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diff --git a/web/webqtl/heatmap/slink.py b/web/webqtl/heatmap/slink.py
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+# Copyright (C) University of Tennessee Health Science Center, Memphis, TN.
+#
+# This program is free software: you can redistribute it and/or modify it
+# under the terms of the GNU Affero General Public License
+# as published by the Free Software Foundation, either version 3 of the
+# License, or (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+# See the GNU Affero General Public License for more details.
+#
+# This program is available from Source Forge: at GeneNetwork Project
+# (sourceforge.net/projects/genenetwork/).
+#
+# Contact Drs. Robert W. Williams and Xiaodong Zhou (2010)
+# at rwilliams@uthsc.edu and xzhou15@uthsc.edu
+#
+#
+#
+# This module is used by GeneNetwork project (www.genenetwork.org)
+#
+# Created by GeneNetwork Core Team 2010/08/10
+#
+# Last updated by GeneNetwork Core Team 2010/10/20
+
+#--Only imported by correlationPage.py.
+#
+#Functions:
+#slink(lists) -- the only function called outside of this file.
+#nearest(lists,i,j) -- some sort of recursive function.
+#printarray(array,n) -- prints n elements of the given array
+#this is a myseterious piece of code in GN that Kev Adler and Rob Williams do not understand.
+#but is used in some way by the Traits Correlation function
+#Kev and Rob suspect that the d2 matrix below is unused 
+#We do not understand the signifance of "d" but Kev suspects it is unimportant
+#These comments by Kev and Rob: May 23, 2008
+
+d = [[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]]
+d2 = [[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]]
+
+def nearest(lists,i,j):
+	if type(i) == type(1) and type(j) == type(1):
+		return lists[i][j]
+	elif type(i) == type(1):
+		dist = 1e10
+		for itemj in j[:-1]:
+			d = nearest(lists,i,itemj)
+			if dist > d:
+				dist = d
+	elif type(j) == type(1):
+		dist = 1e10
+		for itemi in i[:-1]:
+			d = nearest(lists,itemi,j)
+			if dist > d:
+				dist = d
+	else:
+		dist = 1e10
+		for itemi in i[:-1]:
+			for itemj in j[:-1]:
+				d = nearest(lists,itemi,itemj)
+				if dist > d:
+					dist = d
+	return dist
+
+def printarray(array,n):
+	print "\n"
+	for i in range(n):
+		print array[i][:n]
+	print "\n"
+
+def slink(lists):
+	try:
+		if type(lists) != type([]) and type(lists) != type(()):
+			raise 'FormatError'
+		else:
+			size = len(lists)
+			for item in lists:
+				if type(item) != type([]) and type(item) != type(()):
+					raise 'FormatError'
+				else:
+					if len(item) != size:
+						raise 'LengthError'
+			for i in range(size):
+				if lists[i][i] != 0:
+					raise 'ValueError'
+				for j in range(0,i):
+					if lists[i][j] < 0:
+						raise 'ValueError'
+					if lists[i][j] != lists[j][i]:
+						raise 'MirrorError'
+	except 'FormatError':
+		print "the format of the list is incorrect!"
+		return []
+	except 'LengthError':
+		print "the list is not a square list!"
+		return []
+	except 'MirrorError':
+		print "the list is not symmetric!"
+		return []
+	except 'ValueError':
+		print "the distance is negative value!"
+		return []
+	except:
+		print "Unknown Error"
+		return [] 
+	listindex = range(size)
+	listindexcopy = range(size) 
+	listscopy = []
+	for i in range(size):
+		listscopy.append(lists[i][:])
+	initSize = size
+	candidate = []
+	while initSize >2:
+		mindist = 1e10
+		for i in range(initSize):
+			for j in range(i+1,initSize):
+				if listscopy[i][j] < mindist:
+					mindist =  listscopy[i][j]
+					candidate=[[i,j]]
+				elif listscopy[i][j] == mindist:
+					mindist =  listscopy[i][j]
+					candidate.append([i,j])
+				else:
+					pass
+		newmem = (listindexcopy[candidate[0][0]],listindexcopy[candidate[0][1]],mindist)
+		listindexcopy.pop(candidate[0][1])
+		listindexcopy[candidate[0][0]] = newmem
+		
+		initSize -= 1
+		for i in range(initSize):
+			for j in range(i+1,initSize):
+				listscopy[i][j] = nearest(lists,listindexcopy[i],listindexcopy[j])
+				listscopy[j][i] = listscopy[i][j]
+		#print listindexcopy
+		#printarray(listscopy,initSize)
+	listindexcopy.append(nearest(lists,listindexcopy[0],listindexcopy[1]))
+	return listindexcopy
+	
+	
+