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Diffstat (limited to 'web/webqtl/basicStatistics/BasicStatisticsFunctions.py')
| -rwxr-xr-x | web/webqtl/basicStatistics/BasicStatisticsFunctions.py | 174 |
1 files changed, 0 insertions, 174 deletions
diff --git a/web/webqtl/basicStatistics/BasicStatisticsFunctions.py b/web/webqtl/basicStatistics/BasicStatisticsFunctions.py deleted file mode 100755 index a22b50a2..00000000 --- a/web/webqtl/basicStatistics/BasicStatisticsFunctions.py +++ /dev/null @@ -1,174 +0,0 @@ -#import string -from math import * -import piddle as pid -#import os - -import reaper -from htmlgen import HTMLgen2 as HT - -from utility import Plot -from utility import webqtlUtil -from base import webqtlConfig -from dbFunction import webqtlDatabaseFunction - -def basicStatsTable(vals, trait_type=None, cellid=None, heritability=None): - - valsOnly = [] - dataXZ = vals[:] - for i in range(len(dataXZ)): - valsOnly.append(dataXZ[i][1]) - - traitmean, traitmedian, traitvar, traitstdev, traitsem, N = reaper.anova(valsOnly) #ZS: Should convert this from reaper to R in the future - - tbl = HT.TableLite(cellpadding=20, cellspacing=0) - dataXZ = vals[:] - dataXZ.sort(webqtlUtil.cmpOrder) - tbl.append(HT.TR(HT.TD("Statistic",align="left", Class="fs14 fwb ffl b1 cw cbrb", width = 180), - HT.TD("Value", align="right", Class="fs14 fwb ffl b1 cw cbrb", width = 60))) - tbl.append(HT.TR(HT.TD("N of Samples",align="left", Class="fs13 b1 cbw c222"), - HT.TD(N,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - tbl.append(HT.TR(HT.TD("Mean",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%2.3f" % traitmean,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - tbl.append(HT.TR(HT.TD("Median",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%2.3f" % traitmedian,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - #tbl.append(HT.TR(HT.TD("Variance",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - # HT.TD("%2.3f" % traitvar,nowrap="yes",align="left", Class="fs13 b1 cbw c222"))) - tbl.append(HT.TR(HT.TD("Standard Error (SE)",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%2.3f" % traitsem,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - tbl.append(HT.TR(HT.TD("Standard Deviation (SD)", align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%2.3f" % traitstdev,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - tbl.append(HT.TR(HT.TD("Minimum", align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%s" % dataXZ[0][1],nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - tbl.append(HT.TR(HT.TD("Maximum", align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%s" % dataXZ[-1][1],nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - if (trait_type != None and trait_type == 'ProbeSet'): - #IRQuest = HT.Href(text="Interquartile Range", url=webqtlConfig.glossaryfile +"#Interquartile",target="_blank", Class="fs14") - #IRQuest.append(HT.BR()) - #IRQuest.append(" (fold difference)") - tbl.append(HT.TR(HT.TD("Range (log2)",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%2.3f" % (dataXZ[-1][1]-dataXZ[0][1]),nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - tbl.append(HT.TR(HT.TD(HT.Span("Range (fold)"),align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%2.2f" % pow(2.0,(dataXZ[-1][1]-dataXZ[0][1])), nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - tbl.append(HT.TR(HT.TD(HT.Span(HT.Href(url="/glossary.html#Interquartile", target="_blank", text="Interquartile Range", Class="non_bold")), align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%2.2f" % pow(2.0,(dataXZ[int((N-1)*3.0/4.0)][1]-dataXZ[int((N-1)/4.0)][1])), nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - - #XZ, 04/01/2009: don't try to get H2 value for probe. - if cellid: - pass - else: - if heritability: - tbl.append(HT.TR(HT.TD(HT.Span("Heritability"),align="center", Class="fs13 b1 cbw c222",nowrap="yes"),HT.TD("%s" % heritability, nowrap="yes",align="center", Class="fs13 b1 cbw c222"))) - else: - pass - # Lei Yan - # 2008/12/19 - - return tbl - -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 plotBoxPlot(vals): - - valsOnly = [] - dataXZ = vals[:] - for i in range(len(dataXZ)): - valsOnly.append(dataXZ[i][1]) - - plotHeight = 320 - plotWidth = 220 - xLeftOffset = 60 - xRightOffset = 40 - yTopOffset = 40 - yBottomOffset = 60 - - canvasHeight = plotHeight + yTopOffset + yBottomOffset - canvasWidth = plotWidth + xLeftOffset + xRightOffset - canvas = pid.PILCanvas(size=(canvasWidth,canvasHeight)) - XXX = [('', valsOnly[:])] - - Plot.plotBoxPlot(canvas, XXX, offset=(xLeftOffset, xRightOffset, yTopOffset, yBottomOffset), XLabel= "Trait") - filename= webqtlUtil.genRandStr("Box_") - canvas.save(webqtlConfig.IMGDIR+filename, format='gif') - img=HT.Image('/image/'+filename+'.gif',border=0) - - plotLink = HT.Span("More about ", HT.Href(text="Box Plots", url="http://davidmlane.com/hyperstat/A37797.html", target="_blank", Class="fs13")) - - return img, plotLink - -def plotBarGraph(identification='', RISet='', vals=None, type="name"): - - this_identification = "unnamed trait" - if identification: - this_identification = identification - - if type=="rank": - dataXZ = vals[:] - dataXZ.sort(webqtlUtil.cmpOrder) - title='%s' % this_identification - else: - dataXZ = vals[:] - title='%s' % this_identification - - tvals = [] - tnames = [] - tvars = [] - for i in range(len(dataXZ)): - tvals.append(dataXZ[i][1]) - tnames.append(webqtlUtil.genShortStrainName(RISet=RISet, input_strainName=dataXZ[i][0])) - tvars.append(dataXZ[i][2]) - nnStrain = len(tnames) - - sLabel = 1 - - ###determine bar width and space width - if nnStrain < 20: - sw = 4 - elif nnStrain < 40: - sw = 3 - else: - sw = 2 - - ### 700 is the default plot width minus Xoffsets for 40 strains - defaultWidth = 650 - if nnStrain > 40: - defaultWidth += (nnStrain-40)*10 - defaultOffset = 100 - bw = int(0.5+(defaultWidth - (nnStrain-1.0)*sw)/nnStrain) - if bw < 10: - bw = 10 - - plotWidth = (nnStrain-1)*sw + nnStrain*bw + defaultOffset - plotHeight = 500 - #print [plotWidth, plotHeight, bw, sw, nnStrain] - c = pid.PILCanvas(size=(plotWidth,plotHeight)) - Plot.plotBarText(c, tvals, tnames, variance=tvars, YLabel='Value', title=title, sLabel = sLabel, barSpace = sw) - - filename= webqtlUtil.genRandStr("Bar_") - c.save(webqtlConfig.IMGDIR+filename, format='gif') - img=HT.Image('/image/'+filename+'.gif',border=0) - - return img |