def __init__(self, fname, sname):
super(CoreMinEdgesExperiments, self).__init__()
self.fname = fname
self.sname = sname
self.graph = nx.read_edgelist(self.fname)
self.kcore = kcore.KCore(self.graph)
self.number_of_nodes = self.graph.number_of_nodes()
self.number_of_edges = self.graph.number_of_edges()
def __init__(self, base, sname, adjacency=False):
super(KCoreGraph, self).__init__()
self.sname = sname
if adjacency:
self.graph = nx.read_adjlist(base)
else:
self.graph = nx.read_edgelist(base)
self.cnumber = kcore.KCore(self.graph).coreNumber()
self.top = [1, 0.2, 0.1]
self.ori_graph = self.graph.copy()
def __init__(self, fname, sname, adjacency=False, ftype='file'):
super(KCoreHistogram, self).__init__()
self.sname = sname # do not save if sname is none
if ftype == 'file':
if not adjacency:
self.graph = nx.read_edgelist(fname)
else:
self.graph = nx.read_adjlist(fname)
else:
self.graph = fname.copy() # fname is a networkx graph
self.kcore = kcore.KCore(self.graph)
print('Number of nodes: {}\t Number of edges: {}'.format(\
self.graph.number_of_nodes(), self.graph.number_of_edges()))
def __init__(self,
fname,
sname,
adjacency=False,
mode='111',
ftype='file',
top=None):
super(KCoreExperiment, self).__init__()
self.fname = fname
self.sname = sname # If sname is none retults are turned not saved
self.adj = adjacency
"""
1st digit for random node deletion,
2nd digit for random edge deletion,
3rd digit for random rewiring preserving degree dist
"""
self.mode = mode
if ftype == 'file': # ftype can be file on graph. if graph fname is a networkx graph object
if not self.adj:
self.graph = nx.read_edgelist(self.fname)
self.graph.remove_edges_from(self.graph.selfloop_edges())
else:
self.graph = nx.read_adjlist(self.fname)
self.graph.remove_edges_from(self.graph.selfloop_edges())
self.ori_graph = None
else:
self.graph = fname.copy()
self.ori_graph = fname.copy()
self.kcore = kcore.KCore(self.graph)
self.number_of_nodes = self.graph.number_of_nodes()
self.number_of_edges = self.graph.number_of_edges()
if top is None:
self.top = [x / 100 for x in range(100, 1, -5)
] # Percentage of top nodes consider
else:
self.top = top
self.stats = statistics.Statistics()
def __init__(self, fname, sname):
super(KCoreTriangles, self).__init__()
self.graph = nx.read_edgelist(fname)
self.kcore = kcore.KCore(self.graph)
self.top = int(self.graph.number_of_nodes() * 0.1)
self.sname = sname