--- /dev/null
+#include "trialswap2.h"
+
+
+//The sum_of_squares, havel_hakimi and calc_c_score algorithms have been adapted from I. Miklos and J. Podani. 2004. Randomization of presence-absence matrices: comments and new algorithms. Ecology 85:86-92.
+
+
+double TrialSwap2::calc_c_score (vector<vector<int> > &co_matrix, vector<int> rowtotal, int ncols, int nrows)
+{
+ try {
+ double cscore = 0.0;
+ double maxD;
+ double D;
+ double normcscore = 0.0;
+ int nonzeros = 0;
+ //int ncols = co_matrix[0].size(); int nrows = rowtotal.size();
+ vector<vector<double> > s; s.resize(nrows);
+ for (int i = 0; i < nrows; i++) { s[i].resize(nrows,0.0); }//only fill half the matrix
+
+
+ for(int i=0;i<nrows-1;i++)
+ {
+
+ for(int j=i+1;j<nrows;j++)
+ {
+ if (m->control_pressed) { return 0; }
+ for(int k=0;k<ncols;k++)
+ {
+ if((co_matrix[i][k]==1)&&(co_matrix[j][k]==1)) //if both are 1s ie co-occurrence
+ s[i][j]++; //s counts co-occurrences
+ }
+
+ //rowtotal[i] = A, rowtotal[j] = B, ncols = P, s[i][j] = J
+ cscore += (rowtotal[i]-s[i][j])*(rowtotal[j]-s[i][j]);///(nrows*(nrows-1)/2);
+ D = (rowtotal[i]-s[i][j])*(rowtotal[j]-s[i][j]);
+
+ if(ncols < (rowtotal[i] + rowtotal[j]))
+ {
+ maxD = (ncols-rowtotal[i])*(ncols-rowtotal[j]);
+ }
+ else
+ {
+ maxD = rowtotal[i] * rowtotal[j];
+ }
+
+ if(maxD != 0)
+ {
+ normcscore += D/maxD;
+ nonzeros++;
+ }
+ }
+ }
+
+ cscore = cscore/(double)(nrows*(nrows-1)/2);
+ //cout << "normalized c score: " << normcscore/nonzeros << endl;
+
+ return cscore;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "TrialSwap2", "calc_c_score");
+ exit(1);
+ }
+}
+/**************************************************************************************************/
+int TrialSwap2::calc_checker (vector<vector<int> > &co_matrix, vector<int> rowtotal, int ncols, int nrows)
+{
+ try {
+ int cunits=0;
+ //int s[nrows][ncols];
+ //int ncols = co_matrix[0].size(); int nrows = rowtotal.size();
+ vector<vector<int> > s; s.resize(nrows);
+ for (int i = 0; i < nrows; i++) { s[i].resize(nrows,0); }//only fill half the matrix
+
+ for(int i=0;i<nrows-1;i++)
+ {
+ for(int j=i+1;j<nrows;j++)
+ {
+ if (m->control_pressed) { return 0; }
+ //s[i][j]=0;
+ for(int k=0;k<ncols;k++)
+ {
+ //cout << s[i][j] << endl;
+ //iterates through the row and counts co-occurrences. The total number of co-occurrences for each row pair is kept in matrix s at location s[i][j].
+ if((co_matrix[i][k]==1)&&(co_matrix[j][k]==1)) //if both are 1s ie co-occurrence
+ s[i][j]++; //s counts co-occurrences
+
+ }
+ //cout << "rowtotal: " << rowtotal[i] << endl;
+ //cout << "co-occurrences: " << s[i][j] << endl;
+ //cunits+=(rowtotal[i]-s[i][j])*(rowtotal[j]-s[i][j]);
+ if (s[i][j] == 0)
+ {
+ cunits+=1;
+ }
+ //cunits+=s[i][j];
+ }
+ }
+
+ return cunits;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "TrialSwap2", "calc_checker");
+ exit(1);
+ }
+}
+/**************************************************************************************************/
+double TrialSwap2::calc_vratio (int nrows, int ncols, vector<int> rowtotal, vector<int> columntotal)
+{
+ try {
+ //int nrows = rowtotal.size();
+ //int ncols = columntotal.size();
+ int sumCol = accumulate(columntotal.begin(), columntotal.end(), 0 );
+ // int sumRow = accumulate(rowtotal.begin(), rowtotal.end(), 0 );
+
+ double colAvg = (double) sumCol / (double) ncols;
+ // double rowAvg = (double) sumRow / (double) nrows;
+
+ double p = 0.0;
+
+ // double totalRowVar = 0.0;
+ double rowVar = 0.0;
+ double colVar = 0.0;
+
+ for(int i=0;i<nrows;i++)
+ {
+ if (m->control_pressed) { return 0; }
+ p = (double) rowtotal[i]/(double) ncols;
+ rowVar += p * (1.0-p);
+ }
+
+ for(int i=0;i<ncols;i++)
+ {
+ if (m->control_pressed) { return 0; }
+ colVar += pow(((double) columntotal[i]-colAvg),2);
+ }
+
+ colVar = (1.0/(double)ncols) * colVar;
+
+ return colVar/rowVar;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "TrialSwap2", "calc_vratio");
+ exit(1);
+ }
+
+}
+/**************************************************************************************************/
+int TrialSwap2::calc_combo (int nrows, int ncols, vector<vector<int> > &nullmatrix)
+{
+ try {
+ //need to transpose so we can compare rows (row-major order)
+ int tmpnrows = nrows;
+ vector<vector<int> > tmpmatrix;
+
+ vector<int> tmprow;
+ if(!tmpmatrix.empty())
+ tmpmatrix.clear();
+ for (int i=0;i<ncols;i++)
+ {
+ for (int j=0;j<nrows;j++)
+ {
+ tmprow.push_back(nullmatrix[j][i]);
+ }
+
+ tmpmatrix.push_back(tmprow);
+ tmprow.clear();
+ }
+
+ int unique = 0;
+ int match = 0;
+ for(int j=0;j<ncols;j++)
+ {
+ match = 0;
+ for(int i=j+1;i<=ncols;i++)
+ {
+ //comparing matrix rows
+ if( (tmpmatrix[j] == tmpmatrix[i]))
+ {
+ match++;
+ break;
+ }
+ }
+
+ //on the last iteration of a previously matched row it will add itself because it doesn't match any following rows, so that combination is counted
+ if (match == 0)
+ unique++;
+ }
+ return unique;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "TrialSwap2", "calc_combo");
+ exit(1);
+ }
+}
+/**************************************************************************************************/
+int TrialSwap2::swap_checkerboards (vector<vector<int> > &co_matrix, int ncols, int nrows)
+{
+ try {
+ //do 100 runs to make sure enough swaps are happening. This does NOT mean that there will be 1000 swaps, but that is the theoretical max.
+ for(int a=0;a<1000;a++){
+ int i, j, k, l;
+ i = m->getRandomIndex(nrows-1);
+ while((j = m->getRandomIndex(nrows-1) ) == i ) {;if (m->control_pressed) { return 0; }}
+ k = m->getRandomIndex(ncols-1);
+ while((l = m->getRandomIndex(ncols-1)) == k ) {;if (m->control_pressed) { return 0; }}
+
+ if((co_matrix[i][k]*co_matrix[j][l]==1 && co_matrix[i][l]+co_matrix[j][k]==0)||(co_matrix[i][k]+co_matrix[j][l]==0 && co_matrix[i][l]*co_matrix[j][k]==1)) //checking for checkerboard value and swap
+ {
+ co_matrix[i][k]=1-co_matrix[i][k];
+ co_matrix[i][l]=1-co_matrix[i][l];
+ co_matrix[j][k]=1-co_matrix[j][k];
+ co_matrix[j][l]=1-co_matrix[j][l];
+
+ }
+ }
+
+ return 0;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "TrialSwap2", "swap_checkerboards");
+ exit(1);
+ }
+}
+/**************************************************************************************************/
+double TrialSwap2::calc_pvalue_greaterthan (vector<double> scorevec, double initialscore)
+{
+ try {
+ int runs = scorevec.size();
+ double p = 0.0;
+ for( int i=0;i<runs;i++)
+ {
+ if (m->control_pressed) { return 0; }
+ if(scorevec[i]>=initialscore)
+ p++;
+ }
+ return p/(double)runs;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "TrialSwap2", "calc_pvalue_greaterthan");
+ exit(1);
+ }
+}
+/**************************************************************************************************/
+double TrialSwap2::calc_pvalue_lessthan (vector<double> scorevec, double initialscore)
+{
+ try {
+ int runs = scorevec.size();
+ double p = 0.0;
+ for( int i=0;i<runs;i++)
+ {
+ if (m->control_pressed) { return 0; }
+ if(scorevec[i]<=initialscore)
+ p++;
+ }
+ return p/(double)runs;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "TrialSwap2", "calc_pvalue_lessthan");
+ exit(1);
+ }
+}
+/**************************************************************************************************/
+double TrialSwap2::t_test (double initialscore, int runs, double nullMean, vector<double> scorevec)
+{
+ try {
+ double t;
+ double sampleSD;
+ double sum = 0;
+
+ for(int i=0;i<runs;i++)
+ {
+ if (m->control_pressed) { return 0; }
+ sum += pow((scorevec[i] - nullMean),2);
+ //cout << "scorevec[" << i << "]" << scorevec[i] << endl;
+ }
+
+ m->mothurOut("nullMean: " + toString(nullMean)); m->mothurOutEndLine();
+
+ m->mothurOut("sum: " + toString(sum)); m->mothurOutEndLine();
+
+ sampleSD = sqrt( (1/runs) * sum );
+
+ m->mothurOut("samplSD: " + toString(sampleSD)); m->mothurOutEndLine();
+
+ t = (nullMean - initialscore) / (sampleSD / sqrt(runs));
+
+ return t;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "TrialSwap2", "t_test");
+ exit(1);
+ }
+}
+/**************************************************************************************************/
+int TrialSwap2::print_matrix(vector<vector<int> > &matrix, int nrows, int ncols)
+{
+ try {
+ m->mothurOut("matrix:"); m->mothurOutEndLine();
+
+ for (int i = 0; i < nrows; i++)
+ {
+ if (m->control_pressed) { return 0; }
+ for (int j = 0; j < ncols; j++)
+ {
+ m->mothurOut(toString(matrix[i][j]));
+ }
+ m->mothurOutEndLine();
+ }
+ return 0;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "TrialSwap2", "print_matrix");
+ exit(1);
+ }
+}
+/**************************************************************************************************/
+
+
+
+
+
projects / mothur.git / blobdiff