54 lines
1.1 KiB
TeX
54 lines
1.1 KiB
TeX
\documentclass[margin=0.5cm]{standalone}
|
|
\usepackage{tikz}
|
|
\usepackage{pyluatex}
|
|
\usepackage{pgf}
|
|
|
|
\begin{document}
|
|
\begin{python}
|
|
# %%
|
|
import io
|
|
|
|
import numpy as np
|
|
import matplotlib.pyplot as plt
|
|
from sklearn.cluster import KMeans
|
|
|
|
# %%
|
|
|
|
|
|
data = """g1,10
|
|
g2,12
|
|
g3,9
|
|
g4,15
|
|
g5,17
|
|
g6,18"""
|
|
|
|
points =[int(row.split(",")[1]) for row in data.split("\n")]
|
|
X = np.array([[point] for point in points])
|
|
initial_means = [[10], [9]]
|
|
points
|
|
|
|
# %%
|
|
kmeans_values = []
|
|
for i in range(1,4):
|
|
kmeans = KMeans(n_clusters=2, random_state=42, max_iter=i, init=initial_means, n_init=1)
|
|
kmeans.fit(X)
|
|
kmeans_values.append(kmeans.cluster_centers_)
|
|
|
|
|
|
# %%
|
|
fig, axs = plt.subplots(len(kmeans_values), 1, sharex=True)
|
|
for i, centroids in enumerate(kmeans_values):
|
|
ax = axs[i]
|
|
ax.scatter(centroids, [i]*len(centroids), marker='x')
|
|
ax.scatter(points, [i]*len(points), s=2, color="black")
|
|
ax.axis('off')
|
|
|
|
|
|
with io.StringIO() as file:
|
|
fig.savefig(file, format="pgf", bbox_inches="tight", pad_inches=0.1)
|
|
print(file.getvalue())
|
|
\end{python}
|
|
\begin{tikzpicture}
|
|
|
|
\end{tikzpicture}
|
|
\end{document} |