def plot_error_profiles_total(options, data, fieldsize):
xpositions = np.arange(fieldsize)
for sample, _ in options['profiles']:
profile = data[sample][COLFORSTATS]
fig = plt.figure(figsize=(3.5, 2.8))
subst_freq = []
ins_freq = []
del_freq = []
for fn in range(fieldsize):
inserted = (profile[fn] * MASK_INS).sum()
deleted = (profile[fn] * MASK_DEL).sum()
substed = (profile[fn] * MASK_SUBST).sum()
total = profile[fn].sum()
subst_freq.append(substed / total * 100)
ins_freq.append(inserted / total * 100)
del_freq.append(deleted / total * 100)
plt.plot(xpositions, subst_freq, label='subst', c=iwork_colors.yellow, linewidth=1.2)
plt.plot(xpositions, ins_freq, label='ins', c=iwork_colors.red, linewidth=1.2)
plt.plot(xpositions, del_freq, label='del', c=iwork_colors.blue, linewidth=1.2)
ax = plt.gca()
plt.setp(ax.get_xticklabels(), visible=False)
plt.xlim(0, fieldsize-1)
plt.xlabel('Position in tag')
plt.ylabel('Frequency (percent)')
plt.title(sample)
box = ax.get_position()
ax.set_position([box.x0 + 0.1, box.y0 + box.height * 0.2,
box.width * 0.9, box.height * 0.77])
ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.1), ncol=3, columnspacing=0.5,
frameon=False, handletextpad=0.5)
adjust_numbers_style(ax, xgrid=True)
for format in PLOT_FORMATS:
plt.savefig(options['plots'].format(format=format, type='total', sample=sample))
plt.cla()
plt.clf()
def plot_error_profiles_pertype(options, data, fieldsize, plottype):
xpositions = np.arange(fieldsize)
freqmask = {'del': MASK_DEL, 'subst': MASK_SUBST}[plottype]
for sample, _ in options['profiles']:
profile = data[sample][COLFORSTATS]
fig = plt.figure(figsize=(3.5, 2.8))
freqs = [[] for i in range(len(BASES) - 1)]
for fn in range(fieldsize):
profmasked = profile[fn] * freqmask
for basei, freqtbl in enumerate(freqs):
basereads = profile[fn, basei].sum()
freqtbl.append(profmasked[basei].sum() / basereads)
for base, freqtbl, color in zip(BASES, freqs, iwork_colors):
plt.plot(xpositions, freqtbl, label=base, c=color, linewidth=1.2)
ax = plt.gca()
plt.setp(ax.get_xticklabels(), visible=False)
plt.xlim(0, fieldsize-1)
plt.xlabel('Position in tag')
plt.ylabel('Frequency (percent)')
plt.title(sample)
box = ax.get_position()
ax.set_position([box.x0 + 0.1, box.y0 + box.height * 0.2,
box.width * 0.9, box.height * 0.77])
ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.1), ncol=4, columnspacing=0.5,
frameon=False, handletextpad=0.5)
adjust_numbers_style(ax, xgrid=True)
for format in PLOT_FORMATS:
plt.savefig(options['plots'].format(format=format, type=plottype, sample=sample))
plt.cla()
plt.clf()
def write_plot(result, pdf=None, png=None):
fig = plt.figure(figsize=(3.8, 2))
plt.hist([r['z'] for r in result], bins=20, facecolor='#444444', rwidth=0.8)
plt.xlabel('Enrichment (z)')
plt.ylabel('Number of seq.')
plt.axvline(1.644854, color='red') # top 0.05 line
adjust_numbers_style(plt.gca())
plt.tight_layout()
if pdf is not None:
plt.savefig(pdf, format='pdf')
if png is not None:
plt.savefig(png, format='png')
plt.clf()
plt.cla()
def plot_to_file(options, stats, outputs):
figwidth = 2 + len(options['samples']) * len(options['plot_classes']) / 4
fig = plt.figure(figsize=(figwidth, 3))
ax = fig.add_subplot(1, 1, 1)
class_names = options['plot_classes']
xstep = 0.8 / len(options['samples'])
xwidth = xstep * 0.8
xcenterbase = np.arange(0, len(options['plot_classes']), 1)
xleftbase = xcenterbase - 0.4
for sampleno, sample in enumerate(options['samples']):
name = sample['name']
xlefts = xleftbase + xstep * sampleno
data = [stats[cls][name] for cls in options['plot_classes']]
plt.bar(xlefts, data, width=xwidth, facecolor=iwork_colors[sampleno],
label=name, edgecolor='#666666', zorder=6)
plt.xlim(-0.5, len(options['plot_classes']) - 0.5)
plt.xticks(xcenterbase)
ax.set_xticklabels(class_names)
plt.setp(ax.get_xticklines(), visible=False)
plt.legend(loc='best')
plt.xlabel('Class')
plt.ylabel('% Reads')
if options['branding']:
plt.annotate(options['branding'], (3, 3), fontsize=8, color='#888888',
textcoords='figure points', horizontalalignment='left',
verticalalignment='bottom')
adjust_numbers_style(ax)
plt.tight_layout()
for output in outputs:
plt.savefig(output)