openjij.model.model Namespace Reference

Functions
	make_BinaryQuadraticModel (dict linear, dict quadratic, sparse)
	make_BinaryQuadraticModel_from_JSON (dict obj)
	BinaryQuadraticModel (linear, quadratic, *args, **kwargs)
	bqm_from_numpy_matrix (mat, list variables=None, offset=0.0, vartype="BINARY", **kwargs)
	bqm_from_qubo (Q, offset=0.0, **kwargs)
	bqm_from_ising (linear, quadratic, offset=0.0, **kwargs)
	make_BinaryPolynomialModel (polynomial, index_type=None, tuple_size=0)
	make_BinaryPolynomialModel_from_JSON (obj)
	BinaryPolynomialModel (*args, **kwargs)
	_BinaryPolynomialModel_from_dict (dict polynomial, vartype)
	_BinaryPolynomialModel_from_list (list keys, list values, vartype)
	make_BinaryPolynomialModel_from_hising (*args, **kwargs)
	_make_BinaryPolynomialModel_from_hising_from_dict (dict polynomial)
	_make_BinaryPolynomialModel_from_hising_from_list (list keys, list values)
	make_BinaryPolynomialModel_from_hubo (*args, **kwargs)
	_make_BinaryPolynomialModel_from_hubo_from_dict (dict polynomial)
	_make_BinaryPolynomialModel_from_hubo_from_list (list keys, list values)
	_to_cxxcimod (vartype)

Variables
	from_numpy_matrix
	from_qubo
	from_ising
	from_serializable
	from_hising
	from_hubo
	model_type

Detailed Description

| This module defines the BinaryQuadraticModel with the Hamiltonian,

.. math::

    H = \\sum_{i\\neq j} J_{ij}\\sigma_i \\sigma_j + \\sum_{i} h_{i}\\sigma_i,

| in an Ising form and

.. math::

    H = \\sum_{ij} Q_{ij}x_i x_j + \\sum_{i} H_{i}x_i,

| in a QUBO form.
| The methods and usage are basically the same as `dimod <https://github.com/dwavesystems/dimod>`_.

Function Documentation

_BinaryPolynomialModel_from_dict()

openjij.model.model._BinaryPolynomialModel_from_dict ( dict  polynomial,   vartype  )

protected

References openjij.model.model._to_cxxcimod().

Referenced by openjij.model.model.BinaryPolynomialModel().

Here is the call graph for this function:

Here is the caller graph for this function:

_BinaryPolynomialModel_from_list()

openjij.model.model._BinaryPolynomialModel_from_list ( list  keys, list  values,   vartype  )

protected

References openjij.model.model._to_cxxcimod().

Referenced by openjij.model.model.BinaryPolynomialModel().

Here is the call graph for this function:

Here is the caller graph for this function:

_make_BinaryPolynomialModel_from_hising_from_dict()

openjij.model.model._make_BinaryPolynomialModel_from_hising_from_dict ( dict  polynomial )

protected

References openjij.model.model.from_hising.

Referenced by openjij.model.model.make_BinaryPolynomialModel_from_hising().

Here is the caller graph for this function:

_make_BinaryPolynomialModel_from_hising_from_list()

openjij.model.model._make_BinaryPolynomialModel_from_hising_from_list ( list  keys, list  values  )

protected

References openjij.model.model.from_hising.

Referenced by openjij.model.model.make_BinaryPolynomialModel_from_hising().

Here is the caller graph for this function:

_make_BinaryPolynomialModel_from_hubo_from_dict()

openjij.model.model._make_BinaryPolynomialModel_from_hubo_from_dict ( dict  polynomial )

protected

References openjij.model.model.from_hubo.

Referenced by openjij.model.model.make_BinaryPolynomialModel_from_hubo().

Here is the caller graph for this function:

_make_BinaryPolynomialModel_from_hubo_from_list()

openjij.model.model._make_BinaryPolynomialModel_from_hubo_from_list ( list  keys, list  values  )

protected

References openjij.model.model.from_hubo.

Referenced by openjij.model.model.make_BinaryPolynomialModel_from_hubo().

Here is the caller graph for this function:

_to_cxxcimod()

openjij.model.model._to_cxxcimod (   vartype )

protected

References openjij.model.model.from_serializable.

Referenced by openjij.model.model._BinaryPolynomialModel_from_dict(), openjij.model.model._BinaryPolynomialModel_from_list(), and openjij.model.model.BinaryPolynomialModel().

Here is the caller graph for this function:

BinaryPolynomialModel()

openjij.model.model.BinaryPolynomialModel	(	*	args,
		**	kwargs
	)

References openjij.model.model._BinaryPolynomialModel_from_dict(), openjij.model.model._BinaryPolynomialModel_from_list(), and openjij.model.model._to_cxxcimod().

Here is the call graph for this function:

BinaryQuadraticModel()

openjij.model.model.BinaryQuadraticModel	(		linear,
			quadratic,
		*	args,
		**	kwargs
	)

Generate BinaryQuadraticModel object.

Attributes:
    vartype (dimod.Vartype): variable type SPIN or BINARY
    linear (dict): represents linear term
    quadratic (dict): represents quadratic term
    offset (float): represents constant energy term when convert to SPIN from BINARY
    num_variables (int): represents number of variables in the model
    variables (list): represents variables of the binary quadratic model
Args:
    linear (dict): linear biases
    quadratic (dict): quadratic biases
    offset (float): offset
    vartype (openjij.variable_type.Vartype): vartype ('SPIN' or 'BINARY')
    kwargs:
Returns:
    generated BinaryQuadraticModel
Examples:
    BinaryQuadraticModel can be initialized by specifing h and J::

        >>> h = {0: 1, 1: -2}
        >>> J = {(0, 1): -1, (1, 2): -3, (2, 3): 0.5}
        >>> bqm = oj.BinaryQuadraticModel(self.h, self.J)

    You can also use strings and tuples of integers (up to 4 elements) as indices::

        >>> h = {'a': 1, 'b': -2}
        >>> J = {('a', 'b'): -1, ('b', 'c'): -3, ('c', 'd'): 0.5}
        >>> bqm = oj.BinaryQuadraticModel(self.h, self.J)

bqm_from_ising()

openjij.model.model.bqm_from_ising	(		linear,
			quadratic,
			offset = 0.0,
		**	kwargs
	)

References openjij.model.model.from_ising.

bqm_from_numpy_matrix()

openjij.model.model.bqm_from_numpy_matrix	(		mat,
		list	variables = None,
			offset = 0.0,
			vartype = "BINARY",
		**	kwargs
	)

References openjij.model.model.from_numpy_matrix.

bqm_from_qubo()

openjij.model.model.bqm_from_qubo	(		Q,
			offset = 0.0,
		**	kwargs
	)

References openjij.model.model.from_qubo.

make_BinaryPolynomialModel()

openjij.model.model.make_BinaryPolynomialModel	(		polynomial,
			index_type = None,
			tuple_size = 0
	)

make_BinaryPolynomialModel_from_hising()

openjij.model.model.make_BinaryPolynomialModel_from_hising	(	*	args,
		**	kwargs
	)

References openjij.model.model._make_BinaryPolynomialModel_from_hising_from_dict(), and openjij.model.model._make_BinaryPolynomialModel_from_hising_from_list().

Here is the call graph for this function:

make_BinaryPolynomialModel_from_hubo()

openjij.model.model.make_BinaryPolynomialModel_from_hubo	(	*	args,
		**	kwargs
	)

References openjij.model.model._make_BinaryPolynomialModel_from_hubo_from_dict(), and openjij.model.model._make_BinaryPolynomialModel_from_hubo_from_list().

Here is the call graph for this function:

make_BinaryPolynomialModel_from_JSON()

openjij.model.model.make_BinaryPolynomialModel_from_JSON

(

obj

)

make_BinaryQuadraticModel()

openjij.model.model.make_BinaryQuadraticModel	(	dict	linear,
		dict	quadratic,
			sparse
	)

BinaryQuadraticModel factory.

Returns:
    generated BinaryQuadraticModel class

make_BinaryQuadraticModel_from_JSON()

openjij.model.model.make_BinaryQuadraticModel_from_JSON

(

dict

obj

)

Make BinaryQuadraticModel from JSON.

Returns:
    corresponding BinaryQuadraticModel type

Variable Documentation

from_hising

openjij.model.model.from_hising

Referenced by openjij.model.model._make_BinaryPolynomialModel_from_hising_from_dict(), and openjij.model.model._make_BinaryPolynomialModel_from_hising_from_list().

from_hubo

openjij.model.model.from_hubo

Referenced by openjij.model.model._make_BinaryPolynomialModel_from_hubo_from_dict(), and openjij.model.model._make_BinaryPolynomialModel_from_hubo_from_list().

from_ising

openjij.model.model.from_ising

Referenced by openjij.model.model.bqm_from_ising().

from_numpy_matrix

openjij.model.model.from_numpy_matrix

Referenced by openjij.model.model.bqm_from_numpy_matrix().

from_qubo

openjij.model.model.from_qubo

Referenced by openjij.model.model.bqm_from_qubo().

from_serializable

openjij.model.model.from_serializable

Referenced by openjij.model.model._to_cxxcimod().

model_type

openjij.model.model.model_type