else {
//valid paramters for this command
- string Array[] = {"phylip","column","name","cutoff","precision","method","splitmethod","taxonomy","showabund","timing","hard","processors","outputdir","inputdir"};
+ string Array[] = {"phylip","column","name","cutoff","precision","method","splitmethod","taxonomy","taxlevel","showabund","timing","hard","processors","outputdir","inputdir"};
vector<string> myArray (Array, Array+(sizeof(Array)/sizeof(string)));
OptionParser parser(option);
temp = validParameter.validFile(parameters, "processors", false); if (temp == "not found"){ temp = "1"; }
convert(temp, processors);
- temp = validParameter.validFile(parameters, "cutoff", false);
- if (temp == "not found") { temp = "10"; }
+ splitmethod = validParameter.validFile(parameters, "splitmethod", false); if (splitmethod == "not found") { splitmethod = "distance"; }
+
+ temp = validParameter.validFile(parameters, "cutoff", false); if (temp == "not found") { temp = "10"; }
convert(temp, cutoff);
cutoff += (5 / (precision * 10.0));
- method = validParameter.validFile(parameters, "method", false); if (method == "not found") { method = "furthest"; }
+ temp = validParameter.validFile(parameters, "taxlevel", false); if (temp == "not found") { temp = "1"; }
+ convert(temp, taxLevelCutoff);
- splitmethod = validParameter.validFile(parameters, "splitmethod", false); if (splitmethod == "not found") { method = "distance"; }
+ method = validParameter.validFile(parameters, "method", false); if (method == "not found") { method = "furthest"; }
if ((method == "furthest") || (method == "nearest") || (method == "average")) { }
else { m->mothurOut("Not a valid clustering method. Valid clustering algorithms are furthest, nearest or average."); m->mothurOutEndLine(); abort = true; }
void ClusterSplitCommand::help(){
try {
- m->mothurOut("The cluster.split command parameter options are cutoff, splitcutoff, precision, method, splitmethod, phylip, column, name, showabund, timing. Phylip or column and name are required.\n");
+ m->mothurOut("The cluster.split command parameter options are phylip, column, name, cutoff, precision, method, splitmethod, taxonomy, taxlevel, showabund, timing, hard, processors. Phylip or column and name are required.\n");
m->mothurOut("The phylip and column parameter allow you to enter your distance file. \n");
m->mothurOut("The name parameter allows you to enter your name file and is required if your distance file is in column format. \n");
+ m->mothurOut("The cutoff parameter allow you to set the distance you want to cluster to, default is 10.0. \n");
+ m->mothurOut("The precision parameter allows you specify the precision of the precision of the distances outputted, default=100, meaning 2 decimal places. \n");
+ m->mothurOut("The method allows you to specify what clustering algorythm you want to use, default=furthest, option furthest, nearest, or average. \n");
+ m->mothurOut("The splitmethod parameter allows you to specify how you want to split your distance file before you cluster, default=distance, options distance or classify. \n");
+ m->mothurOut("The taxonomy parameter allows you to enter the taxonomy file for your sequences, this is only valid if you are using splitmethod=classify. Be sure your taxonomy file does not include the probability scores. \n");
+ m->mothurOut("The taxlevel parameter allows you to specify the taxonomy level you want to use to split the distance file, default=1. \n");
m->mothurOut("The cluster.split command should be in the following format: \n");
- m->mothurOut("cluster.split(column=youDistanceFile, name=yourNameFile, method=yourMethod, cutoff=yourCutoff, precision=yourPrecision) \n");
- m->mothurOut("Example: cluster.split(column=abrecovery.dist, name=abrecovery.names, method=furthest, cutoff=0.10, precision=1000, splitmethod=classify) \n");
+ m->mothurOut("cluster.split(column=youDistanceFile, name=yourNameFile, method=yourMethod, cutoff=yourCutoff, precision=yourPrecision, splitmethod=yourSplitmethod, taxonomy=yourTaxonomyfile, taxlevel=yourtaxlevel) \n");
+ m->mothurOut("Example: cluster.split(column=abrecovery.dist, name=abrecovery.names, method=furthest, cutoff=0.10, precision=1000, splitmethod=classify, taxonomy=abrecovery.silva.slv.taxonomy, taxlevel=5) \n");
}
catch(exception& e) {
time_t estart = time(NULL);
//split matrix into non-overlapping groups
- SplitMatrix* split = new SplitMatrix(distfile, namefile, taxFile, cutoff, splitmethod);
+ SplitMatrix* split;
+ if (splitmethod == "distance") { split = new SplitMatrix(distfile, namefile, taxFile, cutoff, splitmethod); }
+ else { split = new SplitMatrix(distfile, namefile, taxFile, taxLevelCutoff, splitmethod); }
+
split->split();
if (m->control_pressed) { delete split; return 0; }
outputNames.push_back(fileroot+ tag + ".sabund");
outputNames.push_back(fileroot+ tag + ".rabund");
outputNames.push_back(fileroot+ tag + ".list");
-
+
//read in singletons
ListVector* listSingle = NULL;
if (singleton != "none") {
it--;
}
}
-
+
//sort order
sort(orderFloat.begin(), orderFloat.end());
lastLabels.push_back(tempList.getLabel());
in.close();
}
-
+
ListVector* merged = NULL;
//for each label needed
}
//add in singletons
- for (int j = 0; j < listSingle->getNumBins(); j++) {
- merged->push_back(listSingle->get(j));
+ if (listSingle != NULL) {
+ for (int j = 0; j < listSingle->getNumBins(); j++) {
+ merged->push_back(listSingle->get(j));
+ }
}
-
+
//print to files
printData(merged);
oldList.print(listFile);
if (labels.count(toString(rndPreviousDist, length-1)) == 0) { labels.insert(toString(rndPreviousDist, length-1)); }
}
-
+
delete matrix; delete list; delete cluster; delete rabund;
listFile.close();
remove(thisNamefile.c_str());
}
-
+
return listFileNames;
}
projects / mothur.git / blobdiff