exit(1);
}
}
-
+/*********************************************************************************************************************************/
+double LinearAlgebra::calcKruskalWallis(vector<spearmanRank>& values, double& pValue){
+ try {
+ double H;
+ set<string> treatments;
+
+ //rank values
+ sort(values.begin(), values.end(), compareSpearman);
+ vector<spearmanRank*> ties;
+ int rankTotal = 0;
+ vector<int> TIES;
+ for (int j = 0; j < values.size(); j++) {
+ treatments.insert(values[j].name);
+ rankTotal += (j+1);
+ ties.push_back(&(values[j]));
+
+ if (j != values.size()-1) { // you are not the last so you can look ahead
+ if (values[j].score != values[j+1].score) { // you are done with ties, rank them and continue
+ if (ties.size() > 1) { TIES.push_back(ties.size()); }
+ for (int k = 0; k < ties.size(); k++) {
+ double thisrank = rankTotal / (double) ties.size();
+ (*ties[k]).score = thisrank;
+ }
+ ties.clear();
+ rankTotal = 0;
+ }
+ }else { // you are the last one
+ if (ties.size() > 1) { TIES.push_back(ties.size()); }
+ for (int k = 0; k < ties.size(); k++) {
+ double thisrank = rankTotal / (double) ties.size();
+ (*ties[k]).score = thisrank;
+ }
+ }
+ }
+
+
+ // H = 12/(N*(N+1)) * (sum Ti^2/n) - 3(N+1)
+ map<string, double> sums;
+ map<string, double> counts;
+ for (set<string>::iterator it = treatments.begin(); it != treatments.end(); it++) { sums[*it] = 0.0; counts[*it] = 0; }
+
+ for (int j = 0; j < values.size(); j++) {
+ sums[values[j].name] += values[j].score;
+ counts[values[j].name]+= 1.0;
+ }
+
+ double middleTerm = 0.0;
+ for (set<string>::iterator it = treatments.begin(); it != treatments.end(); it++) {
+ middleTerm += ((sums[*it]*sums[*it])/counts[*it]);
+ }
+
+ double firstTerm = 12 / (double) (values.size()*(values.size()+1));
+ double lastTerm = 3 * (values.size()+1);
+
+ H = firstTerm * middleTerm - lastTerm;
+
+ //adjust for ties
+ if (TIES.size() != 0) {
+ double sum = 0.0;
+ for (int j = 0; j < TIES.size(); j++) { sum += ((TIES[j]*TIES[j]*TIES[j])-TIES[j]); }
+ double result = 1.0 - (sum / (double) ((values.size()*values.size()*values.size())-values.size()));
+ H /= result;
+ }
+
+ //Numerical Recipes pg221
+ pValue = 1.0 - (gammp(((treatments.size()-1)/(double)2.0), H/2.0));
+
+ return H;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "LinearAlgebra", "calcKruskalWallis");
+ exit(1);
+ }
+}
/*********************************************************************************************************************************/
//assumes both matrices are square and the same size
double LinearAlgebra::calcKendall(vector< vector<double> >& euclidDists, vector< vector<double> >& userDists){
exit(1);
}
}
+/*********************************************************************************************************************************/
+double LinearAlgebra::calcWilcoxon(vector<double>& x, vector<double>& y, double& sig){
+ try {
+ if (x.size() != y.size()) { m->mothurOut("[ERROR]: vector size mismatch."); m->mothurOutEndLine(); return 0.0; }
+
+ double W = 0.0;
+ sig = 0.0;
+
+ vector<double> signPairs;
+ vector<spearmanRank> absV;
+ for (int i = 0; i < x.size(); i++) {
+ if (m->control_pressed) { return W; }
+ double temp = y[i]-x[i];
+ double signV = sign(temp);
+ if (signV != 0) { // exclude zeros
+ spearmanRank member(toString(i), abs(temp));
+ absV.push_back(member);
+ signPairs.push_back(signV);
+ }
+ }
+
+ //rank absV
+ //sort xscores
+ sort(absV.begin(), absV.end(), compareSpearman);
+
+ //convert scores to ranks of x
+ vector<spearmanRank*> ties;
+ int rankTotal = 0;
+ for (int j = 0; j < absV.size(); j++) {
+ if (m->control_pressed) { return W; }
+ rankTotal += (j+1);
+ ties.push_back(&(absV[j]));
+
+ if (j != absV.size()-1) { // you are not the last so you can look ahead
+ if (absV[j].score != absV[j+1].score) { // you are done with ties, rank them and continue
+ for (int k = 0; k < ties.size(); k++) {
+ float thisrank = rankTotal / (float) ties.size();
+ (*ties[k]).score = thisrank;
+ }
+ ties.clear();
+ rankTotal = 0;
+ }
+ }else { // you are the last one
+ for (int k = 0; k < ties.size(); k++) {
+ float thisrank = rankTotal / (float) ties.size();
+ (*ties[k]).score = thisrank;
+ }
+ }
+ }
+ //sum ranks times sign
+ for (int i = 0; i < absV.size(); i++) {
+ if (m->control_pressed) { return W; }
+ W += (absV[i].score*signPairs[i]);
+ }
+ W = abs(W);
+
+ //find zScore
+ cout << "still need to find sig!!" << endl;
+
+ return W;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "LinearAlgebra", "calcWilcoxon");
+ exit(1);
+ }
+}
/*********************************************************************************************************************************/
double LinearAlgebra::calcSpearman(vector<double>& x, vector<double>& y, double& sig){
try {
/*********************************************************************************************************************************/
vector<vector<double> > LinearAlgebra::getObservedEuclideanDistance(vector<vector<double> >& relAbundData){
+ try {
- int numSamples = relAbundData.size();
- int numOTUs = relAbundData[0].size();
-
- vector<vector<double> > dMatrix(numSamples);
- for(int i=0;i<numSamples;i++){
- dMatrix[i].resize(numSamples);
+ int numSamples = relAbundData.size();
+ int numOTUs = relAbundData[0].size();
+
+ vector<vector<double> > dMatrix(numSamples);
+ for(int i=0;i<numSamples;i++){
+ dMatrix[i].resize(numSamples);
+ }
+
+ for(int i=0;i<numSamples;i++){
+ for(int j=0;j<numSamples;j++){
+
+ if (m->control_pressed) { return dMatrix; }
+
+ double d = 0;
+ for(int k=0;k<numOTUs;k++){
+ d += pow((relAbundData[i][k] - relAbundData[j][k]), 2.0000);
+ }
+ dMatrix[i][j] = pow(d, 0.50000);
+ dMatrix[j][i] = dMatrix[i][j];
+
+ }
+ }
+ return dMatrix;
}
-
- for(int i=0;i<numSamples;i++){
- for(int j=0;j<numSamples;j++){
-
- double d = 0;
- for(int k=0;k<numOTUs;k++){
- d += pow((relAbundData[i][k] - relAbundData[j][k]), 2.0000);
- }
- dMatrix[i][j] = pow(d, 0.50000);
- dMatrix[j][i] = dMatrix[i][j];
-
- }
+ catch(exception& e) {
+ m->errorOut(e, "LinearAlgebra", "getObservedEuclideanDistance");
+ exit(1);
+ }
+}
+
+/*********************************************************************************************************************************/
+vector<double> LinearAlgebra::solveEquations(vector<vector<double> > A, vector<double> b){
+ try {
+ int length = (int)b.size();
+ vector<double> x(length, 0);
+ vector<int> index(length);
+ for(int i=0;i<length;i++){ index[i] = i; }
+ double d;
+
+ ludcmp(A, index, d); if (m->control_pressed) { return b; }
+ lubksb(A, index, b);
+
+ return b;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "LinearAlgebra", "solveEquations");
+ exit(1);
+ }
+}
+/*********************************************************************************************************************************/
+vector<float> LinearAlgebra::solveEquations(vector<vector<float> > A, vector<float> b){
+ try {
+ int length = (int)b.size();
+ vector<double> x(length, 0);
+ vector<int> index(length);
+ for(int i=0;i<length;i++){ index[i] = i; }
+ float d;
+
+ ludcmp(A, index, d); if (m->control_pressed) { return b; }
+ lubksb(A, index, b);
+
+ return b;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "LinearAlgebra", "solveEquations");
+ exit(1);
+ }
+}
+
+/*********************************************************************************************************************************/
+
+void LinearAlgebra::ludcmp(vector<vector<double> >& A, vector<int>& index, double& d){
+ try {
+ double tiny = 1e-20;
+
+ int n = (int)A.size();
+ vector<double> vv(n, 0.0);
+ double temp;
+ int imax;
+
+ d = 1.0;
+
+ for(int i=0;i<n;i++){
+ double big = 0.0;
+ for(int j=0;j<n;j++){ if((temp=fabs(A[i][j])) > big ) big=temp; }
+ if(big==0.0){ m->mothurOut("Singular matrix in routine ludcmp\n"); }
+ vv[i] = 1.0/big;
+ }
+
+ for(int j=0;j<n;j++){
+ if (m->control_pressed) { break; }
+ for(int i=0;i<j;i++){
+ double sum = A[i][j];
+ for(int k=0;k<i;k++){ sum -= A[i][k] * A[k][j]; }
+ A[i][j] = sum;
+ }
+
+ double big = 0.0;
+ for(int i=j;i<n;i++){
+ double sum = A[i][j];
+ for(int k=0;k<j;k++){ sum -= A[i][k] * A[k][j]; }
+ A[i][j] = sum;
+ double dum;
+ if((dum = vv[i] * fabs(sum)) >= big){
+ big = dum;
+ imax = i;
+ }
+ }
+ if(j != imax){
+ for(int k=0;k<n;k++){
+ double dum = A[imax][k];
+ A[imax][k] = A[j][k];
+ A[j][k] = dum;
+ }
+ d = -d;
+ vv[imax] = vv[j];
+ }
+ index[j] = imax;
+
+ if(A[j][j] == 0.0){ A[j][j] = tiny; }
+
+ if(j != n-1){
+ double dum = 1.0/A[j][j];
+ for(int i=j+1;i<n;i++){ A[i][j] *= dum; }
+ }
+ }
+ }
+ catch(exception& e) {
+ m->errorOut(e, "LinearAlgebra", "ludcmp");
+ exit(1);
+ }
+}
+
+/*********************************************************************************************************************************/
+
+void LinearAlgebra::lubksb(vector<vector<double> >& A, vector<int>& index, vector<double>& b){
+ try {
+ double total;
+ int n = (int)A.size();
+ int ii = 0;
+
+ for(int i=0;i<n;i++){
+ if (m->control_pressed) { break; }
+ int ip = index[i];
+ total = b[ip];
+ b[ip] = b[i];
+
+ if (ii != 0) {
+ for(int j=ii-1;j<i;j++){
+ total -= A[i][j] * b[j];
+ }
+ }
+ else if(total != 0){ ii = i+1; }
+ b[i] = total;
+ }
+ for(int i=n-1;i>=0;i--){
+ total = b[i];
+ for(int j=i+1;j<n;j++){ total -= A[i][j] * b[j]; }
+ b[i] = total / A[i][i];
+ }
+ }
+ catch(exception& e) {
+ m->errorOut(e, "LinearAlgebra", "lubksb");
+ exit(1);
+ }
+}
+/*********************************************************************************************************************************/
+
+void LinearAlgebra::ludcmp(vector<vector<float> >& A, vector<int>& index, float& d){
+ try {
+ double tiny = 1e-20;
+
+ int n = (int)A.size();
+ vector<float> vv(n, 0.0);
+ double temp;
+ int imax;
+
+ d = 1.0;
+
+ for(int i=0;i<n;i++){
+ float big = 0.0;
+ for(int j=0;j<n;j++){ if((temp=fabs(A[i][j])) > big ) big=temp; }
+ if(big==0.0){ m->mothurOut("Singular matrix in routine ludcmp\n"); }
+ vv[i] = 1.0/big;
+ }
+
+ for(int j=0;j<n;j++){
+ if (m->control_pressed) { break; }
+ for(int i=0;i<j;i++){
+ float sum = A[i][j];
+ for(int k=0;k<i;k++){ sum -= A[i][k] * A[k][j]; }
+ A[i][j] = sum;
+ }
+
+ float big = 0.0;
+ for(int i=j;i<n;i++){
+ float sum = A[i][j];
+ for(int k=0;k<j;k++){ sum -= A[i][k] * A[k][j]; }
+ A[i][j] = sum;
+ float dum;
+ if((dum = vv[i] * fabs(sum)) >= big){
+ big = dum;
+ imax = i;
+ }
+ }
+ if(j != imax){
+ for(int k=0;k<n;k++){
+ float dum = A[imax][k];
+ A[imax][k] = A[j][k];
+ A[j][k] = dum;
+ }
+ d = -d;
+ vv[imax] = vv[j];
+ }
+ index[j] = imax;
+
+ if(A[j][j] == 0.0){ A[j][j] = tiny; }
+
+ if(j != n-1){
+ float dum = 1.0/A[j][j];
+ for(int i=j+1;i<n;i++){ A[i][j] *= dum; }
+ }
+ }
+ }
+ catch(exception& e) {
+ m->errorOut(e, "LinearAlgebra", "ludcmp");
+ exit(1);
+ }
+}
+
+/*********************************************************************************************************************************/
+
+void LinearAlgebra::lubksb(vector<vector<float> >& A, vector<int>& index, vector<float>& b){
+ try {
+ float total;
+ int n = (int)A.size();
+ int ii = 0;
+
+ for(int i=0;i<n;i++){
+ if (m->control_pressed) { break; }
+ int ip = index[i];
+ total = b[ip];
+ b[ip] = b[i];
+
+ if (ii != 0) {
+ for(int j=ii-1;j<i;j++){
+ total -= A[i][j] * b[j];
+ }
+ }
+ else if(total != 0){ ii = i+1; }
+ b[i] = total;
+ }
+ for(int i=n-1;i>=0;i--){
+ total = b[i];
+ for(int j=i+1;j<n;j++){ total -= A[i][j] * b[j]; }
+ b[i] = total / A[i][i];
+ }
+ }
+ catch(exception& e) {
+ m->errorOut(e, "LinearAlgebra", "lubksb");
+ exit(1);
+ }
+}
+
+
+/*********************************************************************************************************************************/
+
+vector<vector<double> > LinearAlgebra::getInverse(vector<vector<double> > matrix){
+ try {
+ int n = (int)matrix.size();
+
+ vector<vector<double> > inverse(n);
+ for(int i=0;i<n;i++){ inverse[i].assign(n, 0.0000); }
+
+ vector<double> column(n, 0.0000);
+ vector<int> index(n, 0);
+ double dummy;
+
+ ludcmp(matrix, index, dummy);
+
+ for(int j=0;j<n;j++){
+ if (m->control_pressed) { break; }
+
+ column.assign(n, 0);
+
+ column[j] = 1.0000;
+
+ lubksb(matrix, index, column);
+
+ for(int i=0;i<n;i++){ inverse[i][j] = column[i]; }
+ }
+
+ return inverse;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "LinearAlgebra", "getInverse");
+ exit(1);
}
- return dMatrix;
-
}
/*********************************************************************************************************************************/
projects / mothur.git / blobdiff