def drawClonesizeDist(outdir, options, sample2data):
options.out = os.path.join( outdir, "cloneVsRead" )
fig, pdf = iseqlib.initImage( 10.0, 8.0, options )
axes = fig.add_axes( [0.12, 0.15, 0.85, 0.75] )
lines = []
sampleNames = sorted(sample2data.keys())
#draw
colors = iseqlib.getColors6()
lightColors = iseqlib.getColors6light()
markers = ['o', '*', 's', 'd', '^', 'p', 'v']
c = 0
xdata = []
xticklabels = []
for sample in sampleNames:
#xticklabels, ydata = binData( sample2freqs[sample] )
(xticklabels, ydata) = sample2data[sample]
print sample
print xdata
print ydata
xdata = range(0, len(xticklabels), 1)
markersize = 10.0
m = markers[c]
if m == '*':
markersize = 12.0
elif m == 's':
markersize = 8.0
l = axes.plot(xdata, ydata, color=colors[c], marker=m, markeredgecolor=colors[c], markersize=markersize, linestyle='none')
axes.plot(xdata, ydata, color=lightColors[c], linestyle='-', linewidth=0.2)
lines.append(l)
c += 1
iseqlib.editSpine(axes)
axes.set_title('Clone Size Distribution', size='xx-large')
axes.set_xlabel('Clone size as percentage of total reads', size='large')
axes.set_ylabel('Percentage of total clones', size='large')
fontP = FontProperties()
fontP.set_size('medium')
legend = axes.legend( lines, sampleNames, numpoints=1, loc='best', ncol=1, prop=fontP)
legend._drawFrame = False
axes.xaxis.set_ticklabels( xticklabels )
axes.xaxis.set_ticks( [x - 0.5 for x in xdata] )
axes.set_xlim(-0.5, len(xdata) - 0.5)
axes.set_ylim(-0.5, 50)
for label in axes.get_xticklabels():
label.set_fontsize('medium')
label.set_rotation(45)
for label in axes.get_yticklabels():
label.set_fontsize('medium')
axes.yaxis.grid(b=True, color="#BDBDBD", linestyle='-', linewidth=0.005)
axes.xaxis.grid(b=True, color="#BDBDBD", linestyle='-', linewidth=0.005)
iseqlib.writeImage(fig, pdf, options)
def drawDistData(axes, sam2nt2aa):
#sam2nt2aa = getNumNtPerAa(samples)
lines = []
labels = []
colors = iseqlib.getColors6()
if len(colors) < len(sam2nt2aa.keys()):
colors.extend( iseqlib.getColors6light() )
if len(colors) < len(sam2nt2aa.keys()):
colors.extend( iseqlib.getColors6dark() )
#colors = iseqlib.getColors0()
#lightColors = getColors6light()
markersize = 10.0
c = -1
axes.set_yscale('log')
for s in sorted( sam2nt2aa.keys() ):
nt2aa = sam2nt2aa[s]
c += 1
xdata = sorted( nt2aa.keys() )
ydata = [ nt2aa[x] for x in xdata ]
line = axes.plot(xdata, ydata, color=colors[c], marker='o', markeredgecolor=colors[c], markersize = markersize, linestyle='-', linewidth=2)
#axes.plot(xdata, ydata, color=lightColors[c], linestyle='-', linewidth=0.5)
lines.append(line)
labels.append(s)
print s
print xdata
print ydata
xticks = xrange(0,8,1)
xticklabels = [ str(x) for x in xticks]
axes.xaxis.set_ticks(xticks)
axes.xaxis.set_ticklabels( xticklabels )
#axes.set_xlim(0.5, 5.5)
#axes.set_ylim(-0.1, 40)
axes.set_title('Nucleotide sequences to amino acid sequence', size="xx-large")
iseqlib.editSpine( axes )
axes.set_xlabel("Number of nucleotide sequences", size='x-large')
#axes.set_ylabel("Number of amino acid sequences", size='x-large')
axes.set_ylabel("Percentage of amino acid sequences", size='x-large')
legend = axes.legend( lines, labels, numpoints=1, loc='best', ncol=1)
legend.__drawFrame = False
axes.yaxis.grid(b=True, color="#BDBDBD", linestyle='-', linewidth=0.005)
axes.xaxis.grid(b=True, color="#BDBDBD", linestyle='-', linewidth=0.005)
def drawOverlapReadsData(axes, exps, sample, sampleOrder):
if len( exps ) <= 0:
return
if sampleOrder:
exps = sortByOrder(exps, sampleOrder)
else:
exps = sorted( exps, key = lambda exp: (exp.exp, exp.size) )
colors = iseqlib.getColors6()
lightcolors = iseqlib.getColors6light()
markers = ['o', '*', 's', 'd', '^', 'p', 'v']
textsize = 'large'
lines = []
expnames = []
cutoffs = exps[0].cutoffs
xticklabels = [ str(c) for c in cutoffs ]
xdata = cutoffs
for i, x in enumerate(xdata):
if x == 0 and i < len(xdata) - 1:
xdata[i] = xdata[i + 1]/10.0
prevexp = ''
colorIndex = 0
markerIndex = -1
axes.set_xscale('log')
#axes.set_yscale('log')
maxy = 0
miny = 'inf'
for exp in exps:
expnames.append( exp.name )
ydata, stddata = getStats(exp, sample)
maxy = max( [max(ydata), maxy] )
miny = min( [min(ydata), miny] )
if prevexp != '' and prevexp != exp.exp:
colorIndex += 1
markerIndex = 0
else:
markerIndex += 1
prevexp = exp.exp
markersize = 12.0
if markers[markerIndex] == '*':
markersize += 2.0
elif markers[markerIndex] == 's':
markersize -= 2.0
l = axes.plot(xdata, ydata, color=colors[colorIndex], marker=markers[markerIndex], markeredgecolor=colors[colorIndex], markersize=markersize, linestyle='none')
axes.plot( xdata, ydata, color=lightcolors[colorIndex], linestyle='-', linewidth=0.2 )
lines.append(l)
axes.set_title('Percentage of Reads in Overlapped Clones', size='xx-large')
axes.set_xlabel('Minimum clone size (percentage of total reads)', size=textsize)
axes.set_ylabel('Percentage of reads overlapped', size=textsize)
axes.xaxis.set_ticklabels( xticklabels )
axes.xaxis.set_ticks( xdata )
minx = min(xdata)
maxx = max(xdata)
axes.set_xlim( 7*minx/10, maxx*1.5 )
#axes.set_ylim(-2, 102 )
axes.set_ylim(-0.5, 8 )
axes.yaxis.grid(b=True, color="#CCCCCC", linestyle='-', linewidth=0.005)
axes.xaxis.grid(b=True, color="#CCCCCC", linestyle='-', linewidth=0.005)
legend = axes.legend( lines, expnames , numpoints=1, loc='best', ncol=1)
legend._drawFrame = False