资源简介
基于传统自适应蓝噪声采样(图形学中采样方法),实现离散数据的蓝噪声采样
代码片段和文件信息
import networkx as nx
import matplotlib.pyplot as plt
import community
import datetime;
starttime = datetime.datetime.now()
G=nx.DiGraph();G1=nx.DiGraph();
fo = open(“Count_1.csv“‘r‘encoding=‘utf-8‘);
fw = open(“bc/bc.txt“‘w‘encoding=‘utf-8‘);
fw1 = open(“bc/bc1.txt“‘w‘encoding=‘utf-8‘);
fw2 = open(“bc/bc2.txt“‘w‘encoding=‘utf-8‘);
edges = [];
weighted_edges = [];
for line in fo.readlines():
term = line.strip().split(‘‘);
edges.append((int(term[0])int(term[1])));
weighted_edges.append((int(term[0])int(term[1])int(term[2])));
G.add_edges_from(edges);
G1.add_weighted_edges_from(weighted_edges);
#algorithm from networkx
#print(G.edges.data());print(G1.edges.data());
C = nx.edge_betweenness_centrality(Gnormalized =False);
C1 = nx.edge_betweenness_centrality(G1normalized = False weight=‘weight‘);
C2 = nx.edge_betweenness_centrality(G1normalized =False);
nDG = G.to_undirected(False);
partials = community.best_partition(nDGweight=‘weight‘);
par_s = [];
for i in partials.values():
par_s.append(i);
print(max(par_s));
print(len(partials));
print(partials);
#C = nx.communicability_betweenness_centrality(Gnormalized=False);
endtime = datetime.datetime.now()
print (endtime - starttime).seconds
for ij in zip(CC.values()):
fw.write(str(i)+str(j)+‘\n‘);
fw1.write(str(len(C1))+‘\n‘);
for ij in zip(C1C1.values()):
fw1.write(str(i)+str(j)+‘\n‘);
for ij in zip(C2C2.values()):
fw2.write(str(i)+str(j)+‘\n‘);
fw.close();fw1.close();fw2.close();
print(‘end!‘);
# layout = nx.spring_layout(G)
# plt.figure(1)
# nx.draw(G pos=layout node_color=‘y‘)
# plt.figure(2)
# nx.draw(G pos=layout node_size=[(x+1) * 10 for x in C2.values()]node_color=‘r‘with_labels=True)
# plt.show()
# not use nx lib
# valication of nx betweenness
# CB = dict.fromkeys(G0.0)
# for s in G.nodes():
# Pred = {w:[] for w in G.nodes()}
# dist = dict.fromkeys(GNone)
# sigma = dict.fromkeys(G0.0)
# dist[s] = 0
# sigma[s] = 1
# Q = Queue()
# Q.put(s)
# S = []
# while not Q.empty():
# v = Q.get()
# S.append(v)
# for w in G.neighbors(v):
# if dist[w] == None:
# dist[w] = dist[v] + 1
# Q.put(w)
# if dist[w] == dist[v] + 1:
# sigma[w] += sigma[v]
# Pred[w].append(v)
# delta = dict.fromkeys(G0.0)
# for w in S[::-1]:
# for v in Pred[w]:
# delta[v] += sigma[v]/sigma[w]*(1+delta[w])
# if w != s:
# CB[w] += delta[w]
# for v in CB:
# CB[v] /= 2.0
#
# #compare with networkx‘s implements
# print(sum(abs(CB[v]-C[v]) for v in G)) #1.59428026336e-13
属性 大小 日期 时间 名称
----------- --------- ---------- ----- ----
文件 391 2017-11-19 13:55 py_blueNoiseSampling\.project
文件 499 2018-03-10 20:41 py_blueNoiseSampling\.pydevproject
文件 125 2018-03-09 16:23 py_blueNoiseSampling\.settings\org.eclipse.core.resources.prefs
文件 106 2018-03-09 16:32 py_blueNoiseSampling\.settings\org.eclipse.ltk.core.refactoring.prefs
文件 260934 2018-03-05 21:58 py_blueNoiseSampling\allstation_w2v_name_sampling_2.txt
文件 17534 2018-03-06 15:15 py_blueNoiseSampling\All_data_community.csv
文件 0 2018-03-12 19:48 py_blueNoiseSampling\bc\bc.txt
文件 0 2018-03-12 19:48 py_blueNoiseSampling\bc\bc1.txt
文件 0 2018-03-12 19:48 py_blueNoiseSampling\bc\bc2.txt
文件 2777 2018-03-12 19:48 py_blueNoiseSampling\betweenness-test.py
文件 3247 2018-03-04 09:55 py_blueNoiseSampling\blue_noise_particles.py
文件 771 2018-03-07 13:43 py_blueNoiseSampling\clique.py
文件 84909 2018-03-12 19:51 py_blueNoiseSampling\Count_1.csv
文件 109695994 2017-12-03 16:44 py_blueNoiseSampling\data\traincsv
文件 1857 2017-12-03 16:44 py_blueNoiseSampling\data\train-0-5.pgm
文件 1883 2017-12-03 16:44 py_blueNoiseSampling\data\train-1-0.pgm
文件 1788 2017-12-03 16:44 py_blueNoiseSampling\data\train-2-4.pgm
文件 1745 2017-12-03 16:44 py_blueNoiseSampling\data\train-3-1.pgm
文件 1816 2017-12-03 16:44 py_blueNoiseSampling\data\train-4-9.pgm
文件 1886 2017-12-03 16:44 py_blueNoiseSampling\data\train-5-2.pgm
文件 1750 2017-12-03 16:44 py_blueNoiseSampling\data\train-6-1.pgm
文件 1923 2017-12-03 16:44 py_blueNoiseSampling\data\train-7-3.pgm
文件 1693 2017-12-03 16:44 py_blueNoiseSampling\data\train-8-1.pgm
文件 1801 2017-12-03 16:44 py_blueNoiseSampling\data\train-9-4.pgm
文件 47040016 1996-11-18 23:36 py_blueNoiseSampling\data\train-images.idx3-ubyte
文件 60008 1996-11-18 23:36 py_blueNoiseSampling\data\train-labels.idx1-ubyte
文件 109695994 2017-12-03 16:45 py_blueNoiseSampling\data\train.csv
文件 1827377 2018-03-09 22:14 py_blueNoiseSampling\edge_bt_all.csv
文件 0 2018-03-11 14:21 py_blueNoiseSampling\edge_bt_all_static.txt
文件 2444 2018-03-10 11:45 py_blueNoiseSampling\edg_bar.py
............此处省略21个文件信息
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