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plot_graph.py
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from util import normal_util
import networkx as nx
import pylab as plt
from networkx.drawing.nx_agraph import graphviz_layout
import re
from datasets import UCI_loader
from datasets import SBM_loader
from datasets import USLegis_loader
from datasets import canVote_loader
def plot_UCI():
'''
plot statistics from UCI Message
'''
fname = "datasets/UCI_processed/OCnodeslinks_chars.txt"
max_nodes = 1901
G_times = UCI_loader.load_temporarl_edgelist(fname, max_nodes=max_nodes)
graph_name = "UCI_Message"
'''
dictionary of weak labels
'''
labels_dict = {}
print ("edge")
labels_dict['edge'] = normal_util.plot_edges(G_times, graph_name)
print ("acc")
labels_dict['acc'] = normal_util.plot_avg_clustering(G_times, graph_name)
print ("component")
labels_dict['component'] = normal_util.plot_num_components_directed(G_times, graph_name)
print ("weights")
labels_dict['weights'] = normal_util.plot_weighted_edges(G_times, graph_name)
print ("degree")
labels_dict['degree'] = normal_util.plot_degree_changes(G_times, graph_name)
return labels_dict
def plot_UCI_allinOne():
fname = "datasets/UCI_processed/OCnodeslinks_chars.txt"
max_nodes = 1901
G_times = UCI_loader.load_temporarl_edgelist(fname, max_nodes=max_nodes)
LAD = [69,70,184,185,187,188,189,191,192,194]
activity = [57,75,78,85,89,90,104,176,188,192]
CPD = [13,16,17,20,22,23,24,31,38,40,124]
label_sets = []
label_sets.append(LAD)
label_sets.append(activity)
label_sets.append(CPD)
graph_name = "UCI_Message"
normal_util.all_in_one_compare(G_times, graph_name, label_sets, True)
graph_name = "UCI_Message"
normal_util.all_plots_in_one(G_times, graph_name)
def print_labels(labels_dict):
for label in labels_dict:
print (label)
print (labels_dict[label])
def plot_synthetic():
fname = "datasets/SBM_processed/config_edgelist.txt"
#fname = "datasets/SBM_processed/ER_synthetic_edgelist_sudden_0.002_0.3.txt"
max_nodes = 100
max_time = 150
G_times = SBM_loader.load_temporarl_edgelist(fname, max_nodes=max_nodes, max_time=max_time)
graph_name = "synthetic"
outliers = normal_util.plot_edges(G_times, graph_name)
normal_util.plot_num_components_undirected(G_times, graph_name)
print (outliers)
def plot_legislative_allinOne():
fname = "datasets/USLegis_processed/LegisEdgelist.txt"
G_times = USLegis_loader.load_legis_temporarl_edgelist(fname)
LAD = [3,7]
label_sets = []
label_sets.append(LAD)
graph_name = "USLegislative"
normal_util.all_in_one_compare(G_times, graph_name, label_sets, False)
def plot_canVote_allinOne():
fname = "datasets/canVote_processed/canVote_edgelist.txt"
G_times = canVote_loader.load_canVote_temporarl_edgelist(fname)
LAD = [2,7,11]
label_sets = []
label_sets.append(LAD)
window = 1
initial_window = 2
percent_ranked = 0.2
graph_name = "canVote"
normal_util.all_in_one_compare(G_times, graph_name, label_sets, True, window, initial_window, percent_ranked)
def plot_spectrum(pkl_name, graph_name):
eigen_slices = normal_util.load_object(pkl_name)
normal_util.plot_activity_intensity(eigen_slices, graph_name)
def plot_vis(G):
pos = nx.spring_layout(G)
node_list = []
for node in G:
if (G.degree[node] > 50):
node_list.append(node)
print (len(node_list))
print(node_list)
colors = range(len(G))
options = {
"nodelist" : node_list,
"node_size" : 5,
"node_color": "#ffa600",
"edge_color": "#ff6361",
"width": 0.05
}
nx.draw(G, pos, **options)
plt.axis("off")
plt.savefig('graph_vis.pdf')
def plot_illus():
G = nx.Graph()
G.add_edges_from([(0, 1), (0, 2), (0,3), (0,4), (0,5)])
node_list = list (G.nodes)
pos = nx.spring_layout(G)
options = {
"nodelist" : node_list,
"node_size" : 500,
"node_color": "#ffa600",
"edge_color": "#66E3D8",
"width": 3
}
nx.draw(G, pos, **options)
labels={}
labels[0]='0'
labels[1]='1'
labels[2]='2'
labels[3]='3'
labels[4]='4'
labels[5]='5'
nx.draw_networkx_labels(G,pos,labels,font_size=16)
plt.axis("off")
plt.savefig('graph_illus.pdf')
def load_mp():
fname = "datasets/canVote_processed/mp_dict.pkl"
MP_dict = normal_util.load_object(fname)
return MP_dict
def export_gephi():
G_times = canVote_loader.load_canVote_temporarl_edgelist("datasets/canVote_processed/canVote_edgelist.txt")
MP_dict = load_mp()
labels = list(range(2006,2020,1))
print (len(MP_dict))
for i in range(len(G_times)):
#party for everyone!
G = G_times[i]
count = 0
for node in G.nodes:
if (node in MP_dict):
if (len(MP_dict[node]["party"]) > 0):
node_party = MP_dict[node]["party"][-1]
else:
node_party = MP_dict[node]["party"][0]
if (node_party == 'Conservative'):
#blue
G.nodes[node]['viz'] = {'color': {'r': 49, 'g': 130, 'b': 189, 'a': 0}}
# if (node_party == 'Progressive Conservative'):
# #Han Purple
# #http://www.flatuicolorpicker.com/blue-rgba-color-model/
# G.nodes[node]['viz'] = {'color': {'r': 77, 'g': 5, 'b': 232, 'a': 1}}
# if (node_party == 'Reform'):
# #light green
# #http://www.flatuicolorpicker.com/green-hex-color-model/
# G.nodes[node]['viz'] = {'color': {'r': 123, 'g': 239, 'b': 178, 'a': 1}}
# if (node_party == 'Canadian Alliance'):
# #Mariner
# #http://www.flatuicolorpicker.com/blue-rgba-color-model/
# G.nodes[node]['viz'] = {'color': {'r': 44, 'g': 130, 'b': 201, 'a': 1}}
if (node_party == 'Progressive Conservative'):
#blue
G.nodes[node]['viz'] = {'color': {'r': 49, 'g': 130, 'b': 189, 'a': 0}}
if (node_party == 'Reform'):
#blue
G.nodes[node]['viz'] = {'color': {'r': 49, 'g': 130, 'b': 189, 'a': 0}}
if (node_party == 'Canadian Alliance'):
#blue
G.nodes[node]['viz'] = {'color': {'r': 49, 'g': 130, 'b': 189, 'a': 0}}
if (node_party == 'Liberal'):
#red
G.nodes[node]['viz'] = {'color': {'r': 227, 'g': 74, 'b': 51, 'a': 0}}
if (node_party == 'Bloc'):
#purple
G.nodes[node]['viz'] = {'color': {'r': 136, 'g': 86, 'b': 167, 'a': 0}}
if (node_party == 'NDP'):
#green
G.nodes[node]['viz'] = {'color': {'r': 49, 'g': 163, 'b': 84, 'a': 0}}
if (node_party == 'Independent'):
#black
G.nodes[node]['viz'] = {'color': {'r': 99, 'g': 99, 'b': 99, 'a': 0}}
if (node_party == 'Green'):
#green
#https://www.greenparty.ca/en/downloads
#https://www.color-hex.com/color/3d9b35
G.nodes[node]['viz'] = {'color': {'r': 61, 'g': 155, 'b': 53, 'a': 0}}
else:
#black is default color
G.nodes[node]['viz'] = {'color': {'r': 99, 'g': 99, 'b': 99, 'a': 0}}
# graph.node['red']['viz'] = {'color': {'r': 255, 'g': 0, 'b': 0, 'a': 0}}
# graph.node['green']['viz'] = {'color': {'r': 0, 'g': 255, 'b': 0, 'a': 0}}
# graph.node['blue']['viz'] = {'color': {'r': 0, 'g': 0, 'b': 255, 'a': 0}}
# print (count)
nx.write_gexf(G, "gephi_new/" + str(labels[i]) + ".gexf", version="1.2draft")
def main():
export_gephi()
if __name__ == "__main__":
main()