//**********************************************************************************************************************
vector<string> NMDSCommand::getValidParameters(){
try {
- string Array[] = {"phylip","axes","dimension","maxiters","step","outputdir","inputdir"};
+ string Array[] = {"phylip","axes","mindim","maxdim","iters","maxiters","trace","epsilon","outputdir","inputdir"};
vector<string> myArray (Array, Array+(sizeof(Array)/sizeof(string)));
return myArray;
}
else {
//valid paramters for this command
- string Array[] = {"phylip","axes","dimension","maxiters","step","outputdir", "inputdir"};
+ string Array[] = {"phylip","axes","mindim","maxdim","iters","maxiters","trace","epsilon","outputdir", "inputdir"};
vector<string> myArray (Array, Array+(sizeof(Array)/sizeof(string)));
OptionParser parser(option);
outputDir += m->hasPath(phylipfile); //if user entered a file with a path then preserve it
}
- string temp = validParameter.validFile(parameters, "dimension", false); if (temp == "not found") { temp = "2"; }
- convert(temp, dimension);
+ string temp = validParameter.validFile(parameters, "mindim", false); if (temp == "not found") { temp = "1"; }
+ convert(temp, mindim);
- temp = validParameter.validFile(parameters, "maxiters", false); if (temp == "not found") { temp = "1000"; }
+ temp = validParameter.validFile(parameters, "maxiters", false); if (temp == "not found") { temp = "500"; }
convert(temp, maxIters);
- temp = validParameter.validFile(parameters, "step", false); if (temp == "not found") { temp = "0.2"; }
- convert(temp, step);
+ temp = validParameter.validFile(parameters, "iters", false); if (temp == "not found") { temp = "10"; }
+ convert(temp, iters);
- temp = validParameter.validFile(parameters, "cutoff", false); if (temp == "not found") { temp = "2"; }
- convert(temp, cutoff);
- cutoff /= 100.0;
+ temp = validParameter.validFile(parameters, "maxdim", false); if (temp == "not found") { temp = "2"; }
+ convert(temp, maxdim);
+
+ temp = validParameter.validFile(parameters, "epsilon", false); if (temp == "not found") { temp = "0.000000000001"; }
+ convert(temp, epsilon);
+
+ temp = validParameter.validFile(parameters, "trace", false); if (temp == "not found") { temp = "F"; }
+ trace = m->isTrue(temp);
+
+ if (mindim < 1) { m->mothurOut("mindim must be at least 1."); m->mothurOutEndLine(); abort = true; }
+ if (maxdim < mindim) { m->mothurOut("maxdim must be greater than mindim."); m->mothurOutEndLine(); abort = true; }
}
}
//**********************************************************************************************************************
void NMDSCommand::help(){
try {
-
- m->mothurOut("The nmds command parameters are phylip, axes, dimension, maxiters, cutoff and step."); m->mothurOutEndLine();
+ m->mothurOut("The nmds command is modelled after the nmds code written in R by Sarah Goslee, using Non-metric multidimensional scaling function using the majorization algorithm from Borg & Groenen 1997, Modern Multidimensional Scaling."); m->mothurOutEndLine();
+ m->mothurOut("The nmds command parameters are phylip, axes, mindim, maxdim, maxiters, iters, epsilon and trace."); m->mothurOutEndLine();
m->mothurOut("The phylip parameter allows you to enter your distance file."); m->mothurOutEndLine();
m->mothurOut("The axes parameter allows you to enter a file containing a starting configuration."); m->mothurOutEndLine();
- m->mothurOut("The dimension parameter allows you to select how many dimensions to use. Default=2"); m->mothurOutEndLine();
- m->mothurOut("The maxiters parameter allows you to select the maximum number of iters to try. Default=1000"); m->mothurOutEndLine();
- m->mothurOut("The cutoff parameter allows you to select set an acceptable percentage of magnitude. Default=2, meaning when magnitude of g reaches 2% of it's starting value the process will stop."); m->mothurOutEndLine();
- m->mothurOut("The step parameter allows you to set a starting step. Default=0.2"); m->mothurOutEndLine();
+ m->mothurOut("The maxdim parameter allows you to select how maximum dimensions to use. Default=2"); m->mothurOutEndLine();
+ m->mothurOut("The mindim parameter allows you to select how minimum dimensions to use. Default=1"); m->mothurOutEndLine();
+ m->mothurOut("The maxiters parameter allows you to select the maximum number of iters to try with each random configuration. Default=500"); m->mothurOutEndLine();
+ m->mothurOut("The iters parameter allows you to select the number of random configuration to try. Default=10"); m->mothurOutEndLine();
+ m->mothurOut("The epsilon parameter allows you to select set an acceptable stopping point. Default=1e-12."); m->mothurOutEndLine();
+ m->mothurOut("The trace parameter allows you to see the output after each iter. Default=F"); m->mothurOutEndLine();
m->mothurOut("Example nmds(phylip=yourDistanceFile).\n");
m->mothurOut("Note: No spaces between parameter labels (i.e. phylip), '=' and parameters (i.e.yourDistanceFile).\n\n");
}
cout.setf(ios::fixed, ios::floatfield);
cout.setf(ios::showpoint);
- cerr.setf(ios::fixed, ios::floatfield);
- cerr.setf(ios::showpoint);
vector<string> names;
- vector<seqDist> matrix; //seqDist = int, int, float - index of seq1 in names, index of seq2 in names, their distance
+ vector< vector< double> > matrix;
//read in phylip file
ReadPhylipVector readFile(phylipfile);
names = readFile.read(matrix);
if (m->control_pressed) { return 0; }
-
- //randomly generate the starting configuration - step 2
- vector< vector<double> > axes;
- if (axesfile == "") { axes = generateStartingConfiguration(names.size()); }
- else { axes = readAxes(names); }
- if (m->control_pressed) { return 0; }
- //sort matrix from smallest distance to largest - step 5
- sort(matrix.begin(), matrix.end(), compareSequenceDistance);
+ //read axes
+ vector< vector<double> > axes;
+ if (axesfile != "") { axes = readAxes(names); }
- bool stable = false;
- int count = 0;
- vector<double> previousStresses;
- vector< vector<double> > previousGradient = axes;
- double initialMagnitude;
- m->mothurOutEndLine(); m->mothurOut("Iter\tStress\tMagnitude"); m->mothurOutEndLine();
- while ((count != maxIters) && (!stable)) {
- count++;
-
- //normalize axes - step 3
- normalizeConfiguration(axes, names.size());
- if (m->control_pressed) { return 0; }
+ for (int i = mindim; i <= maxdim; i++) {
+ m->mothurOut("Processing Dimension: " + toString(i)); m->mothurOutEndLine();
- //calculate Euclidean distances - step 4
- vector< vector<double> > euclid = linearCalc.calculateEuclidianDistance(axes);
- if (m->control_pressed) { return 0; }
+ string outputFileName = outputDir + m->getRootName(m->getSimpleName(phylipfile)) + "dim" + toString(i) + ".nmds";
+ string stressFileName = outputDir + m->getRootName(m->getSimpleName(phylipfile)) + "dim" + toString(i) + ".stress.nmds";
+ outputNames.push_back(outputFileName); outputTypes["nmds"].push_back(outputFileName);
+ outputNames.push_back(stressFileName); outputTypes["stress"].push_back(stressFileName);
- //order euclid elements in same order as matrix - step 6
- //if there are ties in the matrix we want to arrange the euclid distances in the best way so we do not to add unnecessary stress
- vector<seqDist> eDists;
- vector<seqDist> ties;
- for (int i = 0; i < matrix.size(); i++) {
-
- seqDist temp(matrix[i].seq1, matrix[i].seq2, euclid[matrix[i].seq1][matrix[i].seq2]);
- ties.push_back(temp);
-
- if (i != matrix.size()-1) { // you are not the last so you can look ahead
- if (matrix[i].dist != matrix[i+1].dist) { // you are done with ties, sort and save them, then continue
- sort(ties.begin(), ties.end(), compareSequenceDistance);
- for (int k = 0; k < ties.size(); k++) { eDists.push_back(ties[k]); }
- ties.clear();
- }
- }else { // you are the last one
- sort(ties.begin(), ties.end(), compareSequenceDistance);
- for (int k = 0; k < ties.size(); k++) { eDists.push_back(ties[k]); }
- }
- }
+ ofstream out, out2;
+ m->openOutputFile(outputFileName, out);
+ m->openOutputFile(stressFileName, out2);
- for (int i = 0; i < euclid.size(); i++) { euclid[i].clear(); } euclid.clear();
- if (m->control_pressed) { return 0; }
+ out2.setf(ios::fixed, ios::floatfield);
+ out2.setf(ios::showpoint);
+ out.setf(ios::fixed, ios::floatfield);
+ out.setf(ios::showpoint);
- //find D - from step 7
- vector<seqDist> D = satisfyMonotonicity(eDists);
- if (m->control_pressed) { return 0; }
+ out2 << "Iter\tStress\tCorr" << endl;
- //calculate the raw stress and normalize it - steps 8 and 9
- double rawStress;
- double stress = calculateStress(eDists, D, rawStress);
- previousStresses.push_back(stress);
- if (stress == 0) { m->mothurOut("Stress reached zero after " + toString(count) + " iters, stopping."); m->mothurOutEndLine(); break; }
- if (m->control_pressed) { return 0; }
-
- //calculate stress gradient - step 10
- vector< vector<double> > stressGradient = calculateStressGradientVector(eDists, D, rawStress, stress, axes);
- if (m->control_pressed) { return 0; }
-
- //calculate magnitude
- double magnitude = calculateMagnitude(stressGradient);
- if (count == 1) { initialMagnitude = magnitude; }
- if (m->control_pressed) { return 0; }
-
- //save gradient before adjusting config.
- previousGradient = stressGradient;
-
- if ((count % 100) == 0) { m->mothurOut(toString(count) + "\t" + toString(previousStresses[previousStresses.size()-1]) + "\t" + toString(magnitude)); m->mothurOutEndLine(); }
+ for (int j = 0; j < iters; j++) {
+ if (trace) { m->mothurOut(toString(j+1)); m->mothurOutEndLine(); }
+
+ //get configuration - either randomly generate or resize to this dimension
+ vector< vector<double> > thisConfig;
+ if (axesfile == "") { thisConfig = generateStartingConfiguration(names.size(), i); }
+ else { thisConfig = getConfiguration(axes, i); }
+ if (m->control_pressed) { out.close(); out2.close(); for (int k = 0; k < outputNames.size(); k++) { remove(outputNames[k].c_str()); } return 0; }
+
+ //calc nmds for this dimension
+ double stress;
+ vector< vector<double> > endConfig = nmdsCalc(matrix, thisConfig, stress);
+ if (m->control_pressed) { out.close(); out2.close(); for (int k = 0; k < outputNames.size(); k++) { remove(outputNames[k].c_str()); } return 0; }
+
+ //calc euclid distances for new config
+ vector< vector<double> > newEuclid = linearCalc.calculateEuclidianDistance(endConfig);
+ if (m->control_pressed) { out.close(); out2.close(); for (int k = 0; k < outputNames.size(); k++) { remove(outputNames[k].c_str()); } return 0; }
+
+ //calc correlation between original distances and euclidean distances from this config
+ double corr = linearCalc.calcPearson(matrix, newEuclid);
+ corr *= corr;
+ if (m->control_pressed) { out.close(); out2.close(); for (int k = 0; k < outputNames.size(); k++) { remove(outputNames[k].c_str()); } return 0; }
+
+ //output results
+ out << "Config" << (j+1) << '\t';
+ for (int k = 0; k < i; k++) { out << "X" << (k+1) << '\t'; }
+ out << endl;
+ out2 << (j+1) << '\t' << stress << '\t' << corr << endl;
+
+ output(endConfig, names, out);
+
+ if (m->control_pressed) { out.close(); out2.close(); for (int k = 0; k < outputNames.size(); k++) { remove(outputNames[k].c_str()); } return 0; }
- //are we done - we are done if percentage of magnitude compared to initial magnitude is less than cutoff
- double percentage = magnitude / initialMagnitude;
- if (percentage < cutoff) { stable = true; }
- else {
-
- //calculate new step size
- step = calculateStep(previousGradient, stressGradient, previousStresses);
- cout << "count = " << count << '\t' << step << endl;
- if (m->control_pressed) { return 0; }
-
- //find new config.
- axes = calculateNewConfiguration(magnitude, axes, stressGradient);
- if (m->control_pressed) { return 0; }
}
+
+ out.close(); out2.close();
}
- if (m->control_pressed) { return 0; }
-
- string outputFileName = outputDir + m->getRootName(m->getSimpleName(phylipfile)) + "nmds";
- string stressFileName = outputDir + m->getRootName(m->getSimpleName(phylipfile)) + "stress.nmds";
- outputNames.push_back(outputFileName); outputTypes["nmds"].push_back(outputFileName);
- outputNames.push_back(stressFileName); outputTypes["stress"].push_back(stressFileName);
-
- output(outputFileName, stressFileName, previousGradient, previousStresses, names);
-
if (m->control_pressed) { for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } return 0; }
m->mothurOutEndLine();
exit(1);
}
}
+//**********************************************************************************************************************
+vector< vector<double> > NMDSCommand::nmdsCalc(vector< vector<double> >& matrix, vector< vector<double> >& config, double& stress1) {
+ try {
+
+ vector< vector<double> > newConfig = config;
+
+ //calc euclid distances
+ vector< vector<double> > euclid = linearCalc.calculateEuclidianDistance(newConfig);
+ if (m->control_pressed) { return newConfig; }
+
+ double stress2 = calculateStress(matrix, euclid);
+ stress1 = stress2 + 1.0 + epsilon;
+
+ if (trace) { m->mothurOutEndLine(); m->mothurOut("Iter\tStress"); m->mothurOutEndLine(); }
+
+ int count = 0;
+ while ((count < maxIters) && (abs(stress1 - stress2) > epsilon)) {
+ count++;
+
+ stress1 = stress2;
+
+ if (m->control_pressed) { return newConfig; }
+
+ vector< vector<double> > b; b.resize(euclid.size());
+ for (int i = 0; i < b.size(); i++) { b[i].resize(euclid[i].size(), 0.0); }
+
+ vector<double> columnSums; columnSums.resize(euclid.size(), 0.0);
+ for (int i = 0; i < euclid.size(); i++) {
+ for (int j = 0; j < euclid[i].size(); j++) {
+ //eliminate divide by zero error
+ if (euclid[i][j] != 0) {
+ b[i][j] = matrix[i][j] / euclid[i][j];
+ columnSums[j] += b[i][j];
+ b[i][j] *= -1.0;
+ }
+ }
+ }
+
+ //put in diagonal sums
+ for (int i = 0; i < euclid.size(); i++) { b[i][i] = columnSums[i]; }
+
+ int numInLowerTriangle = matrix.size() * (matrix.size()-1) / 2.0;
+ double n = (1.0 + sqrt(1.0 + 8.0 * numInLowerTriangle)) / 2.0;
+
+ //matrix mult
+ newConfig = linearCalc.matrix_mult(newConfig, b);
+ for (int i = 0; i < newConfig.size(); i++) {
+ for (int j = 0; j < newConfig[i].size(); j++) {
+ newConfig[i][j] *= (1.0 / n);
+ }
+ }
+
+ euclid = linearCalc.calculateEuclidianDistance(newConfig);
+
+ stress2 = calculateStress(matrix, euclid);
+
+ if (trace) { m->mothurOut(count + "\t" + toString(stress1)); m->mothurOutEndLine(); }
+
+ }
+
+ return newConfig;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "NMDSCommand", "generateStartingConfiguration");
+ exit(1);
+ }
+}
+
//**********************************************************************************************************************
//generate random config
-vector< vector<double> > NMDSCommand::generateStartingConfiguration(int numNames) {
+vector< vector<double> > NMDSCommand::generateStartingConfiguration(int numNames, int dimension) {
try {
vector< vector<double> > axes; axes.resize(dimension);
for (int i = 0; i < axes.size(); i++) { axes[i].resize(numNames); }
}
//**********************************************************************************************************************
//normalize configuration
-int NMDSCommand::normalizeConfiguration(vector< vector<double> >& axes, int numNames) {
+int NMDSCommand::normalizeConfiguration(vector< vector<double> >& axes, int numNames, int dimension) {
try {
vector<double> averageAxes; averageAxes.resize(dimension, 0.0);
}
}
//**********************************************************************************************************************
-//adjust eDists so that it creates monotonically increasing series of succesive values that increase or stay the same, but never decrease
-vector<seqDist> NMDSCommand::satisfyMonotonicity(vector<seqDist> eDists) {
+//get configuration
+vector< vector<double> > NMDSCommand::getConfiguration(vector< vector<double> >& axes, int dimension) {
try {
+ vector< vector<double> > newAxes; newAxes.resize(dimension);
- vector<seqDist> D = eDists;
-
- for (int i = 0; i < (D.size()-1); i++) {
-
- if (m->control_pressed) { return D; }
-
- //is the distance in i+1 smaller than i, if yes then adjust
- if (D[i+1].dist < D[i].dist) { D[i+1].dist = D[i].dist; }
+ for (int i = 0; i < dimension; i++) {
+ newAxes[i] = axes[i];
}
-
- return D;
+
+ return newAxes;
}
catch(exception& e) {
- m->errorOut(e, "NMDSCommand", "satisfyMonotonicity");
+ m->errorOut(e, "NMDSCommand", "getConfiguration");
exit(1);
}
}
//**********************************************************************************************************************
//find raw stress, and normalize using
-double NMDSCommand::calculateStress(vector<seqDist>& eDists, vector<seqDist>& D, double& rawStress) {
+double NMDSCommand::calculateStress(vector< vector<double> >& matrix, vector< vector<double> >& config) {
try {
double normStress = 0.0;
double denom = 0.0;
- rawStress = 0.0;
+ double rawStress = 0.0;
//find raw stress
- for (int i = 0; i < D.size(); i++) {
-
- if (m->control_pressed) { return normStress; }
-
- rawStress += ((eDists[i].dist - D[i].dist) * (eDists[i].dist - D[i].dist));
- denom += (eDists[i].dist * eDists[i].dist);
+ for (int i = 0; i < matrix.size(); i++) {
+ for (int j = 0; j < matrix[i].size(); j++) {
+ if (m->control_pressed) { return normStress; }
+
+ rawStress += ((matrix[i][j] - config[i][j]) * (matrix[i][j] - config[i][j]));
+ denom += (config[i][j] * config[i][j]);
+ }
}
//normalize stress
- if (rawStress != 0.0) {
- normStress = 100 * sqrt((rawStress / denom));
+ if ((rawStress != 0.0) && (denom != 0.0)) {
+ normStress = sqrt((rawStress / denom));
}
-
+
return normStress;
}
catch(exception& e) {
exit(1);
}
}
+
//**********************************************************************************************************************
-vector< vector<double> > NMDSCommand::calculateStressGradientVector(vector<seqDist>& eDists, vector<seqDist>& D, double rawStress, double stress, vector< vector<double> >& axes) {
- try {
- vector< vector<double> > gradient; gradient.resize(dimension);
- for (int i = 0; i < gradient.size(); i++) { gradient[i].resize(axes[0].size(), 0.0); }
-
- double sumDij = 0.0;
- for (int i = 0; i < eDists.size(); i++) { sumDij += (eDists[i].dist * eDists[i].dist); }
-
- for (int i = 0; i < eDists.size(); i++) {
-
- for (int j = 0; j < dimension; j++) {
-
- if (m->control_pressed) { return gradient; }
-
- double firstTerm1 = (stress / rawStress) * (eDists[i].dist - D[i].dist);
- double firstTerm2 = eDists[i].dist * (stress / sumDij);
- double firstTerm = firstTerm1 - firstTerm2;
-
- double secondTerm = (axes[j][eDists[i].seq1] - axes[j][eDists[i].seq2]) / eDists[i].dist;
-
- double results = (firstTerm * secondTerm);
-
- gradient[j][eDists[i].seq1] += results;
- gradient[j][eDists[i].seq2] -= results;
- }
- }
-
- return gradient;
- }
- catch(exception& e) {
- m->errorOut(e, "NMDSCommand", "calculateStressGradientVector");
- exit(1);
- }
-}
-//**********************************************************************************************************************
-double NMDSCommand::calculateMagnitude(vector< vector<double> >& gradient) {
- try {
- double magnitude = 0.0;
-
- double sum = 0.0;
- for (int i = 0; i < gradient.size(); i++) {
- for (int j = 0; j < gradient[i].size(); j++) {
- sum += (gradient[i][j] * gradient[i][j]);
- }
- }
-
- magnitude = sqrt(((1.0/(float)gradient[0].size()) * sum));
-
- return magnitude;
- }
- catch(exception& e) {
- m->errorOut(e, "NMDSCommand", "calculateMagnitude");
- exit(1);
- }
-}
-//**********************************************************************************************************************
-//described in Kruskal paper page 121 + 122
-double NMDSCommand::calculateStep(vector< vector<double> >& prevGrad, vector< vector<double> >& grad, vector<double>& prevStress) {
- try {
- double newStep = step;
-
- //calc the cos theta
- double sumNum = 0.0;
- double sumDenom1 = 0.0;
- double sumDenom2 = 0.0;
- for (int i = 0; i < prevGrad.size(); i++) {
- for (int j = 0; j < prevGrad[i].size(); j++) {
- sumDenom1 += (grad[i][j] * grad[i][j]);
- sumDenom2 += (prevGrad[i][j] * prevGrad[i][j]);
- sumNum += (grad[i][j] * prevGrad[i][j]);
- }
- }
-
- double cosTheta = sumNum / (sqrt(sumDenom1) * sqrt(sumDenom2));
- cosTheta *= cosTheta;
-
- //calc angle factor
- double angle = pow(4.0, cosTheta);
-
- //calc 5 step ratio
- double currentStress = prevStress[prevStress.size()-1];
- double lastStress = prevStress[0];
- if (prevStress.size() > 1) { lastStress = prevStress[prevStress.size()-2]; }
- double fivePrevStress = prevStress[0];
- if (prevStress.size() > 5) { fivePrevStress = prevStress[prevStress.size()-6]; }
-
- double fiveStepRatio = min(1.0, (currentStress / fivePrevStress));
-
- //calc relaxation factor
- double relaxation = 1.3 / (1.0 + pow(fiveStepRatio, 5.0));
-
- //calc good luck factor
- double goodLuck = min(1.0, (currentStress / lastStress));
-
- //calc newStep
- cout << "\ncos = " << cosTheta << " step = " << step << " angle = " << angle << " relaxation = " << relaxation << " goodluck = " << goodLuck << endl;
- newStep = step * angle * relaxation * goodLuck;
-
- return newStep;
- }
- catch(exception& e) {
- m->errorOut(e, "NMDSCommand", "calculateStep");
- exit(1);
- }
-}
-//**********************************************************************************************************************
-vector< vector<double> > NMDSCommand::calculateNewConfiguration(double magnitude, vector< vector<double> >& axes, vector< vector<double> >& gradient) {
- try {
-
- vector< vector<double> > newAxes = axes;
-
- for (int i = 0; i < newAxes.size(); i++) {
-
- if (m->control_pressed) { return newAxes; }
-
- for (int j = 0; j < newAxes[i].size(); j++) {
- newAxes[i][j] = axes[i][j] + ((step / magnitude) * gradient[i][j]);
- }
- }
-
- return newAxes;
- }
- catch(exception& e) {
- m->errorOut(e, "NMDSCommand", "calculateNewConfiguration");
- exit(1);
- }
-}
-//**********************************************************************************************************************
-int NMDSCommand::output(string outputFileName, string stressFileName, vector< vector<double> >& config, vector<double>& stresses, vector<string>& names) {
+int NMDSCommand::output(vector< vector<double> >& config, vector<string>& names, ofstream& out) {
try {
- ofstream out, out2;
- m->openOutputFile(outputFileName, out);
- m->openOutputFile(stressFileName, out2);
-
- //output headers
- out << "group\t";
- for (int i = 0; i < dimension; i++) { out << "axis" << (i+1) << '\t'; }
- out << endl;
-
- out2 << "Iter\tStress" << endl;
-
- //output nmds file
- for (int i = 0; i < config[0].size(); i++) {
-
- if (m->control_pressed) { out.close(); out2.close(); return 0; }
+ for (int i = 0; i < names.size(); i++) {
out << names[i] << '\t';
out << endl;
}
- out.close();
- //output stress file
- for (int j = 0; j < stresses.size(); j++) {
- if (m->control_pressed) { out2.close(); return 0; }
+ out << endl << endl;
- out2 << (j+1) << '\t' << stresses[j] << endl;
- }
- out2.close();
-
-
return 0;
}
catch(exception& e) {
/*****************************************************************/
vector< vector<double> > NMDSCommand::readAxes(vector<string> names){
try {
- vector< vector<double> > axes;
-
ifstream in;
m->openInputFile(axesfile, in);
}else { done = true; }
}
- if (dimension > count) { m->mothurOut("You requested " + toString(dimension) + " axes, but your file only includes " + toString(count) + ". Using " + toString(count) + "."); m->mothurOutEndLine(); dimension = count; }
+ if (maxdim > count) {
+ m->mothurOut("You requested maxdim = " + toString(maxdim) + ", but your file only includes " + toString(count) + ". Using " + toString(count) + "."); m->mothurOutEndLine();
+ maxdim = count;
+ if (maxdim < mindim) { m->mothurOut("Also adjusting mindim to " + toString(maxdim-1) + "."); m->mothurOutEndLine(); }
+ }
+
+ vector< vector<double> > axes; axes.resize(maxdim);
+ for (int i = 0; i < axes.size(); i++) { axes[i].resize(names.size(), 0.0); }
+
+ map <string, vector<double> > orderedAxes;
+ map <string, vector<double> >::iterator it;
while (!in.eof()) {
in >> temp;
//only save the axis we want
- if (i < dimension) { thisGroupsAxes.push_back(temp); }
+ if (i < maxdim) { thisGroupsAxes.push_back(temp); }
}
- if (!ignore) { axes.push_back(thisGroupsAxes); }
+ if (!ignore) { orderedAxes[group] = thisGroupsAxes; }
m->gobble(in);
}
in.close();
-
+
//sanity check
- if (names.size() != axes.size()) { m->mothurOut("[ERROR]: your axes file does not match your distance file, aborting."); m->mothurOutEndLine(); m->control_pressed = true; }
+ if (names.size() != orderedAxes.size()) { m->mothurOut("[ERROR]: your axes file does not match your distance file, aborting."); m->mothurOutEndLine(); m->control_pressed = true; return axes; }
+
+ //put axes info in same order as distance file, just in case
+ for (int i = 0; i < names.size(); i++) {
+ it = orderedAxes.find(names[i]);
+
+ if (it != orderedAxes.end()) {
+ vector<double> thisGroupsAxes = it->second;
+
+ for (int j = 0; j < thisGroupsAxes.size(); j++) {
+ axes[j][i] = thisGroupsAxes[j];
+ }
+
+ }else { m->mothurOut("[ERROR]: your axes file does not match your distance file, aborting."); m->mothurOutEndLine(); m->control_pressed = true; return axes; }
+ }
return axes;
}
exit(1);
}
}
+/**********************************************************************************************************************
+ vector< vector<double> > NMDSCommand::calculateStressGradientVector(vector<seqDist>& eDists, vector<seqDist>& D, double rawStress, double stress, vector< vector<double> >& axes) {
+ try {
+ vector< vector<double> > gradient; gradient.resize(dimension);
+ for (int i = 0; i < gradient.size(); i++) { gradient[i].resize(axes[0].size(), 0.0); }
+
+ double sumDij = 0.0;
+ for (int i = 0; i < eDists.size(); i++) { sumDij += (eDists[i].dist * eDists[i].dist); }
+
+ for (int i = 0; i < eDists.size(); i++) {
+
+ for (int j = 0; j < dimension; j++) {
+
+ if (m->control_pressed) { return gradient; }
+
+ double firstTerm1 = (stress / rawStress) * (eDists[i].dist - D[i].dist);
+ double firstTerm2 = (stress / sumDij) * eDists[i].dist;
+ double firstTerm = firstTerm1 - firstTerm2;
+
+ float r = (dimension-1.0);
+ double temp = 1.0 / (pow(eDists[i].dist, r));
+ float absTemp = abs(axes[j][eDists[i].seq1] - axes[j][eDists[i].seq2]);
+ double secondTerm = pow(absTemp, r) * temp;
+
+ double sigNum = 1.0;
+ if ((axes[j][eDists[i].seq1] - axes[j][eDists[i].seq2]) == 0) { sigNum = 0.0; }
+ else if ((axes[j][eDists[i].seq1] - axes[j][eDists[i].seq2]) < 0) { sigNum = -1.0; }
+
+ double results = (firstTerm * secondTerm * sigNum);
+ cout << i << '\t' << j << '\t' << "results = " << results << endl;
+ gradient[j][eDists[i].seq1] += results;
+ gradient[j][eDists[i].seq2] -= results;
+ }
+ }
+
+ return gradient;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "NMDSCommand", "calculateStressGradientVector");
+ exit(1);
+ }
+ }
+ //**********************************************************************************************************************
+ double NMDSCommand::calculateMagnitude(vector< vector<double> >& gradient) {
+ try {
+ double magnitude = 0.0;
+
+ double sum = 0.0;
+ for (int i = 0; i < gradient.size(); i++) {
+ for (int j = 0; j < gradient[i].size(); j++) {
+ sum += (gradient[i][j] * gradient[i][j]);
+ }
+ }
+
+ magnitude = sqrt(((1.0/(float)gradient[0].size()) * sum));
+
+ return magnitude;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "NMDSCommand", "calculateMagnitude");
+ exit(1);
+ }
+ }
+ //**********************************************************************************************************************
+ //described in Kruskal paper page 121 + 122
+ double NMDSCommand::calculateStep(vector< vector<double> >& prevGrad, vector< vector<double> >& grad, vector<double>& prevStress) {
+ try {
+ double newStep = step;
+
+ //calc the cos theta
+ double sumNum = 0.0;
+ double sumDenom1 = 0.0;
+ double sumDenom2 = 0.0;
+ for (int i = 0; i < prevGrad.size(); i++) {
+ for (int j = 0; j < prevGrad[i].size(); j++) {
+ sumDenom1 += (grad[i][j] * grad[i][j]);
+ sumDenom2 += (prevGrad[i][j] * prevGrad[i][j]);
+ sumNum += (grad[i][j] * prevGrad[i][j]);
+ }
+ }
+
+ double cosTheta = sumNum / (sqrt(sumDenom1) * sqrt(sumDenom2));
+ cosTheta *= cosTheta;
+
+ //calc angle factor
+ double angle = pow(4.0, cosTheta);
+
+ //calc 5 step ratio
+ double currentStress = prevStress[prevStress.size()-1];
+ double lastStress = prevStress[0];
+ if (prevStress.size() > 1) { lastStress = prevStress[prevStress.size()-2]; }
+ double fivePrevStress = prevStress[0];
+ if (prevStress.size() > 5) { fivePrevStress = prevStress[prevStress.size()-6]; }
+
+ double fiveStepRatio = min(1.0, (currentStress / fivePrevStress));
+
+ //calc relaxation factor
+ double relaxation = 1.3 / (1.0 + pow(fiveStepRatio, 5.0));
+
+ //calc good luck factor
+ double goodLuck = min(1.0, (currentStress / lastStress));
+
+ //calc newStep
+ //cout << "\ncos = " << cosTheta << " step = " << step << " angle = " << angle << " relaxation = " << relaxation << " goodluck = " << goodLuck << endl;
+ newStep = step * angle * relaxation * goodLuck;
+
+ return newStep;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "NMDSCommand", "calculateStep");
+ exit(1);
+ }
+ }
+ //**********************************************************************************************************************
+ vector< vector<double> > NMDSCommand::calculateNewConfiguration(double magnitude, vector< vector<double> >& axes, vector< vector<double> >& gradient) {
+ try {
+
+ vector< vector<double> > newAxes = axes;
+
+ for (int i = 0; i < newAxes.size(); i++) {
+
+ if (m->control_pressed) { return newAxes; }
+
+ for (int j = 0; j < newAxes[i].size(); j++) {
+ newAxes[i][j] = axes[i][j] + ((step / magnitude) * gradient[i][j]);
+ }
+ }
+
+ return newAxes;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "NMDSCommand", "calculateNewConfiguration");
+ exit(1);
+ }
+ }*/
+/**********************************************************************************************************************
+ //adjust eDists so that it creates monotonically increasing series of succesive values that increase or stay the same, but never decrease
+ vector<seqDist> NMDSCommand::satisfyMonotonicity(vector<seqDist> eDists, vector<int> partitions) {
+ try {
+
+ //find averages of each partitions
+ vector<double> sums; sums.resize(partitions.size(), 0.0);
+ vector<int> sizes; sizes.resize(partitions.size(), 0);
+
+ for (int i = 0; i < partitions.size(); i++) {
+ //i is not the last one
+ int start = partitions[i];
+ int end;
+ if (i != (partitions.size()-1)) { end = partitions[i+1]; }
+ else{ end = eDists.size(); }
+
+ for (int j = start; j < end; j++) { sums[i] += eDists[j].dist; }
+
+ sizes[i] = (end - start);
+ }
+
+
+ vector<seqDist> D = eDists;
+
+ //i represents the "active block"
+ int i = 0;
+ while (i < partitions.size()) {
+
+ if (m->control_pressed) { return D; }
+
+ bool upActive = true;
+ bool upSatisfied = false;
+ bool downSatisfied = false;
+
+ //while we are not done with this block
+ while ((!upSatisfied) || (!downSatisfied)) {
+
+ if (upActive) {
+
+ //are we are upSatisfied? - is the average of the next block greater than mine?
+ if (i != (partitions.size()-1)) { //if we are the last guy then we are upsatisfied
+ if ((sums[i+1]/(float)sizes[i+1]) >= (sums[i]/(float)sizes[i])) {
+ upSatisfied = true;
+ upActive = false;
+ }else {
+ //find new weighted average
+ double newSum = sums[i] + sums[i+1];
+
+ //merge blocks - putting everything in i
+ sums[i] = newSum;
+ sizes[i] += sizes[i+1];
+ partitions[i] = partitions[i+1];
+
+ sums.erase(sums.begin()+(i+1));
+ sizes.erase(sizes.begin()+(i+1));
+ partitions.erase(partitions.begin()+(i+1));
+
+ upActive = false;
+ }
+ }else { upSatisfied = true; upActive = false; }
+
+ }else { //downActive
+
+ //are we are DownSatisfied? - is the average of the previous block less than mine?
+ if (i != 0) { //if we are the first guy then we are downSatisfied
+ if ((sums[i-1]/(float)sizes[i-1]) <= (sums[i]/(float)sizes[i])) {
+ downSatisfied = true;
+ upActive = true;
+ }else {
+ //find new weighted average
+ double newSum = sums[i] + sums[i-1];;
+
+ //merge blocks - putting everything in i-1
+ sums[i-1] = newSum;
+ sizes[i-1] += sizes[i];
+
+ sums.erase(sums.begin()+i);
+ sizes.erase(sizes.begin()+i);
+ partitions.erase(partitions.begin()+i);
+ i--;
+
+ upActive = true;
+ }
+ }else { downSatisfied = true; upActive = true; }
+ }
+ }
+
+ i++; // go to next block
+ }
+
+ //sanity check - for rounding errors
+ vector<double> averages; averages.resize(sums.size(), 0.0);
+ for (int i = 0; i < sums.size(); i++) { averages[i] = sums[i] / (float) sizes[i]; }
+ for (int i = 0; i < averages.size(); i++) { if (averages[i+1] < averages[i]) { averages[i+1] = averages[i]; } }
+
+ //fill D
+ int placeHolder = 0;
+ for (int i = 0; i < averages.size(); i++) {
+ for (int j = 0; j < sizes[i]; j++) {
+ D[placeHolder].dist = averages[i];
+ placeHolder++;
+ }
+ }
+
+ return D;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "NMDSCommand", "satisfyMonotonicity");
+ exit(1);
+ }
+ }*/
+
//**********************************************************************************************************************
projects / mothur.git / commitdiff