def plotCrossCompartmentHeatmap(cyDfA, cyDfB, bicluster=False, n_clusters=4):
rho,pvalue,qvalue = crosscorr(cyDfA[sorted(cyDfA.columns)], cyDfB[sorted(cyDfB.columns)])
if n_clusters is None:
heatmap(rho, vmin=-1, vmax=1)
else:
if bicluster:
rho_sorted = plotBicluster(rho, n_clusters=n_clusters)
else:
plotCorrHeatmap(dmat=rho)
def plotCrossCompartmentHeatmap(cyDfA, cyDfB, bicluster=False, n_clusters=4):
rho, pvalue, qvalue = crosscorr(cyDfA[sorted(cyDfA.columns)],
cyDfB[sorted(cyDfB.columns)])
if n_clusters is None:
heatmap(rho, vmin=-1, vmax=1)
else:
if bicluster:
rho_sorted = plotBicluster(rho, n_clusters=n_clusters)
else:
plotCorrHeatmap(dmat=rho)
def plotCrossCompartmentBoxplot(cyDfA, cyDfB):
rho,pvalue,qvalue = crosscorr(cyDfA[sorted(cyDfA.columns)], cyDfB[sorted(cyDfB.columns)])
s = [rho.loc[i,j] for i,j in itertools.product(rho.index, rho.columns) if i == j]
d = [rho.loc[i,j] for i,j in itertools.product(rho.index, rho.columns) if i != j]
a = pd.DataFrame({'Group':['Same']*len(s) + ['Different']*len(d), '$\\rho$':s+d})
plt.clf()
sns.boxplot(x='Group', y='$\\rho$', data=a)
sns.stripplot(x='Group', y='$\\rho$', data=a, jitter=True)
plt.xlabel('')
plt.ylim((-1,1))
plt.tight_layout()
def plotCrossCompartmentBoxplot(cyDfA, cyDfB):
rho, pvalue, qvalue = crosscorr(cyDfA[sorted(cyDfA.columns)],
cyDfB[sorted(cyDfB.columns)])
s = [
rho.loc[i, j] for i, j in itertools.product(rho.index, rho.columns)
if i == j
]
d = [
rho.loc[i, j] for i, j in itertools.product(rho.index, rho.columns)
if i != j
]
a = pd.DataFrame({
'Group': ['Same'] * len(s) + ['Different'] * len(d),
'$\\rho$': s + d
})
plt.clf()
sns.boxplot(x='Group', y='$\\rho$', data=a)
sns.stripplot(x='Group', y='$\\rho$', data=a, jitter=True)
plt.xlabel('')
plt.ylim((-1, 1))
plt.tight_layout()
