def main(): # pragma: no cover
# Load data from saved pickle files
category = "astrophysics" # arxiv = stat.ML / astro-ph / stat # mag = machine_learning / astrophysics / statistics
edge_pickle_arxiv = "../pickle_file/edges_arxiv_{0}.pkl".format(category)
node_pickle_arxiv = "../pickle_file/nodes_arxiv_{0}.pkl".format(category)
edge_pickle_mag = "../pickle_file/mag_co_author_edges_{0}.pkl".format(
category)
node_pickle_mag = "../pickle_file/mag_co_author_nodes_{0}.pkl".format(
category)
edge_weight_arxiv = "../pickle_file/edges_weight_arxiv_{0}.pkl".format(
category)
node_weight_arxiv = "../pickle_file/nodes_weight_arxiv_{0}.pkl".format(
category)
edge_weight_mag = "../pickle_file/edges_weight_mag_spec_{0}.pkl".format(
category)
node_weight_mag = "../pickle_file/nodes_weight_mag_spec_{0}.pkl".format(
category)
# auth_graph_pickle = "../pickle_file/mag_co_author_graph_{0}.pkl".format(category)
# auth_graph_pickle = "../pickle_file/mag_weight_co_author_graph_{0}.pkl".format(category)
# auth_graph_pickle = "../pickle_file/arxiv_co_author_graph_{0}.pkl".format(category)
# auth_graph_pickle = "../pickle_file/arxiv_weight_co_author_graph_{0}.pkl".format(category)
signal = "" # weight for weighted graph # null
# use for non-weighted
edge_file = edge_pickle_mag # arxiv # mag
node_file = node_pickle_mag # arxiv # mag
# use for weighted
#edge_file = edge_weight_arxiv # arxiv # mag
#node_file = node_weight_arxiv # arxiv # mag
auth_graph = loadGraphPickle(edge_file, node_file, signal)
#with open(auth_graph_pickle, 'wb') as f:
# pickle.dump(auth_graph, f)
node_count, edge_count = basicStats(auth_graph)
deg = calcCentrality(auth_graph)
# Plot results
histo_title = "mag" # arxiv # mag
signal = "double_log" # single_log: log(fraction) # double_log: log(fraction) vs log(deg)
label = "Log" # log # <empty>
x_title = "log" # log # <empty>
weighted = "" # weighted # <empty>
dp.drawHistogramSequence(deg, node_count,
("{0}_{1}_{2}_simple_deg_distro").format(
histo_title, category, weighted), "Degree")
dp.drawLogHistogram(deg, node_count, signal,
("{0}_{1}_{2}_{3}_log_deg_distro").format(
histo_title, category, weighted, x_title),
"{0} Degree".format(label), "Log Fraction")
def createGraphFromInputs(mainFrame):
graphSettings = ConfigGraphFile.getFileConfigs()
for i in range(len(mainFrame.graphInputs)):
lista, period, startBit = ListCleaning.clearList(
mainFrame.graphInputs[i])
lista = ListCleaning.convertList(lista)
print(period)
graph = DrawGraph.drawGraph(
5,
10,
lista,
len(lista),
height=graphSettings[7],
sizeDivision=0.05,
zoom=1000,
fontSize=graphSettings[0],
fontColor=QtGui.QColor(graphSettings[2][0], graphSettings[2][1],
graphSettings[2][2]),
fontStyle=graphSettings[1],
lineThick=graphSettings[6],
lineColor=QtGui.QColor(graphSettings[4][0], graphSettings[4][1],
graphSettings[4][2]),
divisionLineColor=QtGui.QColor(graphSettings[5][0],
graphSettings[5][1],
graphSettings[5][2]),
backgroundColor=QtGui.QColor(graphSettings[3][0],
graphSettings[3][1],
graphSettings[3][2]))
scrollArea = QtGui.QScrollArea()
scrollArea.setWidget(graph)
mainFrame.grid.setRowMinimumHeight(
i + 1, 10 + graphSettings[7] + graphSettings[0] * 2 + 20)
#mainFrame.grid.addWidget(scrollArea, i+1, 2,i+6,10)
mainFrame.grid.addWidget(scrollArea, i + 1, 2, i + 1, 10)
def run():
#ターミナルコマンド
cmd = "ls"
subprocess.call(cmd, shell=True)
#データ読み込みと集計、結果をCSVで出力
rawdatafiles = ReadData.rawfilelisting("../data/updates/YoutubePakistan/")
#ReadData.readupdatedata(rawdatafiles)
#データチェック
# ReadData.checklink()
# ReadData.checkupdate()
# CSVからグラフへ
timerange = 60
number_of_files = int(timerange / 15)
DrawGraph.draw(number_of_files) #15分間分のファイル 4つ分読み込んでグラフへ
def insertGraph(self):
lista=[1,0,1,1,1,0,1,0,1,1,1,0,0,1,1,0,0,1]
size=500
PosX=10
PosY=10
self.graph = DrawGraph.drawGraph(PosX, PosY, lista,size, self.graphHeight,size/len(lista), 'ms', 1, self.fontSize, self.fontColor, self.fontStyle, self.lineThick, self.lineColor, self.divisionLineColor, self.backgroundColor)
scrollArea=QtGui.QScrollArea()
scrollArea.setWidgetResizable(True)
scrollArea.setWidget(self.graph)
self.grid.addWidget(scrollArea, 0,3,7,20)
def main(): # pragma: no cover
mongo_url = "mongodb://*****:*****@xxx:xxx/arxiv"
collection_name = "machine_learning" # machine_learning # astrophysics # statistics
# edge_pickle_file = "../pickle_file/mag_spec_cn_edges_{0}.pkl".format(collection_name)
# node_pickle_file = "../pickle_file/mag_spec_cn_nodes_{0}.pkl".format(collection_name)
graph_file = ("../pickle_file/mag_spec_cn_graph_{0}.pkl").format(collection_name)
# load the graph
graph = None
with open(graph_file, 'rb') as f:
graph = pickle.load(f)
nodes_count, edges_count = directGraphBasicStat(graph)
in_d,out_d = calcDeg(graph)
signal = "double_log" # single_log: log(fraction) # double_log: log(fraction) vs log(deg)
dp.drawHistogramSequence(in_d,nodes_count,("mag_{0}_simple_in_deg_distro").format(collection_name),"In Degree")
dp.drawHistogramSequence(out_d,nodes_count,("mag_{0}_simple_out_deg_distro").format(collection_name),"Out Degree")
dp.drawLogHistogram(in_d,nodes_count,signal,("mag_{0}_log_log_in_deg_distro").format(collection_name),"Log In Degree", "Log Fraction")
dp.drawLogHistogram(out_d,nodes_count,signal,("mag_{0}_log_log_out_deg_distro").format(collection_name),"Log Out Degree", "Log Fraction")
def createGraph():
graphSettings = ConfigGraphFile.getFileConfigs()
graph = DrawGraph.drawGraph(
5,
10 + 240 - graphSettings[7] - 2 * graphSettings[0], [],
550,
height=graphSettings[7],
sizeDivision=1,
zoom=50,
fontSize=graphSettings[0],
fontColor=QtGui.QColor(graphSettings[2][0], graphSettings[2][1],
graphSettings[2][2]),
fontStyle=graphSettings[1],
lineThick=graphSettings[6],
lineColor=QtGui.QColor(graphSettings[4][0], graphSettings[4][1],
graphSettings[4][2]),
divisionLineColor=QtGui.QColor(graphSettings[5][0],
graphSettings[5][1],
graphSettings[5][2]),
backgroundColor=QtGui.QColor(graphSettings[3][0], graphSettings[3][1],
graphSettings[3][2]))
return graph
import DrawGraph
V, E = map(int, input().split())
vertices = []
edges = []
for i in range(V):
vertices.append(input())
for i in range(E):
u, v = input().split()
edges.append((u, v))
draw = DrawGraph.DrawGraph(vertices=vertices,
edges=edges,
weight=[1, 2],
directed=True)
draw.colorVertices([], 'sds')
draw.colorEdges([], 'sds')
draw.show()
import GraphCreator
import DrawGraph
import networkx as nx
"""
This script is meant to draw the specified actor, as well as all the actors they've worked with
"""
"""
Specify actor name here
"""
actor_name = 'Tom Hanks'
g = GraphCreator.json_to_graph("data.json")
hub_list = [actor_name]
for movie in nx.neighbors(g, actor_name):
hub_list.append(movie)
for actor in nx.neighbors(g, movie):
hub_list.append(actor)
g_small = g.subgraph(hub_list)
DrawGraph.draw_graph(g_small, True)
def pie(self):
data = self.aggregate()
Draw.draw_pie(data)
def bar(self):
data = self.aggregate()
Draw.draw_bar(data)
import GraphCreator
import DrawGraph
"""
Display the entire graph
"""
DrawGraph.draw_graph(GraphCreator.json_to_graph('data.json'))