spn/data.py at master · AmurG/spn · GitHub

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
#Some helper functions to make the entire thing run

import math
import numpy as np
import scipy
import scipy.cluster.hierarchy as hcluster
from scipy.cluster.vq import vq, kmeans, whiten

def split(arr,k):
	pholder,clusters = scipy.cluster.vq.kmeans2(arr,k,minit='points')
	print(clusters)
	big = []
	for i in range(0,len(set(clusters))):
		small = []
		for j in range(0,len(arr)):
			if (clusters[j]==i+1):
				small.append(arr[j,:])
		big.append(small)
		#print(big)
	return big

def submat(mat,subset):
	q = len(subset)
	print(q)
	ret = np.zeros(q*q)
	ret = np.reshape(ret,(q,q))
	w = 0
	for i in subset:
		z = 0
		for j in subset:
			ret[w,z] = mat[i,j]
			z=z+1
		w=w+1
	return ret

def submean(mean,subset):
	q = len(subset)
	m = np.zeros(q)
	w = 0
	for i in subset:
		m[w] = mean[i]
		w=w+1
	return m