globaldata = GlobalData::getInstance();
abort = false;
Groups.clear();
-
+
//allow user to run help
if(option == "help") { help(); abort = true; }
}
if (globaldata->gTree.size() == 0) {//no trees were read
- mothurOut("You must execute the read.tree command, before you may execute the unifrac.weighted command."); mothurOutEndLine(); abort = true; }
+ m->mothurOut("You must execute the read.tree command, before you may execute the unifrac.weighted command."); m->mothurOutEndLine(); abort = true; }
//if the user changes the output directory command factory will send this info to us in the output parameter
outputDir = validParameter.validFile(parameters, "outputdir", false); if (outputDir == "not found"){
tmap = globaldata->gTreemap;
sumFile = outputDir + getSimpleName(globaldata->getTreeFile()) + ".wsummary";
openOutputFile(sumFile, outSum);
+ outputNames.push_back(sumFile);
util = new SharedUtil();
string s; //to make work with setgroups
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "UnifracWeightedCommand");
+ m->errorOut(e, "UnifracWeightedCommand", "UnifracWeightedCommand");
exit(1);
}
}
void UnifracWeightedCommand::help(){
try {
- mothurOut("The unifrac.weighted command can only be executed after a successful read.tree command.\n");
- mothurOut("The unifrac.weighted 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 2 valid groups.\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.weighted command should be in the following format: unifrac.weighted(groups=yourGroups, iters=yourIters).\n");
- mothurOut("Example unifrac.weighted(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");
- mothurOut("The unifrac.weighted command output two files: .weighted and .wsummary their descriptions are in the manual.\n");
- mothurOut("Note: No spaces between parameter labels (i.e. groups), '=' and parameters (i.e.yourGroups).\n\n");
+ m->mothurOut("The unifrac.weighted command can only be executed after a successful read.tree command.\n");
+ m->mothurOut("The unifrac.weighted command parameters are groups, iters, distance and random. No parameters are required.\n");
+ m->mothurOut("The groups parameter allows you to specify which of the groups in your groupfile you would like analyzed. You must enter at least 2 valid groups.\n");
+ m->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");
+ m->mothurOut("The distance parameter allows you to create a distance file from the results. The default is false.\n");
+ m->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");
+ m->mothurOut("The unifrac.weighted command should be in the following format: unifrac.weighted(groups=yourGroups, iters=yourIters).\n");
+ m->mothurOut("Example unifrac.weighted(groups=A-B-C, iters=500).\n");
+ m->mothurOut("The default value for groups is all the groups in your groupfile, and iters is 1000.\n");
+ m->mothurOut("The unifrac.weighted command output two files: .weighted and .wsummary their descriptions are in the manual.\n");
+ m->mothurOut("Note: No spaces between parameter labels (i.e. groups), '=' and parameters (i.e.yourGroups).\n\n");
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "help");
+ m->errorOut(e, "UnifracWeightedCommand", "help");
exit(1);
}
}
//get weighted scores for users trees
for (int i = 0; i < T.size(); i++) {
+
+ if (m->control_pressed) {
+ delete randT;
+ if (random) { delete reading; }
+ outSum.close();
+ for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); }
+ return 0;
+ }
+
counter = 0;
rScores.resize(numComp); //data[0] = weightedscore AB, data[1] = weightedscore AC...
uScores.resize(numComp); //data[0] = weightedscore AB, data[1] = weightedscore AC...
- if (random) { output = new ColumnFile(outputDir + getSimpleName(globaldata->getTreeFile()) + toString(i+1) + ".weighted", itersString); }
+ if (random) {
+ output = new ColumnFile(outputDir + getSimpleName(globaldata->getTreeFile()) + toString(i+1) + ".weighted", itersString);
+ outputNames.push_back(outputDir + getSimpleName(globaldata->getTreeFile()) + toString(i+1) + ".weighted");
+ }
userData = weighted->getValues(T[i]); //userData[0] = weightedscore
+ if (m->control_pressed) {
+ delete randT;
+ if (random) { delete reading; delete output; }
+ outSum.close();
+ for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); }
+ return 0;
+ }
+
+
//save users score
for (int s=0; s<numComp; s++) {
//add users score to vector of user scores
//create a random tree with same topology as T[i], but different labels
randT->assembleRandomUnifracTree(globaldata->Groups[r], globaldata->Groups[l]);
+
+ if (m->control_pressed) {
+ delete randT;
+ if (random) { delete reading; delete output; }
+ outSum.close();
+ for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); }
+ return 0;
+ }
+
+
//get wscore of random tree
randomData = weighted->getValues(randT, globaldata->Groups[r], globaldata->Groups[l]);
+ if (m->control_pressed) {
+ delete randT;
+ if (random) { delete reading; delete output; }
+ outSum.close();
+ for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); }
+ return 0;
+ }
+
//save scores
rScores[count].push_back(randomData[0]);
count++;
//so if you have 1000 random trees the index returned is 100
//then there are 900 trees with a score greater then you.
//giving you a signifigance of 0.900
- int index = findIndex(userData[f], f); if (index == -1) { mothurOut("error in UnifracWeightedCommand"); mothurOutEndLine(); exit(1); } //error code
+ int index = findIndex(userData[f], f); if (index == -1) { m->mothurOut("error in UnifracWeightedCommand"); m->mothurOutEndLine(); exit(1); } //error code
//the signifigance is the number of trees with the users score or higher
WScoreSig.push_back((iters-index)/(float)iters);
validScores.clear();
}
+
+ if (m->control_pressed) {
+ delete randT;
+ if (random) { delete reading; }
+ outSum.close();
+ for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); }
+ return 0;
+ }
+
//finish progress bar
if (random) { reading->finish(); delete reading; }
delete randT;
+ if (m->control_pressed) {
+ for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); }
+ return 0;
+ }
+
+ m->mothurOutEndLine();
+ m->mothurOut("Output File Names: "); m->mothurOutEndLine();
+ for (int i = 0; i < outputNames.size(); i++) { m->mothurOut(outputNames[i]); m->mothurOutEndLine(); }
+ m->mothurOutEndLine();
+
return 0;
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "execute");
+ m->errorOut(e, "UnifracWeightedCommand", "execute");
exit(1);
}
}
}
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "printWeightedFile");
+ m->errorOut(e, "UnifracWeightedCommand", "printWeightedFile");
exit(1);
}
}
try {
//column headers
outSum << "Tree#" << '\t' << "Groups" << '\t' << "WScore" << '\t' << "WSig" << endl;
- mothurOut("Tree#\tGroups\tWScore\tWSig"); mothurOutEndLine();
+ m->mothurOut("Tree#\tGroups\tWScore\tWSig"); m->mothurOutEndLine();
//format output
outSum.setf(ios::fixed, ios::floatfield); outSum.setf(ios::showpoint);
if (WScoreSig[count] > (1/(float)iters)) {
outSum << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << WScoreSig[count] << endl;
cout << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << WScoreSig[count] << endl;
- mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t" + toString(WScoreSig[count])); mothurOutEndLine();
+ m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t" + toString(WScoreSig[count])); m->mothurOutEndLine();
}else{
outSum << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << "<" << (1/float(iters)) << endl;
cout << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << "<" << (1/float(iters)) << endl;
- mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t<" + toString((1/float(iters)))); mothurOutEndLine();
+ m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t<" + toString((1/float(iters)))); m->mothurOutEndLine();
}
}else{
outSum << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << "0.00" << endl;
cout << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << "0.00" << endl;
- mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t0.00"); mothurOutEndLine();
+ m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t0.00"); m->mothurOutEndLine();
}
count++;
}
outSum.close();
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "printWSummaryFile");
+ m->errorOut(e, "UnifracWeightedCommand", "printWSummaryFile");
exit(1);
}
}
for (int i = 0; i < T.size(); i++) {
string phylipFileName = outputDir + getSimpleName(globaldata->getTreeFile()) + toString(i+1) + ".weighted.dist";
+ outputNames.push_back(phylipFileName);
ofstream out;
openOutputFile(phylipFileName, out);
//flip it so you can print it
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]);
- dists[l][r] = (1.0 - utreeScores[count]);
+ dists[r][l] = utreeScores[count];
+ dists[l][r] = utreeScores[count];
count++;
}
}
}
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "createPhylipFile");
+ m->errorOut(e, "UnifracWeightedCommand", "createPhylipFile");
exit(1);
}
}
return rScores[index].size();
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "findIndex");
+ m->errorOut(e, "UnifracWeightedCommand", "findIndex");
exit(1);
}
}
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "calculateFreqsCums");
+ m->errorOut(e, "UnifracWeightedCommand", "calculateFreqsCums");
exit(1);
}
}
projects / mothur.git / blobdiff