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;
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;
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, false);
read->read(ct);
}else { read->read(nameMap); }
}
//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); }
}
m->openOutputFile(listFileName, listFile);
outputNames.push_back(listFileName); outputTypes["list"].push_back(listFileName);
-
+ list->printHeaders(listFile);
time_t estart = time(NULL);
float previousDist = 0.00000;