Example

This is heatmapcluster_demo.py. Most of the code is the function make_data, which generates an array of data for the demonstration. The main part of the demo is the last three statements of the script. This script generates the plot shown above:

import numpy as np
import matplotlib.pyplot as plt
from heatmapcluster import heatmapcluster


def make_data(size, seed=None):
    if seed is not None:
        np.random.seed(seed)

    s = np.random.gamma([7, 6, 5], [6, 8, 6], size=(size[1], 3)).T
    i = np.random.choice(range(len(s)), size=size[0])
    x = s[i]

    t = np.random.gamma([8, 5, 6], [3, 3, 2.1], size=(size[0], 3)).T
    j = np.random.choice(range(len(t)), size=size[1])

    x += 1.1*t[j].T

    x += 2*np.random.randn(*size)

    row_labels = [('R%02d' % k) for k in range(x.shape[0])]
    col_labels = [('C%02d' % k) for k in range(x.shape[1])]

    return x, row_labels, col_labels


x, row_labels, col_labels = make_data(size=(64, 48), seed=123)

h = heatmapcluster(x, row_labels, col_labels,
                   num_row_clusters=3, num_col_clusters=0,
                   label_fontsize=6,
                   xlabel_rotation=-75,
                   cmap=plt.cm.coolwarm,
                   show_colorbar=True,
                   top_dendrogram=True)
plt.show()