agglom_demo.ipynb

Kernel: Python 3

# Agglomerative Clustering Demo
# Author: Animesh Gupta

# import superimport

import numpy as np
from scipy.cluster.hierarchy import dendrogram, linkage
import matplotlib.pyplot as plt

# import pyprobml_utils as pml

X = np.array(
    [
        [1, 2],
        [2.5, 4.5],
        [2, 2],
        [4, 1.5],
        [4, 2.5],
    ]
)

labels = range(1, 6)
plt.figure(figsize=(10, 6))
plt.yticks(np.linspace(0, 5, 11))
plt.ylim(0, 5)
plt.grid(color="gray", linestyle="dashed")
plt.scatter(X[:, 0], X[:, 1], label="True Position")

for label, x, y in zip(labels, X[:, 0], X[:, 1]):
    plt.annotate(
        label, xy=(x, y), xytext=(-3, 3), textcoords="offset points", ha="right", va="bottom", fontsize=25, color="red"
    )
plt.savefig("agglom_demo_data.pdf", dpi=300)

linked = linkage(X, "single")

labelList = range(1, 6)

plt.figure(figsize=(10, 7))
dendrogram(linked, orientation="top", labels=labelList, distance_sort="descending", show_leaf_counts=True)
plt.savefig("agglom_demo_dendrogram.pdf", dpi=300)

plt.show()

linked = linkage(X, "single", metric="cityblock")

labelList = range(1, 6)

plt.figure(figsize=(10, 7))
dendrogram(linked, orientation="top", labels=labelList, distance_sort="descending", show_leaf_counts=True)
plt.savefig("agglom_demo_dendrogram_cityblock.pdf", dpi=300)

plt.show()