X-Git-Url: https://git.donarmstrong.com/?a=blobdiff_plain;f=clustersplitcommand.cpp;h=bdc8075342de2f484238c4810ee4da5babb0356c;hb=e150b0b0664caec517485ee6d69dcdade6dcae77;hp=6d908c61c94eb0917730479cf76a7f34cc102d15;hpb=ca9ac1d80c62f57270b0dcd49410ebe08a8aecd6;p=mothur.git

diff --git a/clustersplitcommand.cpp b/clustersplitcommand.cpp
index 6d908c6..bdc8075 100644
--- 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";
@@ -105,6 +105,7 @@ ClusterSplitCommand::ClusterSplitCommand(string option)  {
 		
 		//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();
@@ -263,7 +264,7 @@ 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 +287,7 @@ 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; }