def plotAmplifiedRegion(chrm, vmax, criteria, reorder=None):
fig = plt.figure(figsize=(5,4))
if reorder is None:
reorder = parameters.reorder[::-1]
plotCoverageHeatMap((smoothedValuesNorm[chrm][criteria]/meanReadsPerBasepair)[:, reorder],
vmin=0, vmax=vmax,
cmap='coolwarm',
cluster=False,
rowlabels=parameters.headers[reorder],
metric='correlation',
cbar_label='number of insertions/bp',
colorbar=False)
#plt.title(chrm)
xvalues = windowedLocs[chrm][criteria]
ax = plt.gca()
maxxtick = 25
xtickvec = np.arange(0, maxxtick+5, 5)
ax.set_xticks(xtickvec-0.5)
ax.set_xticklabels((xvalues)[xtickvec]/1E6)
ax.set_xlabel('distance across chromosome %s (Mb)'%chrm)
ax.yaxis.tick_left()
return
for chrm in chrms:
#smoothedValuesNorm[chrm] = smoothedValues[chrm]/np.mean(smoothedValues['chr1'], 0) * np.mean(smoothedValues['chr1'])
# NOTE: not actually normalizing at all
smoothedValuesNorm[chrm] = smoothedValues[chrm]
# what should max plotted value be?
allValues = smoothedValuesNorm[chrms[0]]
for chrm in chrms[1:]:
allValues = np.vstack((allValues, smoothedValuesNorm[chrm]))
vmax = 0.5*np.max(allValues)
for chrm in chrms:
plotCoverageHeatMap(smoothedValuesNorm[chrm], xvalues=windowedLocs[chrm],
vmin=0, vmax=vmax,
cmap='coolwarm',
rowlabels=parameters.headers,
metric='correlation',
cbar_label='number of insertions/bp')
plt.title(chrm)
ax = plt.gca()
ax.set_xlabel('distance across chromosome (%dkb)'%(stepSize/1000.0))
plt.tight_layout()
plt.savefig('coverage.noNorm.window_%.1e.step_%.1e.%s.pdf'%(windowSize, stepSize, chrm))
plt.close()
# call things as way out of line
## define cutoff
cutoff = 3*np.median(allValues, 0)
