def mean(inList, null = "NA"):
    """Calculates mean"""
    
    cList = mData.floatList(inList)
    if len(cList) == 0:
        mean = null
    else:
        mean = sum(cList)/len(cList)
    return (mean)
def mean(inList, null="NA"):
    """Calculates mean"""

    cList = mData.floatList(inList)
    if len(cList) == 0:
        mean = null
    else:
        mean = sum(cList) / len(cList)
    return (mean)
def quartiles(inList):
    """Returns the 25/50/75 quartiles"""
    
    cList = mData.floatList(inList)
    cList.sort()
    if len(cList) < 2:
        boundaries = ["NA", "NA", "NA"]
    else:
        boundaries = [median(cList[:len(cList)/2]), median(cList), median(cList[len(cList)/2:])]
    return(boundaries)
def median(inList):
    """Calculates median"""
    
    cList = mData.floatList(inList)
    cList.sort()
    if len(cList) == 0:
        median = "NA"
    else:
        if len(cList)%2 == 1:
            median = cList[len(cList)/2]
        else:
            median = (cList[len(cList)/2]+cList[(len(cList)/2)-1])/2.0
    return(median)
def median(inList):
    """Calculates median"""

    cList = mData.floatList(inList)
    cList.sort()
    if len(cList) == 0:
        median = "NA"
    else:
        if len(cList) % 2 == 1:
            median = cList[len(cList) / 2]
        else:
            median = (cList[len(cList) / 2] +
                      cList[(len(cList) / 2) - 1]) / 2.0
    return (median)
def quartiles(inList):
    """Returns the 25/50/75 quartiles"""

    cList = mData.floatList(inList)
    cList.sort()
    if len(cList) < 2:
        boundaries = ["NA", "NA", "NA"]
    else:
        boundaries = [
            median(cList[:len(cList) / 2]),
            median(cList),
            median(cList[len(cList) / 2:])
        ]
    return (boundaries)
예제 #7
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def mean_std(inList, sample=True):
    """Calculates mean and std"""
    cList = mData.floatList(inList)
    if len(cList) == 0:
        mean = "NA"
        std = "NA"
    else:
        mean = sum(cList) / float(len(cList))
        std = 0.0
        for i in cList:
            std += (i - mean)**2
        if len(cList) > 1:
            if sample:
                std = math.sqrt(std / (len(cList) - 1))
            else:
                std = math.sqrt(std / len(cList))
        else:
            std = 0.0
    return (mean, std)
예제 #8
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def mean_std(inList, sample = True):
    """Calculates mean and std"""
    cList = mData.floatList(inList)
    if len(cList) == 0:
        mean = "NA"
        std = "NA"
    else:
        mean = sum(cList)/float(len(cList))
        std = 0.0
        for i in cList:
            std += (i-mean)**2
        if len(cList) > 1:
            if sample:
                std = math.sqrt(std/(len(cList)-1))
            else:
                std = math.sqrt(std/len(cList))
        else:
            std = 0.0
    return(mean, std)
def getCohortMinMaxValues(featureList, sampleList, circleData):
	"""Get the minVal and maxVal of sample scores among the specified featureList for the ring/dataset."""
	minValList = []
	maxValList = []

	for ring in xrange(len(circleData)):
		ringVals = []

		# get ring values in effort to find min/max values for each *ring*
		for sample in sampleList:
			if sample in circleData[ring]:
				for feature in featureList:
					if feature in circleData[ring][sample]:
						ringVals.append(circleData[ring][sample][feature])
					elif "*" in circleData[ring][sample]:
						ringVals.append(circleData[ring][sample]["*"])
	
		# find the min & max sample scores for this ring in this feature
		floatList = mData.floatList(ringVals)

		minValList.append(min([-0.01] + floatList))
		maxValList.append(max([0.01] + floatList))

	return (minValList, maxValList)
예제 #10
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def getCohortMinMaxValues(featureList, sampleList, circleData):
    """Get the minVal and maxVal of sample scores among the specified featureList for the ring/dataset."""
    minValList = []
    maxValList = []

    for ring in xrange(len(circleData)):
        ringVals = []

        # get ring values in effort to find min/max values for each *ring*
        for sample in sampleList:
            if sample in circleData[ring]:
                for feature in featureList:
                    if feature in circleData[ring][sample]:
                        ringVals.append(circleData[ring][sample][feature])
                    elif "*" in circleData[ring][sample]:
                        ringVals.append(circleData[ring][sample]["*"])

        # find the min & max sample scores for this ring in this feature
        floatList = mData.floatList(ringVals)

        minValList.append(min([-0.01] + floatList))
        maxValList.append(max([0.01] + floatList))

    return (minValList, maxValList)
예제 #11
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     ## cohort png
     if len(orderFiles) > 0:
         imgFile = "%s/Cohort.png" % (outputDir)
         label = "Cohort"
         centerCol = rgb(255, 255, 255).tohex()
         circleCols = []
         for i in range(len(orderData)):
             ringCols = []
             ringVals = []
             for sample in samples:
                 if sample in orderData[i]:
                     if orderFeature in orderData[i][sample]:
                         ringVals.append(orderData[i][sample][orderFeature])
                     elif "*" in orderData[i][sample]:
                         ringVals.append(orderData[i][sample]["*"])
             minVal = min([-0.01]+mData.floatList(ringVals))
             maxVal = max([0.01]+mData.floatList(ringVals))
             for sample in samples:
                 if sample in orderData[i]:
                     if orderFeature in orderData[i][sample]:
                         ringCols.append(getColor(orderData[i][sample][orderFeature], minVal, maxVal, minColor = orderColors[i][0], zeroColor = orderColors[i][1], maxColor = orderColors[i][2]))
                     elif "*" in orderData[i][sample]:
                         ringCols.append(getColor(orderData[i][sample]["*"], minVal, maxVal, minColor = orderColors[i][0], zeroColor = orderColors[i][1], maxColor = orderColors[i][2]))
                     else:
                         ringCols.append(rgb(200, 200, 200).tohex())
                 else:
                     ringCols.append(rgb(200, 200, 200).tohex())
             circleCols.append(ringCols)
         plotCircle(imgFile, label = label, centerCol = centerCol, circleCols = circleCols, innerRadTotal=0.2, outerRadTotal=0.5, width = 5)
     
 ## plot images
def cli_routine(outputDir, circleFiles, orderFiles, sampleFile, featureFile, orderFeature, centerFile, colorscaleFile, printLabel, verbose, cohortMinMax=False, purpleHack = True):
	"""Routine for program execution via command-line."""
	# I've tried not to touch this method as much as possible.
	# I don't want to break the way it was working for Sam Ng.
	# chrisw
	
	## execute
	samples = []
	features = []
	if sampleFile != None:
		samples = mData.rList(sampleFile)
	if featureFile != None:
		features = mData.rList(featureFile)
	# end section for getting lists of samples and features
	
	## read circleFiles
	# circleData is a list of dict[col][row]=score from each circleFile
	circleData = []
	# circleColorsPalette is a list of (minColor),(zeroColor),(maxColor)
	circleColorsPalette = []

	## read colorscaleFile
	# the format is as follows - header compulsory:
	# min/max	color coding	color1		color2		color 3
	# -2,2		rgb		155,155,155	255,255,255	0,0,0,
	# -		rgb		155,0,155	255,0,255	0,0,0,
	# the "color format" is intended to support more color format, as I have 
	# seen the html-colors in the code.
	# Michael ([email protected])
	colorscaleData = None
	if colorscaleFile != None:

		if cohortMinMax:
			log("WARNING: The -k option overrides -m")

		colorscaleData = mData.retRows(colorscaleFile,aslist=True)
		line=1 
		for cs in colorscaleData:
			line = line + 1
			if len(cs) != 5:
				log("ERROR: color scale needs five fields: datapoints, colorcoding(rgb) and three colors\n", die = True)
			try:
				cs[0] =  [float(x) for x in cs[0].split(",")]
			except ValueError:
				pass
			if len(cs[0]) != 2 and cs[0] != "-":
				print cs[0]
				log("ERROR: Two data points or dash needed for color scale\n", die = True)
			if cs[1].lower() == "rgb":
				try:
					cs[2] =  rgb(*[float(x) for x in cs[2].split(",")])
					cs[3] =  rgb(*[float(x) for x in cs[3].split(",")])
					cs[4] =  rgb(*[float(x) for x in cs[4].split(",")])
				except TypeError:
						log("ERROR: RGB needs three values on line " + str(line) + "\n", die = True)
				except ValueError:
						log("ERROR: RGB color not correctly defined on line " + str(line) + "\n", die=True)
			else:
				log("ERROR: Unknown color coding on line " + str(line) + ": " + str(cs[1]) + "\n", die=True)


	for i in xrange(len(circleFiles)):
		# get data, samples, and features from each circleFile
		# data is a dict[col][row]=score
		# cols is a list of sample names
		# features is a list of feature names
		(data, cols, rows) = mData.rCRSData(circleFiles[i], retFeatures=True)
		circleData.append(data)
		minCol = lightBlueRGB
		zerCol = whiteRGB
		maxCol = redRGB
		if colorscaleFile != None and i<len(colorscaleData):
			#get colors from specified colorscaleFile
			minCol = colorscaleData[i][2]
			zerCol = colorscaleData[i][3]
			maxCol = colorscaleData[i][4]

		# special cases for -meth and -mut
#		if circleFiles[i].endswith("meth"):
#			maxCol = blueRGB
#			minCol = redRGB
#			log("Color: meth\n")
#		elif circleFiles[i].endswith("mut"):
#			maxCol = blackRGB
#			minCol = whiteRGB
#			log("Color: mut\n")

		circleColorsPalette.append((minCol, zerCol, maxCol))

		# if no sampleFile/featureFile, default to using samples/features from circleFiles
		if sampleFile == None:
			samples = list(set(cols) | set(samples))
		if featureFile == None:
			features = list(set(rows) | set(features))
	# end section for reading circleFiles

	## read centerFile
	centerData = None
	if centerFile != None:
		centerData = mData.r2Col(centerFile, header=True)

	## sort
	if orderFeature != None:
		if len(orderFiles) > 0:
			orderData = []
			orderColors = []
			for i in xrange(len(orderFiles)):
				orderData.append(mData.rCRSData(orderFiles[i]))
				minCol = whiteRGB
				zerCol = whiteRGB
				maxCol = blackRGB
				orderColors.append((minCol, zerCol, maxCol))
		else:
			orderData = circleData

		# sort samples based on sample score in orderData
		# priority of sorting determined by orderFiles parameter
		samples.sort(lambda x, y: scmp(x, y, orderFeature, orderData))

		## cohort png
		# cgi will probably not use orderFiles
		if len(orderFiles) > 0:
			imgFile = "%s/Cohort.png" % (outputDir)
			label = "Cohort"
			centerCol = whiteRGB.tohex()
			cohortCircleCols = []
			for i in xrange(len(orderData)):
				ringCols = []
				ringVals = []
				for sample in samples:
					if sample in orderData[i]:
						if orderFeature in orderData[i][sample]:
							ringVals.append(orderData[i][sample][orderFeature])
						elif "*" in orderData[i][sample]:
							ringVals.append(orderData[i][sample]["*"])
				minVal = min([-0.01] + mData.floatList(ringVals))
				maxVal = max([0.01] + mData.floatList(ringVals))
				for sample in samples:
					if sample in orderData[i]:
						if orderFeature in orderData[i][sample]:
							ringCols.append(getColor(orderData[i][sample][orderFeature], minVal, maxVal, minColor=orderColors[i][0], zeroColor=orderColors[i][1], maxColor=orderColors[i][2]))
						elif "*" in orderData[i][sample]:
							ringCols.append(getColor(orderData[i][sample]["*"], minVal, maxVal, minColor=orderColors[i][0], zeroColor=orderColors[i][1], maxColor=orderColors[i][2]))
						else:
							ringCols.append(greyRGB.tohex())
					else:
						ringCols.append(greyRGB.tohex())
				cohortCircleCols.append(ringCols)
			plotCircle(imgFile, label=label, centerCol=centerCol, circleCols=cohortCircleCols, innerRadTotal=0.2, outerRadTotal=0.5, width=5)
	# end section for sample ordering

	## plot images
	if centerData != None:
		centerDataFloatList = mData.floatList(centerData.values())
		centerDataMinVal = min([-0.01] + centerDataFloatList)
		centerDataMaxVal = max([0.01] + centerDataFloatList)

	# get min/max values for datasets
	if cohortMinMax:
		(minValList, maxValList) = getCohortMinMaxValues(features, samples, circleData)
	else:
		(minValList, maxValList) = (None, None)

	if colorscaleData != None:
		(minValList, maxValList) = getColorScaleMinMaxValues(minValList, maxValList, len(circleData), colorscaleData)

	for feature in features:
		log("Drawing %s\n" % (feature))
		centerColHex = None
		if centerData != None:
			if feature in centerData:
				centerColHex = getColor(centerData[feature], centerDataMinVal, centerDataMaxVal, minColor=lightBlueRGB, zeroColor=whiteRGB, purple0Hack=purpleHack)
				
		imgFile = "%s/%s.png" % (outputDir, re.sub("[/:]", "_", feature))

		label = ""
		if printLabel:
			label = feature

		image_width = 5.0

		drawCircleImageForFeature(feature, samples, label, imgFile, circleData, circleColorsPalette, width=image_width, centerColHex=centerColHex, minValList=minValList, maxValList=maxValList, purple0Hack=purpleHack)

	for sample in samples:
		log("ordered samples: %s\n" % (sample))
def drawCircleImageForFeature(feature, samples, label, imgFile, circleData, circleColors, centerColHex=None, width=5, minValList=None, maxValList=None, purple0Hack=False):
	"""Draw a circle map image and write it to a file."""
	# feature - feature to draw image for. This is some kind of concept: for example, a gene.
	# samples - sample names of data
	# label - label to use in image
	# imgFile - file object to which image will be written
	# circleData - data struct containing sample data for features.  It is a list of dict[col][row]=score .
	# circleColors - a list of (minColor),(zeroColor),(maxColor)
	# centerColHex - hex code for center color fill. If none, then make transparent center.

	# centerCol is the color of the center of the circleImage
#	centerCol = whiteRGB.tohex()
	
	# circleCols is a list.  Each member of the list represents a list of colors in a ring.
	circleCols = []

	# iterate through rings of data
	for ring in xrange(len(circleData)):
		ringCols = []

		# get minVal and maxVal
		minVal = None
		maxVal = None
		if minValList == None or maxValList == None or minValList[ring] == None or maxValList[ring] == None:
			ringVals = []
			
			# get ring values in effort to find min/max values for each *ring*
			for sample in samples:
				if sample in circleData[ring]:
					if feature in circleData[ring][sample]:
						ringVals.append(circleData[ring][sample][feature])
					elif "*" in circleData[ring][sample]:
						ringVals.append(circleData[ring][sample]["*"])

			# find the min & max sample scores for this ring in this feature
			floatList = mData.floatList(ringVals)
			minVal = min([-0.01] + floatList)
			maxVal = max([0.01] + floatList)
		else:
			minVal = minValList[ring]
			maxVal = maxValList[ring]

		# convert scores into colors
		for sample in samples:
			if sample in circleData[ring]:
				if feature in circleData[ring][sample]:
					ringCols.append(getColor(circleData[ring][sample][feature], minVal, maxVal, minColor=circleColors[ring][0], zeroColor=circleColors[ring][1], maxColor=circleColors[ring][2], purple0Hack=purple0Hack))
				elif "*" in circleData[ring][sample]:
					ringCols.append(getColor(circleData[ring][sample]["*"], minVal, maxVal, minColor=circleColors[ring][0], zeroColor=circleColors[ring][1], maxColor=circleColors[ring][2], purple0Hack=purple0Hack))
				else:
					# sample exists, but no score for the feature
					ringCols.append(greyRGB.tohex())
			else:
				# this sample not found in the sample data
				ringCols.append(greyRGB.tohex())

		# add the ring
		circleCols.append(ringCols)

	# plot the image
	plotCircle(imgFile, label=label, centerColHex=centerColHex, circleCols=circleCols, innerRadTotal=0.2, outerRadTotal=0.5, width=width)
예제 #14
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def cli_routine(outputDir,
                circleFiles,
                orderFiles,
                sampleFile,
                featureFile,
                orderFeature,
                centerFile,
                colorscaleFile,
                printLabel,
                verbose,
                cohortMinMax=False,
                purpleHack=True):
    """Routine for program execution via command-line."""
    # I've tried not to touch this method as much as possible.
    # I don't want to break the way it was working for Sam Ng.
    # chrisw

    ## execute
    samples = []
    features = []
    if sampleFile != None:
        samples = mData.rList(sampleFile)
    if featureFile != None:
        features = mData.rList(featureFile)
    # end section for getting lists of samples and features

    ## read circleFiles
    # circleData is a list of dict[col][row]=score from each circleFile
    circleData = []
    # circleColorsPalette is a list of (minColor),(zeroColor),(maxColor)
    circleColorsPalette = []

    ## read colorscaleFile
    # the format is as follows - header compulsory:
    # min/max	color coding	color1		color2		color 3
    # -2,2		rgb		155,155,155	255,255,255	0,0,0,
    # -		rgb		155,0,155	255,0,255	0,0,0,
    # the "color format" is intended to support more color format, as I have
    # seen the html-colors in the code.
    # Michael ([email protected])
    colorscaleData = None
    if colorscaleFile != None:

        if cohortMinMax:
            log("WARNING: The -k option overrides -m")

        colorscaleData = mData.retRows(colorscaleFile, aslist=True)
        line = 1
        for cs in colorscaleData:
            line = line + 1
            if len(cs) != 5:
                log("ERROR: color scale needs five fields: datapoints, colorcoding(rgb) and three colors\n",
                    die=True)
            try:
                cs[0] = [float(x) for x in cs[0].split(",")]
            except ValueError:
                pass
            if len(cs[0]) != 2 and cs[0] != "-":
                print cs[0]
                log("ERROR: Two data points or dash needed for color scale\n",
                    die=True)
            if cs[1].lower() == "rgb":
                try:
                    cs[2] = rgb(*[float(x) for x in cs[2].split(",")])
                    cs[3] = rgb(*[float(x) for x in cs[3].split(",")])
                    cs[4] = rgb(*[float(x) for x in cs[4].split(",")])
                except TypeError:
                    log("ERROR: RGB needs three values on line " + str(line) +
                        "\n",
                        die=True)
                except ValueError:
                    log("ERROR: RGB color not correctly defined on line " +
                        str(line) + "\n",
                        die=True)
            else:
                log("ERROR: Unknown color coding on line " + str(line) + ": " +
                    str(cs[1]) + "\n",
                    die=True)

    for i in xrange(len(circleFiles)):
        # get data, samples, and features from each circleFile
        # data is a dict[col][row]=score
        # cols is a list of sample names
        # features is a list of feature names
        (data, cols, rows) = mData.rCRSData(circleFiles[i], retFeatures=True)
        circleData.append(data)
        minCol = lightBlueRGB
        zerCol = whiteRGB
        maxCol = redRGB
        if colorscaleFile != None and i < len(colorscaleData):
            #get colors from specified colorscaleFile
            minCol = colorscaleData[i][2]
            zerCol = colorscaleData[i][3]
            maxCol = colorscaleData[i][4]

        # special cases for -meth and -mut


#		if circleFiles[i].endswith("meth"):
#			maxCol = blueRGB
#			minCol = redRGB
#			log("Color: meth\n")
#		elif circleFiles[i].endswith("mut"):
#			maxCol = blackRGB
#			minCol = whiteRGB
#			log("Color: mut\n")

        circleColorsPalette.append((minCol, zerCol, maxCol))

        # if no sampleFile/featureFile, default to using samples/features from circleFiles
        if sampleFile == None:
            samples = list(set(cols) | set(samples))
        if featureFile == None:
            features = list(set(rows) | set(features))
    # end section for reading circleFiles

    ## read centerFile
    centerData = None
    if centerFile != None:
        centerData = mData.r2Col(centerFile, header=True)

    ## sort
    if orderFeature != None:
        if len(orderFiles) > 0:
            orderData = []
            orderColors = []
            for i in xrange(len(orderFiles)):
                orderData.append(mData.rCRSData(orderFiles[i]))
                minCol = whiteRGB
                zerCol = whiteRGB
                maxCol = blackRGB
                orderColors.append((minCol, zerCol, maxCol))
        else:
            orderData = circleData

        # sort samples based on sample score in orderData
        # priority of sorting determined by orderFiles parameter
        samples.sort(lambda x, y: scmp(x, y, orderFeature, orderData))

        ## cohort png
        # cgi will probably not use orderFiles
        if len(orderFiles) > 0:
            imgFile = "%s/Cohort.png" % (outputDir)
            label = "Cohort"
            centerCol = whiteRGB.tohex()
            cohortCircleCols = []
            for i in xrange(len(orderData)):
                ringCols = []
                ringVals = []
                for sample in samples:
                    if sample in orderData[i]:
                        if orderFeature in orderData[i][sample]:
                            ringVals.append(orderData[i][sample][orderFeature])
                        elif "*" in orderData[i][sample]:
                            ringVals.append(orderData[i][sample]["*"])
                minVal = min([-0.01] + mData.floatList(ringVals))
                maxVal = max([0.01] + mData.floatList(ringVals))
                for sample in samples:
                    if sample in orderData[i]:
                        if orderFeature in orderData[i][sample]:
                            ringCols.append(
                                getColor(orderData[i][sample][orderFeature],
                                         minVal,
                                         maxVal,
                                         minColor=orderColors[i][0],
                                         zeroColor=orderColors[i][1],
                                         maxColor=orderColors[i][2]))
                        elif "*" in orderData[i][sample]:
                            ringCols.append(
                                getColor(orderData[i][sample]["*"],
                                         minVal,
                                         maxVal,
                                         minColor=orderColors[i][0],
                                         zeroColor=orderColors[i][1],
                                         maxColor=orderColors[i][2]))
                        else:
                            ringCols.append(greyRGB.tohex())
                    else:
                        ringCols.append(greyRGB.tohex())
                cohortCircleCols.append(ringCols)
            plotCircle(imgFile,
                       label=label,
                       centerCol=centerCol,
                       circleCols=cohortCircleCols,
                       innerRadTotal=0.2,
                       outerRadTotal=0.5,
                       width=5)
    # end section for sample ordering

    ## plot images
    if centerData != None:
        centerDataFloatList = mData.floatList(centerData.values())
        centerDataMinVal = min([-0.01] + centerDataFloatList)
        centerDataMaxVal = max([0.01] + centerDataFloatList)

    # get min/max values for datasets
    if cohortMinMax:
        (minValList,
         maxValList) = getCohortMinMaxValues(features, samples, circleData)
    else:
        (minValList, maxValList) = (None, None)

    if colorscaleData != None:
        (minValList,
         maxValList) = getColorScaleMinMaxValues(minValList, maxValList,
                                                 len(circleData),
                                                 colorscaleData)

    for feature in features:
        log("Drawing %s\n" % (feature))
        centerColHex = None
        if centerData != None:
            if feature in centerData:
                centerColHex = getColor(centerData[feature],
                                        centerDataMinVal,
                                        centerDataMaxVal,
                                        minColor=lightBlueRGB,
                                        zeroColor=whiteRGB,
                                        purple0Hack=purpleHack)

        imgFile = "%s/%s.png" % (outputDir, re.sub("[/:]", "_", feature))

        label = ""
        if printLabel:
            label = feature

        image_width = 5.0

        drawCircleImageForFeature(feature,
                                  samples,
                                  label,
                                  imgFile,
                                  circleData,
                                  circleColorsPalette,
                                  width=image_width,
                                  centerColHex=centerColHex,
                                  minValList=minValList,
                                  maxValList=maxValList,
                                  purple0Hack=purpleHack)

    for sample in samples:
        log("ordered samples: %s\n" % (sample))
예제 #15
0
def drawCircleImageForFeature(feature,
                              samples,
                              label,
                              imgFile,
                              circleData,
                              circleColors,
                              centerColHex=None,
                              width=5,
                              minValList=None,
                              maxValList=None,
                              purple0Hack=False):
    """Draw a circle map image and write it to a file."""
    # feature - feature to draw image for. This is some kind of concept: for example, a gene.
    # samples - sample names of data
    # label - label to use in image
    # imgFile - file object to which image will be written
    # circleData - data struct containing sample data for features.  It is a list of dict[col][row]=score .
    # circleColors - a list of (minColor),(zeroColor),(maxColor)
    # centerColHex - hex code for center color fill. If none, then make transparent center.

    # centerCol is the color of the center of the circleImage
    #	centerCol = whiteRGB.tohex()

    # circleCols is a list.  Each member of the list represents a list of colors in a ring.
    circleCols = []

    # iterate through rings of data
    for ring in xrange(len(circleData)):
        ringCols = []

        # get minVal and maxVal
        minVal = None
        maxVal = None
        if minValList == None or maxValList == None or minValList[
                ring] == None or maxValList[ring] == None:
            ringVals = []

            # get ring values in effort to find min/max values for each *ring*
            for sample in samples:
                if sample in circleData[ring]:
                    if feature in circleData[ring][sample]:
                        ringVals.append(circleData[ring][sample][feature])
                    elif "*" in circleData[ring][sample]:
                        ringVals.append(circleData[ring][sample]["*"])

            # find the min & max sample scores for this ring in this feature
            floatList = mData.floatList(ringVals)
            minVal = min([-0.01] + floatList)
            maxVal = max([0.01] + floatList)
        else:
            minVal = minValList[ring]
            maxVal = maxValList[ring]

        # convert scores into colors
        for sample in samples:
            if sample in circleData[ring]:
                if feature in circleData[ring][sample]:
                    ringCols.append(
                        getColor(circleData[ring][sample][feature],
                                 minVal,
                                 maxVal,
                                 minColor=circleColors[ring][0],
                                 zeroColor=circleColors[ring][1],
                                 maxColor=circleColors[ring][2],
                                 purple0Hack=purple0Hack))
                elif "*" in circleData[ring][sample]:
                    ringCols.append(
                        getColor(circleData[ring][sample]["*"],
                                 minVal,
                                 maxVal,
                                 minColor=circleColors[ring][0],
                                 zeroColor=circleColors[ring][1],
                                 maxColor=circleColors[ring][2],
                                 purple0Hack=purple0Hack))
                else:
                    # sample exists, but no score for the feature
                    ringCols.append(greyRGB.tohex())
            else:
                # this sample not found in the sample data
                ringCols.append(greyRGB.tohex())

        # add the ring
        circleCols.append(ringCols)

    # plot the image
    plotCircle(imgFile,
               label=label,
               centerColHex=centerColHex,
               circleCols=circleCols,
               innerRadTotal=0.2,
               outerRadTotal=0.5,
               width=width)