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-rwxr-xr-xwqflask/utility/webqtlUtil.py1459
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
-
generated by cgit v1.2.3 (git 2.44.0) at 2024-11-22 17:26:20 +0000