else {
//valid paramters for this command
- string Array[] = {"groups","iters"};
+ string Array[] = {"groups","iters","distance","random"};
vector<string> myArray (Array, Array+(sizeof(Array)/sizeof(string)));
OptionParser parser(option);
globaldata->Groups = Groups;
}
- itersString = validParameter.validFile(parameters, "iters", false); if (itersString == "not found") { itersString = "1000"; }
+ itersString = validParameter.validFile(parameters, "iters", false); if (itersString == "not found") { itersString = "1000"; }
convert(itersString, iters);
+ string temp = validParameter.validFile(parameters, "distance", false); if (temp == "not found") { temp = "false"; }
+ phylip = isTrue(temp);
+ temp = validParameter.validFile(parameters, "random", false); if (temp == "not found") { temp = "true"; }
+ random = isTrue(temp);
+
+ if (!random) { iters = 0; } //turn off random calcs
+
+ //if user selects distance = true and no groups it won't calc the pairwise
+ if ((phylip) && (Groups.size() == 0)) {
+ groups = "all";
+ splitAtDash(groups, Groups);
+ globaldata->Groups = Groups;
+ }
+
if (abort == false) {
T = globaldata->gTree;
tmap = globaldata->gTreemap;
void UnifracUnweightedCommand::help(){
try {
mothurOut("The unifrac.unweighted command can only be executed after a successful read.tree command.\n");
- mothurOut("The unifrac.unweighted command parameters are groups and iters. No parameters are required.\n");
+ mothurOut("The unifrac.unweighted command parameters are groups, iters, distance and random. No parameters are required.\n");
mothurOut("The groups parameter allows you to specify which of the groups in your groupfile you would like analyzed. You must enter at least 1 valid group.\n");
mothurOut("The group names are separated by dashes. The iters parameter allows you to specify how many random trees you would like compared to your tree.\n");
+ mothurOut("The distance parameter allows you to create a distance file from the results. The default is false.\n");
+ mothurOut("The random parameter allows you to shut off the comparison to random trees. The default is true, meaning compare your trees with randomly generated trees.\n");
mothurOut("The unifrac.unweighted command should be in the following format: unifrac.unweighted(groups=yourGroups, iters=yourIters).\n");
mothurOut("Example unifrac.unweighted(groups=A-B-C, iters=500).\n");
mothurOut("The default value for groups is all the groups in your groupfile, and iters is 1000.\n");
for (int i = 0; i < T.size(); i++) {
counter = 0;
- output = new ColumnFile(globaldata->getTreeFile() + toString(i+1) + ".unweighted", itersString);
+ if (random) { output = new ColumnFile(globaldata->getTreeFile() + toString(i+1) + ".unweighted", itersString); }
//get unweighted for users tree
rscoreFreq.resize(numComp);
for(int k = 0; k < numComp; k++) {
//saves users score
utreeScores[k].push_back(userData[k]);
-
+
+ //add users score to validscores
+ validScores[userData[k]] = userData[k];
}
//get unweighted scores for random trees
if (it2 != rscoreFreq[a].end()) { rscoreFreq[a][it->first] /= iters; rcumul-= it2->second; }
else { rscoreFreq[a][it->first] = 0.0000; } //no random trees with that score
}
- UWScoreSig[a].push_back(rCumul[a][userData[a]]);
+
+ if (random) { UWScoreSig[a].push_back(rCumul[a][userData[a]]); }
+ else { UWScoreSig[a].push_back(0.0); }
}
-
-
- printUnweightedFile();
+ //print output files
printUWSummaryFile(i);
+ if (random) { printUnweightedFile(); delete output; }
+ if (phylip) { createPhylipFile(i); }
- delete output;
rscoreFreq.clear();
rCumul.clear();
validScores.clear();
try {
vector<double> data;
vector<string> tags;
- tags.push_back("Score"); tags.push_back("RandFreq"); tags.push_back("RandCumul");
+ tags.push_back("Score");
+ tags.push_back("RandFreq"); tags.push_back("RandCumul");
+
for(int a = 0; a < numComp; a++) {
output->initFile(groupComb[a], tags);
//print each line
for (map<float,float>::iterator it = validScores.begin(); it != validScores.end(); it++) {
- data.push_back(it->first); data.push_back(rscoreFreq[a][it->first]); data.push_back(rCumul[a][it->first]);
+ data.push_back(it->first); data.push_back(rscoreFreq[a][it->first]); data.push_back(rCumul[a][it->first]);
output->output(data);
data.clear();
}
outSum << i+1 << '\t';
mothurOut(toString(i+1) + "\t");
- if (UWScoreSig[a][0] > (1/(float)iters)) {
- outSum << setprecision(6) << groupComb[a] << '\t' << utreeScores[a][0] << '\t' << setprecision(itersString.length()) << UWScoreSig[a][0] << endl;
- cout << setprecision(6) << groupComb[a] << '\t' << utreeScores[a][0] << '\t' << setprecision(itersString.length()) << UWScoreSig[a][0] << endl;
- mothurOutJustToLog(groupComb[a] + "\t" + toString(utreeScores[a][0]) + "\t" + toString(UWScoreSig[a][0])); mothurOutEndLine();
- }else {
- outSum << setprecision(6) << groupComb[a] << '\t' << utreeScores[a][0] << '\t' << setprecision(itersString.length()) << "<" << (1/float(iters)) << endl;
- cout << setprecision(6) << groupComb[a] << '\t' << utreeScores[a][0] << '\t' << setprecision(itersString.length()) << "<" << (1/float(iters)) << endl;
- mothurOutJustToLog(groupComb[a] + "\t" + toString(utreeScores[a][0]) + "\t<" + toString((1/float(iters)))); mothurOutEndLine();
+ if (random) {
+ if (UWScoreSig[a][0] > (1/(float)iters)) {
+ outSum << setprecision(6) << groupComb[a] << '\t' << utreeScores[a][0] << '\t' << setprecision(itersString.length()) << UWScoreSig[a][0] << endl;
+ cout << setprecision(6) << groupComb[a] << '\t' << utreeScores[a][0] << '\t' << setprecision(itersString.length()) << UWScoreSig[a][0] << endl;
+ mothurOutJustToLog(groupComb[a] + "\t" + toString(utreeScores[a][0]) + "\t" + toString(UWScoreSig[a][0])); mothurOutEndLine();
+ }else {
+ outSum << setprecision(6) << groupComb[a] << '\t' << utreeScores[a][0] << '\t' << setprecision(itersString.length()) << "<" << (1/float(iters)) << endl;
+ cout << setprecision(6) << groupComb[a] << '\t' << utreeScores[a][0] << '\t' << setprecision(itersString.length()) << "<" << (1/float(iters)) << endl;
+ mothurOutJustToLog(groupComb[a] + "\t" + toString(utreeScores[a][0]) + "\t<" + toString((1/float(iters)))); mothurOutEndLine();
+ }
+ }else{
+ outSum << setprecision(6) << groupComb[a] << '\t' << utreeScores[a][0] << '\t' << "0.00" << endl;
+ cout << setprecision(6) << groupComb[a] << '\t' << utreeScores[a][0] << '\t' << "0.00" << endl;
+ mothurOutJustToLog(groupComb[a] + "\t" + toString(utreeScores[a][0]) + "\t0.00"); mothurOutEndLine();
}
}
exit(1);
}
}
-
/***********************************************************/
+void UnifracUnweightedCommand::createPhylipFile(int i) {
+ try {
+ string phylipFileName = globaldata->getTreeFile() + toString(i+1) + ".unweighted.dist";
+ ofstream out;
+ openOutputFile(phylipFileName, out);
+
+ //output numSeqs
+ out << globaldata->Groups.size() << endl;
+
+ //make matrix with scores in it
+ vector< vector<float> > dists; dists.resize(globaldata->Groups.size());
+ for (int i = 0; i < globaldata->Groups.size(); i++) {
+ dists[i].resize(globaldata->Groups.size(), 0.0);
+ }
+
+ //flip it so you can print it
+ int count = 0;
+ for (int r=0; r<globaldata->Groups.size(); r++) {
+ for (int l = r+1; l < globaldata->Groups.size(); l++) {
+ dists[r][l] = (1.0 - utreeScores[count][0]);
+ dists[l][r] = (1.0 - utreeScores[count][0]);
+ count++;
+ }
+ }
+
+ //output to file
+ for (int r=0; r<globaldata->Groups.size(); r++) {
+ //output name
+ out << globaldata->Groups[r] << '\t';
+
+ //output distances
+ for (int l = 0; l < r; l++) { out << dists[r][l] << '\t'; }
+ out << endl;
+ }
+ out.close();
+ }
+ catch(exception& e) {
+ errorOut(e, "UnifracUnweightedCommand", "createPhylipFile");
+ exit(1);
+ }
+}
+/***********************************************************/
+
projects / mothur.git / blobdiff