import numpy as np
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
import random
data = np.random.random((50, 50))
df = pd.DataFrame(data)
row_colors = [('b' if random.random() > 0.2 else 'r') for i in range(0, 50)]
cmap = sns.diverging_palette(133, 10, n=7, as_cmap=True)
result = sns.clustermap(df, row_colors=row_colors, col_cluster=False, cmap=
    cmap, linewidths=0)
print(dir(result))
ax = result.ax_heatmap
ax.plot([5, 30], [5, 5], 'k-', lw=10)
plt.show()
Plot on top of seaborn clustermap