Ran reindent.py recursively on wqflask directory

1 files changed, 729 insertions, 730 deletions

diff --git a/wqflask/utility/webqtlUtil.py b/wqflask/utility/webqtlUtil.py
index 6af7f846..6409e781 100755
--- a/wqflask/utility/webqtlUtil.py
+++ b/wqflask/utility/webqtlUtil.py
@@ -90,741 +90,741 @@ PROGRESSBAR = HT.Image('/images/waitAnima2.gif', alt='checkblue',align="middle",
 #########################################
 
 def decodeEscape(str):
-	a = str
-	pattern = re.compile('(%[0-9A-Fa-f][0-9A-Fa-f])')
-	match = pattern.findall(a)
-	matched = []
-	for item in match:
-		if item not in matched:
-			a = a.replace(item, '%c' % eval("0x"+item[-2:]))
-		matched.append(item)
-	return a
-	
+    a = str
+    pattern = re.compile('(%[0-9A-Fa-f][0-9A-Fa-f])')
+    match = pattern.findall(a)
+    matched = []
+    for item in match:
+        if item not in matched:
+            a = a.replace(item, '%c' % eval("0x"+item[-2:]))
+        matched.append(item)
+    return a
+
 def exportData(hddn, tdata, NP = None):
-	for key in tdata.keys():
-		_val, _var, _N = tdata[key].val, tdata[key].var, tdata[key].N
-		if _val != None:
-			hddn[key] = _val
-			if _var != None:
-				hddn['V'+key] = _var
-			if NP and _N != None:
-				hddn['N'+key] = _N
-	
+    for key in tdata.keys():
+        _val, _var, _N = tdata[key].val, tdata[key].var, tdata[key].N
+        if _val != None:
+            hddn[key] = _val
+            if _var != None:
+                hddn['V'+key] = _var
+            if NP and _N != None:
+                hddn['N'+key] = _N
+
 def genShortStrainName(RISet='', input_strainName=''):
-	#aliasStrainDict = {'C57BL/6J':'B6','DBA/2J':'D2'}
-	strainName = input_strainName
-	if RISet != 'AXBXA':
-		if RISet == 'BXD300':
-			this_RISet = 'BXD'
-		elif RISet == 'BDF2-2005':
-			this_RISet = 'CASE05_'
-		else:
-			this_RISet = RISet
-		strainName = string.replace(strainName,this_RISet,'')
-		strainName = string.replace(strainName,'CASE','')
-		try:
-			strainName = "%02d" % int(strainName)
-		except:
-			pass
-	else:
-		strainName = string.replace(strainName,'AXB','A')
-		strainName = string.replace(strainName,'BXA','B')
-		try:
-			strainName = strainName[0] + "%02d" % int(strainName[1:])
-		except:
-			pass
-	return strainName
+    #aliasStrainDict = {'C57BL/6J':'B6','DBA/2J':'D2'}
+    strainName = input_strainName
+    if RISet != 'AXBXA':
+        if RISet == 'BXD300':
+            this_RISet = 'BXD'
+        elif RISet == 'BDF2-2005':
+            this_RISet = 'CASE05_'
+        else:
+            this_RISet = RISet
+        strainName = string.replace(strainName,this_RISet,'')
+        strainName = string.replace(strainName,'CASE','')
+        try:
+            strainName = "%02d" % int(strainName)
+        except:
+            pass
+    else:
+        strainName = string.replace(strainName,'AXB','A')
+        strainName = string.replace(strainName,'BXA','B')
+        try:
+            strainName = strainName[0] + "%02d" % int(strainName[1:])
+        except:
+            pass
+    return strainName
 
 def toInt(in_str):
-	"Converts an arbitrary string to an unsigned integer"
-	start = -1
-	end = -1
-	for i, char in enumerate(in_str):
-		if char >= '0' and char <= '9':
-			if start < 0:
-				start = i
-			end = i+1
-		else:
-			if start >= 0:
-				break
-	if start < end:
-		return int(in_str[start:end])
-	else:
-		return  -1
+    "Converts an arbitrary string to an unsigned integer"
+    start = -1
+    end = -1
+    for i, char in enumerate(in_str):
+        if char >= '0' and char <= '9':
+            if start < 0:
+                start = i
+            end = i+1
+        else:
+            if start >= 0:
+                break
+    if start < end:
+        return int(in_str[start:end])
+    else:
+        return  -1
 
 def transpose(m):
-	'transpose a matrix'
-	n = len(m)
-	return [[m[j][i] for i in range(len(m[0])) for j in range(n)][k*n:k*n+n] for k in range(len(m[0]))]
+    'transpose a matrix'
+    n = len(m)
+    return [[m[j][i] for i in range(len(m[0])) for j in range(n)][k*n:k*n+n] for k in range(len(m[0]))]
 
 def asymTranspose(m):
-	'transpose a matrix'
-	t = max(map(len, m))
-	n = len(m)
-	m2 = [["-"]]*n
-	for i in range(n):
-		m2[i] = m[i] + [""]*(t- len(m[i]))
-	return [[m2[j][i] for i in range(len(m2[0])) for j in range(n)][k*n:k*n+n] for k in range(len(m2[0]))]
+    'transpose a matrix'
+    t = max(map(len, m))
+    n = len(m)
+    m2 = [["-"]]*n
+    for i in range(n):
+        m2[i] = m[i] + [""]*(t- len(m[i]))
+    return [[m2[j][i] for i in range(len(m2[0])) for j in range(n)][k*n:k*n+n] for k in range(len(m2[0]))]
 
 def genRandStr(prefix = "", length=8, chars=string.letters+string.digits):
-	from random import choice
-	_str = prefix[:]
-	for i in range(length):
-		_str += choice(chars)
-	return _str
+    from random import choice
+    _str = prefix[:]
+    for i in range(length):
+        _str += choice(chars)
+    return _str
 
 def generate_session():
-	import sha
-	return sha.new(str(time.time())).hexdigest()
+    import sha
+    return sha.new(str(time.time())).hexdigest()
 
 def cvt2Dict(x):
-	tmp = {}
-	for key in x.keys():
-		tmp[key] = x[key]
-	return tmp
+    tmp = {}
+    for key in x.keys():
+        tmp[key] = x[key]
+    return tmp
 
 def dump_session(session_obj, filename):
-	"It seems mod python can only cPickle most basic data type"
-	import cPickle
-	session_file = open(filename, 'wb')
-	#try:
-	#	pass
-	#except:
-	#	pass
-	cPickle.dump(session_obj, session_file)
-	session_file.close()
-	
+    "It seems mod python can only cPickle most basic data type"
+    import cPickle
+    session_file = open(filename, 'wb')
+    #try:
+    #       pass
+    #except:
+    #       pass
+    cPickle.dump(session_obj, session_file)
+    session_file.close()
+
 def StringAsFloat(str):
-	'Converts string to float but catches any exception and returns None'
-	try:
-		return float(str)
-	except:
-		return None
-	
+    'Converts string to float but catches any exception and returns None'
+    try:
+        return float(str)
+    except:
+        return None
+
 def IntAsFloat(str):
-	'Converts string to Int but catches any exception and returns None'
-	try:
-		return int(str)
-	except:
-		return None
-		
+    'Converts string to Int but catches any exception and returns None'
+    try:
+        return int(str)
+    except:
+        return None
+
 def FloatAsFloat(flt):
-	'Converts float to string but catches any exception and returns None'
-	try:
-		return float("%2.3f" % flt)
-	except:
-		return None
+    'Converts float to string but catches any exception and returns None'
+    try:
+        return float("%2.3f" % flt)
+    except:
+        return None
 
 def RemoveZero(flt):
-	'Converts string to float but catches any exception and returns None'
-	try:
-		if abs(flt) < 1e-6:
-			return None
-		else:
-			return flt
-	except:
-		return None
+    'Converts string to float but catches any exception and returns None'
+    try:
+        if abs(flt) < 1e-6:
+            return None
+        else:
+            return flt
+    except:
+        return None
 
 
 def SciFloat(d):
-	'Converts string to float but catches any exception and returns None'
+    'Converts string to float but catches any exception and returns None'
 
-	try:
-		if abs(d) <= 1.0e-4:	
-			return "%1.2e" % d
-		else:
-			return "%1.5f" % d
-	except:
-		return None
+    try:
+        if abs(d) <= 1.0e-4:
+            return "%1.2e" % d
+        else:
+            return "%1.5f" % d
+    except:
+        return None
 
 ###To be removed
 def FloatList2String(lst):
-	'Converts float list to string but catches any exception and returns None'
-	tt=''
-	try:
-		for item in lst:
-			if item == None:
-				tt += 'X '
-			else:
-				tt += '%f ' % item
-		return tt
-	except:
-		return ""
+    'Converts float list to string but catches any exception and returns None'
+    tt=''
+    try:
+        for item in lst:
+            if item == None:
+                tt += 'X '
+            else:
+                tt += '%f ' % item
+        return tt
+    except:
+        return ""
 
 def ListNotNull(lst):
-	'Determine if the elements in a list are all null'
-	for item in lst:
-		if item is not None:
-			return 1
-	return None
-	
+    'Determine if the elements in a list are all null'
+    for item in lst:
+        if item is not None:
+            return 1
+    return None
+
 ###To be removed
 def FileDataProcess(str):
-	'Remove the description text from the input file if theres any'
-	i=0
-	while i<len(str):
-		if str[i]<'\x7f' and str[i]>'\x20':
-			break
-		else:
-			i+=1
-	str=str[i:]
-	str=string.join(string.split(str,'\000'),'')
-	i=string.find(str,"*****")
-	if i>-1:
-		return str[i+5:]
-	else:
-		return str
+    'Remove the description text from the input file if theres any'
+    i=0
+    while i<len(str):
+        if str[i]<'\x7f' and str[i]>'\x20':
+            break
+        else:
+            i+=1
+    str=str[i:]
+    str=string.join(string.split(str,'\000'),'')
+    i=string.find(str,"*****")
+    if i>-1:
+        return str[i+5:]
+    else:
+        return str
 
 def rank(a,lst,offset=0):
-	"""Calculate the integer rank of a number in an array, can be used to calculate p-value"""
-	n = len(lst)
-	if n == 2:
-		if a <lst[0]:
-			return offset
-		elif a > lst[1]: 
-			return offset + 2 	
-		else:
-			return offset +1	
-	elif n == 1:
-		if a <lst[0]:
-			return offset
-		else:
-			return offset +1
-	elif n== 0:
-		return offset
-	else:
-		mid = n/2
-		if a < lst[mid]:
-			return rank(a,lst[:mid-1],offset)
-		else:
-			return rank(a,lst[mid:],offset+mid)
+    """Calculate the integer rank of a number in an array, can be used to calculate p-value"""
+    n = len(lst)
+    if n == 2:
+        if a <lst[0]:
+            return offset
+        elif a > lst[1]:
+            return offset + 2
+        else:
+            return offset +1
+    elif n == 1:
+        if a <lst[0]:
+            return offset
+        else:
+            return offset +1
+    elif n== 0:
+        return offset
+    else:
+        mid = n/2
+        if a < lst[mid]:
+            return rank(a,lst[:mid-1],offset)
+        else:
+            return rank(a,lst[mid:],offset+mid)
 
 def cmpScanResult(A,B):
-	try:
-		if A.LRS > B.LRS:
-			return 1
-		elif A.LRS == B.LRS:
-			return 0
-		else:
-			return -1	
-	except:
-		return 0
-
-	
+    try:
+        if A.LRS > B.LRS:
+            return 1
+        elif A.LRS == B.LRS:
+            return 0
+        else:
+            return -1
+    except:
+        return 0
+
+
 def cmpScanResult2(A,B):
-	try:
-		if A.LRS < B.LRS:
-			return 1
-		elif A.LRS == B.LRS:
-			return 0
-		else:
-			return -1	
-	except:
-		return 0
+    try:
+        if A.LRS < B.LRS:
+            return 1
+        elif A.LRS == B.LRS:
+            return 0
+        else:
+            return -1
+    except:
+        return 0
 
 def cmpOrder(A,B):
-	try:
-		if A[1] < B[1]:
-			return -1
-		elif A[1] == B[1]:
-			return 0
-		else:
-			return 1
-	except:
-		return 0
+    try:
+        if A[1] < B[1]:
+            return -1
+        elif A[1] == B[1]:
+            return 0
+        else:
+            return 1
+    except:
+        return 0
 
 def cmpOrder2(A,B):
-	try:
-		if A[-1] < B[-1]:
-			return -1
-		elif A[-1] == B[-1]:
-			return 0
-		else:
-			return 1	
-	except:
-		return 0
+    try:
+        if A[-1] < B[-1]:
+            return -1
+        elif A[-1] == B[-1]:
+            return 0
+        else:
+            return 1
+    except:
+        return 0
 
 
 
 
 def calRank(xVals, yVals, N): ###  Zach Sloan, February 4 2010
-	""" 
-	Returns a ranked set of X and Y values. These are used when generating
-	a Spearman scatterplot. Bear in mind that this sets values equal to each 
-	other as the same rank.
-	"""
-	XX = []
-	YY = []
-	X = [0]*len(xVals)
-	Y = [0]*len(yVals)
-	j = 0
-	
-	for i in range(len(xVals)):
-		
-		if xVals[i] != None and yVals[i] != None:
-			XX.append((j, xVals[i]))
-			YY.append((j, yVals[i]))
-			j = j + 1
-		
-	NN = len(XX)
-	
-	XX.sort(cmpOrder2)
-	YY.sort(cmpOrder2)
-
-	j = 1
-	rank = 0.0
-	
-	while j < NN:
-
-		if XX[j][1] != XX[j-1][1]:	
-			X[XX[j-1][0]] = j
-			j = j+1 
-		
-		else:
-			jt = j+1
-			ji = j
-			for jt in range(j+1, NN):
-				 if (XX[jt][1] != XX[j-1][1]):
-				 	break
-			rank = 0.5*(j+jt)
-			for ji in range(j-1, jt):
-				 X[XX[ji][0]] = rank
-			if (jt == NN-1):
-				if (XX[jt][1] == XX[j-1][1]):
-					X[XX[NN-1][0]] = rank
-			j = jt+1
-				 	
-	if j == NN:
-		if X[XX[NN-1][0]] == 0:
-			X[XX[NN-1][0]] = NN
-		
-	j = 1
-	rank = 0.0
-
-	while j < NN:
-
-		if YY[j][1] != YY[j-1][1]:	
-			Y[YY[j-1][0]] = j
-			j = j+1
-		else:
-			jt = j+1
-			ji = j
-			for jt in range(j+1, NN):
-				 if (YY[jt][1] != YY[j-1][1]):
-				 	break
-			rank = 0.5*(j+jt)
-			for ji in range(j-1, jt):
-				 Y[YY[ji][0]] = rank
-			if (jt == NN-1):
-				if (YY[jt][1] == YY[j-1][1]):
-					Y[YY[NN-1][0]] = rank
-			j = jt+1
-			
-	if j == NN:
-		if Y[YY[NN-1][0]] == 0:
-			Y[YY[NN-1][0]] = NN
-		
-	return (X,Y)	 
+    """
+    Returns a ranked set of X and Y values. These are used when generating
+    a Spearman scatterplot. Bear in mind that this sets values equal to each
+    other as the same rank.
+    """
+    XX = []
+    YY = []
+    X = [0]*len(xVals)
+    Y = [0]*len(yVals)
+    j = 0
+
+    for i in range(len(xVals)):
+
+        if xVals[i] != None and yVals[i] != None:
+            XX.append((j, xVals[i]))
+            YY.append((j, yVals[i]))
+            j = j + 1
+
+    NN = len(XX)
+
+    XX.sort(cmpOrder2)
+    YY.sort(cmpOrder2)
+
+    j = 1
+    rank = 0.0
+
+    while j < NN:
+
+        if XX[j][1] != XX[j-1][1]:
+            X[XX[j-1][0]] = j
+            j = j+1
+
+        else:
+            jt = j+1
+            ji = j
+            for jt in range(j+1, NN):
+                if (XX[jt][1] != XX[j-1][1]):
+                    break
+            rank = 0.5*(j+jt)
+            for ji in range(j-1, jt):
+                X[XX[ji][0]] = rank
+            if (jt == NN-1):
+                if (XX[jt][1] == XX[j-1][1]):
+                    X[XX[NN-1][0]] = rank
+            j = jt+1
+
+    if j == NN:
+        if X[XX[NN-1][0]] == 0:
+            X[XX[NN-1][0]] = NN
+
+    j = 1
+    rank = 0.0
+
+    while j < NN:
+
+        if YY[j][1] != YY[j-1][1]:
+            Y[YY[j-1][0]] = j
+            j = j+1
+        else:
+            jt = j+1
+            ji = j
+            for jt in range(j+1, NN):
+                if (YY[jt][1] != YY[j-1][1]):
+                    break
+            rank = 0.5*(j+jt)
+            for ji in range(j-1, jt):
+                Y[YY[ji][0]] = rank
+            if (jt == NN-1):
+                if (YY[jt][1] == YY[j-1][1]):
+                    Y[YY[NN-1][0]] = rank
+            j = jt+1
+
+    if j == NN:
+        if Y[YY[NN-1][0]] == 0:
+            Y[YY[NN-1][0]] = NN
+
+    return (X,Y)
 
 def calCorrelationRank(xVals,yVals,N):
-	"""
-	Calculated Spearman Ranked Correlation. The algorithm works
-	by setting all tied ranks to the average of those ranks (for 
-	example, if ranks 5-10 all have the same value, each will be set
-	to rank 7.5).
-	"""
-	
-	XX = []
-	YY = []
-	j = 0
-	
-	for i in range(len(xVals)):
-		if xVals[i]!= None and yVals[i]!= None:
-			XX.append((j,xVals[i]))
-			YY.append((j,yVals[i]))
-			j = j+1
-			
-	NN = len(XX)
-	if NN <6:
-		return (0.0,NN)
-	XX.sort(cmpOrder2)
-	YY.sort(cmpOrder2)
-	X = [0]*NN
-	Y = [0]*NN
-	
-	j = 1
-	rank = 0.0
-	t = 0.0
-	sx = 0.0
-	
-	while j < NN:
-
-		if XX[j][1] != XX[j-1][1]:	
-			X[XX[j-1][0]] = j
-			j = j+1 
-		
-		else:
-			jt = j+1
-			ji = j
-			for jt in range(j+1, NN):
-				 if (XX[jt][1] != XX[j-1][1]):
-				 	break
-			rank = 0.5*(j+jt)
-			for ji in range(j-1, jt):
-				 X[XX[ji][0]] = rank
-			t = jt-j
-			sx = sx + (t*t*t-t)
-			if (jt == NN-1):
-				if (XX[jt][1] == XX[j-1][1]):
-					X[XX[NN-1][0]] = rank
-			j = jt+1
-				 	
-	if j == NN:
-		if X[XX[NN-1][0]] == 0:
-			X[XX[NN-1][0]] = NN
-		
-	j = 1
-	rank = 0.0
-	t = 0.0
-	sy = 0.0
-
-	while j < NN:
-
-		if YY[j][1] != YY[j-1][1]:	
-			Y[YY[j-1][0]] = j
-			j = j+1
-		else:
-			jt = j+1
-			ji = j
-			for jt in range(j+1, NN):
-				 if (YY[jt][1] != YY[j-1][1]):
-				 	break
-			rank = 0.5*(j+jt)
-			for ji in range(j-1, jt):
-				 Y[YY[ji][0]] = rank
-			t = jt - j
-			sy = sy + (t*t*t-t)
-			if (jt == NN-1):
-				if (YY[jt][1] == YY[j-1][1]):
-					Y[YY[NN-1][0]] = rank
-			j = jt+1
-			
-	if j == NN:
-		if Y[YY[NN-1][0]] == 0:
-			Y[YY[NN-1][0]] = NN
-				
-	D = 0.0
-	
-	for i in range(NN):
-		D += (X[i]-Y[i])*(X[i]-Y[i])
-		
-	fac = (1.0 -sx/(NN*NN*NN-NN))*(1.0-sy/(NN*NN*NN-NN))
-	
-	return ((1-(6.0/(NN*NN*NN-NN))*(D+(sx+sy)/12.0))/math.sqrt(fac),NN)
-	
-	
+    """
+    Calculated Spearman Ranked Correlation. The algorithm works
+    by setting all tied ranks to the average of those ranks (for
+    example, if ranks 5-10 all have the same value, each will be set
+    to rank 7.5).
+    """
+
+    XX = []
+    YY = []
+    j = 0
+
+    for i in range(len(xVals)):
+        if xVals[i]!= None and yVals[i]!= None:
+            XX.append((j,xVals[i]))
+            YY.append((j,yVals[i]))
+            j = j+1
+
+    NN = len(XX)
+    if NN <6:
+        return (0.0,NN)
+    XX.sort(cmpOrder2)
+    YY.sort(cmpOrder2)
+    X = [0]*NN
+    Y = [0]*NN
+
+    j = 1
+    rank = 0.0
+    t = 0.0
+    sx = 0.0
+
+    while j < NN:
+
+        if XX[j][1] != XX[j-1][1]:
+            X[XX[j-1][0]] = j
+            j = j+1
+
+        else:
+            jt = j+1
+            ji = j
+            for jt in range(j+1, NN):
+                if (XX[jt][1] != XX[j-1][1]):
+                    break
+            rank = 0.5*(j+jt)
+            for ji in range(j-1, jt):
+                X[XX[ji][0]] = rank
+            t = jt-j
+            sx = sx + (t*t*t-t)
+            if (jt == NN-1):
+                if (XX[jt][1] == XX[j-1][1]):
+                    X[XX[NN-1][0]] = rank
+            j = jt+1
+
+    if j == NN:
+        if X[XX[NN-1][0]] == 0:
+            X[XX[NN-1][0]] = NN
+
+    j = 1
+    rank = 0.0
+    t = 0.0
+    sy = 0.0
+
+    while j < NN:
+
+        if YY[j][1] != YY[j-1][1]:
+            Y[YY[j-1][0]] = j
+            j = j+1
+        else:
+            jt = j+1
+            ji = j
+            for jt in range(j+1, NN):
+                if (YY[jt][1] != YY[j-1][1]):
+                    break
+            rank = 0.5*(j+jt)
+            for ji in range(j-1, jt):
+                Y[YY[ji][0]] = rank
+            t = jt - j
+            sy = sy + (t*t*t-t)
+            if (jt == NN-1):
+                if (YY[jt][1] == YY[j-1][1]):
+                    Y[YY[NN-1][0]] = rank
+            j = jt+1
+
+    if j == NN:
+        if Y[YY[NN-1][0]] == 0:
+            Y[YY[NN-1][0]] = NN
+
+    D = 0.0
+
+    for i in range(NN):
+        D += (X[i]-Y[i])*(X[i]-Y[i])
+
+    fac = (1.0 -sx/(NN*NN*NN-NN))*(1.0-sy/(NN*NN*NN-NN))
+
+    return ((1-(6.0/(NN*NN*NN-NN))*(D+(sx+sy)/12.0))/math.sqrt(fac),NN)
+
+
 def calCorrelationRankText(dbdata,userdata,N): ### dcrowell = David Crowell, July 2008
-        """Calculates correlation ranks with data formatted from the text file.
-        dbdata, userdata are lists of strings.  N is an int.  Returns a float.
-        Used by correlationPage"""
-        XX = []
-        YY = []
-        j = 0
-        for i in range(N):
-                if (dbdata[i]!= None and userdata[i]!=None) and (dbdata[i]!= 'None' and userdata[i]!='None'):
-                        XX.append((j,float(dbdata[i])))
-                        YY.append((j,float(userdata[i])))
-                        j += 1
-	NN = len(XX)
-	if NN <6:
-		return (0.0,NN)
-	XX.sort(cmpOrder2)
-	YY.sort(cmpOrder2)
-	X = [0]*NN
-	Y = [0]*NN
-	
-	j = 1
-	rank = 0.0
-	t = 0.0
-	sx = 0.0
-	
-	while j < NN:
-
-		if XX[j][1] != XX[j-1][1]:	
-			X[XX[j-1][0]] = j
-			j = j+1 
-		
-		else:
-			jt = j+1
-			ji = j
-			for jt in range(j+1, NN):
-				 if (XX[jt][1] != XX[j-1][1]):
-				 	break
-			rank = 0.5*(j+jt)
-			for ji in range(j-1, jt):
-				 X[XX[ji][0]] = rank
-			t = jt-j
-			sx = sx + (t*t*t-t)
-			if (jt == NN-1):
-				if (XX[jt][1] == XX[j-1][1]):
-					X[XX[NN-1][0]] = rank
-			j = jt+1
-				 	
-	if j == NN:
-		if X[XX[NN-1][0]] == 0:
-			X[XX[NN-1][0]] = NN
-		
-	j = 1
-	rank = 0.0
-	t = 0.0
-	sy = 0.0
-
-	while j < NN:
-
-		if YY[j][1] != YY[j-1][1]:	
-			Y[YY[j-1][0]] = j
-			j = j+1
-		else:
-			jt = j+1
-			ji = j
-			for jt in range(j+1, NN):
-				 if (YY[jt][1] != YY[j-1][1]):
-				 	break
-			rank = 0.5*(j+jt)
-			for ji in range(j-1, jt):
-				 Y[YY[ji][0]] = rank
-			t = jt - j
-			sy = sy + (t*t*t-t)
-			if (jt == NN-1):
-				if (YY[jt][1] == YY[j-1][1]):
-					Y[YY[NN-1][0]] = rank
-			j = jt+1
-			
-	if j == NN:
-		if Y[YY[NN-1][0]] == 0:
-			Y[YY[NN-1][0]] = NN
-				
-	D = 0.0
-	
-	for i in range(NN):
-		D += (X[i]-Y[i])*(X[i]-Y[i])
-		
-	fac = (1.0 -sx/(NN*NN*NN-NN))*(1.0-sy/(NN*NN*NN-NN))
-	
-	return ((1-(6.0/(NN*NN*NN-NN))*(D+(sx+sy)/12.0))/math.sqrt(fac),NN)
+    """Calculates correlation ranks with data formatted from the text file.
+    dbdata, userdata are lists of strings.  N is an int.  Returns a float.
+    Used by correlationPage"""
+    XX = []
+    YY = []
+    j = 0
+    for i in range(N):
+        if (dbdata[i]!= None and userdata[i]!=None) and (dbdata[i]!= 'None' and userdata[i]!='None'):
+            XX.append((j,float(dbdata[i])))
+            YY.append((j,float(userdata[i])))
+            j += 1
+    NN = len(XX)
+    if NN <6:
+        return (0.0,NN)
+    XX.sort(cmpOrder2)
+    YY.sort(cmpOrder2)
+    X = [0]*NN
+    Y = [0]*NN
+
+    j = 1
+    rank = 0.0
+    t = 0.0
+    sx = 0.0
+
+    while j < NN:
+
+        if XX[j][1] != XX[j-1][1]:
+            X[XX[j-1][0]] = j
+            j = j+1
+
+        else:
+            jt = j+1
+            ji = j
+            for jt in range(j+1, NN):
+                if (XX[jt][1] != XX[j-1][1]):
+                    break
+            rank = 0.5*(j+jt)
+            for ji in range(j-1, jt):
+                X[XX[ji][0]] = rank
+            t = jt-j
+            sx = sx + (t*t*t-t)
+            if (jt == NN-1):
+                if (XX[jt][1] == XX[j-1][1]):
+                    X[XX[NN-1][0]] = rank
+            j = jt+1
+
+    if j == NN:
+        if X[XX[NN-1][0]] == 0:
+            X[XX[NN-1][0]] = NN
+
+    j = 1
+    rank = 0.0
+    t = 0.0
+    sy = 0.0
+
+    while j < NN:
+
+        if YY[j][1] != YY[j-1][1]:
+            Y[YY[j-1][0]] = j
+            j = j+1
+        else:
+            jt = j+1
+            ji = j
+            for jt in range(j+1, NN):
+                if (YY[jt][1] != YY[j-1][1]):
+                    break
+            rank = 0.5*(j+jt)
+            for ji in range(j-1, jt):
+                Y[YY[ji][0]] = rank
+            t = jt - j
+            sy = sy + (t*t*t-t)
+            if (jt == NN-1):
+                if (YY[jt][1] == YY[j-1][1]):
+                    Y[YY[NN-1][0]] = rank
+            j = jt+1
+
+    if j == NN:
+        if Y[YY[NN-1][0]] == 0:
+            Y[YY[NN-1][0]] = NN
+
+    D = 0.0
+
+    for i in range(NN):
+        D += (X[i]-Y[i])*(X[i]-Y[i])
+
+    fac = (1.0 -sx/(NN*NN*NN-NN))*(1.0-sy/(NN*NN*NN-NN))
+
+    return ((1-(6.0/(NN*NN*NN-NN))*(D+(sx+sy)/12.0))/math.sqrt(fac),NN)
 
 
 
 def calCorrelation(dbdata,userdata,N):
-	X = []
-	Y = []
-	for i in range(N):
-		if dbdata[i]!= None and userdata[i]!= None:
-			X.append(dbdata[i])
-			Y.append(userdata[i])
-	NN = len(X)
-	if NN <6:
-		return (0.0,NN)
-	sx = reduce(lambda x,y:x+y,X,0.0)
-	sy = reduce(lambda x,y:x+y,Y,0.0)
-	meanx = sx/NN
-	meany = sy/NN
-	xyd = 0.0
-	sxd = 0.0
-	syd = 0.0
-	for i in range(NN):
-		xyd += (X[i] - meanx)*(Y[i]-meany)
-		sxd += (X[i] - meanx)*(X[i] - meanx)
-		syd += (Y[i] - meany)*(Y[i] - meany)
-	try:
-		corr = xyd/(sqrt(sxd)*sqrt(syd))
-	except:
-		corr = 0
-	return (corr,NN)
+    X = []
+    Y = []
+    for i in range(N):
+        if dbdata[i]!= None and userdata[i]!= None:
+            X.append(dbdata[i])
+            Y.append(userdata[i])
+    NN = len(X)
+    if NN <6:
+        return (0.0,NN)
+    sx = reduce(lambda x,y:x+y,X,0.0)
+    sy = reduce(lambda x,y:x+y,Y,0.0)
+    meanx = sx/NN
+    meany = sy/NN
+    xyd = 0.0
+    sxd = 0.0
+    syd = 0.0
+    for i in range(NN):
+        xyd += (X[i] - meanx)*(Y[i]-meany)
+        sxd += (X[i] - meanx)*(X[i] - meanx)
+        syd += (Y[i] - meany)*(Y[i] - meany)
+    try:
+        corr = xyd/(sqrt(sxd)*sqrt(syd))
+    except:
+        corr = 0
+    return (corr,NN)
 
 def calCorrelationText(dbdata,userdata,N): ### dcrowell July 2008
-        """Calculates correlation coefficients with values formatted from text files. dbdata, userdata are lists of strings.  N is an int.  Returns a float
-        Used by correlationPage"""
-        X = []
-        Y = []
-        for i in range(N):
-                #if (dbdata[i]!= None and userdata[i]!= None) and (dbdata[i]!= 'None' and userdata[i]!= 'None'):
-                #               X.append(float(dbdata[i]))
-                #               Y.append(float(userdata[i]))
-                if dbdata[i] == None or dbdata[i] == 'None' or userdata[i] == None or userdata[i] == 'None':
-                        continue
-                else:
-                        X.append(float(dbdata[i]))
-                        Y.append(float(userdata[i]))
-        NN = len(X)
-        if NN <6:
-                return (0.0,NN)
-        sx = sum(X)
-        sy = sum(Y)
-        meanx = sx/float(NN)
-        meany = sy/float(NN)
-        xyd = 0.0
-        sxd = 0.0
-        syd = 0.0
-        for i in range(NN):
-                x1 = X[i]-meanx
-                y1 = Y[i]-meany
-                xyd += x1*y1
-                sxd += x1**2
-                syd += y1**2
-        try:
-                corr = xyd/(sqrt(sxd)*sqrt(syd))
-        except:
-                corr = 0
-        return (corr,NN)
+    """Calculates correlation coefficients with values formatted from text files. dbdata, userdata are lists of strings.  N is an int.  Returns a float
+    Used by correlationPage"""
+    X = []
+    Y = []
+    for i in range(N):
+        #if (dbdata[i]!= None and userdata[i]!= None) and (dbdata[i]!= 'None' and userdata[i]!= 'None'):
+        #               X.append(float(dbdata[i]))
+        #               Y.append(float(userdata[i]))
+        if dbdata[i] == None or dbdata[i] == 'None' or userdata[i] == None or userdata[i] == 'None':
+            continue
+        else:
+            X.append(float(dbdata[i]))
+            Y.append(float(userdata[i]))
+    NN = len(X)
+    if NN <6:
+        return (0.0,NN)
+    sx = sum(X)
+    sy = sum(Y)
+    meanx = sx/float(NN)
+    meany = sy/float(NN)
+    xyd = 0.0
+    sxd = 0.0
+    syd = 0.0
+    for i in range(NN):
+        x1 = X[i]-meanx
+        y1 = Y[i]-meany
+        xyd += x1*y1
+        sxd += x1**2
+        syd += y1**2
+    try:
+        corr = xyd/(sqrt(sxd)*sqrt(syd))
+    except:
+        corr = 0
+    return (corr,NN)
 
 
 def readLineCSV(line): ### dcrowell July 2008
-        """Parses a CSV string of text and returns a list containing each element as a string.
-        Used by correlationPage"""
-        returnList = line.split('","')
-        returnList[-1]=returnList[-1][:-2]
-        returnList[0]=returnList[0][1:]
-        return returnList
+    """Parses a CSV string of text and returns a list containing each element as a string.
+    Used by correlationPage"""
+    returnList = line.split('","')
+    returnList[-1]=returnList[-1][:-2]
+    returnList[0]=returnList[0][1:]
+    return returnList
 
 
 def cmpCorr(A,B):
-	try:
-		if abs(A[1]) < abs(B[1]):
-			return 1
-		elif abs(A[1]) == abs(B[1]):
-			return 0
-		else:
-			return -1	
-	except:
-		return 0
+    try:
+        if abs(A[1]) < abs(B[1]):
+            return 1
+        elif abs(A[1]) == abs(B[1]):
+            return 0
+        else:
+            return -1
+    except:
+        return 0
 
 def cmpLitCorr(A,B):
-	try:
-		if abs(A[3]) < abs(B[3]): return 1
-		elif abs(A[3]) == abs(B[3]):
-                     if abs(A[1]) < abs(B[1]): return 1
-		     elif abs(A[1]) == abs(B[1]): return 0
-                     else: return -1
-		else: return -1	
-	except:
-		return 0
+    try:
+        if abs(A[3]) < abs(B[3]): return 1
+        elif abs(A[3]) == abs(B[3]):
+            if abs(A[1]) < abs(B[1]): return 1
+            elif abs(A[1]) == abs(B[1]): return 0
+            else: return -1
+        else: return -1
+    except:
+        return 0
 
 def cmpPValue(A,B):
-	try:
-		if A.corrPValue < B.corrPValue:
-			return -1
-		elif A.corrPValue == B.corrPValue:
-			if abs(A.corr) > abs(B.corr):
-				return -1
-			elif abs(A.corr) < abs(B.corr):
-				return 1
-			else:
-				return 0
-		else:
-			return 1	
-	except:
-		return 0
+    try:
+        if A.corrPValue < B.corrPValue:
+            return -1
+        elif A.corrPValue == B.corrPValue:
+            if abs(A.corr) > abs(B.corr):
+                return -1
+            elif abs(A.corr) < abs(B.corr):
+                return 1
+            else:
+                return 0
+        else:
+            return 1
+    except:
+        return 0
 
 def cmpEigenValue(A,B):
-	try:
-		if A[0] > B[0]:
-			return -1
-		elif A[0] == B[0]:
-			return 0
-		else:
-			return 1	
-	except:
-		return 0
+    try:
+        if A[0] > B[0]:
+            return -1
+        elif A[0] == B[0]:
+            return 0
+        else:
+            return 1
+    except:
+        return 0
 
 
 def cmpLRSFull(A,B):
-	try:
-		if A[0] < B[0]:
-			return -1
-		elif A[0] == B[0]:
-			return 0
-		else:
-			return 1	
-	except:
-		return 0
+    try:
+        if A[0] < B[0]:
+            return -1
+        elif A[0] == B[0]:
+            return 0
+        else:
+            return 1
+    except:
+        return 0
 
 def cmpLRSInteract(A,B):
-	try:
-		if A[1] < B[1]:
-			return -1
-		elif A[1] == B[1]:
-			return 0
-		else:
-			return 1	
-	except:
-		return 0
-
-	
+    try:
+        if A[1] < B[1]:
+            return -1
+        elif A[1] == B[1]:
+            return 0
+        else:
+            return 1
+    except:
+        return 0
+
+
 def cmpPos(A,B):
-	try:
-		try: 
-			AChr = int(A.chr)
-		except:
-			AChr = 20
-		try: 
-			BChr = int(B.chr)
-		except:
-			BChr = 20
-		if AChr > BChr:
-			return 1
-		elif AChr == BChr:
-			if A.mb > B.mb:
-				return 1
-			if A.mb == B.mb:
-				return 0
-			else:
-				return -1
-		else:
-			return -1	
-	except:
-		return 0
-	
+    try:
+        try:
+            AChr = int(A.chr)
+        except:
+            AChr = 20
+        try:
+            BChr = int(B.chr)
+        except:
+            BChr = 20
+        if AChr > BChr:
+            return 1
+        elif AChr == BChr:
+            if A.mb > B.mb:
+                return 1
+            if A.mb == B.mb:
+                return 0
+            else:
+                return -1
+        else:
+            return -1
+    except:
+        return 0
+
 def cmpGenoPos(A,B):
-	try:
-		A1 = A.chr
-		B1 = B.chr
-		try:
-			A1 = int(A1)
-		except:
-			A1 = 25
-		try:
-			B1 = int(B1)
-		except:
-			B1 = 25
-		if A1 > B1:
-			return 1
-		elif A1 == B1:
-			if A.mb > B.mb:
-				return 1
-			if A.mb == B.mb:
-				return 0
-			else:
-				return -1
-		else:
-			return -1	
-	except:
-		return 0
+    try:
+        A1 = A.chr
+        B1 = B.chr
+        try:
+            A1 = int(A1)
+        except:
+            A1 = 25
+        try:
+            B1 = int(B1)
+        except:
+            B1 = 25
+        if A1 > B1:
+            return 1
+        elif A1 == B1:
+            if A.mb > B.mb:
+                return 1
+            if A.mb == B.mb:
+                return 0
+            else:
+                return -1
+        else:
+            return -1
+    except:
+        return 0
 
 #XZhou: Must use "BINARY" to enable case sensitive comparison.
 def authUser(name,password,db, encrypt=None):
-	try:
-		if encrypt:
-			query = 'SELECT privilege, id,name,password, grpName FROM User WHERE name= BINARY \'%s\' and password= BINARY \'%s\'' % (name,password)
-		else:
-			query = 'SELECT privilege, id,name,password, grpName FROM User WHERE name= BINARY \'%s\' and password= BINARY SHA(\'%s\')' % (name,password)
-		db.execute(query)
-		records = db.fetchone()
-		if not records:
-			raise ValueError
-		return records#(privilege,id,name,password,grpName)
-	except:
-		return (None, None, None, None, None)
+    try:
+        if encrypt:
+            query = 'SELECT privilege, id,name,password, grpName FROM User WHERE name= BINARY \'%s\' and password= BINARY \'%s\'' % (name,password)
+        else:
+            query = 'SELECT privilege, id,name,password, grpName FROM User WHERE name= BINARY \'%s\' and password= BINARY SHA(\'%s\')' % (name,password)
+        db.execute(query)
+        records = db.fetchone()
+        if not records:
+            raise ValueError
+        return records#(privilege,id,name,password,grpName)
+    except:
+        return (None, None, None, None, None)
 
 
 def hasAccessToConfidentialPhenotypeTrait(privilege, userName, authorized_users):
@@ -840,9 +840,9 @@ def hasAccessToConfidentialPhenotypeTrait(privilege, userName, authorized_users)
 
 class VisualizeException(Exception):
     def __init__(self, message):
-	        self.message = message	
+        self.message = message
     def __str__(self):
-                return self.message
+        return self.message
 
 # safeConvert : (string -> A) -> A -> A
 # to convert a string to type A, using the supplied default value
@@ -852,12 +852,12 @@ def safeConvert(f, value, default):
         return f(value)
     except:
         return default
-    
+
 # safeFloat : string -> float -> float
 # to convert a string to a float safely
 def safeFloat(value, default):
     return safeConvert(float, value, default)
-    
+
 # safeInt: string -> int -> int
 # to convert a string to an int safely
 def safeInt(value, default):
@@ -878,7 +878,7 @@ def yesNoToInt(value):
     if value == "yes":
         return 1
     elif value == "no":
-       	return 0
+        return 0
     else:
         return None
 
@@ -890,79 +890,79 @@ def intToYesNo(value):
     elif value == 0:
         return "no"
     else:
-        return None	
-       
+        return None
+
 def formatField(name):
-	name = name.replace("_", " ")
-	name = name.title()
-        #name = name.replace("Mb Mm6", "Mb");  
-	return name.replace("Id", "ID")  
+    name = name.replace("_", " ")
+    name = name.title()
+    #name = name.replace("Mb Mm6", "Mb");
+    return name.replace("Id", "ID")
 
 #XZ, 03/27/2009: This function is very specific.
 #It is used by AJAX_table.py, correlationPage.py and dataPage.py
 
 
 def genTableObj(tblobj=None, file="", sortby = ("", ""), tableID = "sortable", addIndex = "1", hiddenColumns=[]):
-	header = tblobj['header']
-	body = tblobj['body']
-	field, order = sortby
-	
-	#ZAS 9/12/2011 - The hiddenColumns array needs to be converted into a string so they can be placed into the javascript of each up/down button
-	hiddenColumnsString = ",".join(hiddenColumns)
-
-	tbl = HT.TableLite(Class="collap b2", cellspacing=1, cellpadding=5)
-
-	hiddenColumnIdx = [] #indices of columns to hide
-	idx = -1
-	last_idx = 0 #ZS: This is the index of the last item in the regular table header (without any extra parameters). It is used to determine the index of each extra parameter.
-	for row in header:
-		hr = HT.TR()
-		for i, item in enumerate(row):
-			if (item.text == '') or (item.text not in hiddenColumns):
-				if item.sort and item.text:			
-					down = HT.Href("javascript:xmlhttpPost('%smain.py?FormID=AJAX_table', '%s', 'sort=%s&order=down&file=%s&tableID=%s&addIndex=%s&hiddenColumns=%s')" % (webqtlConfig.CGIDIR, tableID, item.text, file, tableID, addIndex, hiddenColumnsString),IMGDESC)		
-					up = HT.Href("javascript:xmlhttpPost('%smain.py?FormID=AJAX_table', '%s', 'sort=%s&order=up&file=%s&tableID=%s&addIndex=%s&hiddenColumns=%s')" % (webqtlConfig.CGIDIR, tableID, item.text, file, tableID, addIndex, hiddenColumnsString),IMGASC)
-					if item.text == field:	
-						idx = item.idx
-						last_idx = idx
-						if order == 'up':
-							up = IMGASCON
-						elif order == 'down':
-							down = IMGDESCON
-					item.html.append(HT.Div(up, down, style="float: bottom;"))
-				hr.append(item.html)
-			else:
-				hiddenColumnIdx.append(i)
-		tbl.append(hr)
-
-	for i, row in enumerate(body):
-		for j, item in enumerate(row):
-			if order == 'down':
-				if (item.val == '' or item.val == 'x' or item.val == 'None'):
-					item.val = 0 
-			if order == 'up':
-				if (item.val == '' or item.val == 'x' or item.val == 'None'):
-					item.val = 'zzzzz' 
-
-	if idx >= 0:
-		if order == 'down':
-			body.sort(lambda A, B: cmp(B[idx].val, A[idx].val), key=natsort_key)
-		elif order == 'up':
-			body.sort(lambda A, B: cmp(A[idx].val, B[idx].val), key=natsort_key)
-		else:
-			pass
-			
-	for i, row in enumerate(body):
-		hr = HT.TR(Id = row[0].text)
-		for j, item in enumerate(row):
-			if (j not in hiddenColumnIdx):
-				if j == 0:
-					if addIndex == "1":
-						item.html.contents = [i+1] + item.html.contents
-				hr.append(item.html)
-		tbl.append(hr)
-
-	return tbl	
+    header = tblobj['header']
+    body = tblobj['body']
+    field, order = sortby
+
+    #ZAS 9/12/2011 - The hiddenColumns array needs to be converted into a string so they can be placed into the javascript of each up/down button
+    hiddenColumnsString = ",".join(hiddenColumns)
+
+    tbl = HT.TableLite(Class="collap b2", cellspacing=1, cellpadding=5)
+
+    hiddenColumnIdx = [] #indices of columns to hide
+    idx = -1
+    last_idx = 0 #ZS: This is the index of the last item in the regular table header (without any extra parameters). It is used to determine the index of each extra parameter.
+    for row in header:
+        hr = HT.TR()
+        for i, item in enumerate(row):
+            if (item.text == '') or (item.text not in hiddenColumns):
+                if item.sort and item.text:
+                    down = HT.Href("javascript:xmlhttpPost('%smain.py?FormID=AJAX_table', '%s', 'sort=%s&order=down&file=%s&tableID=%s&addIndex=%s&hiddenColumns=%s')" % (webqtlConfig.CGIDIR, tableID, item.text, file, tableID, addIndex, hiddenColumnsString),IMGDESC)
+                    up = HT.Href("javascript:xmlhttpPost('%smain.py?FormID=AJAX_table', '%s', 'sort=%s&order=up&file=%s&tableID=%s&addIndex=%s&hiddenColumns=%s')" % (webqtlConfig.CGIDIR, tableID, item.text, file, tableID, addIndex, hiddenColumnsString),IMGASC)
+                    if item.text == field:
+                        idx = item.idx
+                        last_idx = idx
+                        if order == 'up':
+                            up = IMGASCON
+                        elif order == 'down':
+                            down = IMGDESCON
+                    item.html.append(HT.Div(up, down, style="float: bottom;"))
+                hr.append(item.html)
+            else:
+                hiddenColumnIdx.append(i)
+        tbl.append(hr)
+
+    for i, row in enumerate(body):
+        for j, item in enumerate(row):
+            if order == 'down':
+                if (item.val == '' or item.val == 'x' or item.val == 'None'):
+                    item.val = 0
+            if order == 'up':
+                if (item.val == '' or item.val == 'x' or item.val == 'None'):
+                    item.val = 'zzzzz'
+
+    if idx >= 0:
+        if order == 'down':
+            body.sort(lambda A, B: cmp(B[idx].val, A[idx].val), key=natsort_key)
+        elif order == 'up':
+            body.sort(lambda A, B: cmp(A[idx].val, B[idx].val), key=natsort_key)
+        else:
+            pass
+
+    for i, row in enumerate(body):
+        hr = HT.TR(Id = row[0].text)
+        for j, item in enumerate(row):
+            if (j not in hiddenColumnIdx):
+                if j == 0:
+                    if addIndex == "1":
+                        item.html.contents = [i+1] + item.html.contents
+                hr.append(item.html)
+        tbl.append(hr)
+
+    return tbl
 
 def natsort_key(string):
     r = []
@@ -974,4 +974,3 @@ def natsort_key(string):
         except:
             r.append(c)
     return r
-