G = nx.convert_node_labels_to_integers(G, first_label=0)
file_coords = "./../example/coords.txt"
coords = []
with open(file_coords, 'rb') as csvfile:
spamreader = csv.reader(csvfile, delimiter=' ', quotechar='|')
for row in spamreader:
row = [int(float(i)) for i in row]
coords.append(row)
coords = np.array(coords)
file_clustering = "./membership_SLA2.csv"
communities = []
lines = [line.rstrip('\n') for line in open(file_clustering)]
for l in lines:
communities.append(float(l))
co = communities
k = max(communities)
for i in xrange(len(communities)):
communities[i] = communities[i]/k
pl.my_plot_network_3d(G.edges(), coords, communities, theme = "Blues", north_west_flag = True)
sys.path.insert(0, './../')
import plot_network_3d as pl
file_data="example.graphml"
G = nx.read_graphml(file_data)
G = nx.convert_node_labels_to_integers(G, first_label=0)
file_coords = "coords.txt"
coords = []
with open(file_coords, 'rb') as csvfile:
spamreader = csv.reader(csvfile, delimiter=' ', quotechar='|')
for row in spamreader:
row = [int(float(i)) for i in row]
coords.append(row)
xyz = np.array(coords)
v_colors = [0]*90
v_colors[80] = 1
v_colors[81] = 2
v_colors[48] = 1
v_colors[25] = 2
v_colors[45] = 2
pl.my_plot_network_3d(G.edges(), xyz, v_colors, theme = 'Blues', north_west_flag = True)
