cn;j++)
-           		{
-              	   tau_mat[j]=(double *)malloc(sizeof(double)*(cn+1));
- 	              } 
-         
-      		       
-           		tau_mat[j]=(double *)malloc(sizeof(double)*(cn+1));          
-
-                     ///////////////////prepare parameters  and run c code////////////////////////////////
-              	loglik_sum=0.0;
-              	k=k2;
-      	       	y=(double *)calloc(network.row,sizeof(double));
-              	label=(char **)malloc(sizeof(char *)*(ds));  //label array
-  	       	a=(int *)calloc((ds+1),sizeof(int));
-              	l_list=(int *)malloc(sizeof(int)*(ds));
-
-          		for(j=0;j<ds;j++)
-              		label[j]=(char *)malloc(sizeof(char)*100);
-       	   
-          		for(j=0;j<ds;j++)
-          		{
-              		l=discrete[j];
-               		l_list[j]=network.node[l].type; 
-              
-          		}
-
-                   
-          		for(jj=0;jj<k;jj++)                
-              	{
-
-                     	nu=(nk*2.0)/k2;
-	      			rho=nu+cn;	
-				mu_mat[0]=network.node[i].prob[1];
-
-                            for(j1=0;j1<cn;j1++)
-           		            mu_mat[j1+1]=0;
-
-				phi=network.node[i].prob[0]*nu/2;
-	                    //preparing tau
-                   		//**tau_mat
-             			for(j=0;j<=cn;j++)
-                               for(m=0;m<=cn;m++)
-                               {
-                   			   tau_mat[j][m]=1.0;
-                     	    }
-             
-              		for(j=0;j<cn;j++)
-              		{
-                 			l=continuous[j];
-                 			mu_p=network.node[l].prob[1];
-                 			phi_p=network.node[l].prob[0]*(nk/k2);
-                
-                 			phiinv=1/phi_p; 
-                 			tau11 = 1/nu + mu_p*phiinv*mu_p;
-                 			tau22 = phiinv;
-                 			tau12 = -mu_p*phiinv;
-                 			div=tau11*tau22-tau12*tau12;
-                 			if(j==0) 
-                  			    tau_mat[0][0]=tau22/div;
-                 
-			              tau_mat[0][j+1]=-tau12/div;
-                 			tau_mat[j+1][0]=tau_mat[0][j+1];
-                 			tau_mat[j+1][j+1]=tau11/div;
-       
-                
-              		}
-               		for(j=0;j<=cn;j++)
-                    			 for(m=0;m<=cn;m++)
-                    			 {
-			                       if(tau_mat[j][m]==1.0)
-                       		         { 
-			                            tau_mat[j][m]=tau_mat[0][j]*(tau_mat[0][m]/tau_mat[0][0]);
-                              		  }
-
-                       			j1=j*(cn+1)+m;
-                       			tau_send[j1]=tau_mat[j][m];
-                                           
-                     		   //printf("%.2lf\t",tau_mat[j][m]);
-                                    }
-                                    //printf("\n");
-              	       loglik=0.0;
-              
-  	      
-             		       cn_send=cn+1; 
-
- 	               	
-                            get_next_seq(a,l_list,ds);   // prepare a new combination of labels for parent
-       	      		for(i1=0;i1<ds;i1++)
-             			{
-                 			j1=a[i1];
-                 			l=discrete[i1];
-                 			strcpy(label[i1],network.node[l].label[j1]); 
-                     	}  
-             	       	y_count=0;
-                            z_count=0; 	
-             			for(i1=0;i1<network.row;i1++)  // search through parents data and count how many number of matches for current label list. prepare post alpha from count+alpha
-             			{
-                     		flag=0;
-                     		for(m=0;m<ds;m++)
-                     		{
-                        		
-                       			l=discrete[m];
-                        			if(strcmp(label[m],network.node[l].ddata[i1])!=0)
-                        			{
-                          				flag=1;
-                        			}      
-                     		}  
-                    		     
-                   			if(flag==0)
-                   			{
-                        			y[y_count]=network.node[i].cdata[i1];
-
-                                          //prepare z send matrix
-                                          z_send[z_count]=1;
-                                          z_count++;
-                                          for(j1=0;j1<cn;j1++)
-                                          {
-                 			          l=continuous[j1];
-                 			          z_send[z_count]=network.node[l].cdata[i1];   
-                                             z_count++;                                            
-                                          }
-                        			y_count++;
-                   			}
-             			}
-          
-                            postc(mu_mat,tau_send,&rho,&phi,&loglik,y,z_send,&y_count,&cn_send);
- 
-                     	loglik_sum+=loglik;
-          
-
-              	}
-
-              	loglik=loglik_sum;
-                        
-                     free(y);
- 			//free(z);
- 			free(z_send);
- 			free(tau_send);
-                     for(j=0;j<=cn;j++)
-                        free(tau_mat[j]);
-          	       free(tau_mat);
- 			free(mu_mat);
-                     for(j=0;j<ds;j++)
-                         free(label[j]);  
- 			free(label);
- 			free(a);
- 			free(l_list);       
-
-              }//end of else part for hybrid when parents are mixed       
-
-       }//end of else part for hybrid
-       
- free(continuous);
- free(discrete); 
- return loglik;
-
-	
-}
-
-void get_next_seq(int *a,int *l,int size)
-{
-  int j,idx;
-  idx=size-1;
-  a[idx]+=1;
-  if(a[idx]==l[idx])
-  {
-      a[idx]=0;
-      for(j=idx-1;j>=0;j--){
-        a[j]+=1;
-        if(a[j]==l[j])
-           a[j]=0;
-        else
-            break;
-      }
-  }
-}
-
-
-- 
cgit 1.4.1