def make_graph_UPA(num_nodes, num_edges_per_node):
"""
Function that creates an undirected graph with num_nodes nodes
represented as an adjacency list using an adapted DPA algorithm given in
assignment #1: 'Analysis of Citation Graphs' to generate the edges.
"""
# Test num_nodes and num_edges_per_node to determine whether
# the algoritnm can be used
_num_nodes = int(num_nodes)
_num_edges_per_node = int(num_edges_per_node)
if _num_nodes < _num_edges_per_node:
print "###> Error: _num_nodes must be larger than or equal to _num_edges_per_node!"
quit()
# Create a complete graph of size num_edges_per_node
print "Generating the initial graph."
_graph = degree.make_complete_graph(_num_edges_per_node)
# Initialize variables
_node_counter = _num_edges_per_node
_edge_counter = int( 0.5 * _num_edges_per_node * ( _num_edges_per_node - 1 ))
print "...............", _node_counter, "nodes generated."
print "....................", _edge_counter, "edges generated."
print
# Add nodes to graph according to the UPA algorithm
# Create UPATrial object that is used to generate the edges with
# the newly generated nodes
_trail = UPA.UPATrial(_num_edges_per_node)
print "Generating additional nodes."
for _index in range(_num_edges_per_node, _num_nodes):
# Create additional node
_new_nodes_edges = _trail.run_trial(_num_edges_per_node)
# Add the new node to _graph
_graph[_index] = _new_nodes_edges
# Add the edges from the selected nodes to the new node
for _node in _new_nodes_edges:
_graph[_node].add(_index)
_node_counter += 1
_edge_counter += len(_new_nodes_edges)
if _node_counter % 100 == 0:
print "...............", _node_counter, "nodes generated."
print "...............", _node_counter, "nodes generated."
print "....................", _edge_counter, "edges generated."
# Return the resulting graph
return _graph
def make_graph_DPA(num_nodes, num_edges_per_node):
"""
Function that creates a directed graph with num_nodes nodes
represented as an adjacency list using the DPA algorithm given in the
assignment.
"""
# Test num_nodes and num_edges_per_node to determine whether
# the algoritnm can be used
_num_nodes = int(num_nodes)
_num_edges_per_node = int(num_edges_per_node)
if _num_nodes < _num_edges_per_node:
print "###> Error: _num_nodes must be larger than or eagle to _num_edges_per_node!"
quit()
# Create a complete graph of size num_edges_per_node and compute its in degrees
print "Generating the initial graph."
_graph = degree.make_complete_graph(_num_edges_per_node)
# Initialize variables
_counter = _num_edges_per_node
# Add nodes to graph according to the DPA algorithm
# Create DPATrial object the is used to generate the edges with the new nodes
_trail = DPA.DPATrial(_num_edges_per_node)
print "Generating additional nodes."
for _index in range(_num_edges_per_node, _num_nodes):
# Create additional node
_new_nodes_edges = _trail.run_trial(_num_edges_per_node)
# Add the new node to _graph
_graph[_index] = _new_nodes_edges
_counter += 1
if _counter % 1000 == 0:
print "...............", _counter, "nodes generated."
# Return the resulting graph
return _graph