1.18.0

[mothur.git] / clustersplitcommand.cpp

diff --git a/clustersplitcommand.cpp b/clustersplitcommand.cpp
index 6d908c61c94eb0917730479cf76a7f34cc102d15..a695a6a750eefc5620e83bb5b9a294b9921495fc 100644 (file)
--- a/clustersplitcommand.cpp
+++ b/clustersplitcommand.cpp
@@ -32,8 +32,8 @@ vector<string> ClusterSplitCommand::setParameters(){
                CommandParameter pprocessors("processors", "Number", "", "1", "", "", "",false,false); parameters.push_back(pprocessors);
                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 phard("hard", "Boolean", "", "F", "", "", "",false,false); parameters.push_back(phard);
+               CommandParameter pmethod("method", "Multiple", "furthest-nearest-average-weighted", "average", "", "", "",false,false); parameters.push_back(pmethod);
+               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);
                        
@@ -62,7 +62,7 @@ string ClusterSplitCommand::getHelpString(){
                helpString += "The name parameter allows you to enter your name file and is required if your distance file is in column format. \n";
                helpString += "The cutoff parameter allow you to set the distance you want to cluster to, default is 10.0. \n";
                helpString += "The precision parameter allows you specify the precision of the precision of the distances outputted, default=100, meaning 2 decimal places. \n";
-               helpString += "The method allows you to specify what clustering algorythm you want to use, default=furthest, option furthest, nearest, or average. \n";
+               helpString += "The method allows you to specify what clustering algorythm you want to use, default=average, option furthest, nearest, or average. \n";
                helpString += "The splitmethod parameter allows you to specify how you want to split your distance file before you cluster, default=distance, options distance, classify or fasta. \n";
                helpString += "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";
                helpString += "The taxlevel parameter allows you to specify the taxonomy level you want to use to split the distance file, default=1, meaning use the first taxon in each list. \n";
@@ -263,7 +263,7 @@ ClusterSplitCommand::ClusterSplitCommand(string option)  {
                        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, "large", false);                    if (temp == "not found") { temp = "F"; }
@@ -286,7 +286,7 @@ ClusterSplitCommand::ClusterSplitCommand(string option)  {
                        temp = validParameter.validFile(parameters, "taxlevel", false);         if (temp == "not found")  { temp = "1"; }
                        convert(temp, taxLevelCutoff); 
                        
-                       method = validParameter.validFile(parameters, "method", false);         if (method == "not found") { method = "furthest"; }
+                       method = validParameter.validFile(parameters, "method", false);         if (method == "not found") { method = "average"; }
                        
                        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; }