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", "furthest", "", "", "",false,false); parameters.push_back(pmethod);
+ 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", "", "F", "", "", "",false,false); parameters.push_back(phard);
+ 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);
helpString += "The cluster command parameter options are phylip, column, name, 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 += "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 furthest is assumed.\n\n";
+ helpString += "The acceptable cluster methods are furthest, nearest, average and weighted. If no method is provided then average is assumed.\n";
return helpString;
}
catch(exception& e) {
//allow user to run help
if(option == "help") { help(); abort = true; calledHelp = true; }
+ else if(option == "citation") { citation(); abort = true; calledHelp = true;}
else {
vector<string> myArray = setParameters();
//is there are current file available for either of these?
//give priority to column, then phylip
columnfile = m->getColumnFile();
- if (columnfile != "") { m->mothurOut("Using " + columnfile + " as input file for the column parameter."); m->mothurOutEndLine(); }
+ if (columnfile != "") { distfile = columnfile; format = "column"; m->mothurOut("Using " + columnfile + " as input file for the column parameter."); m->mothurOutEndLine(); }
else {
phylipfile = m->getPhylipFile();
- if (phylipfile != "") { m->mothurOut("Using " + phylipfile + " as input file for the phylip parameter."); m->mothurOutEndLine(); }
+ if (phylipfile != "") { distfile = phylipfile; format = "phylip"; m->mothurOut("Using " + phylipfile + " as input file for the phylip parameter."); m->mothurOutEndLine(); }
else {
m->mothurOut("No valid current files. You must provide a phylip or column file before you can use the cluster command."); m->mothurOutEndLine();
abort = true;
length = temp.length();
convert(temp, precision);
- temp = validParameter.validFile(parameters, "hard", false); if (temp == "not found") { temp = "F"; }
+ temp = validParameter.validFile(parameters, "hard", false); if (temp == "not found") { temp = "T"; }
hard = m->isTrue(temp);
temp = validParameter.validFile(parameters, "sim", false); if (temp == "not found") { temp = "F"; }
cutoff += (5 / (precision * 10.0));
method = validParameter.validFile(parameters, "method", false);
- if (method == "not found") { method = "furthest"; }
+ if (method == "not found") { method = "average"; }
if ((method == "furthest") || (method == "nearest") || (method == "average") || (method == "weighted")) { }
else { m->mothurOut("Not a valid clustering method. Valid clustering algorithms are furthest, nearest, average, and weighted."); m->mothurOutEndLine(); abort = true; }