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+# Copyright (C) University of Tennessee Health Science Center, Memphis, TN.
+#
+# This program is free software: you can redistribute it and/or modify it
+# under the terms of the GNU Affero General Public License
+# as published by the Free Software Foundation, either version 3 of the
+# License, or (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+# See the GNU Affero General Public License for more details.
+#
+# This program is available from Source Forge: at GeneNetwork Project
+# (sourceforge.net/projects/genenetwork/).
+#
+# Contact Drs. Robert W. Williams and Xiaodong Zhou (2010)
+# at rwilliams@uthsc.edu and xzhou15@uthsc.edu
+#
+#
+#
+# This module is used by GeneNetwork project (www.genenetwork.org)
+#
+# Created by GeneNetwork Core Team 2010/08/10
+#
+# Last updated by GeneNetwork Core Team 2010/10/20
+
+import piddle as pid
+from math import *
+import random
+import sys, os
+from numarray import linear_algebra as la
+from numarray import ones, array, dot, swapaxes
+
+import reaper
+
+import svg
+import webqtlUtil
+from base import webqtlConfig
+
+
+def cformat(d, rank=0):
+ 'custom string format'
+ strD = "%2.6f" % d
+
+ if rank == 0:
+ while strD[-1] in ('0','.'):
+ if strD[-1] == '0' and strD[-2] == '.' and len(strD) <= 4:
+ break
+ elif strD[-1] == '.':
+ strD = strD[:-1]
+ break
+ else:
+ strD = strD[:-1]
+
+ else:
+ strD = strD.split(".")[0]
+
+ if strD == '-0.0':
+ strD = '0.0'
+ return strD
+
+def frange(start, end=None, inc=1.0):
+ "A faster range-like function that does accept float increments..."
+ if end == None:
+ end = start + 0.0
+ start = 0.0
+ else:
+ start += 0.0 # force it to be a float
+ count = int((end - start) / inc)
+ if start + count * inc != end:
+ # Need to adjust the count. AFAICT, it always comes up one short.
+ count += 1
+ L = [start] * count
+ for i in xrange(1, count):
+ L[i] = start + i * inc
+ return L
+
+
+def gammln(xx):
+ cof=[76.18009173,-86.50532033,24.01409822,-1.231739516,0.120858003e-2,-0.536382e-5]
+ x=xx-1.0
+ tmp=x+5.5
+ tmp -=(x+0.5)*log(tmp)
+ ser=1.0
+ for item in cof:
+ x+=1.0
+ ser+=item/x
+
+ return -tmp+log(2.50662827465*ser)
+
+
+def gser(a,x):
+ gln=gammln(a)
+ ITMAX=100
+ EPS=3.0e-7
+
+ if x<=0.0:
+ gamser=0.0
+ return [gamser,gln]
+ else:
+ ap=a
+ sum=1.0/a
+ dele=sum
+ for i in range(1,ITMAX+1):
+ ap+=1.0
+ dele*=x/ap
+ sum+=dele
+ if abs(dele)<abs(sum)*EPS:
+ gamser=sum*exp(-x+a*log(x)-gln)
+ return [gamser,gln]
+ return None
+
+def gcf(a,x):
+ ITMAX=100
+ EPS=3.0e-7
+ gold=0.0
+ fac=1
+ b1=1.0
+ b0=0.0
+ a0=1.0
+ gln=gammln(a)
+
+ a1=x
+ for n in range(1,ITMAX+1):
+ an=n+0.0
+ ana=an-a
+ a0=(a1+a0*ana)*fac
+ b0=(b1+b0*ana)*fac
+ anf=an*fac
+ a1=x*a0+anf*a1
+ b1=x*b0+anf*b1
+ if (a1):
+ fac=1.0/a1
+ g=b1*fac
+ if abs((g-gold)/g)<EPS:
+ gammcf=exp(-x+a*log(x)-gln)*g
+ return [gammcf,gln]
+ gold=g
+ return None
+
+def gammp(a,x):
+ if x<0.0 or a<=0.0:
+ return None
+ if x<(a+1.0):
+ a=gser(a,x)[0]
+ return a
+ else:
+ a=gcf(a,x)[0]
+ return 1.0-a
+def U(n):
+ x=pow(0.5,1.0/n)
+ m=[1-x]
+ for i in range(2,n):
+ a=(i-0.3175)/(n+0.365)
+ m.append(a)
+ m.append(x)
+ return m
+
+def erf(x):
+ if x<0.0:
+ return -gammp(0.5,x*x)
+ else:
+ return gammp(0.5,x*x)
+
+def erfcc(x):
+ z=abs(x)
+ t=1.0/(1.0+0.5*z)
+ ans=t*exp(-z*z-1.26551223+t*(1.00002368+t*(0.37409196+t*(0.09678418+t*(-0.18628806+t*(0.27886807+t*(-1.13520398+t*(1.48851587+t*(-0.82215223+t*0.17087277)))))))))
+ if x>=0.0:
+ return ans
+ else:
+ return 2.0-ans
+
+def calMeanVar(data):
+ n=len(data)
+ if n<2:
+ return None
+ else:
+ sum=reduce(lambda x,y:x+y,data,0.0)
+ mean=sum/n
+ z=data[:]
+ for i in range(n):
+ z[i]=z[i]-mean
+ variance=reduce(lambda x,y:x+y*y,z,0.0)
+ variance /= n-1
+ variance =sqrt(variance)
+ for i in range(n):
+ z[i]=z[i]/variance
+ return z
+
+def inverseCumul(p):
+ #Coefficients in rational approximations.
+ a = [-3.969683028665376e+01,2.209460984245205e+02,-2.759285104469687e+02,1.383577518672690e+02,-3.066479806614716e+01,2.506628277459239e+00]
+
+ b = [-5.447609879822406e+01,1.615858368580409e+02,-1.556989798598866e+02,6.680131188771972e+01,-1.328068155288572e+01]
+
+ c = [-7.784894002430293e-03,-3.223964580411365e-01,-2.400758277161838e+00,-2.549732539343734e+00,4.374664141464968e+00,2.938163982698783e+00]
+
+ d = [7.784695709041462e-03,3.224671290700398e-01,2.445134137142996e+00,3.754408661907416e+00]
+
+ #Define break-points.
+
+ p_low = 0.02425
+ p_high = 1 - p_low
+
+ #Rational approximation for lower region.
+
+ if p > 0 and p < p_low:
+ q = sqrt(-2*log(p))
+ x = (((((c[0]*q+c[1])*q+c[2])*q+c[3])*q+c[4])*q+c[5]) / ((((d[0]*q+d[1])*q+d[2])*q+d[3])*q+1)
+
+
+ #Rational approximation for central region.
+
+ elif p>= p_low and p <= p_high:
+ q = p - 0.5
+ r = q*q
+ x = (((((a[0]*r+a[1])*r+a[2])*r+a[3])*r+a[4])*r+a[5])*q /(((((b[0]*r+b[1])*r+b[2])*r+b[3])*r+b[4])*r+1)
+
+ #Rational approximation for upper region.
+
+ elif p>p_high and p < 1:
+ q = sqrt(-2*log(1-p))
+ x = -(((((c[0]*q+c[1])*q+c[2])*q+c[3])*q+c[4])*q+c[5]) /((((d[0]*q+d[1])*q+d[2])*q+d[3])*q+1)
+
+ else:
+ return None
+
+ if p>0 and p < 1:
+ e = 0.5 * erfcc(-x/sqrt(2)) - p
+ u = e * sqrt(2*pi) * exp(x*x/2)
+ x = x - u/(1 + x*u/2)
+ return x
+ else:
+ return None
+
+def gmean(lst):
+ N = len(lst)
+ if N == 0:
+ return 0
+ else:
+ return (reduce(lambda x,y: x+y, lst, 0.0))/N
+
+def gmedian(lst2):
+ lst = lst2[:]
+ N = len(lst)
+ if N == 0:
+ return 0
+ else:
+ lst.sort()
+ if N % 2 == 0:
+ return (lst[N/2]+lst[(N-2)/2])/2.0
+ else:
+ return lst[(N-1)/2]
+
+def gpercentile(lst2, np):
+ lst = lst2[:]
+ N = len(lst)
+ if N == 0 or np > 100 or np < 0:
+ return None
+ else:
+ lst.sort()
+ pNadd1 = (np/100.0)*N
+ k = int(pNadd1)
+ d = pNadd1 - k
+ if k == 0:
+ return lst[0]
+ elif k >= N-1:
+ return lst[N-1]
+ else:
+ return lst[k-1] + d*(lst[k] - lst[k-1])
+
+def findOutliers(vals):
+
+ valsOnly = []
+ dataXZ = vals[:]
+ for i in range(len(dataXZ)):
+ valsOnly.append(dataXZ[i][1])
+
+ data = [('', valsOnly[:])]
+
+ for item in data:
+ itemvalue = item[1]
+ nValue = len(itemvalue)
+ catValue = []
+
+ for item2 in itemvalue:
+ try:
+ tstrain, tvalue = item2
+ except:
+ tvalue = item2
+ if nValue <= 4:
+ continue
+ else:
+ catValue.append(tvalue)
+
+ if catValue != []:
+ lowHinge = gpercentile(catValue, 25)
+ upHinge = gpercentile(catValue, 75)
+ Hstep = 1.5*(upHinge - lowHinge)
+
+ outlier = []
+ extreme = []
+
+ upperBound = upHinge + Hstep
+ lowerBound = lowHinge - Hstep
+
+ for item in catValue:
+ if item >= upHinge + 2*Hstep:
+ extreme.append(item)
+ elif item >= upHinge + Hstep:
+ outlier.append(item)
+ else:
+ pass
+
+ for item in catValue:
+ if item <= lowHinge - 2*Hstep:
+ extreme.append(item)
+ elif item <= lowHinge - Hstep:
+ outlier.append(item)
+ else:
+ pass
+ else:
+ upperBound = 1000
+ lowerBound = -1000
+
+ return upperBound, lowerBound
+
+
+def plotBoxPlot(canvas, data, offset= (40, 40, 40, 40), XLabel="Category", YLabel="Value"):
+ xLeftOffset, xRightOffset, yTopOffset, yBottomOffset = offset
+ plotWidth = canvas.size[0] - xLeftOffset - xRightOffset
+ plotHeight = canvas.size[1] - yTopOffset - yBottomOffset
+ iValues = []
+ for item in data:
+ for item2 in item[1]:
+ try:
+ iValues.append(item2[1])
+ except:
+ iValues.append(item2)
+
+ #draw frame
+ max_Y = max(iValues)
+ min_Y = min(iValues)
+ scaleY = detScale(min_Y, max_Y)
+ Yll = scaleY[0]
+ Yur = scaleY[1]
+ nStep = scaleY[2]
+ stepY = (Yur - Yll)/nStep
+ stepYPixel = plotHeight/(nStep)
+ canvas.drawRect(plotWidth+xLeftOffset, plotHeight + yTopOffset, xLeftOffset, yTopOffset)
+
+ ##draw Y Scale
+ YYY = Yll
+ YCoord = plotHeight + yTopOffset
+ scaleFont=pid.Font(ttf="cour",size=11,bold=1)
+ for i in range(nStep+1):
+ strY = cformat(d=YYY, rank=0)
+ YCoord = max(YCoord, yTopOffset)
+ canvas.drawLine(xLeftOffset,YCoord,xLeftOffset-5,YCoord)
+ canvas.drawString(strY, xLeftOffset -30,YCoord +5,font=scaleFont)
+ YYY += stepY
+ YCoord -= stepYPixel
+
+ ##draw X Scale
+ stepX = plotWidth/len(data)
+ XCoord = xLeftOffset + 0.5*stepX
+ YCoord = plotHeight + yTopOffset
+ scaleFont = pid.Font(ttf="tahoma",size=12,bold=0)
+ labelFont = pid.Font(ttf="tahoma",size=13,bold=0)
+ for item in data:
+ itemname, itemvalue = item
+ canvas.drawLine(XCoord, YCoord,XCoord, YCoord+5, color=pid.black)
+ canvas.drawString(itemname, XCoord - canvas.stringWidth(itemname,font=labelFont)/2.0,\
+ YCoord +20,font=labelFont)
+
+ nValue = len(itemvalue)
+ catValue = []
+ for item2 in itemvalue:
+ try:
+ tstrain, tvalue = item2
+ except:
+ tvalue = item2
+ if nValue <= 4:
+ canvas.drawCross(XCoord, plotHeight + yTopOffset - (tvalue-Yll)*plotHeight/(Yur - Yll), color=pid.red,size=5)
+ else:
+ catValue.append(tvalue)
+ if catValue != []:
+ catMean = gmean(catValue)
+ catMedian = gmedian(catValue)
+ lowHinge = gpercentile(catValue, 25)
+ upHinge = gpercentile(catValue, 75)
+ Hstep = 1.5*(upHinge - lowHinge)
+
+ outlier = []
+ extrem = []
+
+ upperAdj = None
+ for item in catValue:
+ if item >= upHinge + 2*Hstep:
+ extrem.append(item)
+ elif item >= upHinge + Hstep:
+ outlier.append(item)
+ elif item > upHinge and item < upHinge + Hstep:
+ if upperAdj == None or item > upperAdj:
+ upperAdj = item
+ else:
+ pass
+ lowerAdj = None
+ for item in catValue:
+ if item <= lowHinge - 2*Hstep:
+ extrem.append(item)
+ elif item <= lowHinge - Hstep:
+ outlier.append(item)
+ if item < lowHinge and item > lowHinge - Hstep:
+ if lowerAdj == None or item < lowerAdj:
+ lowerAdj = item
+ else:
+ pass
+ canvas.drawRect(XCoord-20, plotHeight + yTopOffset - (lowHinge-Yll)*plotHeight/(Yur - Yll), \
+ XCoord+20, plotHeight + yTopOffset - (upHinge-Yll)*plotHeight/(Yur - Yll))
+ canvas.drawLine(XCoord-20, plotHeight + yTopOffset - (catMedian-Yll)*plotHeight/(Yur - Yll), \
+ XCoord+20, plotHeight + yTopOffset - (catMedian-Yll)*plotHeight/(Yur - Yll))
+ if upperAdj != None:
+ canvas.drawLine(XCoord, plotHeight + yTopOffset - (upHinge-Yll)*plotHeight/(Yur - Yll), \
+ XCoord, plotHeight + yTopOffset - (upperAdj-Yll)*plotHeight/(Yur - Yll))
+ canvas.drawLine(XCoord-20, plotHeight + yTopOffset - (upperAdj-Yll)*plotHeight/(Yur - Yll), \
+ XCoord+20, plotHeight + yTopOffset - (upperAdj-Yll)*plotHeight/(Yur - Yll))
+ if lowerAdj != None:
+ canvas.drawLine(XCoord, plotHeight + yTopOffset - (lowHinge-Yll)*plotHeight/(Yur - Yll), \
+ XCoord, plotHeight + yTopOffset - (lowerAdj-Yll)*plotHeight/(Yur - Yll))
+ canvas.drawLine(XCoord-20, plotHeight + yTopOffset - (lowerAdj-Yll)*plotHeight/(Yur - Yll), \
+ XCoord+20, plotHeight + yTopOffset - (lowerAdj-Yll)*plotHeight/(Yur - Yll))
+
+ outlierFont = pid.Font(ttf="cour",size=12,bold=0)
+ if outlier != []:
+ for item in outlier:
+ yc = plotHeight + yTopOffset - (item-Yll)*plotHeight/(Yur - Yll)
+ #canvas.drawEllipse(XCoord-3, yc-3, XCoord+3, yc+3)
+ canvas.drawString('o', XCoord-3, yc+5, font=outlierFont, color=pid.orange)
+ if extrem != []:
+ for item in extrem:
+ yc = plotHeight + yTopOffset - (item-Yll)*plotHeight/(Yur - Yll)
+ #canvas.drawEllipse(XCoord-3, yc-3, XCoord+3, yc+3)
+ canvas.drawString('*', XCoord-3, yc+6, font=outlierFont, color=pid.red)
+
+ canvas.drawCross(XCoord, plotHeight + yTopOffset - (catMean-Yll)*plotHeight/(Yur - Yll), \
+ color=pid.blue,size=3)
+ #print (catMean, catMedian, cat25per, cat75per)
+ pass
+
+ XCoord += stepX
+
+ labelFont=pid.Font(ttf="verdana",size=18,bold=0)
+ canvas.drawString(XLabel, xLeftOffset + (plotWidth -canvas.stringWidth(XLabel,font=labelFont))/2.0, \
+ YCoord +40, font=labelFont)
+ canvas.drawString(YLabel,xLeftOffset-40, YCoord-(plotHeight -canvas.stringWidth(YLabel,font=labelFont))/2.0,\
+ font=labelFont, angle =90)
+
+def plotSecurity(canvas, text="12345"):
+ if not text:
+ return
+
+ plotWidth = canvas.size[0]
+ plotHeight = canvas.size[1]
+ if plotHeight<=0 or plotWidth<=0:
+ return
+
+ bgColor = pid.Color(0.6+0.4*random.random(), 0.6+0.4*random.random(), 0.6+0.4*random.random())
+ canvas.drawRect(0,0,plotWidth,plotHeight, edgeColor=bgColor, fillColor=bgColor)
+
+ for i in range(30):
+ randomColor = pid.Color(0.6+0.4*random.random(), 0.6+0.4*random.random(), 0.6+0.4*random.random())
+ scaleFont=pid.Font(ttf="cour",size=random.choice(range(20, 50)))
+ canvas.drawString(random.choice('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'),
+ int(random.random()*plotWidth), int(random.random()*plotHeight), font=scaleFont,
+ color=randomColor, angle=random.choice(range(-45, 50)))
+
+ step = (plotWidth-20)/len(text)
+ startX = 20
+ for item in text:
+ randomColor = pid.Color(0.6*random.random(),0.6*random.random(), 0.6*random.random())
+ scaleFont=pid.Font(ttf="verdana",size=random.choice(range(50, 60)),bold=1)
+ canvas.drawString(item, startX, plotHeight/2-10, font=scaleFont,
+ color=randomColor, angle=random.choice(range(-45, 50)))
+ startX += step
+
+# parameter: data is either object returned by reaper permutation function (called by MarkerRegressionPage.py)
+# or the first object returned by direct (pair-scan) permu function (called by DirectPlotPage.py)
+def plotBar(canvas, data, barColor=pid.blue, axesColor=pid.black, labelColor=pid.black, XLabel=None, YLabel=None, title=None, offset= (60, 20, 40, 40), zoom = 1):
+
+ xLeftOffset, xRightOffset, yTopOffset, yBottomOffset = offset
+
+ plotWidth = canvas.size[0] - xLeftOffset - xRightOffset
+ plotHeight = canvas.size[1] - yTopOffset - yBottomOffset
+ if plotHeight<=0 or plotWidth<=0:
+ return
+
+ if len(data) < 2:
+ return
+
+ max_D = max(data)
+ min_D = min(data)
+ #add by NL 06-20-2011: fix the error: when max_D is infinite, log function in detScale will go wrong
+ if max_D == float('inf') or max_D>webqtlConfig.MAXLRS:
+ max_D=webqtlConfig.MAXLRS #maximum LRS value
+
+ xLow, xTop, stepX = detScale(min_D, max_D)
+
+ #reduce data
+ step = ceil((xTop-xLow)/50.0)
+ j = xLow
+ dataXY = []
+ Count = []
+ while j <= xTop:
+ dataXY.append(j)
+ Count.append(0)
+ j += step
+
+ for i, item in enumerate(data):
+ if item == float('inf') or item>webqtlConfig.MAXLRS:
+ item = webqtlConfig.MAXLRS #maximum LRS value
+ j = int((item-xLow)/step)
+ Count[j] += 1
+
+ yLow, yTop, stepY=detScale(0,max(Count))
+
+ #draw data
+ xScale = plotWidth/(xTop-xLow)
+ yScale = plotHeight/(yTop-yLow)
+ barWidth = xScale*step
+
+ for i, count in enumerate(Count):
+ if count:
+ xc = (dataXY[i]-xLow)*xScale+xLeftOffset
+ yc =-(count-yLow)*yScale+yTopOffset+plotHeight
+ canvas.drawRect(xc+2,yc,xc+barWidth-2,yTopOffset+plotHeight,edgeColor=barColor,fillColor=barColor)
+
+ #draw drawing region
+ canvas.drawRect(xLeftOffset, yTopOffset, xLeftOffset+plotWidth, yTopOffset+plotHeight)
+
+ #draw scale
+ scaleFont=pid.Font(ttf="cour",size=11,bold=1)
+ x=xLow
+ for i in range(stepX+1):
+ xc=xLeftOffset+(x-xLow)*xScale
+ canvas.drawLine(xc,yTopOffset+plotHeight,xc,yTopOffset+plotHeight+5, color=axesColor)
+ strX = cformat(d=x, rank=0)
+ canvas.drawString(strX,xc-canvas.stringWidth(strX,font=scaleFont)/2,yTopOffset+plotHeight+14,font=scaleFont)
+ x+= (xTop - xLow)/stepX
+
+ y=yLow
+ for i in range(stepY+1):
+ yc=yTopOffset+plotHeight-(y-yLow)*yScale
+ canvas.drawLine(xLeftOffset,yc,xLeftOffset-5,yc, color=axesColor)
+ strY = "%d" %y
+ canvas.drawString(strY,xLeftOffset-canvas.stringWidth(strY,font=scaleFont)-6,yc+5,font=scaleFont)
+ y+= (yTop - yLow)/stepY
+
+ #draw label
+ labelFont=pid.Font(ttf="tahoma",size=17,bold=0)
+ if XLabel:
+ canvas.drawString(XLabel,xLeftOffset+(plotWidth-canvas.stringWidth(XLabel,font=labelFont))/2.0,
+ yTopOffset+plotHeight+yBottomOffset-10,font=labelFont,color=labelColor)
+
+ if YLabel:
+ canvas.drawString(YLabel, 19, yTopOffset+plotHeight-(plotHeight-canvas.stringWidth(YLabel,font=labelFont))/2.0,
+ font=labelFont,color=labelColor,angle=90)
+
+ labelFont=pid.Font(ttf="verdana",size=16,bold=0)
+ if title:
+ canvas.drawString(title,xLeftOffset+(plotWidth-canvas.stringWidth(title,font=labelFont))/2.0,
+ 20,font=labelFont,color=labelColor)
+
+def plotBarText(canvas, data, label, variance=None, barColor=pid.blue, axesColor=pid.black, labelColor=pid.black, XLabel=None, YLabel=None, title=None, sLabel = None, offset= (80, 20, 40, 100), barSpace = 2, zoom = 1):
+ xLeftOffset, xRightOffset, yTopOffset, yBottomOffset = offset
+ plotWidth = canvas.size[0] - xLeftOffset - xRightOffset
+ plotHeight = canvas.size[1] - yTopOffset - yBottomOffset
+ if plotHeight<=0 or plotWidth<=0:
+ return
+
+ NNN = len(data)
+ if NNN < 2 or NNN != len(label):
+ return
+ if variance and len(variance)!=NNN:
+ variance = []
+
+ Y2 = data[:]
+ if variance:
+ for i in range(NNN):
+ if variance[i]:
+ Y2 += [data[i]-variance[i]]
+
+ #Y axis
+ YLow, YTop, stepY = detScale(min(Y2), max(Y2))
+ YScale = plotHeight/(YTop - YLow)
+
+ if YLow < 0 and YTop > 0:
+ drawZero = 1
+ else:
+ drawZero = 0
+
+ #X axis
+ X = range(NNN)
+ Xll= 0
+ Xur= NNN-1
+
+
+ if drawZero:
+ YZero = yTopOffset+plotHeight-YScale*(0-YLow)
+ canvas.drawLine(xLeftOffset, YZero, xLeftOffset+plotWidth, YZero)
+ else:
+ YZero = yTopOffset+plotHeight
+ #draw data
+ spaceWidth = barSpace
+ if spaceWidth < 1:
+ spaceWidth = 1
+ barWidth = int((plotWidth - (NNN-1.0)*spaceWidth)/NNN)
+
+ xc= xLeftOffset
+ scaleFont=pid.Font(ttf="verdana",size=11,bold=0)
+ for i in range(NNN):
+ yc = yTopOffset+plotHeight-(data[i]-YLow)*YScale
+ canvas.drawRect(xc,YZero,xc+barWidth-1, yc, edgeColor=barColor,fillColor=barColor)
+ if variance and variance[i]:
+ varlen = variance[i]*YScale
+ if yc-varlen < yTopOffset:
+ topYd = yTopOffset
+ else:
+ topYd = yc-varlen
+ canvas.drawLine(xc+barWidth/2-2,yc-varlen,xc+barWidth/2+2,yc-varlen,color=pid.red)
+ canvas.drawLine(xc+barWidth/2,yc+varlen,xc+barWidth/2,topYd,color=pid.red)
+ canvas.drawLine(xc+barWidth/2-2,yc+varlen,xc+barWidth/2+2,yc+varlen,color=pid.red)
+ strX = label[i]
+ canvas.drawString(strX,xc+barWidth/2.0+2,yTopOffset+plotHeight+2+canvas.stringWidth(strX,font=scaleFont),font=scaleFont,angle=90)
+ xc += barWidth + spaceWidth
+
+ #draw drawing region
+ canvas.drawRect(xLeftOffset, yTopOffset, xLeftOffset+plotWidth, yTopOffset+plotHeight)
+
+ #draw Y scale
+ scaleFont=pid.Font(ttf="cour",size=16,bold=1)
+ y=YLow
+ for i in range(stepY+1):
+ yc=yTopOffset+plotHeight-(y-YLow)*YScale
+ canvas.drawLine(xLeftOffset,yc,xLeftOffset-5,yc, color=axesColor)
+ strY = cformat(d=y, rank=0)
+ canvas.drawString(strY,xLeftOffset-canvas.stringWidth(strY,font=scaleFont)-6,yc+5,font=scaleFont)
+ y+= (YTop - YLow)/stepY
+
+ #draw label
+ labelFont=pid.Font(ttf="verdana",size=17,bold=0)
+ if XLabel:
+ canvas.drawString(XLabel,xLeftOffset+(plotWidth-canvas.stringWidth(XLabel,font=labelFont))/2.0,yTopOffset+plotHeight+65,font=labelFont,color=labelColor)
+
+ if YLabel:
+ canvas.drawString(YLabel,xLeftOffset-50, yTopOffset+plotHeight-(plotHeight-canvas.stringWidth(YLabel,font=labelFont))/2.0,font=labelFont,color=labelColor,angle=90)
+
+ labelFont=pid.Font(ttf="verdana",size=18,bold=0)
+ if title:
+ canvas.drawString(title,xLeftOffset,yTopOffset-15,font=labelFont,color=labelColor)
+
+ return
+
+def plotXY(canvas, dataX, dataY, rank=0, dataLabel=[], plotColor = pid.black, axesColor=pid.black, labelColor=pid.black, lineSize="thin", lineColor=pid.grey, idFont="arial", idColor=pid.blue, idSize="14", symbolColor=pid.black, symbolType="circle", filled="yes", symbolSize="tiny", XLabel=None, YLabel=None, title=None, fitcurve=None, connectdot=1, displayR=None, loadingPlot = 0, offset= (80, 20, 40, 60), zoom = 1, specialCases=[], showLabel = 1, bufferSpace = 15):
+ 'displayR : correlation scatter plot, loadings : loading plot'
+
+ dataXRanked, dataYRanked = webqtlUtil.calRank(dataX, dataY, len(dataX))
+
+ #get ID font size
+ idFontSize = int(idSize)
+
+ #If filled is yes, set fill color
+ if filled == "yes":
+ fillColor = symbolColor
+ else:
+ fillColor = None
+
+ if symbolSize == "large":
+ sizeModifier = 7
+ fontModifier = 12
+ elif symbolSize == "medium":
+ sizeModifier = 5
+ fontModifier = 8
+ elif symbolSize == "small":
+ sizeModifier = 3
+ fontModifier = 3
+ else:
+ sizeModifier = 1
+ fontModifier = -1
+
+ if rank == 0: # Pearson correlation
+ bufferSpace = 0
+ dataXPrimary = dataX
+ dataYPrimary = dataY
+ dataXAlt = dataXRanked #Values used just for printing the other corr type to the graph image
+ dataYAlt = dataYRanked #Values used just for printing the other corr type to the graph image
+ else: # Spearman correlation: Switching Ranked and Unranked X and Y values
+ dataXPrimary = dataXRanked
+ dataYPrimary = dataYRanked
+ dataXAlt = dataX #Values used just for printing the other corr type to the graph image
+ dataYAlt = dataY #Values used just for printing the other corr type to the graph image
+
+ xLeftOffset, xRightOffset, yTopOffset, yBottomOffset = offset
+ plotWidth = canvas.size[0] - xLeftOffset - xRightOffset
+ plotHeight = canvas.size[1] - yTopOffset - yBottomOffset
+ if plotHeight<=0 or plotWidth<=0:
+ return
+ if len(dataXPrimary) < 1 or len(dataXPrimary) != len(dataYPrimary) or (dataLabel and len(dataXPrimary) != len(dataLabel)):
+ return
+
+ max_X=max(dataXPrimary)
+ min_X=min(dataXPrimary)
+ max_Y=max(dataYPrimary)
+ min_Y=min(dataYPrimary)
+
+ #for some reason I forgot why I need to do this
+ if loadingPlot:
+ min_X = min(-0.1,min_X)
+ max_X = max(0.1,max_X)
+ min_Y = min(-0.1,min_Y)
+ max_Y = max(0.1,max_Y)
+
+ xLow, xTop, stepX=detScale(min_X,max_X)
+ yLow, yTop, stepY=detScale(min_Y,max_Y)
+ xScale = plotWidth/(xTop-xLow)
+ yScale = plotHeight/(yTop-yLow)
+
+ #draw drawing region
+ canvas.drawRect(xLeftOffset-bufferSpace, yTopOffset, xLeftOffset+plotWidth, yTopOffset+plotHeight+bufferSpace)
+ canvas.drawRect(xLeftOffset-bufferSpace+1, yTopOffset, xLeftOffset+plotWidth, yTopOffset+plotHeight+bufferSpace-1)
+
+ #calculate data points
+ data = map(lambda X, Y: (X, Y), dataXPrimary, dataYPrimary)
+ xCoord = map(lambda X, Y: ((X-xLow)*xScale + xLeftOffset, yTopOffset+plotHeight-(Y-yLow)*yScale), dataXPrimary, dataYPrimary)
+
+ labelFont=pid.Font(ttf=idFont,size=idFontSize,bold=0)
+
+ if loadingPlot:
+ xZero = -xLow*xScale+xLeftOffset
+ yZero = yTopOffset+plotHeight+yLow*yScale
+ for point in xCoord:
+ canvas.drawLine(xZero,yZero,point[0],point[1],color=pid.red)
+ else:
+ if connectdot:
+ canvas.drawPolygon(xCoord,edgeColor=plotColor,closed=0)
+ else:
+ pass
+
+ symbolFont = pid.Font(ttf="fnt_bs", size=12+fontModifier,bold=0)
+
+ for i, item in enumerate(xCoord):
+ if dataLabel and dataLabel[i] in specialCases:
+ canvas.drawRect(item[0]-3, item[1]-3, item[0]+3, item[1]+3, edgeColor=pid.green)
+ #canvas.drawCross(item[0],item[1],color=pid.blue,size=5)
+ else:
+ if symbolType == "vertRect":
+ canvas.drawRect(x1=item[0]-sizeModifier+2,y1=item[1]-sizeModifier-2, x2=item[0]+sizeModifier-1,y2=item[1]+sizeModifier+2, edgeColor=symbolColor, edgeWidth=1, fillColor=fillColor)
+ elif (symbolType == "circle" and filled != "yes"):
+ canvas.drawString(":", item[0]-canvas.stringWidth(":",font=symbolFont)/2+1,item[1]+2,color=symbolColor, font=symbolFont)
+ elif (symbolType == "circle" and filled == "yes"):
+ canvas.drawString("5", item[0]-canvas.stringWidth("5",font=symbolFont)/2+1,item[1]+2,color=symbolColor, font=symbolFont)
+ elif symbolType == "horiRect":
+ canvas.drawRect(x1=item[0]-sizeModifier-1,y1=item[1]-sizeModifier+3, x2=item[0]+sizeModifier+3,y2=item[1]+sizeModifier-2, edgeColor=symbolColor, edgeWidth=1, fillColor=fillColor)
+ elif (symbolType == "square"):
+ canvas.drawRect(x1=item[0]-sizeModifier+1,y1=item[1]-sizeModifier-4, x2=item[0]+sizeModifier+2,y2=item[1]+sizeModifier-3, edgeColor=symbolColor, edgeWidth=1, fillColor=fillColor)
+ elif (symbolType == "diamond" and filled != "yes"):
+ canvas.drawString(",", item[0]-canvas.stringWidth(",",font=symbolFont)/2+2, item[1]+6, font=symbolFont, color=symbolColor)
+ elif (symbolType == "diamond" and filled == "yes"):
+ canvas.drawString("D", item[0]-canvas.stringWidth("D",font=symbolFont)/2+2, item[1]+6, font=symbolFont, color=symbolColor)
+ elif symbolType == "4-star":
+ canvas.drawString("l", item[0]-canvas.stringWidth("l",font=symbolFont)/2+1, item[1]+3, font=symbolFont, color=symbolColor)
+ elif symbolType == "3-star":
+ canvas.drawString("k", item[0]-canvas.stringWidth("k",font=symbolFont)/2+1, item[1]+3, font=symbolFont, color=symbolColor)
+ else:
+ canvas.drawCross(item[0],item[1]-2,color=symbolColor, size=sizeModifier+2)
+
+ if showLabel and dataLabel:
+ if (symbolType == "vertRect" or symbolType == "diamond"):
+ labelGap = 15
+ elif (symbolType == "4-star" or symbolType == "3-star"):
+ labelGap = 12
+ else:
+ labelGap = 11
+ canvas.drawString(dataLabel[i], item[0]- canvas.stringWidth(dataLabel[i],
+ font=labelFont)/2 + 1, item[1]+(labelGap+sizeModifier+(idFontSize-12)), font=labelFont, color=idColor)
+
+ #draw scale
+ scaleFont=pid.Font(ttf="cour",size=16,bold=1)
+
+
+ x=xLow
+ for i in range(stepX+1):
+ xc=xLeftOffset+(x-xLow)*xScale
+ if ((x == 0) & (rank == 1)):
+ pass
+ else:
+ canvas.drawLine(xc,yTopOffset+plotHeight + bufferSpace,xc,yTopOffset+plotHeight+5 + bufferSpace, color=axesColor)
+ strX = cformat(d=x, rank=rank)
+ if ((strX == "0") & (rank == 1)):
+ pass
+ else:
+ canvas.drawString(strX,xc-canvas.stringWidth(strX,font=scaleFont)/2,yTopOffset+plotHeight+20 + bufferSpace,font=scaleFont)
+ x+= (xTop - xLow)/stepX
+
+ y=yLow
+ for i in range(stepY+1):
+ yc=yTopOffset+plotHeight-(y-yLow)*yScale
+ if ((y == 0) & (rank == 1)):
+ pass
+ else:
+ canvas.drawLine(xLeftOffset - bufferSpace,yc,xLeftOffset-5 - bufferSpace,yc, color=axesColor)
+ strY = cformat(d=y, rank=rank)
+ if ((strY == "0") & (rank == 1)):
+ pass
+ else:
+ canvas.drawString(strY,xLeftOffset-canvas.stringWidth(strY,font=scaleFont)- 10 - bufferSpace,yc+4,font=scaleFont)
+ y+= (yTop - yLow)/stepY
+
+ #draw label
+
+ labelFont=pid.Font(ttf="verdana",size=canvas.size[0]/45,bold=0)
+ titleFont=pid.Font(ttf="verdana",size=canvas.size[0]/40,bold=0)
+
+ if (rank == 1 and not title):
+ canvas.drawString("Spearman Rank Correlation", xLeftOffset-canvas.size[0]*.025+(plotWidth-canvas.stringWidth("Spearman Rank Correlation",font=titleFont))/2.0,
+ 25,font=titleFont,color=labelColor)
+ elif (rank == 0 and not title):
+ canvas.drawString("Pearson Correlation", xLeftOffset-canvas.size[0]*.025+(plotWidth-canvas.stringWidth("Pearson Correlation",font=titleFont))/2.0,
+ 25,font=titleFont,color=labelColor)
+
+ if XLabel:
+ canvas.drawString(XLabel,xLeftOffset+(plotWidth-canvas.stringWidth(XLabel,font=labelFont))/2.0,
+ yTopOffset+plotHeight+yBottomOffset-25,font=labelFont,color=labelColor)
+
+ if YLabel:
+ canvas.drawString(YLabel, xLeftOffset-65, yTopOffset+plotHeight- (plotHeight-canvas.stringWidth(YLabel,font=labelFont))/2.0,
+ font=labelFont,color=labelColor,angle=90)
+
+ labelFont=pid.Font(ttf="verdana",size=20,bold=0)
+ if title:
+ canvas.drawString(title,xLeftOffset+(plotWidth-canvas.stringWidth(title,font=labelFont))/2.0,
+ 20,font=labelFont,color=labelColor)
+
+ if fitcurve:
+ import sys
+ sys.argv = [ "mod_python" ]
+ #from numarray import linear_algebra as la
+ #from numarray import ones, array, dot, swapaxes
+ fitYY = array(dataYPrimary)
+ fitXX = array([ones(len(dataXPrimary)),dataXPrimary])
+ AA = dot(fitXX,swapaxes(fitXX,0,1))
+ BB = dot(fitXX,fitYY)
+ bb = la.linear_least_squares(AA,BB)[0]
+
+ xc1 = xLeftOffset
+ yc1 = yTopOffset+plotHeight-(bb[0]+bb[1]*xLow-yLow)*yScale
+ if yc1 > yTopOffset+plotHeight:
+ yc1 = yTopOffset+plotHeight
+ xc1 = (yLow-bb[0])/bb[1]
+ xc1=(xc1-xLow)*xScale+xLeftOffset
+ elif yc1 < yTopOffset:
+ yc1 = yTopOffset
+ xc1 = (yTop-bb[0])/bb[1]
+ xc1=(xc1-xLow)*xScale+xLeftOffset
+ else:
+ pass
+
+ xc2 = xLeftOffset + plotWidth
+ yc2 = yTopOffset+plotHeight-(bb[0]+bb[1]*xTop-yLow)*yScale
+ if yc2 > yTopOffset+plotHeight:
+ yc2 = yTopOffset+plotHeight
+ xc2 = (yLow-bb[0])/bb[1]
+ xc2=(xc2-xLow)*xScale+xLeftOffset
+ elif yc2 < yTopOffset:
+ yc2 = yTopOffset
+ xc2 = (yTop-bb[0])/bb[1]
+ xc2=(xc2-xLow)*xScale+xLeftOffset
+ else:
+ pass
+
+ canvas.drawLine(xc1 - bufferSpace,yc1 + bufferSpace,xc2,yc2,color=lineColor)
+ if lineSize == "medium":
+ canvas.drawLine(xc1 - bufferSpace,yc1 + bufferSpace+1,xc2,yc2+1,color=lineColor)
+ if lineSize == "thick":
+ canvas.drawLine(xc1 - bufferSpace,yc1 + bufferSpace+1,xc2,yc2+1,color=lineColor)
+ canvas.drawLine(xc1 - bufferSpace,yc1 + bufferSpace-1,xc2,yc2-1,color=lineColor)
+
+
+ if displayR:
+ labelFont=pid.Font(ttf="trebuc",size=canvas.size[0]/60,bold=0)
+ NNN = len(dataX)
+ corr = webqtlUtil.calCorrelation(dataXPrimary,dataYPrimary,NNN)[0]
+
+ if NNN < 3:
+ corrPValue = 1.0
+ else:
+ if abs(corr) >= 1.0:
+ corrPValue = 0.0
+ else:
+ ZValue = 0.5*log((1.0+corr)/(1.0-corr))
+ ZValue = ZValue*sqrt(NNN-3)
+ corrPValue = 2.0*(1.0 - reaper.normp(abs(ZValue)))
+
+ NStr = "N = %d" % NNN
+ strLenN = canvas.stringWidth(NStr,font=labelFont)
+
+ if rank == 1:
+ if corrPValue < 0.0000000000000001:
+ corrStr = "Rho = %1.3f P < 1.00 E-16" % (corr)
+ else:
+ corrStr = "Rho = %1.3f P = %3.2E" % (corr, corrPValue)
+ else:
+ if corrPValue < 0.0000000000000001:
+ corrStr = "r = %1.3f P < 1.00 E-16" % (corr)
+ else:
+ corrStr = "r = %1.3f P = %3.2E" % (corr, corrPValue)
+ strLen = canvas.stringWidth(corrStr,font=labelFont)
+
+ canvas.drawString(NStr,xLeftOffset,yTopOffset-10,font=labelFont,color=labelColor)
+ canvas.drawString(corrStr,xLeftOffset+plotWidth-strLen,yTopOffset-10,font=labelFont,color=labelColor)
+
+ return xCoord
+
+def plotXYSVG(drawSpace, dataX, dataY, rank=0, dataLabel=[], plotColor = "black", axesColor="black", labelColor="black", symbolColor="red", XLabel=None, YLabel=None, title=None, fitcurve=None, connectdot=1, displayR=None, loadingPlot = 0, offset= (80, 20, 40, 60), zoom = 1, specialCases=[], showLabel = 1):
+ 'displayR : correlation scatter plot, loadings : loading plot'
+
+ dataXRanked, dataYRanked = webqtlUtil.calRank(dataX, dataY, len(dataX))
+
+ # Switching Ranked and Unranked X and Y values if a Spearman Rank Correlation
+ if rank == 0:
+ dataXPrimary = dataX
+ dataYPrimary = dataY
+ dataXAlt = dataXRanked
+ dataYAlt = dataYRanked
+
+ else:
+ dataXPrimary = dataXRanked
+ dataYPrimary = dataYRanked
+ dataXAlt = dataX
+ dataYAlt = dataY
+
+
+
+ xLeftOffset, xRightOffset, yTopOffset, yBottomOffset = offset
+ plotWidth = drawSpace.attributes['width'] - xLeftOffset - xRightOffset
+ plotHeight = drawSpace.attributes['height'] - yTopOffset - yBottomOffset
+ if plotHeight<=0 or plotWidth<=0:
+ return
+ if len(dataXPrimary) < 1 or len(dataXPrimary) != len(dataYPrimary) or (dataLabel and len(dataXPrimary) != len(dataLabel)):
+ return
+
+ max_X=max(dataXPrimary)
+ min_X=min(dataXPrimary)
+ max_Y=max(dataYPrimary)
+ min_Y=min(dataYPrimary)
+
+ #for some reason I forgot why I need to do this
+ if loadingPlot:
+ min_X = min(-0.1,min_X)
+ max_X = max(0.1,max_X)
+ min_Y = min(-0.1,min_Y)
+ max_Y = max(0.1,max_Y)
+
+ xLow, xTop, stepX=detScale(min_X,max_X)
+ yLow, yTop, stepY=detScale(min_Y,max_Y)
+ xScale = plotWidth/(xTop-xLow)
+ yScale = plotHeight/(yTop-yLow)
+
+ #draw drawing region
+ r = svg.rect(xLeftOffset, yTopOffset, plotWidth, plotHeight, 'none', axesColor, 1)
+ drawSpace.addElement(r)
+
+ #calculate data points
+ data = map(lambda X, Y: (X, Y), dataXPrimary, dataYPrimary)
+ xCoord = map(lambda X, Y: ((X-xLow)*xScale + xLeftOffset, yTopOffset+plotHeight-(Y-yLow)*yScale), dataXPrimary, dataYPrimary)
+ labelFontF = "verdana"
+ labelFontS = 11
+
+ if loadingPlot:
+ xZero = -xLow*xScale+xLeftOffset
+ yZero = yTopOffset+plotHeight+yLow*yScale
+ for point in xCoord:
+ drawSpace.addElement(svg.line(xZero,yZero,point[0],point[1], "red", 1))
+ else:
+ if connectdot:
+ pass
+ #drawSpace.drawPolygon(xCoord,edgeColor=plotColor,closed=0)
+ else:
+ pass
+
+ for i, item in enumerate(xCoord):
+ if dataLabel and dataLabel[i] in specialCases:
+ drawSpace.addElement(svg.rect(item[0]-3, item[1]-3, 6, 6, "none", "green", 0.5))
+ #drawSpace.drawCross(item[0],item[1],color=pid.blue,size=5)
+ else:
+ drawSpace.addElement(svg.line(item[0],item[1]+5,item[0],item[1]-5,symbolColor,1))
+ drawSpace.addElement(svg.line(item[0]+5,item[1],item[0]-5,item[1],symbolColor,1))
+ if showLabel and dataLabel:
+ pass
+ drawSpace.addElement(svg.text(item[0], item[1]+14, dataLabel[i], labelFontS,
+ labelFontF, text_anchor="middle", style="stroke:blue;stroke-width:0.5;"))
+ #canvas.drawString(, item[0]- canvas.stringWidth(dataLabel[i],
+ # font=labelFont)/2, item[1]+14, font=labelFont, color=pid.blue)
+
+ #draw scale
+ #scaleFont=pid.Font(ttf="cour",size=14,bold=1)
+ x=xLow
+ for i in range(stepX+1):
+ xc=xLeftOffset+(x-xLow)*xScale
+ drawSpace.addElement(svg.line(xc,yTopOffset+plotHeight,xc,yTopOffset+plotHeight+5, axesColor, 1))
+ strX = cformat(d=x, rank=rank)
+ drawSpace.addElement(svg.text(xc,yTopOffset+plotHeight+20,strX,13, "courier", text_anchor="middle"))
+ x+= (xTop - xLow)/stepX
+
+ y=yLow
+ for i in range(stepY+1):
+ yc=yTopOffset+plotHeight-(y-yLow)*yScale
+ drawSpace.addElement(svg.line(xLeftOffset,yc,xLeftOffset-5,yc, axesColor, 1))
+ strY = cformat(d=y, rank=rank)
+ drawSpace.addElement(svg.text(xLeftOffset-10,yc+5,strY,13, "courier", text_anchor="end"))
+ y+= (yTop - yLow)/stepY
+
+ #draw label
+ labelFontF = "verdana"
+ labelFontS = 17
+ if XLabel:
+ drawSpace.addElement(svg.text(xLeftOffset+plotWidth/2.0,
+ yTopOffset+plotHeight+yBottomOffset-10,XLabel,
+ labelFontS, labelFontF, text_anchor="middle"))
+
+ if YLabel:
+ drawSpace.addElement(svg.text(xLeftOffset-50,
+ yTopOffset+plotHeight/2,YLabel,
+ labelFontS, labelFontF, text_anchor="middle", style="writing-mode:tb-rl", transform="rotate(270 %d %d)" % (xLeftOffset-50, yTopOffset+plotHeight/2)))
+ #drawSpace.drawString(YLabel, xLeftOffset-50, yTopOffset+plotHeight- (plotHeight-drawSpace.stringWidth(YLabel,font=labelFont))/2.0,
+ # font=labelFont,color=labelColor,angle=90)
+
+
+ if fitcurve:
+ sys.argv = [ "mod_python" ]
+ #from numarray import linear_algebra as la
+ #from numarray import ones, array, dot, swapaxes
+ fitYY = array(dataYPrimary)
+ fitXX = array([ones(len(dataXPrimary)),dataXPrimary])
+ AA = dot(fitXX,swapaxes(fitXX,0,1))
+ BB = dot(fitXX,fitYY)
+ bb = la.linear_least_squares(AA,BB)[0]
+
+ xc1 = xLeftOffset
+ yc1 = yTopOffset+plotHeight-(bb[0]+bb[1]*xLow-yLow)*yScale
+ if yc1 > yTopOffset+plotHeight:
+ yc1 = yTopOffset+plotHeight
+ xc1 = (yLow-bb[0])/bb[1]
+ xc1=(xc1-xLow)*xScale+xLeftOffset
+ elif yc1 < yTopOffset:
+ yc1 = yTopOffset
+ xc1 = (yTop-bb[0])/bb[1]
+ xc1=(xc1-xLow)*xScale+xLeftOffset
+ else:
+ pass
+
+ xc2 = xLeftOffset + plotWidth
+ yc2 = yTopOffset+plotHeight-(bb[0]+bb[1]*xTop-yLow)*yScale
+ if yc2 > yTopOffset+plotHeight:
+ yc2 = yTopOffset+plotHeight
+ xc2 = (yLow-bb[0])/bb[1]
+ xc2=(xc2-xLow)*xScale+xLeftOffset
+ elif yc2 < yTopOffset:
+ yc2 = yTopOffset
+ xc2 = (yTop-bb[0])/bb[1]
+ xc2=(xc2-xLow)*xScale+xLeftOffset
+ else:
+ pass
+
+ drawSpace.addElement(svg.line(xc1,yc1,xc2,yc2,"green", 1))
+
+ if displayR:
+ labelFontF = "trebuc"
+ labelFontS = 14
+ NNN = len(dataX)
+
+ corr = webqtlUtil.calCorrelation(dataXPrimary,dataYPrimary,NNN)[0]
+
+ if NNN < 3:
+ corrPValue = 1.0
+ else:
+ if abs(corr) >= 1.0:
+ corrPValue = 0.0
+ else:
+ ZValue = 0.5*log((1.0+corr)/(1.0-corr))
+ ZValue = ZValue*sqrt(NNN-3)
+ corrPValue = 2.0*(1.0 - reaper.normp(abs(ZValue)))
+
+ NStr = "N of Cases=%d" % NNN
+
+ if rank == 1:
+ corrStr = "Spearman's r=%1.3f P=%3.2E" % (corr, corrPValue)
+ else:
+ corrStr = "Pearson's r=%1.3f P=%3.2E" % (corr, corrPValue)
+
+ drawSpace.addElement(svg.text(xLeftOffset,yTopOffset-10,NStr,
+ labelFontS, labelFontF, text_anchor="start"))
+ drawSpace.addElement(svg.text(xLeftOffset+plotWidth,yTopOffset-25,corrStr,
+ labelFontS, labelFontF, text_anchor="end"))
+ """
+ """
+ return
+
+
+# This function determines the scale of the plot
+def detScaleOld(min,max):
+ if min>=max:
+ return None
+ elif min == -1.0 and max == 1.0:
+ return [-1.2,1.2,12]
+ else:
+ a=max-min
+ b=floor(log10(a))
+ c=pow(10.0,b)
+ if a < c*5.0:
+ c/=2.0
+ #print a,b,c
+ low=c*floor(min/c)
+ high=c*ceil(max/c)
+ return [low,high,round((high-low)/c)]
+
+def detScale(min=0,max=0,bufferSpace=3):
+
+ if min>=max:
+ return None
+ elif min == -1.0 and max == 1.0:
+ return [-1.2,1.2,12]
+ else:
+ a=max-min
+ if max != 0:
+ max += 0.1*a
+ if min != 0:
+ if min > 0 and min < 0.1*a:
+ min = 0.0
+ else:
+ min -= 0.1*a
+ a=max-min
+ b=floor(log10(a))
+ c=pow(10.0,b)
+ low=c*floor(min/c)
+ high=c*ceil(max/c)
+ n = round((high-low)/c)
+ div = 2.0
+ while n < 5 or n > 15:
+ if n < 5:
+ c /= div
+ else:
+ c *= div
+ if div == 2.0:
+ div =5.0
+ else:
+ div =2.0
+ low=c*floor(min/c)
+ high=c*ceil(max/c)
+ n = round((high-low)/c)
+
+ return [low,high,n]
+
+
+
+def colorSpectrumOld(n):
+ if n == 1:
+ return [pid.Color(1,0,0)]
+ elif n == 2:
+ return [pid.Color(1,0,0),pid.Color(0,0,1)]
+ elif n == 3:
+ return [pid.Color(1,0,0),pid.Color(0,1,0),pid.Color(0,0,1)]
+ else:
+ step = 2.0/(n-1)
+ red = 1.0
+ green = 0.0
+ blue = 0.0
+ colors = [pid.Color(red,green,blue)]
+ i = 1
+ greenpeak = 0
+ while i < n:
+ if red >= step:
+ red -= step
+ green += step
+ if green >= 1.0:
+ greenpeak = 1
+ blue += green -1.0
+ green = 1.0
+ else:
+ red = 0.0
+ if greenpeak:
+ green -= step
+ blue += step
+ else:
+ green += step
+ if green >= 1.0:
+ greenpeak = 1
+ blue += green -1.0
+ green = 2.0 -green
+ elif green < 0.0:
+ green = 0.0
+ else:
+ pass
+ colors.append(pid.Color(red,green,blue))
+ i += 1
+ return colors
+
+
+
+
+def bluefunc(x):
+ return 1.0 / (1.0 + exp(-10*(x-0.6)))
+
+
+def redfunc(x):
+ return 1.0 / (1.0 + exp(10*(x-0.5)))
+
+def greenfunc(x):
+ return 1 - pow(redfunc(x+0.2),2) - bluefunc(x-0.3)
+
+def colorSpectrum(n=100):
+ multiple = 10
+ if n == 1:
+ return [pid.Color(1,0,0)]
+ elif n == 2:
+ return [pid.Color(1,0,0),pid.Color(0,0,1)]
+ elif n == 3:
+ return [pid.Color(1,0,0),pid.Color(0,1,0),pid.Color(0,0,1)]
+ N = n*multiple
+ out = [None]*N;
+ for i in range(N):
+ x = float(i)/N
+ out[i] = pid.Color(redfunc(x), greenfunc(x), bluefunc(x));
+ out2 = [out[0]]
+ step = N/float(n-1)
+ j = 0
+ for i in range(n-2):
+ j += step
+ out2.append(out[int(j)])
+ out2.append(out[-1])
+ return out2
+
+
+def colorSpectrumSVG(n=100):
+ multiple = 10
+ if n == 1:
+ return ["rgb(255,0,0)"]
+ elif n == 2:
+ return ["rgb(255,0,0)","rgb(0,0,255)"]
+ elif n == 3:
+ return ["rgb(255,0,0)","rgb(0,255,0)","rgb(0,0,255)"]
+ N = n*multiple
+ out = [None]*N;
+ for i in range(N):
+ x = float(i)/N
+ out[i] = "rgb(%d, %d, %d)" % (redfunc(x)*255, greenfunc(x)*255, bluefunc(x)*255);
+ out2 = [out[0]]
+ step = N/float(n-1)
+ j = 0
+ for i in range(n-2):
+ j += step
+ out2.append(out[int(j)])
+ out2.append(out[-1])
+ return out2
+
+
+def BWSpectrum(n=100):
+ multiple = 10
+ if n == 1:
+ return [pid.Color(0,0,0)]
+ elif n == 2:
+ return [pid.Color(0,0,0),pid.Color(1,1,1)]
+ elif n == 3:
+ return [pid.Color(0,0,0),pid.Color(0.5,0.5,0.5),pid.Color(1,1,1)]
+
+ step = 1.0/n
+ x = 0.0
+ out = []
+ for i in range(n):
+ out.append(pid.Color(x,x,x));
+ x += step
+ return out
generated by cgit v1.2.3 (git 2.44.0) at 2024-10-19 19:51:59 +0000