//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"){
outputDir = "";
- outputDir += hasPath(globaldata->inputFileName); //if user entered a file with a path then preserve it
+ outputDir += m->hasPath(globaldata->inputFileName); //if user entered a file with a path then preserve it
}
//check for optional parameter and set defaults
groups = validParameter.validFile(parameters, "groups", false);
if (groups == "not found") { groups = ""; }
else {
- splitAtDash(groups, Groups);
+ m->splitAtDash(groups, Groups);
globaldata->Groups = Groups;
}
convert(itersString, iters);
string temp = validParameter.validFile(parameters, "distance", false); if (temp == "not found") { temp = "false"; }
- phylip = isTrue(temp);
+ phylip = m->isTrue(temp);
- temp = validParameter.validFile(parameters, "random", false); if (temp == "not found") { temp = "true"; }
- random = isTrue(temp);
+ temp = validParameter.validFile(parameters, "random", false); if (temp == "not found") { temp = "F"; }
+ random = m->isTrue(temp);
if (!random) { iters = 0; } //turn off random calcs
if (abort == false) {
T = globaldata->gTree;
tmap = globaldata->gTreemap;
- sumFile = outputDir + getSimpleName(globaldata->getTreeFile()) + ".wsummary";
- openOutputFile(sumFile, outSum);
+ sumFile = outputDir + m->getSimpleName(globaldata->getTreeFile()) + ".wsummary";
+ m->openOutputFile(sumFile, outSum);
outputNames.push_back(sumFile);
util = new SharedUtil();
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 random parameter allows you to shut off the comparison to random trees. The default is false, meaning don't 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");
if (abort == true) { return 0; }
+ int start = time(NULL);
+
Progress* reading;
if (random) { reading = new Progress("Comparing to random:", iters); }
//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);
- outputNames.push_back(outputDir + getSimpleName(globaldata->getTreeFile()) + toString(i+1) + ".weighted");
+ output = new ColumnFile(outputDir + m->getSimpleName(globaldata->getTreeFile()) + toString(i+1) + ".weighted", itersString);
+ outputNames.push_back(outputDir + m->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++;
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->mothurOut("It took " + toString(time(NULL) - start) + " secs to run unifrac.weighted."); m->mothurOutEndLine();
+
m->mothurOutEndLine();
m->mothurOut("Output File Names: "); m->mothurOutEndLine();
for (int i = 0; i < outputNames.size(); i++) { m->mothurOut(outputNames[i]); m->mothurOutEndLine(); }
//for each tree
for (int i = 0; i < T.size(); i++) {
- string phylipFileName = outputDir + getSimpleName(globaldata->getTreeFile()) + toString(i+1) + ".weighted.dist";
+ string phylipFileName = outputDir + m->getSimpleName(globaldata->getTreeFile()) + toString(i+1) + ".weighted.dist";
outputNames.push_back(phylipFileName);
ofstream out;
- openOutputFile(phylipFileName, out);
+ m->openOutputFile(phylipFileName, out);
//output numSeqs
out << globaldata->Groups.size() << endl;
//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++;
}
}
projects / mothur.git / blobdiff