def drawRef2(rexps, exps, options, outfile, numCats):
options.out = outfile
fig, pdf = libplot.initImage( 8.0, 10.0, options )
axes = fig.add_axes( [0.12, 0.14, 0.85, 0.8] )
if len(rexps) < 1:
return
sampleNotherRefmapped = []
ref = ''
for sample in rexps:
if sample == 'average':
continue
e = rexps[sample]
ref = e.ref
sampleNotherRefmapped.append( (sample, e.total) )
otherRefName = libplot.properName( ref )
#Set title:
#axes.set_title("Mapability of C. Ref. in Comparison to %s" % otherRefName)
#HACK
axes.set_title("Mapability of C. Ref. in Comparison to GRCh37 haplotypes")
sampleNotherRefmapped = sorted( sampleNotherRefmapped, key=lambda item: item[1], reverse=True )
samples = [ item[0] for item in sampleNotherRefmapped]
samples.append( 'average' )
xdata = range( 0, len(samples) )
colors = libplot.getColors4()
c = -1
#c = 0
lines = []
#titleDict = {'mapped':'Mapped', 'uniquelyMapped':'Uniquely Mapped', 'properlyPaired':'Properly Paired', 'uniquelyMappedAndProperlyPaired':'Uniquely Mapped And Properly Paired', 'snps':'Snp'}
titleDict = {'mapped':'Mapped', 'properlyPaired':'Properly Paired', 'uniquelyMapped':'Uniquely Mapped', 'uniquelyMappedAndProperlyPaired':'Uniquely Mapped And Properly Paired'}
ydataList, miny, maxy = getData2(samples, rexps, exps, titleDict.keys())
#ydataList, miny, maxy = getData2(samples, exps, titleDict.keys())
#refs = sorted( ydataList.keys() )
offset = 0.12
scale = -1
if miny > 1000:
scale = len( str(int(miny)) ) - 1
linenames = []
categories = ["mapped", "properlyPaired", "uniquelyMapped", "uniquelyMappedAndProperlyPaired"]
cats = categories[:numCats]
for i, key in enumerate( cats ):
xdatai = [ x + offset*i for x in xdata ]
ydata = ydataList[key]
if scale > 0:
ydata = [ float(y)/10**scale for y in ydata ]
c += 1
l = axes.plot( xdatai, ydata, color=colors[c], marker='.', markersize=16.0, linestyle='none')
lines.append(l)
linenames.append( titleDict[key] )
if scale > 0:
miny = float(miny)/10**scale
maxy = float(maxy)/10**scale
#Draw horizontal line at y = 0:
xmin = -0.4
xmax = len(samples) - 1 + offset*len(linenames) + offset
axes.plot( [xmin, xmax], [0,0], color="#6B6B6B", linewidth=0.005)
fontP = FontProperties()
fontP.set_size('x-small')
yrange = maxy - miny
miny = miny - yrange*0.05
maxy = maxy + yrange*0.2
#Draw vertical lines to separate each sample:
for i in xrange(1, len(samples)):
d = (1 - offset*len(linenames))/2.0
x = [i - d, i - d]
y = [miny , maxy]
axes.plot(x,y, color="#CCCCCC", linewidth=0.005)
axes.set_xlim(xmin, xmax )
axes.set_ylim( miny, maxy )
#HACK:
#axes.set_ylim( -2, 0 )
libplot.editSpine( axes )
axes.set_xticks( [ i + offset*(len(linenames)/2.0) for i in range(0, len(samples))] )
axes.set_xticklabels( samples )
for label in axes.xaxis.get_ticklabels():
label.set_rotation(90)
axes.xaxis.set_ticks_position( 'bottom' )
axes.yaxis.set_ticks_position( 'left' )
legend = pyplot.legend( lines, linenames, numpoints=1, loc='upper right', prop=fontP)
legend._drawFrame = False
axes.set_xlabel( 'Samples' )
axes.set_ylabel( 'Percentage of mapping difference between C. Ref. and %s' % otherRefName) #NEED TO DO
#axes.set_ylabel( 'Percentage of mapping difference between C. Ref. and GRCh37 haplotypes')
if scale > 0:
axes.set_ylabel( 'Event counts (x%d)' %(10**scale) )
#axes.xaxis.grid(b=True, color="#CCCCCC", linestyle='-', linewidth=0.005)
axes.yaxis.grid(b=True, color="#CCCCCC", linestyle='-', linewidth=0.005)
libplot.writeImage( fig, pdf, options )
def drawPlot(rexps, exps, options, outfile, type):
options.out = outfile
fig, pdf = libplot.initImage( 8.0, 10.0, options )
axes = fig.add_axes( [0.12, 0.14, 0.85, 0.8] )
#Set title:
titleDict = {'mapped':'Mapped reads', 'uniquelyMapped':'Uniquely Mapped Reads', 'properlyPaired':'Properly Paired Reads', 'uniquelyMappedAndProperlyPaired':'Uniquely Mapped And Properly Paired Reads', 'snps':'SNPs'}
axes.set_title( titleDict[type] )
if len(rexps) < 1:
return
sampleNotherRefmapped = []
ref = ''
for sample in rexps:
if sample == 'average':
continue
exp = rexps[sample]
ref = exp.ref
sampleNotherRefmapped.append( (sample, exp.total) )
otherRefName = libplot.properName( ref )
sampleNotherRefmapped = sorted( sampleNotherRefmapped, key=lambda item: item[1], reverse=True )
samples = [ item[0] for item in sampleNotherRefmapped]
samples.append( 'average' )
xdata = range( 0, len(samples) )
colors = libplot.getColors4()
#c = -1
c = 0
lines = []
ydataList, miny, maxy = getData(samples, exps, rexps, type)
#print ydataList
refs = sorted( ydataList.keys() )
#miny = float('inf')
#maxy = 0
#offset = 0.075
offset = 0.12
#if type != 'snps':
# offset = 0
#axes.set_yscale('log')
scale = -1
if miny > 1000:
scale = len( str(int(miny)) ) - 1
#Draw line connecting the data for each sample (each bin):
binXdataList = [ [] for x in xdata ]
binYdataList = [ [] for x in xdata ]
for i, ref in enumerate(refs):
xdatai = [ x + offset*i for x in xdata ]
ydata = ydataList[ref]
if scale > 0:
ydata = [ float(y)/10**scale for y in ydata ]
for j, x in enumerate(xdatai):
binXdataList[j].append(x)
binYdataList[j].append( ydata[j] )
for i in xrange( len(binXdataList) ):
axes.plot( binXdataList[i], binYdataList[i], color="#CCCCCC", linestyle='-', linewidth=0.005 )
#Draw main plots:
for i, ref in enumerate(refs):
xdatai = [ x + offset*i for x in xdata ]
ydata = ydataList[ref]
if scale > 0:
ydata = [ float(y)/10**scale for y in ydata ]
c += 1
l = axes.plot( xdatai, ydata, color=colors[c], marker='.', markersize=16.0, linestyle='none')
lines.append(l)
if scale > 0:
miny = float(miny)/10**scale
maxy = float(maxy)/10**scale
#Draw horizontal line at y = 0:
xmin = -0.4
xmax = len(samples) - 1 + offset*len(refs) + offset
axes.plot( [xmin, xmax], [0,0], color="#6B6B6B", linewidth=0.005)
fontP = FontProperties()
fontP.set_size('x-small')
yrange = maxy - miny
miny = miny - yrange*0.05
maxy = maxy + yrange*0.2
#Draw vertical lines to separate each sample:
#for i in xrange(1, len(samples)):
# d = (1 - offset*len(refs))/2.0
# x = [i - d, i - d]
# y = [miny , maxy]
# axes.plot(x,y, color="#CCCCCC", linewidth=0.005)
axes.set_xlim(xmin, xmax )
axes.set_ylim( miny, maxy )
libplot.editSpine( axes )
axes.set_xticks( [ i + offset*(len(refs)/2.0) for i in range(0, len(samples))] )
axes.set_xticklabels( samples )
for label in axes.xaxis.get_ticklabels():
label.set_rotation(90)
axes.xaxis.set_ticks_position( 'bottom' )
axes.yaxis.set_ticks_position( 'left' )
properRefs = []
for r in refs:
if re.search('cactusRef', r):
r = r.lstrip('cactusRef')
properRefs.append( "%s %s" %(libplot.properName('cactusRef'), r))
else:
properRefs.append( libplot.properName(r) )
legend = pyplot.legend( lines,properRefs, numpoints=1, loc='best', prop=fontP)
legend._drawFrame = False
axes.set_xlabel( 'Samples' )
axes.set_ylabel( 'Percentage of mapping difference between C. Ref. and %s' % otherRefName)
if scale > 0:
axes.set_ylabel( 'Event counts (x%d)' %(10**scale) )
#axes.xaxis.grid(b=True, color="#CCCCCC", linestyle='-', linewidth=0.005)
axes.yaxis.grid(b=True, color="#CCCCCC", linestyle='-', linewidth=0.005)
libplot.writeImage( fig, pdf, options )
