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