def plotNormalProbability(vals=None, RISet='', title=None, showstrains=0, specialStrains=[None], size=(750,500)):
dataXZ = vals[:]
dataXZ.sort(webqtlUtil.cmpOrder)
dataLabel = []
dataX = map(lambda X: X[1], dataXZ)
showLabel = showstrains
if len(dataXZ) > 50:
showLabel = 0
for item in dataXZ:
strainName = webqtlUtil.genShortStrainName(RISet=RISet, input_strainName=item[0])
dataLabel.append(strainName)
dataY=Plot.U(len(dataX))
dataZ=map(Plot.inverseCumul,dataY)
c = pid.PILCanvas(size=(750,500))
Plot.plotXY(c, dataZ, dataX, dataLabel = dataLabel, XLabel='Expected Z score', connectdot=0, YLabel='Trait value', title=title, specialCases=specialStrains, showLabel = showLabel)
filename= webqtlUtil.genRandStr("nP_")
c.save(webqtlConfig.IMGDIR+filename, format='gif')
img=HT.Image('/image/'+filename+'.gif',border=0)
return img
def screePlot(self, NNN=0, pearsonEigenValue=None):
c1 = pid.PILCanvas(size=(700,500))
Plot.plotXY(canvas=c1, dataX=range(1,NNN+1), dataY=pearsonEigenValue, rank=0, labelColor=pid.blue,plotColor=pid.red, symbolColor=pid.blue, XLabel='Factor Number', connectdot=1,YLabel='Percent of Total Variance %', title='Pearson\'s R Scree Plot')
filename= webqtlUtil.genRandStr("Scree_")
c1.save(webqtlConfig.IMGDIR+filename, format='gif')
img=HT.Image('/image/'+filename+'.gif',border=0)
return img
def factorLoadingsPlot(self, pearsonEigenVectors=None, traitList=None):
traitname = map(lambda X:str(X.name), traitList)
c2 = pid.PILCanvas(size=(700,500))
Plot.plotXY(c2, pearsonEigenVectors[0],pearsonEigenVectors[1], 0, dataLabel = traitname, labelColor=pid.blue, plotColor=pid.red, symbolColor=pid.blue,XLabel='Factor (1)', connectdot=1, YLabel='Factor (2)', title='Factor Loadings Plot (Pearson)', loadingPlot=1)
filename= webqtlUtil.genRandStr("FacL_")
c2.save(webqtlConfig.IMGDIR+filename, format='gif')
img = HT.Image('/image/'+filename+'.gif',border=0)
return img
def factorLoadingsPlot(self, pearsonEigenVectors=None, traitList=None):
traitname = map(lambda X:str(X.name), traitList)
c2 = pid.PILCanvas(size=(700,500))
if type(pearsonEigenVectors[0][0]).__name__ == 'complex':
pearsonEigenVectors_0 = self.removeimag_array(values=pearsonEigenVectors[0])
else:
pearsonEigenVectors_0 = pearsonEigenVectors[0]
if type(pearsonEigenVectors[1][0]).__name__ == 'complex':
pearsonEigenVectors_1 = self.removeimag_array(values=pearsonEigenVectors[1])
else:
pearsonEigenVectors_1 = pearsonEigenVectors[1]
Plot.plotXY(c2, pearsonEigenVectors_0,pearsonEigenVectors_1, 0, dataLabel = traitname, labelColor=pid.blue, plotColor=pid.red, symbolColor=pid.blue,XLabel='Factor (1)', connectdot=1, YLabel='Factor (2)', title='Factor Loadings Plot (Pearson)', loadingPlot=1)
filename= webqtlUtil.genRandStr("FacL_")
c2.save(webqtlConfig.IMGDIR+filename, format='gif')
img = HT.Image('/image/'+filename+'.gif',border=0)
return img
def __init__(self, fd):
templatePage.__init__(self, fd)
self.initializeDisplayParameters(fd)
if not fd.genotype:
fd.readGenotype()
if fd.allstrainlist:
mdpchoice = fd.formdata.getvalue('MDPChoice')
if mdpchoice == "1":
strainlist = fd.f1list + fd.strainlist
elif mdpchoice == "2":
strainlist = []
strainlist2 = fd.f1list + fd.strainlist
for strain in fd.allstrainlist:
if strain not in strainlist2:
strainlist.append(strain)
#So called MDP Panel
if strainlist:
strainlist = fd.f1list+fd.parlist+strainlist
else:
strainlist = fd.allstrainlist
fd.readData(fd.allstrainlist)
else:
mdpchoice = None
strainlist = fd.strainlist
fd.readData()
#if fd.allstrainlist:
# fd.readData(fd.allstrainlist)
# strainlist = fd.allstrainlist
#else:
# fd.readData()
# strainlist = fd.strainlist
if not self.openMysql():
return
isSampleCorr = 0 #XZ: initial value is false
isTissueCorr = 0 #XZ: initial value is false
#Javascript functions (showCorrelationPlot2, showTissueCorrPlot) have made sure the correlation type is either sample correlation or tissue correlation.
if (self.database and (self.ProbeSetID != 'none')):
isSampleCorr = 1
elif (self.X_geneSymbol and self.Y_geneSymbol):
isTissueCorr = 1
else:
heading = "Correlation Type Error"
detail = ["For the input parameters, GN can not recognize the correlation type is sample correlation or tissue correlation."]
self.error(heading=heading,detail=detail)
return
TD_LR = HT.TD(colspan=2,height=200,width="100%",bgColor='#eeeeee', align="left", wrap="off")
dataX=[]
dataY=[]
dataZ=[] # shortname
fullTissueName=[]
if isTissueCorr:
dataX, dataY, xlabel, ylabel, dataZ, fullTissueName = self.getTissueLabelsValues(X_geneSymbol=self.X_geneSymbol, Y_geneSymbol=self.Y_geneSymbol, TissueProbeSetFreezeId=self.TissueProbeSetFreezeId)
plotHeading = HT.Paragraph('Tissue Correlation Scatterplot')
plotHeading.__setattr__("class","title")
if self.xAxisLabel == '':
self.xAxisLabel = xlabel
if self.yAxisLabel == '':
self.yAxisLabel = ylabel
if isSampleCorr:
plotHeading = HT.Paragraph('Sample Correlation Scatterplot')
plotHeading.__setattr__("class","title")
#XZ: retrieve trait 1 info, Y axis
trait1_data = [] #trait 1 data
trait1Url = ''
try:
Trait1 = webqtlTrait(db=self.database, name=self.ProbeSetID, cellid=self.CellID, cursor=self.cursor)
Trait1.retrieveInfo()
Trait1.retrieveData()
except:
heading = "Retrieve Data"
detail = ["The database you just requested has not been established yet."]
self.error(heading=heading,detail=detail)
return
trait1_data = Trait1.exportData(strainlist)
if Trait1.db.type == 'Publish' and Trait1.confidential:
trait1Url = Trait1.genHTML(dispFromDatabase=1, privilege=self.privilege, userName=self.userName, authorized_users=Trait1.authorized_users)
else:
trait1Url = Trait1.genHTML(dispFromDatabase=1)
if self.yAxisLabel == '':
self.yAxisLabel= '%s : %s' % (Trait1.db.shortname, Trait1.name)
if Trait1.cellid:
self.yAxisLabel += ' : ' + Trait1.cellid
#XZ, retrieve trait 2 info, X axis
traitdata2 = [] #trait 2 data
_vals = [] #trait 2 data
trait2Url = ''
if ( self.database2 and (self.ProbeSetID2 != 'none') ):
try:
Trait2 = webqtlTrait(db=self.database2, name=self.ProbeSetID2, cellid=self.CellID2, cursor=self.cursor)
Trait2.retrieveInfo()
Trait2.retrieveData()
except:
heading = "Retrieve Data"
detail = ["The database you just requested has not been established yet."]
self.error(heading=heading,detail=detail)
return
if Trait2.db.type == 'Publish' and Trait2.confidential:
trait2Url = Trait2.genHTML(dispFromDatabase=1, privilege=self.privilege, userName=self.userName, authorized_users=Trait2.authorized_users)
else:
trait2Url = Trait2.genHTML(dispFromDatabase=1)
traitdata2 = Trait2.exportData(strainlist)
_vals = traitdata2[:]
if self.xAxisLabel == '':
self.xAxisLabel = '%s : %s' % (Trait2.db.shortname, Trait2.name)
if Trait2.cellid:
self.xAxisLabel += ' : ' + Trait2.cellid
else:
for item in strainlist:
if fd.allTraitData.has_key(item):
_vals.append(fd.allTraitData[item].val)
else:
_vals.append(None)
if self.xAxisLabel == '':
if fd.identification:
self.xAxisLabel = fd.identification
else:
self.xAxisLabel = "User Input Data"
try:
Trait2 = webqtlTrait(fullname=fd.formdata.getvalue('fullname'), cursor=self.cursor)
trait2Url = Trait2.genHTML(dispFromDatabase=1)
except:
trait2Url = self.xAxisLabel
if (_vals and trait1_data):
if len(_vals) != len(trait1_data):
errors = HT.Blockquote(HT.Font('Error: ',color='red'),HT.Font('The number of traits are inconsistent, Program quit',color='black'))
errors.__setattr__("class","subtitle")
TD_LR.append(errors)
self.dict['body'] = str(TD_LR)
return
for i in range(len(_vals)):
if _vals[i]!= None and trait1_data[i]!= None:
dataX.append(_vals[i])
dataY.append(trait1_data[i])
strainName = strainlist[i]
if self.showstrains:
dataZ.append(webqtlUtil.genShortStrainName(RISet=fd.RISet, input_strainName=strainName))
else:
heading = "Correlation Plot"
detail = ['Empty Dataset for sample correlation, please check your data.']
self.error(heading=heading,detail=detail)
return
#XZ: We have gotten all data for both traits.
if len(dataX) >= self.corrMinInformative:
if self.rankOrder == 0:
rankPrimary = 0
rankSecondary = 1
else:
rankPrimary = 1
rankSecondary = 0
lineColor = self.setLineColor();
symbolColor = self.setSymbolColor();
idColor = self.setIdColor();
c = pid.PILCanvas(size=(self.plotSize, self.plotSize*0.90))
data_coordinate = Plot.plotXY(canvas=c, dataX=dataX, dataY=dataY, rank=rankPrimary, dataLabel = dataZ, labelColor=pid.black, lineSize=self.lineSize, lineColor=lineColor, idColor=idColor, idFont=self.idFont, idSize=self.idSize, symbolColor=symbolColor, symbolType=self.symbol, filled=self.filled, symbolSize=self.symbolSize, XLabel=self.xAxisLabel, connectdot=0, YLabel=self.yAxisLabel, title='', fitcurve=self.showline, displayR =1, offset= (90, self.plotSize/20, self.plotSize/10, 90), showLabel = self.showIdentifiers)
if rankPrimary == 1:
dataXlabel, dataYlabel = webqtlUtil.calRank(xVals=dataX, yVals=dataY, N=len(dataX))
else:
dataXlabel, dataYlabel = dataX, dataY
gifmap1 = HT.Map(name='CorrelationPlotImageMap1')
for i, item in enumerate(data_coordinate):
one_rect_coordinate = "%d, %d, %d, %d" % (item[0] - 5, item[1] - 5, item[0] + 5, item[1] + 5)
if isTissueCorr:
one_rect_title = "%s (%s, %s)" % (fullTissueName[i], dataXlabel[i], dataYlabel[i])
else:
one_rect_title = "%s (%s, %s)" % (dataZ[i], dataXlabel[i], dataYlabel[i])
gifmap1.areas.append(HT.Area(shape='rect',coords=one_rect_coordinate, title=one_rect_title) )
filename= webqtlUtil.genRandStr("XY_")
c.save(webqtlConfig.IMGDIR+filename, format='gif')
img1=HT.Image('/image/'+filename+'.gif',border=0, usemap='#CorrelationPlotImageMap1')
mainForm_1 = HT.Form( cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), enctype='multipart/form-data', name='showDatabase', submit=HT.Input(type='hidden'))
hddn = {'FormID':'showDatabase','ProbeSetID':'_','database':'_','CellID':'_','RISet':fd.RISet, 'ProbeSetID2':'_', 'database2':'_', 'CellID2':'_', 'allstrainlist':string.join(fd.strainlist, " "), 'traitList': fd.formdata.getvalue("traitList")}
if fd.incparentsf1:
hddn['incparentsf1'] = 'ON'
for key in hddn.keys():
mainForm_1.append(HT.Input(name=key, value=hddn[key], type='hidden'))
if isSampleCorr:
mainForm_1.append(HT.P(), HT.Blockquote(HT.Strong('X axis:'),HT.Blockquote(trait2Url),HT.Strong('Y axis:'),HT.Blockquote(trait1Url), style='width: %spx;' % self.plotSize, wrap="hard"))
graphForm = HT.Form(cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), name='MDP_Form',submit=HT.Input(type='hidden'))
graph_hddn = self.setHiddenParameters(fd, rankPrimary)
webqtlUtil.exportData(graph_hddn, fd.allTraitData) #XZ: This is necessary to replot with different groups of strains
for key in graph_hddn.keys():
graphForm.append(HT.Input(name=key, value=graph_hddn[key], type='hidden'))
options = self.createOptionsMenu(fd, mdpchoice)
if (self.showOptions == '0'):
showOptionsButton = HT.Input(type='button' ,name='optionsButton',value='Hide Options', onClick="showHideOptions();", Class="button")
else:
showOptionsButton = HT.Input(type='button' ,name='optionsButton',value='Show Options', onClick="showHideOptions();", Class="button")
# updated by NL: 12-07-2011 add variables for tissue abbreviation page
if isTissueCorr:
graphForm.append(HT.Input(name='shortTissueName', value='', type='hidden'))
graphForm.append(HT.Input(name='fullTissueName', value='', type='hidden'))
shortTissueNameStr=string.join(dataZ, ",")
fullTissueNameStr=string.join(fullTissueName, ",")
tissueAbbrButton=HT.Input(type='button' ,name='tissueAbbrButton',value='Show Abbreviations', onClick="showTissueAbbr('MDP_Form','%s','%s')" % (shortTissueNameStr,fullTissueNameStr), Class="button")
graphForm.append(showOptionsButton,' ',tissueAbbrButton, HT.BR(), HT.BR())
else:
graphForm.append(showOptionsButton, HT.BR(), HT.BR())
graphForm.append(options, HT.BR())
graphForm.append(HT.HR(), HT.BR(), HT.P())
TD_LR.append(plotHeading, HT.BR(),graphForm, HT.BR(), gifmap1, HT.P(), img1, HT.P(), mainForm_1)
TD_LR.append(HT.BR(), HT.HR(color="grey", size=5, width="100%"))
c = pid.PILCanvas(size=(self.plotSize, self.plotSize*0.90))
data_coordinate = Plot.plotXY(canvas=c, dataX=dataX, dataY=dataY, rank=rankSecondary, dataLabel = dataZ, labelColor=pid.black,lineColor=lineColor, lineSize=self.lineSize, idColor=idColor, idFont=self.idFont, idSize=self.idSize, symbolColor=symbolColor, symbolType=self.symbol, filled=self.filled, symbolSize=self.symbolSize, XLabel=self.xAxisLabel, connectdot=0, YLabel=self.yAxisLabel,title='', fitcurve=self.showline, displayR =1, offset= (90, self.plotSize/20, self.plotSize/10, 90), showLabel = self.showIdentifiers)
if rankSecondary == 1:
dataXlabel, dataYlabel = webqtlUtil.calRank(xVals=dataX, yVals=dataY, N=len(dataX))
else:
dataXlabel, dataYlabel = dataX, dataY
gifmap2 = HT.Map(name='CorrelationPlotImageMap2')
for i, item in enumerate(data_coordinate):
one_rect_coordinate = "%d, %d, %d, %d" % (item[0] - 6, item[1] - 6, item[0] + 6, item[1] + 6)
if isTissueCorr:
one_rect_title = "%s (%s, %s)" % (fullTissueName[i], dataXlabel[i], dataYlabel[i])
else:
one_rect_title = "%s (%s, %s)" % (dataZ[i], dataXlabel[i], dataYlabel[i])
gifmap2.areas.append(HT.Area(shape='rect',coords=one_rect_coordinate, title=one_rect_title) )
filename= webqtlUtil.genRandStr("XY_")
c.save(webqtlConfig.IMGDIR+filename, format='gif')
img2=HT.Image('/image/'+filename+'.gif',border=0, usemap='#CorrelationPlotImageMap2')
mainForm_2 = HT.Form( cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), enctype='multipart/form-data', name='showDatabase2', submit=HT.Input(type='hidden'))
hddn = {'FormID':'showDatabase2','ProbeSetID':'_','database':'_','CellID':'_','RISet':fd.RISet, 'ProbeSetID2':'_', 'database2':'_', 'CellID2':'_', 'allstrainlist':string.join(fd.strainlist, " "), 'traitList': fd.formdata.getvalue("traitList")}
if fd.incparentsf1:
hddn['incparentsf1'] = 'ON'
for key in hddn.keys():
mainForm_2.append(HT.Input(name=key, value=hddn[key], type='hidden'))
if isSampleCorr:
mainForm_2.append(HT.P(), HT.Blockquote(HT.Strong('X axis:'),HT.Blockquote(trait2Url),HT.Strong('Y axis:'),HT.Blockquote(trait1Url), style='width:%spx;' % self.plotSize))
TD_LR.append(HT.BR(), HT.P())
TD_LR.append('\n', gifmap2, HT.P(), HT.P(), img2, HT.P(), mainForm_2)
self.dict['body'] = str(TD_LR)
else:
heading = "Correlation Plot"
detail = ['Fewer than %d strain data were entered for %s data set. No statitical analysis has been attempted.' % (self.corrMinInformative, fd.RISet)]
self.error(heading=heading,detail=detail)
return
def __init__(self, fd):
templatePage.__init__(self, fd)
self.initializeDisplayParameters(fd)
if not fd.genotype:
fd.readGenotype()
mdpchoice = None
strainlist = fd.strainlist
fd.readData()
if not self.openMysql():
return
isSampleCorr = 1
isTissueCorr = 0
TD_LR = HT.TD(colspan=2, height=200, width="100%", bgColor="#eeeeee", align="left", wrap="off")
dataX = []
dataY = []
dataZ = [] # shortname
fullTissueName = []
xlabel = ""
ylabel = ""
if isSampleCorr:
plotHeading = HT.Paragraph("Sample Correlation Scatterplot")
plotHeading.__setattr__("class", "title")
# XZ: retrieve trait 1 info, Y axis
trait1_data = [] # trait 1 data
trait1Url = ""
try:
Trait1 = webqtlTrait(db=self.database, name=self.ProbeSetID, cellid=self.CellID, cursor=self.cursor)
Trait1.retrieveInfo()
Trait1.retrieveData()
except:
heading = "Retrieve Data"
detail = ["The database you just requested has not been established yet."]
self.error(heading=heading, detail=detail)
return
trait1_data = Trait1.exportData(strainlist)
trait1Url = Trait1.genHTML(dispFromDatabase=1)
ylabel = "%s : %s" % (Trait1.db.shortname, Trait1.name)
if Trait1.cellid:
ylabel += " : " + Trait1.cellid
# XZ, retrieve trait 2 info, X axis
trait2_data = [] # trait 2 data
trait2Url = ""
try:
Trait2 = webqtlTrait(db=self.database2, name=self.ProbeSetID2, cellid=self.CellID2, cursor=self.cursor)
Trait2.retrieveInfo()
Trait2.retrieveData()
except:
heading = "Retrieve Data"
detail = ["The database you just requested has not been established yet."]
self.error(heading=heading, detail=detail)
return
trait2_data = Trait2.exportData(strainlist)
trait2Url = Trait2.genHTML(dispFromDatabase=1)
xlabel = "%s : %s" % (Trait2.db.shortname, Trait2.name)
if Trait2.cellid:
xlabel += " : " + Trait2.cellid
for strain in Trait1.data.keys():
if Trait2.data.has_key(strain):
dataX.append(Trait2.data[strain].val)
dataY.append(Trait1.data[strain].val)
if self.showstrains:
dataZ.append(webqtlUtil.genShortStrainName(RISet=fd.RISet, input_strainName=strain))
# XZ: We have gotten all data for both traits.
if len(dataX) >= self.corrMinInformative:
if self.rankOrder == 0:
rankPrimary = 0
rankSecondary = 1
else:
rankPrimary = 1
rankSecondary = 0
lineColor = self.setLineColor()
symbolColor = self.setSymbolColor()
idColor = self.setIdColor()
c = pid.PILCanvas(size=(self.plotSize, self.plotSize * 0.90))
data_coordinate = Plot.plotXY(
canvas=c,
dataX=dataX,
dataY=dataY,
rank=rankPrimary,
dataLabel=dataZ,
labelColor=pid.black,
lineSize=self.lineSize,
lineColor=lineColor,
idColor=idColor,
idFont=self.idFont,
idSize=self.idSize,
symbolColor=symbolColor,
symbolType=self.symbol,
filled=self.filled,
symbolSize=self.symbolSize,
XLabel=xlabel,
connectdot=0,
YLabel=ylabel,
title="",
fitcurve=self.showline,
displayR=1,
offset=(90, self.plotSize / 20, self.plotSize / 10, 90),
showLabel=self.showIdentifiers,
)
if rankPrimary == 1:
dataXlabel, dataYlabel = webqtlUtil.calRank(xVals=dataX, yVals=dataY, N=len(dataX))
else:
dataXlabel, dataYlabel = dataX, dataY
gifmap1 = HT.Map(name="CorrelationPlotImageMap1")
for i, item in enumerate(data_coordinate):
one_rect_coordinate = "%d, %d, %d, %d" % (item[0] - 5, item[1] - 5, item[0] + 5, item[1] + 5)
if isTissueCorr:
one_rect_title = "%s (%s, %s)" % (fullTissueName[i], dataXlabel[i], dataYlabel[i])
else:
one_rect_title = "%s (%s, %s)" % (dataZ[i], dataXlabel[i], dataYlabel[i])
gifmap1.areas.append(HT.Area(shape="rect", coords=one_rect_coordinate, title=one_rect_title))
filename = webqtlUtil.genRandStr("XY_")
c.save(webqtlConfig.IMGDIR + filename, format="gif")
img1 = HT.Image("/image/" + filename + ".gif", border=0, usemap="#CorrelationPlotImageMap1")
mainForm_1 = HT.Form(
cgi=os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE),
enctype="multipart/form-data",
name="showDatabase",
submit=HT.Input(type="hidden"),
)
hddn = {
"FormID": "showDatabase",
"ProbeSetID": "_",
"database": "_",
"CellID": "_",
"RISet": fd.RISet,
"ProbeSetID2": "_",
"database2": "_",
"CellID2": "_",
"allstrainlist": string.join(fd.strainlist, " "),
"traitList": fd.formdata.getvalue("traitList"),
}
if fd.incparentsf1:
hddn["incparentsf1"] = "ON"
for key in hddn.keys():
mainForm_1.append(HT.Input(name=key, value=hddn[key], type="hidden"))
if isSampleCorr:
mainForm_1.append(
HT.P(),
HT.Blockquote(
HT.Strong("X axis:"),
HT.Blockquote(trait2Url),
HT.Strong("Y axis:"),
HT.Blockquote(trait1Url),
style="width: %spx;" % self.plotSize,
wrap="hard",
),
)
graphForm = HT.Form(
cgi=os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE),
name="MDP_Form",
submit=HT.Input(type="hidden"),
)
graph_hddn = self.setHiddenParameters(fd, rankPrimary)
webqtlUtil.exportData(
graph_hddn, fd.allTraitData
) # XZ: This is necessary to replot with different groups of strains
for key in graph_hddn.keys():
graphForm.append(HT.Input(name=key, value=graph_hddn[key], type="hidden"))
options = self.createOptionsMenu(fd, mdpchoice)
if self.showOptions == "0":
showOptionsButton = HT.Input(
type="button",
name="optionsButton",
value="Hide Options",
onClick="showHideOptions();",
Class="button",
)
else:
showOptionsButton = HT.Input(
type="button",
name="optionsButton",
value="Show Options",
onClick="showHideOptions();",
Class="button",
)
# updated by NL: 12-07-2011 add variables for tissue abbreviation page
if isTissueCorr:
graphForm.append(HT.Input(name="shortTissueName", value="", type="hidden"))
graphForm.append(HT.Input(name="fullTissueName", value="", type="hidden"))
shortTissueNameStr = string.join(dataZ, ",")
fullTissueNameStr = string.join(fullTissueName, ",")
tissueAbbrButton = HT.Input(
type="button",
name="tissueAbbrButton",
value="Show Abbreviations",
onClick="showTissueAbbr('MDP_Form','%s','%s')" % (shortTissueNameStr, fullTissueNameStr),
Class="button",
)
graphForm.append(showOptionsButton, " ", tissueAbbrButton, HT.BR(), HT.BR())
else:
graphForm.append(showOptionsButton, HT.BR(), HT.BR())
graphForm.append(options, HT.BR())
graphForm.append(HT.HR(), HT.BR(), HT.P())
TD_LR.append(plotHeading, HT.BR(), graphForm, HT.BR(), gifmap1, HT.P(), img1, HT.P(), mainForm_1)
TD_LR.append(HT.BR(), HT.HR(color="grey", size=5, width="100%"))
c = pid.PILCanvas(size=(self.plotSize, self.plotSize * 0.90))
data_coordinate = Plot.plotXY(
canvas=c,
dataX=dataX,
dataY=dataY,
rank=rankSecondary,
dataLabel=dataZ,
labelColor=pid.black,
lineColor=lineColor,
lineSize=self.lineSize,
idColor=idColor,
idFont=self.idFont,
idSize=self.idSize,
symbolColor=symbolColor,
symbolType=self.symbol,
filled=self.filled,
symbolSize=self.symbolSize,
XLabel=xlabel,
connectdot=0,
YLabel=ylabel,
title="",
fitcurve=self.showline,
displayR=1,
offset=(90, self.plotSize / 20, self.plotSize / 10, 90),
showLabel=self.showIdentifiers,
)
if rankSecondary == 1:
dataXlabel, dataYlabel = webqtlUtil.calRank(xVals=dataX, yVals=dataY, N=len(dataX))
else:
dataXlabel, dataYlabel = dataX, dataY
gifmap2 = HT.Map(name="CorrelationPlotImageMap2")
for i, item in enumerate(data_coordinate):
one_rect_coordinate = "%d, %d, %d, %d" % (item[0] - 6, item[1] - 6, item[0] + 6, item[1] + 6)
if isTissueCorr:
one_rect_title = "%s (%s, %s)" % (fullTissueName[i], dataXlabel[i], dataYlabel[i])
else:
one_rect_title = "%s (%s, %s)" % (dataZ[i], dataXlabel[i], dataYlabel[i])
gifmap2.areas.append(HT.Area(shape="rect", coords=one_rect_coordinate, title=one_rect_title))
filename = webqtlUtil.genRandStr("XY_")
c.save(webqtlConfig.IMGDIR + filename, format="gif")
img2 = HT.Image("/image/" + filename + ".gif", border=0, usemap="#CorrelationPlotImageMap2")
mainForm_2 = HT.Form(
cgi=os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE),
enctype="multipart/form-data",
name="showDatabase2",
submit=HT.Input(type="hidden"),
)
hddn = {
"FormID": "showDatabase2",
"ProbeSetID": "_",
"database": "_",
"CellID": "_",
"RISet": fd.RISet,
"ProbeSetID2": "_",
"database2": "_",
"CellID2": "_",
"allstrainlist": string.join(fd.strainlist, " "),
"traitList": fd.formdata.getvalue("traitList"),
}
if fd.incparentsf1:
hddn["incparentsf1"] = "ON"
for key in hddn.keys():
mainForm_2.append(HT.Input(name=key, value=hddn[key], type="hidden"))
if isSampleCorr:
mainForm_2.append(
HT.P(),
HT.Blockquote(
HT.Strong("X axis:"),
HT.Blockquote(trait2Url),
HT.Strong("Y axis:"),
HT.Blockquote(trait1Url),
style="width:%spx;" % self.plotSize,
),
)
TD_LR.append(HT.BR(), HT.P())
TD_LR.append("\n", gifmap2, HT.P(), HT.P(), img2, HT.P(), mainForm_2)
self.dict["body"] = str(TD_LR)
else:
heading = "Correlation Plot"
detail = [
"Fewer than %d strain data were entered for %s data set. No statitical analysis has been attempted."
% (self.corrMinInformative, fd.RISet)
]
self.error(heading=heading, detail=detail)
return
