def drawN50data( axes, samples, options ):
#key can be 'blockN50', 'sequenceN50', 'contigPathN50', or 'scaffolfPathN50'
keys = options.keys
colors = libplot.getColors6()
#markers = [".", "s", "^", "--"]
c = -1
lines = []
for key in keys:
ydata = []
for sample in samples:
y = int(sample.attrib[ key ])
ydata.append( y )
if options.logscale:
ydata = log10( array(ydata) )
c += 1
l = axes.plot( ydata, color=colors[c], marker=".", markersize=10.0, linestyle='none' )
lines.append(l)
libplot.editSpine( axes )
pyplot.xlabel( 'Samples' )
if options.logscale:
pyplot.ylabel( 'Log 10 of N50' )
else:
pyplot.ylabel( 'N50' )
return lines
def drawPlot(exps, options, outfile, type):
options.out = outfile
fig, pdf = libplot.initImage( 11.2, 10.0, options )
axes = fig.add_axes( [0.12, 0.18, 0.85, 0.75] )
#Set title:
titleDict = {'tpfn':'Indel Overlap with dbSNP', 'tp':'True Positives According to dbSNP', 'tp2':'Indel Overlap with dbSNP', 'fn':'False Negatives According to dbSNP', 'total':'Total Indels Called'}
axes.set_title( titleDict[type] )
if 'All' not in exps:
return
samples = getSamplesOrder( exps['All'], type )
if len( samples ) < 1:
return
samples.append('average')
if type != 'fn':
samples.append('reference')
samples.append('panTro3')
xdata = range( 0, len(samples) )
colors = libplot.getColors6()
c = -1
lines = []
pointsize = 10.0
offset = 0.15
#exporder = ['All', 'No repeats', 'Wobble', 'Wobble, No repeats']
exporder = ['Wobble', 'Wobble, No repeats', 'All', 'No repeats']
if type == 'fn':
exporder = ['Wobble', 'All']
elif type == 'total':
exporder = ['All', 'No repeats']
elif type == 'tp2' or type == 'tpfn':
exporder = ['Wobble', 'Wobble, No repeats']
#pointsize = 16.0
#offset = 0.3
#Get ydata
ydataList, ymin, ymax = getData(samples, exps, type, exporder)
scale = -1
if ymin > 1000:
scale = len( str(int(ymin)) ) -1
if scale > 0:
for exp in ydataList:
ydataList[exp] = [ float(y)/10**scale for y in ydataList[exp]]
if type == 'tpfn':
for j,t in enumerate(['tp', 'fn']):
for i, exp in enumerate(exporder):
if i > 0 and t == 'fn':
continue
if t == 'tp':
xdatai = [x + offset*(j*2+i) for x in xdata]
else:
xdatai = [x + offset*(j*2+i) for x in xdata[: len(xdata) -3]]
ydata = ydataList["%s.%s" %(exp,t)]
c +=1
lines.append(axes.plot(xdatai, ydata, color=colors[c], marker='.', markersize=pointsize, linestyle='none'))
else:
for i, exp in enumerate(exporder):
xdatai = [x + offset*i for x in xdata]
ydata = ydataList[exp]
c += 1
l = axes.plot(xdatai, ydata, color=colors[c], marker='.', markersize=pointsize, linestyle='none')
if type == 'fn':
c += 1
lines.append(l)
xmin = -0.4
xmax = len(samples) - 1 + offset*len(exps) + offset*3
fontP = FontProperties()
fontP.set_size('x-small')
if scale > 0:
ymin = float(ymin)/10**scale
ymax = float(ymax)/10**scale
datarange = ymax -ymin
ymin = ymin - datarange*0.01
ymax = ymax + datarange*0.01
#Draw vertical lines to separate each sample:
for i in xrange(1, len(samples)):
d = (1 - offset*len(exporder))/2.0
x = [i - d, i - d]
y = [ymin , ymax]
axes.plot(x,y, color="#CCCCCC", linewidth=0.005)
axes.set_xlim(xmin, xmax)
axes.set_ylim(ymin, ymax)
libplot.editSpine( axes )
axes.set_xticks( [ i + offset*(len(exps)/2-1) for i in range(0, len(samples))] )
axes.set_xticklabels( [ libplot.properName(s) for s in samples] )
for label in axes.xaxis.get_ticklabels():
label.set_rotation(90)
axes.xaxis.set_ticks_position( 'bottom' )
axes.yaxis.set_ticks_position( 'left' )
if type == 'tp':
legend = pyplot.legend(lines, ['All', 'No repeats', 'No wobble', 'No wobble, No repeats'], numpoints=1, loc='best', prop=fontP)
elif type == 'fn':
legend = pyplot.legend( lines, ['All', 'No wobble'], numpoints=1, loc='best', prop=fontP)
elif type == 'tpfn':
legend = pyplot.legend(lines, ['All, TP', 'No repeats, TP', 'All, FN'], numpoints=1, loc='best', prop=fontP)
elif type == 'tp2':
legend = pyplot.legend( lines, ['All', 'No repeats'], numpoints=1, loc='best', prop=fontP)
else:
legend = pyplot.legend( lines, exporder, numpoints=1, loc='best', prop=fontP)
legend._drawFrame = False
axes.set_xlabel( 'Samples' )
ylabel = "Percentage"
if type == 'total':
ylabel = 'Number of indels'
if scale > 0:
ylabel += '(x%d)' %10**scale
axes.set_ylabel(ylabel)
axes.yaxis.grid(b=True, color="#CCCCCC", linestyle='-', linewidth=0.005)
libplot.writeImage( fig, pdf, options )
def drawPlot2(exps, options, outfile, type):
options.out = outfile
fig, pdf = libplot.initImage( 11.2, 10.0, options )
#Set title:
titleDict = {'total':'Total Indels Called'}
if 'All' not in exps:
return
samples = getSamplesOrder( exps['All'], type )
if len( samples ) < 1:
return
samples.append('average')
samples.append('reference')
samples.append('panTro3')
xdata = range( 0, len(samples) )
colors = libplot.getColors6()
c = -1
lines = []
pointsize = 10.0
offset = 0.15
exporder = ['All', 'No repeats']
#Get ydata
ydataList, ymin, ymax = getData(samples, exps, type, exporder)
yrange = ymax - ymin
#Get normal range and outlier range:
normalvals, outliers = getOutliers(ydataList)
minNormal = min(normalvals) - 0.05*yrange
maxNormal = max(normalvals) + 0.05*yrange
minOutlier = min(outliers) - 0.05*yrange
maxOutlier = max(outliers) + 0.05*yrange
if minNormal< 0:
minNormal = -0.5
#Set up the axes
ax, ax2 = setAxes(fig, maxOutlier - minOutlier, maxNormal - minNormal)
scale = -1
if minNormal > 1000:
scale = len( str(int(minNormal)) ) -1
if scale > 0:
for exp in ydataList:
ydataList[exp] = [ float(y)/10**scale for y in ydataList[exp]]
#PLOT
for i, exp in enumerate(exporder):
xdatai = [x + offset*i for x in xdata]
ydata = ydataList[exp]
c += 1
#Outlier plot
l = ax.plot(xdatai, ydata, color=colors[c], marker='.', markersize=pointsize, linestyle='none')
lines.append(l)
#Normal range plot
ax2.plot(xdatai, ydata, color=colors[c], marker='.', markersize=pointsize, linestyle='none')
xmin = -0.4
xmax = len(samples) - 1 + offset*len(exps) + offset*3
fontP = FontProperties()
fontP.set_size('x-small')
if scale > 0:
minNormal = float(minNormal)/10**scale
maxNormal = float(maxNormal)/10**scale
minOutlier = float(minOutlier)/10**scale
maxOutlier = float(maxOutlier)/10**scale
#Draw the Discontinue sign:
d = 0.2 #how big to make the diagonal lines in axes coordinates
if scale == -1:
d = 50
ax.plot( (-1, 0), (minOutlier +d, minOutlier - d), color = "k", clip_on=False )
ax2.plot( (-1, 0), (maxNormal +d, maxNormal - d), color = "k", clip_on=False )
#Draw vertical lines to separate each sample:
for i in xrange(1, len(samples)):
d = (1 - offset*len(exporder))/2.0
x = [i - d, i - d]
y = [minNormal , maxOutlier]
ax.plot(x,y, color="#CCCCCC", linewidth=0.005)
ax2.plot(x,y, color="#CCCCCC", linewidth=0.005)
xticklabels = [libplot.properName(s) for s in samples]
#Set limit for the top plot (outlier)
ax.set_ylim(minOutlier, maxOutlier)
ax.set_xlim(xmin, xmax)
ax.set_xticks( [ i + offset*(len(exps)/2-1) for i in range(0, len(samples))] )
dummyxticklabels = [ "" for l in xticklabels ]
ax.set_xticklabels(dummyxticklabels)
#Make sure the y ticks of the top plot is the same with the bottom plot:
step = 2
if scale == -1:
step = 500
ytickpositions = []
ytickpos = 0
while ytickpos < maxOutlier:
if ytickpos >= minOutlier:
ytickpositions.append(ytickpos)
ytickpos += step
ax.set_yticks(ytickpositions)
#Set limit for the bottom plot:
ax2.set_ylim(minNormal, maxNormal)
ax2.set_xlim(xmin, xmax)
#Hide the spines between ax and ax2:
ax.spines['bottom'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('none')
ax2.spines['top'].set_visible(False)
ax2.spines['right'].set_visible(False)
ax2.xaxis.tick_bottom()
ax2.yaxis.set_ticks_position( 'left' )
ax2.set_xticks( [ i + offset*(len(exps)/2-1) for i in range(0, len(samples))] )
ax2.set_xticklabels( xticklabels )
for label in ax2.xaxis.get_ticklabels():
label.set_rotation(75)
legend = pyplot.legend( lines, exporder, numpoints=1, loc='upper left', prop=fontP)
legend._drawFrame = False
ax2.set_xlabel( 'Samples' )
ylabel = 'Number of indels'
if scale > 0:
ylabel += '(x%d)' %10**scale
ax2.set_ylabel(ylabel)
ax.set_title( titleDict[type] )
ax.yaxis.grid(b=True, color="#CCCCCC", linestyle='-', linewidth=0.005)
ax2.yaxis.grid(b=True, color="#CCCCCC", linestyle='-', linewidth=0.005)
libplot.writeImage( fig, pdf, options )
def drawCompareN50data( axes, xsamples, ysamples, options ):
keys = options.keys
lineNames = []
colors = libplot.getColors6()
c = -1
lines = []
xrefname = xsamples[0].attrib[ 'referenceName' ]
yrefname = ysamples[0].attrib[ 'referenceName' ]
minval = inf
maxval = 0
for key in keys:
xdata = []
ydata = []
for xsample in xsamples:
name = xsample.attrib[ 'sampleName' ]
if name == yrefname:
continue
ysample = getSample( ysamples, name )
if ysample == None:
sys.stderr.write( "%s has %s sample, but %s doesn't\n" % (xrefname, name, yrefname) )
continue
xval = int(xsample.attrib[key])
yval = int(ysample.attrib[key])
if xval > 0 and yval > 0:
xdata.append(xval)
ydata.append(yval)
#xdata.append( int(xsample.attrib[ key ]) )
#ydata.append( int(ysample.attrib[ key ]) )
if len(xdata) == 0:
continue
if options.logscale:
xdata = log10( array(xdata) )
ydata = log10( array(ydata) )
c += 1
l = axes.plot( xdata, ydata, color=colors[c], marker=".", markersize=10.0, linestyle='none' )
lines.append(l)
lineNames.append( key )
currmax = max( xdata.max(), ydata.max() )
if maxval < currmax:
maxval = currmax
currmin = min( xdata.min(), ydata.min() )
if minval > currmin:
minval = currmin
if minval == -inf:
minval = 0
#Draw y=x line
span = maxval - minval
#print "MaxVal: %f, MinVal: %f. Span: %f" % (maxval, minval, span)
x = [ minval - span*0.1, maxval + span*0.1 ]
y = [ minval - span*0.1, maxval + span*0.1 ]
axes.plot( x, y, color="0.9" )
libplot.editSpine( axes )
if options.logscale:
#pyplot.ylabel( 'Log 10 of N50' )
pyplot.xlabel( "%s (Log 10)" % libplot.properName(xrefname) )
pyplot.ylabel( "%s (Log 10)" %libplot.properName(yrefname) )
return lines, lineNames, maxval, minval
