+/*
+ * inverse of sim4, MUST BE TRANSPOSED BEFORE CO-OCCURRENCE ANALYSIS
+ *
+ *
+ */
+/**************************************************************************************************/
+int TrialSwap2::sim5(vector<int> initcolumntotal,vector<int> initrowtotal, vector<vector<int> > &initmatrix)
+{
+ try {
+ vector<double> colProb;
+ vector<int> tmprow;//(ncols, 7);
+ vector<vector<int> > tmpmatrix;
+ vector<double> range;
+ vector<double> randNums;
+ int ncols = initcolumntotal.size();
+ int nrows = initrowtotal.size();
+
+ tmprow.clear();
+
+ double colSum = accumulate( initcolumntotal.begin(), initcolumntotal.end(), 0 );
+ //cout << "col sum: " << colSum << endl;
+ for(int i=0;i<ncols;i++)
+ {
+ if (m->control_pressed) { return 0; }
+ colProb.push_back(initcolumntotal[i]/colSum);
+ }
+
+ double start = 0.0;
+
+ for(int i=0;i<ncols;i++)
+ {
+ if (m->control_pressed) { return 0; }
+ range.push_back(start + colProb[i]);
+ start = range[i];
+ }
+
+ for(int i=0;i<nrows;i++)
+ {
+ tmprow.assign(ncols, 0);
+ if (m->control_pressed) { return 0; }
+
+ while ( accumulate( tmprow.begin(), tmprow.end(), 0 ) < initrowtotal[i])
+ {
+ if (m->control_pressed) { return 0; }
+
+ double randNum = rand() / double(RAND_MAX);
+ if(randNum <= range[0])
+ {
+ tmprow[0] = 1;
+ continue;
+ }
+ for(int j=1;j<ncols;j++)
+ {
+ if(randNum <= range[j] && randNum > range[j-1] && tmprow[j] != 1)
+ {
+ tmprow[j] = 1;
+ }
+
+ }
+ }
+ tmpmatrix.push_back(tmprow);
+ tmprow.clear();
+ }
+
+ initmatrix = tmpmatrix;
+ return 0;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "TrialSwap2", "sim5");
+ exit(1);
+ }
+}
+/**************************************************************************************************/
+/*
+ *
+ *
+ *
+ */
+/**************************************************************************************************/
+int TrialSwap2::sim6(vector<int> columntotal, vector<vector<int> > &co_matrix)
+{
+ try {
+ vector<vector<int> > tmpmatrix;
+ vector<double> colProb;
+ vector<int> tmprow;
+ vector<double> range;
+ int ncols = columntotal.size();
+ int nrows = co_matrix.size();
+
+ int colSum = accumulate( columntotal.begin(), columntotal.end(), 0 );
+
+ for(int i=0;i<ncols;i++)
+ {
+ if (m->control_pressed) { return 0; }
+ colProb.push_back(columntotal[i]/double (colSum));
+ }
+
+ double start = 0.0;
+
+ for(int i=0;i<ncols;i++)
+ {
+ if (m->control_pressed) { return 0; }
+ range.push_back(start + colProb[i]);
+ start = range[i];
+ }
+
+ for(int i=0;i<nrows;i++)
+ {
+ if (m->control_pressed) { return 0; }
+ tmprow.assign(ncols, 0);
+ int tmprowtotal;
+ tmprowtotal = (rand() / double (RAND_MAX)) * 10;
+ while ( tmprowtotal > ncols) {
+ if (m->control_pressed) { return 0; }
+ tmprowtotal = (rand() / double (RAND_MAX)) * 10;
+ }
+ //cout << tmprowtotal << endl;
+ //cout << accumulate( tmprow.begin(), tmprow.end(), 0 ) << endl;
+
+ while ( accumulate( tmprow.begin(), tmprow.end(), 0 ) < tmprowtotal)
+ {
+ if (m->control_pressed) { return 0; }
+ double randNum = rand() / double(RAND_MAX);
+ //cout << randNum << endl;
+ if(randNum <= range[0])
+ {
+ tmprow[0] = 1;
+ continue;
+ }
+ for(int j=1;j<ncols;j++)
+ {
+ //cout << range[j] << endl;
+ if(randNum <= range[j] && randNum > range[j-1] && tmprow[j] != 1)
+ {
+ tmprow[j] = 1;
+ }
+
+ }
+
+
+ }
+
+ tmpmatrix.push_back(tmprow);
+ tmprow.clear();
+ }
+
+ co_matrix = tmpmatrix;
+ tmpmatrix.clear();
+
+ return 0;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "TrialSwap2", "sim6");
+ exit(1);
+ }
+}
+/**************************************************************************************************/
+/*
+ * MUST BE TRANSPOSED BEFORE CO-OCCURRENCE ANALYSIS
+ *
+ *
+ */
+/**************************************************************************************************/
+int TrialSwap2::sim7(vector<int> initrowtotal, vector<vector<int> > &co_matrix)
+{
+ try {
+ vector<vector<double> > probmatrix;
+ vector<vector<int> > tmpmatrix;
+ vector<double> colProb;
+ vector<double> probrow;
+ vector<int> tmprow;
+ vector<double> range;
+ double nc;
+ int ncols = co_matrix[0].size(); int nrows = co_matrix.size();
+
+ tmpmatrix.assign(nrows, vector<int>(ncols, 0.));
+
+ int rowsum = accumulate( initrowtotal.begin(), initrowtotal.end(), 0 );
+
+ nc = rowsum * ncols;
+ //cout << nc << endl;
+
+ //assign null matrix based on probabilities
+
+ double start = 0.0; // don't reset start -- probs should be from 0-1 thoughout the entire matrix
+
+ for(int i=0;i<nrows;i++)
+ {
+ if (m->control_pressed) { return 0; }
+ //cout << initrowtotal[i]/double(nc) << endl;
+ double cellprob = initrowtotal[i]/double(nc);
+ //cout << cellprob << endl;
+ for(int j=0;j<ncols;j++)
+ {
+
+ probrow.push_back(start + cellprob);
+ //cout << probrow[j] << endl;
+ //cout << start << endl;
+ start = start + cellprob;
+ }
+ probmatrix.push_back(probrow);
+ probrow.clear();
+ }
+
+
+ //while(tmprowsum < rowsum)
+ //for(int k=0;k<rowsum;k++)
+ int k = 0;
+ while(k < rowsum)
+ {
+ if (m->control_pressed) { return 0; }
+ done:
+ //cout << k << endl;
+ //tmprowsum = accumulate( tmprowtotal.begin(), tmprowtotal.end(), 0 );
+ double randNum = rand() / double(RAND_MAX);
+ //cout << randNum << "+" << endl;
+ //special case for the first entry
+ if(randNum <= probmatrix[0][0] && tmpmatrix[0][0] != 1)
+ {
+ tmpmatrix[0][0] = 1;
+ k++;
+ //cout << k << endl;
+ continue;
+ }
+
+
+ for(int i=0;i<nrows;i++)
+ {
+ if (m->control_pressed) { return 0; }
+ for(int j=0;j<ncols;j++)
+ {
+ //cout << probmatrix[i][j] << endl;
+ if(randNum <= probmatrix[i][j] && randNum > probmatrix[i][j-1] && tmpmatrix[i][j] != 1)
+ {
+ tmpmatrix[i][j] = 1;
+ k++;
+ //cout << k << endl;
+ goto done;
+ }
+ //else
+ //k = k-1;
+ }
+
+ }
+
+ }
+
+ co_matrix = tmpmatrix;
+ return 0;
+ //build probibility matrix
+ /* for(int i=0;i<nrows;i++)
+ {
+ for(int j=0;j<ncols;j++)
+ {
+ probrow.push_back(rowtotal[i]/nc);
+ }
+ probmatrix.pushback(probrow);
+ probrow.clear;
+ }
+ */
+
+ /* int colSum = accumulate( initcolumntotal.begin(), initcolumntotal.end(), 0 );
+
+ for(int i=0;i<ncols;i++)
+ {
+ colProb.push_back(initcolumntotal[i]/double (colSum));
+ }
+
+ double start = 0.0;
+
+ for(int i=0;i<ncols;i++)
+ {
+ range.push_back(start + colProb[i]);
+ start = range[i];
+ }
+
+ for(int i=0;i<nrows;i++)
+ {
+ tmprow.assign(ncols, 0);
+ int tmprowtotal;
+ tmprowtotal = (rand() / double (RAND_MAX)) * 10;
+ while ( tmprowtotal > ncols)
+ tmprowtotal = (rand() / double (RAND_MAX)) * 10;
+ //cout << tmprowtotal << endl;
+ //cout << accumulate( tmprow.begin(), tmprow.end(), 0 ) << endl;
+
+ while ( accumulate( tmprow.begin(), tmprow.end(), 0 ) < tmprowtotal)
+ {
+ double randNum = rand() / double(RAND_MAX);
+ //cout << randNum << endl;
+ if(randNum <= range[0])
+ {
+ tmprow[0] = 1;
+ continue;
+ }
+ for(int j=1;j<ncols;j++)
+ {
+ //cout << range[j] << endl;
+ if(randNum <= range[j] && randNum > range[j-1] && tmprow[j] != 1)
+ {
+ tmprow[j] = 1;
+ }
+ }
+ }
+
+ tmpmatrix.push_back(tmprow);
+ tmprow.clear();
+ }