def __call__(self, **kw):
features = track(kw.get('features'))
signal = [track(sig, chrmeta=features.chrmeta) for sig in kw.get('signal', [])]
labels = None
data = None
for chrom in features.chrmeta:
_l, _d = feature_matrix([s.read(chrom) for s in signal],
features.read(chrom), segment=True)
if _d.size == 0:
continue
if data is None:
labels = _l
data = _d
else:
labels = concatenate((labels, _l))
data = vstack((data, _d))
pdf = self.temporary_path(fname='plot_features', ext='.pdf')
if data is None:
raise ValueError("No data")
kw['mode'] = int(kw.get('mode', 0))
if kw['mode'] == 0:
new = True
for n in range(data.shape[-1] - 1):
heatmap(data[:, :, n], output=pdf, new=new, last=False,
rows=labels, orderRows=True, orderCols=False)
new = False
heatmap(data[:, :, -1], output=pdf, new=new, last=True,
rows=labels, orderRows=True, orderCols=False)
elif kw['mode'] == 1:
X = range(data.shape[1])
Y = data.mean(axis=0)
lineplot(X, [Y[:, n] for n in range(data.shape[-1])],
output=pdf, new=True, last=True)
elif kw['mode'] == 2:
X = range(data.shape[1])
new = True
mfrow = [4, 3]
nplot = min(data.shape[0], max_pages * mfrow[0] * mfrow[1])
for reg in range(nplot - 1):
lineplot(X, [data[reg, :, n] for n in range(data.shape[-1])],
output=pdf, new=new, last=False, mfrow=mfrow)
new = False
mfrow = []
lineplot(X, [data[nplot - 1, :, n] for n in range(data.shape[-1])],
output=pdf, new=new, last=True)
else:
raise ValueError("Mode not implemented: %s" % kw['mode'])
self.new_file(pdf, 'plot_features')
return 1
def __call__(self, **kw):
chrmeta = "guess"
features = track(kw.get('features'), chrmeta=chrmeta)
signals = kw.get('signals', [])
if not isinstance(signals, list): signals = [signals]
snames = [os.path.splitext(os.path.basename(sig))[0]
for sig in signals]
signals = [track(sig) for sig in signals]
labels = None
data = None
for chrom in features.chrmeta:
_l, _d = feature_matrix([s.read(chrom) for s in signals],
features.read(chrom), segment=True,
nbins=nbins, upstream=upstr, downstream=downstr)
if _d.size == 0:
continue
if data is None:
labels = _l
data = _d
else:
labels = concatenate((labels, _l))
data = vstack((data, _d))
pdf = self.temporary_path(fname='plot_features.pdf')
if data is None:
raise ValueError("No data")
kw['mode'] = int(kw.get('mode', 0))
X = array(range(-upstr[1]+1,nbins+downstr[1]+1))/(1.0*nbins)
if kw['mode'] == 0: #heatmap
new = True
for n in range(data.shape[-1]-1):
heatmap(data[:, :, n], output=pdf, new=new, last=False,
rows=labels, columns=X, main=snames[n],
orderRows=True, orderCols=False)
new = False
heatmap(data[:, :, -1], output=pdf, new=new, last=True,
rows=labels, columns=X, main=snames[-1],
orderRows=True, orderCols=False)
elif kw['mode'] == 1: #average lineplot
Y = data.mean(axis=0)
ymin = min([x.min() for x in Y]+[0])
ymax = max([x.max() for x in Y])
lineplot(X, [Y[:, n] for n in range(data.shape[-1])],
output=pdf, new=True, last=True, legend=snames, ylim=(ymin,ymax))
elif kw['mode'] == 2: #mosaic
new = True
mfrow = [4, 3]
nplot = min(data.shape[0], max_pages*mfrow[0]*mfrow[1])
ymin = min([data.min(),0])
ymax = data.max()
for reg in range(nplot-1):
lineplot(X, [data[reg, :, n] for n in range(data.shape[-1])],
output=pdf, new=new, last=False, mfrow=mfrow,
main=labels[reg], ylim=(ymin,ymax))
new = False
mfrow = []
lineplot(X, [data[nplot-1, :, n] for n in range(data.shape[-1])],
output=pdf, new=new, last=True, main=labels[-1],
legend=snames, ylim=(ymin,ymax))
else:
raise ValueError("Mode not implemented: %s" % kw['mode'])
self.new_file(pdf, 'plot_features')
return self.display_time()