//**********************************************************************************************************************
vector<string> ClusterCommand::setParameters(){
try {
- CommandParameter pphylip("phylip", "InputTypes", "", "", "PhylipColumn", "PhylipColumn", "none",false,false); parameters.push_back(pphylip);
- CommandParameter pname("name", "InputTypes", "", "", "NameCount", "none", "ColumnName",false,false); parameters.push_back(pname);
- CommandParameter pcount("count", "InputTypes", "", "", "NameCount", "none", "none",false,false); parameters.push_back(pcount);
- CommandParameter pcolumn("column", "InputTypes", "", "", "PhylipColumn", "PhylipColumn", "ColumnName",false,false); parameters.push_back(pcolumn);
- CommandParameter pcutoff("cutoff", "Number", "", "10", "", "", "",false,false); parameters.push_back(pcutoff);
- CommandParameter pprecision("precision", "Number", "", "100", "", "", "",false,false); parameters.push_back(pprecision);
- CommandParameter pmethod("method", "Multiple", "furthest-nearest-average-weighted", "average", "", "", "",false,false); parameters.push_back(pmethod);
- CommandParameter pshowabund("showabund", "Boolean", "", "T", "", "", "",false,false); parameters.push_back(pshowabund);
- CommandParameter ptiming("timing", "Boolean", "", "F", "", "", "",false,false); parameters.push_back(ptiming);
- CommandParameter psim("sim", "Boolean", "", "F", "", "", "",false,false); parameters.push_back(psim);
- CommandParameter phard("hard", "Boolean", "", "T", "", "", "",false,false); parameters.push_back(phard);
- CommandParameter pinputdir("inputdir", "String", "", "", "", "", "",false,false); parameters.push_back(pinputdir);
- CommandParameter poutputdir("outputdir", "String", "", "", "", "", "",false,false); parameters.push_back(poutputdir);
+ CommandParameter pphylip("phylip", "InputTypes", "", "", "PhylipColumn", "PhylipColumn", "none","list",false,false,true); parameters.push_back(pphylip);
+ CommandParameter pname("name", "InputTypes", "", "", "NameCount", "none", "ColumnName","rabund-sabund",false,false,true); parameters.push_back(pname);
+ CommandParameter pcount("count", "InputTypes", "", "", "NameCount", "none", "none","",false,false,true); parameters.push_back(pcount);
+ CommandParameter pcolumn("column", "InputTypes", "", "", "PhylipColumn", "PhylipColumn", "ColumnName","list",false,false,true); parameters.push_back(pcolumn);
+ CommandParameter pcutoff("cutoff", "Number", "", "10", "", "", "","",false,false,true); parameters.push_back(pcutoff);
+ CommandParameter pprecision("precision", "Number", "", "100", "", "", "","",false,false); parameters.push_back(pprecision);
+ CommandParameter pmethod("method", "Multiple", "furthest-nearest-average-weighted", "average", "", "", "","",false,false,true); parameters.push_back(pmethod);
+ CommandParameter pshowabund("showabund", "Boolean", "", "T", "", "", "","",false,false); parameters.push_back(pshowabund);
+ CommandParameter ptiming("timing", "Boolean", "", "F", "", "", "","",false,false); parameters.push_back(ptiming);
+ CommandParameter psim("sim", "Boolean", "", "F", "", "", "","",false,false); parameters.push_back(psim);
+ CommandParameter phard("hard", "Boolean", "", "T", "", "", "","",false,false); parameters.push_back(phard);
+ CommandParameter pinputdir("inputdir", "String", "", "", "", "", "","",false,false); parameters.push_back(pinputdir);
+ //CommandParameter padjust("adjust", "String", "", "F", "", "", "","",false,false); parameters.push_back(padjust);
+ CommandParameter poutputdir("outputdir", "String", "", "", "", "", "","",false,false); parameters.push_back(poutputdir);
vector<string> myArray;
for (int i = 0; i < parameters.size(); i++) { myArray.push_back(parameters[i].name); }
try {
string helpString = "";
helpString += "The cluster command parameter options are phylip, column, name, count, method, cuttoff, hard, precision, sim, showabund and timing. Phylip or column and name are required, unless you have a valid current file.\n";
- helpString += "The cluster command should be in the following format: \n";
+ //helpString += "The adjust parameter is used to handle missing distances. If you set a cutoff, adjust=f by default. If not, adjust=t by default. Adjust=f, means ignore missing distances and adjust cutoff as needed with the average neighbor method. Adjust=t, will treat missing distances as 1.0. You can also set the value the missing distances should be set to, adjust=0.5 would give missing distances a value of 0.5.\n";
+ helpString += "The cluster command should be in the following format: \n";
helpString += "cluster(method=yourMethod, cutoff=yourCutoff, precision=yourPrecision) \n";
helpString += "The acceptable cluster methods are furthest, nearest, average and weighted. If no method is provided then average is assumed.\n";
return helpString;
}
}
//**********************************************************************************************************************
-string ClusterCommand::getOutputFileNameTag(string type, string inputName=""){
- try {
- string outputFileName = "";
- map<string, vector<string> >::iterator it;
+string ClusterCommand::getOutputPattern(string type) {
+ try {
+ string pattern = "";
- //is this a type this command creates
- it = outputTypes.find(type);
- if (it == outputTypes.end()) { m->mothurOut("[ERROR]: this command doesn't create a " + type + " output file.\n"); }
- else {
- if (type == "list") { outputFileName = "list"; }
- else if (type == "rabund") { outputFileName = "rabund"; }
- else if (type == "sabund") { outputFileName = "sabund"; }
- else { m->mothurOut("[ERROR]: No definition for type " + type + " output file tag.\n"); m->control_pressed = true; }
- }
- return outputFileName;
- }
- catch(exception& e) {
- m->errorOut(e, "ClusterCommand", "getOutputFileNameTag");
- exit(1);
- }
+ if (type == "list") { pattern = "[filename],[clustertag],list-[filename],[clustertag],[tag2],list"; }
+ else if (type == "rabund") { pattern = "[filename],[clustertag],rabund"; }
+ else if (type == "sabund") { pattern = "[filename],[clustertag],sabund"; }
+ else { m->mothurOut("[ERROR]: No definition for type " + type + " output pattern.\n"); m->control_pressed = true; }
+
+ return pattern;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "ClusterCommand", "getOutputPattern");
+ exit(1);
+ }
}
//**********************************************************************************************************************
ClusterCommand::ClusterCommand(){
temp = validParameter.validFile(parameters, "sim", false); if (temp == "not found") { temp = "F"; }
sim = m->isTrue(temp);
+ //bool cutoffSet = false;
temp = validParameter.validFile(parameters, "cutoff", false);
if (temp == "not found") { temp = "10"; }
+ //else { cutoffSet = true; }
m->mothurConvert(temp, cutoff);
- cutoff += (5 / (precision * 10.0));
+ cutoff += (5 / (precision * 10.0));
+
+ //temp = validParameter.validFile(parameters, "adjust", false); if (temp == "not found") { temp = "F"; }
+ //if (m->isNumeric1(temp)) { m->mothurConvert(temp, adjust); }
+ //else if (m->isTrue(temp)) { adjust = 1.0; }
+ //else { adjust = -1.0; }
+ adjust=-1.0;
method = validParameter.validFile(parameters, "method", false);
if (method == "not found") { method = "average"; }
read->read(nameMap);
}else if (countfile != "") {
ct = new CountTable();
- ct->readTable(countfile);
+ ct->readTable(countfile, false);
read->read(ct);
- }
+ }else { read->read(nameMap); }
list = read->getListVector();
matrix = read->getDMatrix();
}
//create cluster
- if (method == "furthest") { cluster = new CompleteLinkage(rabund, list, matrix, cutoff, method); }
- else if(method == "nearest"){ cluster = new SingleLinkage(rabund, list, matrix, cutoff, method); }
- else if(method == "average"){ cluster = new AverageLinkage(rabund, list, matrix, cutoff, method); }
- else if(method == "weighted"){ cluster = new WeightedLinkage(rabund, list, matrix, cutoff, method); }
+ if (method == "furthest") { cluster = new CompleteLinkage(rabund, list, matrix, cutoff, method, adjust); }
+ else if(method == "nearest"){ cluster = new SingleLinkage(rabund, list, matrix, cutoff, method, adjust); }
+ else if(method == "average"){ cluster = new AverageLinkage(rabund, list, matrix, cutoff, method, adjust); }
+ else if(method == "weighted"){ cluster = new WeightedLinkage(rabund, list, matrix, cutoff, method, adjust); }
tag = cluster->getTag();
if (outputDir == "") { outputDir += m->hasPath(distfile); }
fileroot = outputDir + m->getRootName(m->getSimpleName(distfile));
- string sabundFileName = fileroot+ tag + "." + getOutputFileNameTag("sabund");
- string rabundFileName = fileroot+ tag + "." + getOutputFileNameTag("rabund");
- string listFileName = fileroot+ tag + ".";
- if (countfile != "") { listFileName += "unique_"; }
- listFileName += getOutputFileNameTag("list");
+ map<string, string> variables;
+ variables["[filename]"] = fileroot;
+ variables["[clustertag]"] = tag;
+ string sabundFileName = getOutputFileName("sabund", variables);
+ string rabundFileName = getOutputFileName("rabund", variables);
+ if (countfile != "") { variables["[tag2]"] = "unique_list"; }
+ string listFileName = getOutputFileName("list", variables);
if (countfile == "") {
m->openOutputFile(sabundFileName, sabundFile);
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