gpp.py File Reference

model for the graph partitioning problem More...

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Functions
def	gpp (V, E)
def	gpp_qo (V, E)
def	gpp_qo_ps (V, E)
def	gpp_soco (V, E)
def	make_data (n, prob)

Variables
	V
	E
	model = gpp(V,E)
	x = model.data
	status = model.getStatus()
	s
	z

Detailed Description

model for the graph partitioning problem

Definition in file gpp.py.

Function Documentation

def gpp.gpp	(		V,
			E
	)

gpp -- model for the graph partitioning problem
Parameters:
    - V: set/list of nodes in the graph
    - E: set/list of edges in the graph
Returns a model, ready to be solved.

Definition at line 9 of file gpp.py.

def gpp.gpp_qo	(		V,
			E
	)

gpp_qo -- quadratic optimization model for the graph partitioning problem
Parameters:
    - V: set/list of nodes in the graph
    - E: set/list of edges in the graph
Returns a model, ready to be solved.

Definition at line 37 of file gpp.py.

def gpp.gpp_qo_ps	(		V,
			E
	)

gpp_qo_ps -- quadratic optimization, positive semidefinite model for the graph partitioning problem
Parameters:
    - V: set/list of nodes in the graph
    - E: set/list of edges in the graph
Returns a model, ready to be solved.

Definition at line 58 of file gpp.py.

def gpp.gpp_soco	(		V,
			E
	)

gpp -- model for the graph partitioning problem in soco
Parameters:
    - V: set/list of nodes in the graph
    - E: set/list of edges in the graph
Returns a model, ready to be solved.

Definition at line 79 of file gpp.py.

def gpp.make_data	(		n,
			prob
	)

make_data: prepare data for a random graph
Parameters:
    - n: number of vertices
    - prob: probability of existence of an edge, for each pair of vertices
Returns a tuple with a list of vertices and a list edges.

Definition at line 120 of file gpp.py.