-
Notifications
You must be signed in to change notification settings - Fork 0
/
Clustering.py
89 lines (62 loc) · 2.5 KB
/
Clustering.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
import os
import numpy as np
from sklearn.manifold import TSNE
from matplotlib import pyplot as plt
from sklearn.decomposition import PCA
def pca_cluster(X=None, Y=None, components=2, visualize=True, tit=None, save=False, name=""):
pca = PCA(n_components=components)
x = pca.fit_transform(X)
x = x - np.min(np.min(x))
x = x / np.max(np.max(x))
if visualize:
cluster_plot(x, Y, tit, save, name)
return x
def tsne_cluster(X=None, Y=None, components=2, visualize=True, iterations=100, tit=None, save=False, name=""):
tsne = TSNE(n_components=components, n_iter=iterations, perplexity=7,
learning_rate=100, init='random')
x = tsne.fit_transform(X, Y)
x = x - np.min(np.min(x))
x = x / np.max(np.max(x))
if visualize:
cluster_plot(x, Y, tit, save, name)
return x
def cluster_plot(X=None, Y=None, tit=None, save=False, name=""):
if X.shape[1] == 2:
scatter_2d_plot(X, Y, tit, save, name)
elif X.shape[1] == 3:
scatter_3d_plot(X, Y, tit, save, name)
else:
print("Cannot plot with " + str(X.shape[1]) + " dimension")
return
def scatter_2d_plot(X=None, Y=None, tit=None, save=False, name=""):
fig, ax = plt.subplots(figsize=(30, 20))
for i in range(X.shape[0]):
ax.scatter(X[i, 0], X[i, 1], color=[Y[i, 0], 0.4, Y[i, 1]], marker='o', linewidth=15 - Y[i, 1]*7)
if Y[i, 1] == 1:
ax.text(X[i, 0], X[i, 1] + X[i, 1]*0.02, str(int(i/(X.shape[0]/20))))
else:
ax.text(X[i, 0], X[i, 1] - X[i, 1]*0.02, str(int(i/(X.shape[0]/20))))
ax.grid(True)
ax.set_title(tit)
fig.show()
if save:
try:
fig.savefig("Plots/" + name + ".png")
except:
os.mkdir("Plots")
fig.savefig("Plots/" + name + ".png")
return
def scatter_3d_plot(X=None, Y=None, tit=None, save=False, name=""):
fig = plt.figure(figsize=(30, 20))
ax = fig.add_subplot(projection='3d')
for i in range(X.shape[0]):
ax.scatter(X[i, 0], X[i, 1], X[i, 2], color=[Y[i, 0], 0.4, Y[i, 1]], marker='o', linewidth=12 - Y[i, 1]*6)
ax.set_title(tit)
fig.show()
if save:
try:
fig.savefig("Plots/" + name + ".png")
except:
os.mkdir("Plots")
fig.savefig("Plots/" + name + ".png")
return