def emptyNode_test():
Friends = []
G = Graph()
G.add_nodes_from(Friends)
obs = G.G
exp = {}
assert_equal(exp, obs)
def NotGraphDD_test():
# case where graph is empty
G_empt = Graph()
obs = G_empt.degree_distribution()
exp = {}
# capture standard out
assert_equal(exp, obs)
def __init__(self):
"""INIT
1) Inherit the graph class from nets
2) Create the CBN and NIC data structures.
"""
Graph.__init__(self)
self.CBN = {} # nodes are the key, community the value.
self.NIC = {} # communities are the key, nodes the values.
def listOList_test():
G = Graph()
G.add_nodes_from([[
'A',
], ['B']])
obs = G.G.keys()
exp = {'A', 'B'}
assert_equal(exp, obs)
def removePartEdge_test():
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
exp = G.edges()
# remove an edge but give a single part of the edge
G.remove_edge(['Alex'])
obs = G.edges()
assert_equal(exp, obs)
def addNoEdge_test():
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
exp = G.edges()
# remove an edge but give an empty list
G.remove_edge([])
obs = G.edges()
assert_equal(exp, obs)
def removeNodeSet_test():
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
# try to remove an empty set
G.remove_node({})
exp = {'Alex', 'Julie', 'Rob', 'Ved', 'Michael', 'Mark', 'Jeff'}
obs = G.nodes()
assert_equal(exp, obs)
def removeEmptylst_test():
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
# try and remove an empty list
G.remove_node(node=[])
exp = {'Alex', 'Julie', 'Rob', 'Ved', 'Michael', 'Mark', 'Jeff'}
obs = G.nodes()
assert_equal(exp, obs)
def removeEmptyStr_test():
# try to remove a node but user gives an empty string
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
G.remove_node('')
exp = {'Alex', 'Julie', 'Rob', 'Ved', 'Michael', 'Mark', 'Jeff'}
obs = G.nodes()
assert_equal(exp, obs)
def removeEdgeMorethan2_test():
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
# remove an edge but give three entries
G.remove_edge(['Alex', 'Julie', 'Michael'])
exp = 21
obs = len(G.edges())
assert_equal(exp, obs)
def info_test():
# return info of an empty graph
G = Graph()
obs = G.info()
exp = {
'num_nodes': 0,
'num_edgeSets': 0,
'mean_degree': [],
'degree_std': [],
'orph_edges': [],
'orph_nodes': []
}
assert_equal(exp, obs)
def ClusteringCoefNodesDontExist_test():
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
obs = G.clustering_coef(['Lexa', 'Roy', 'Demmi'])
exp = {}
assert_equal(exp, obs)
def hasNodeEmpty_test():
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
# given an empty list to "has_node" should return empty list
exp = False
obs = G.has_node([])
assert_equal(exp, obs)
def clustCoefempty_test():
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
# give an empty list
obs = G.clustering_coef(node_list=[])
exp = {}
assert_equal(exp, obs)
def degreeNodeList():
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
# give and empty list
obs = G.degree(node_L=[])
exp = False
assert_equal(exp, obs)
def emptyEdges_test():
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
# test "edges" when given a string and not a list of strings
obs = G.edges('Alex')
exp = [['Alex', 'Julie'], ['Alex', 'Michael'], ['Alex', 'Ved']]
assert_equal(exp, obs)
def numNode_test():
# create a small graph
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
exp = {'Alex', 'Julie', 'Rob', 'Ved', 'Michael', 'Mark', 'Jeff'}
obs = G.nodes()
assert_equal(exp, obs)
def neighborsNoNode_test():
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
# give empty list
obs = G.neighbors([])
# need to figure how to capture standard out
exp = False
assert_equal(exp, obs)
def writecomms(Graph, filename, delimiter="\t", edge_list=False):
"""This function takes in a graph in 'dictionary form' and
writes it to a file of text. There are three values it
requires: 1) the Graph() class or network that the user
wants written, 2) a file name for the file that will be printed,
and 3) the desired delimiter that will seperate values.
The Graph() lass is specific to this particular module.
The actual graph object in the Graph() class must be in
dictionary form. Here the nodes are dictionary keys
and values of keys are the other nodes the key node are linked
to.
The default setting will only create a node to community list. if
edge_list = True then it was print a and edge list as well as the
community that first column node belongs to.
The file name can be made up of any alpha numeric combination.
However, it must be utf-8 encoding.
The delimiter default is a tab denoted by '\t'. However,
the user can specify any utf-8 alpha-numeric character.
This does not return anything, but prints to a file through
standard out."""
network_file = open(filename, "w")
# G has to be a dictionary object
# loop through each dictionary key
if edge_list:
for n in Graph.G:
# loop through each item in a dictionary
for ne in Graph.G[n]:
comm = C.CBN[n][0]
# write each edge as a seperate line in the output file
network_file.write(''.join(
[n, delimiter, ne, delimiter, comm, '\n']))
# print to console to make sure things look okay
print(n, delimiter, ne)
# close the file
network_file.close()
else:
for n in Graph.nodes():
# loop through each item in a dictionary
comm = C.CBN[n][0]
# write each edge as a seperate line in the output file
network_file.write(''.join([n, delimiter, comm, '\n']))
# print to console to make sure things look okay
print(n, delimiter, ne)
# close the file
network_file.close()
def relabelNodesUneven_test():
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
Notsame = ['A', 'B', 'C', 'D', 'E', 'F']
obs = relabel_nodes(G, Notsame)
exp = False
# get standard out
assert_equal(exp, obs)
def relabelNodesBlank_test():
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
Blank = ['', '', '', '', '', '', '']
# give a blank list, a list with stuff, but they are all the same
# and are empty character strings
obs = relabel_nodes(G, Blank)
exp = {'': ['', '', '']}
assert_equal(exp, obs)
def Graph_setup():
Friends = ['Alex', 'Julie', 'Rob', 'Ved', 'Michael', 'Mark', 'Jeff']
Relationships = [['Alex', 'Julie'], ['Julie', 'Alex'], ['Alex', 'Michael'],
['Michael', 'Alex'], ['Julie', 'Michael'],
['Michael', 'Julie'], ['Mark', 'Michael'],
['Michael', 'Mark'], ['Jeff', 'Mark'], ['Mark', 'Jeff'],
['Ved', 'Michael'], ['Michael', 'Ved'], ['Alex', 'Ved'],
['Ved', 'Alex'], ['Ved', 'Jeff'], ['Jeff', 'Ved'],
['Ved', 'Rob'], ['Rob', 'Ved'], ['Julie', 'Rob'],
['Rob', 'Julie'], ['Rob', 'Jeff'], ['Jeff', 'Rob']]
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
def subgraphNoneNode_test():
G = Graph()
G.add_nodes_from(Friends)
G.add_edges_from(Relationships)
# A node in the subgraph list does not exist in "Nodes"
sub_list = ['Alex', 'Michael', 'Julie', 'Matt']
obs = subgraph(G, sub_list).G
exp = {
'Alex': ['Julie', 'Michael'],
'Julie': ['Alex', 'Michael'],
'Michael': ['Alex', 'Julie', 'Ved']
}
assert_equal(exp, obs)
def configuration_model(self):
"""configuration_model()
Build a configuration model using the degree distribution
of the current graph."""
DD = self.degree_distribution()
# build a second dictionary from DD where each node is a key
# and the value is the node's degree distribution.
keys_DD = DD.keys()
cm_DD = {}
num_edges = 0
# loop through all degrees and find all the nodes with that
# degree
for nn in keys_DD:
# grab each node with a particular degree
nodes = DD[nn]
# put that node with its degree into a dictionary where
# the node is the key, and its degree is the value
# there should only be 1 value for each key
for d in nodes:
num_edges = num_edges + nn
cm_DD[d] = [nn]
# loops through all the nodes, and randomly
# connect them with other nodes, creating a
# new randomly generated graph.
nodes = list(cm_DD.keys())
num_nodes = len(nodes)
edge_listCM = []
# create a graph and add all nodes
CMG = Graph()
CMG.add_nodes_from(nodes)
choices = list(range(0, num_nodes))
NN_remain = len(choices)
while NN_remain > 0:
#print(choices)
# randomly choose a "originating node"
pick_n1 = random.choice(choices)
node1 = nodes[pick_n1]
C_index1 = choices.index(pick_n1)
# randomly choose another node for the
# "orginating node" to connect to
# ("connecting node")
if C_index1 == len(choices) - 1:
choices2 = choices[0:C_index1]
elif C_index1 == 0:
choices2 = choices[1:len(choices) + 1]
else:
P1 = choices[0:C_index1]
P2 = choices[C_index1 + 1:len(choices)]
choices2 = P1 + P2
pick_n2 = random.choice(choices2)
node2 = nodes[pick_n2]
# create an edge
edge = [node1, node2]
rev_edge = [node2, node1]
# add the node to the graph
EB1 = CMG.add_edge(edge)
#EB2 = CMG.add_edge(rev_edge)
#print(EB1, EB2)
# if the edge sets did not exist then remove a degree
# from the two randomly choosen nodes, remove a node from
# NN_remain if the degree of a node reaches 0. If
# the edge set already existed then choose another edge set
if EB1:
node_val1 = [cm_DD[node1][0] - 1]
node_val2 = [cm_DD[node2][0] - 1]
#print(node_val1, node_val2)
cm_DD[node1] = node_val1
cm_DD[node2] = node_val2
if cm_DD[node1][0] == 0:
#print(choices)
#print("P1", pick_n1)
#print(choices)
choices.remove(pick_n1)
if cm_DD[node2][0] == 0:
#print(choices2)
#print("P2", pick_n2)
choices.remove(pick_n2)
#print(choices)
NN_remain = len(choices)
#print(NN_remain)
#print(NN_remain, choices)
#print(cm_DD)
#num_edges = num_edges/2
#for e in num_edges:
#random.random()
#return(cm_DD)
return (CMG.G)
def moreThanOne_test():
G = Graph()
G.add_node(['A', 'B'])
obs = G.G
exp = {'A': []}
assert_equal(exp, obs)
def emptySetNodes_test():
G = Graph()
obs = G.nodes()
exp = set()
# check nodes when the graph is empty
assert_equal(exp, obs)