QuadraticModel¶

class QuadraticModel¶

Bases: ABC

The base of the deprecated quadratic models of Amplify v0.

Use Model. A subclass fixes the type of the variable that the intermediate model accepts, and this class holds a Model and converts it on demand. Do not use this class itself: it is abstract, and only the subclasses below name a variable type.

Methods

`__init__`
`check_constraints`	Test every input constraint against the values.

Attributes

`input_constraints`	The constraints that the model received.
`input_matrix`	The objective function as a matrix.
`input_poly`	The objective function that the model received.
`logical_mapping`	The map from the input variables to the intermediate variables.
`logical_matrix`	The intermediate model as a matrix.
`logical_model_matrix`	The unconstrained intermediate model as a matrix.
`logical_model_poly`	The intermediate model as one polynomial with no constraint.
`logical_poly`	The objective function of the intermediate model.
`num_input_vars`	The number of the variables that the input model uses.
`num_logical_vars`	The number of the variables that the intermediate model uses.
`substitution_multiplier`	The multiplier of the penalty that the quadratization adds.

__add__(arg: Constraint | ConstraintList)¶

Return a new model that holds this model and the constraint.

Parameters:: arg – The constraint to add.
Returns:: A model of the same class.

__iadd__(arg: Constraint | ConstraintList)¶

Add the constraint to this model and return this model.

Parameters:: arg – The constraint to add.
Returns:: This model.

__init__( arg0: Poly, arg1: Constraint | ConstraintList | None = None, *, method: QuadratizationMethod = QuadratizationMethod.IshikawaKZFD, )¶
__init__( arg0: Matrix, arg1: Constraint | ConstraintList | None = None, *, method: QuadratizationMethod = QuadratizationMethod.IshikawaKZFD, )
__init__(arg0: Model, arg1=None, *, method: QuadratizationMethod = QuadratizationMethod.IshikawaKZFD)
__init__( arg0: Constraint | ConstraintList, arg1=None, *, method: QuadratizationMethod = QuadratizationMethod.IshikawaKZFD, )

__radd__(arg: Constraint | ConstraintList)¶

Return a new model that holds the constraint and this model.

Parameters:: arg – The constraint to add.
Returns:: A model of the same class.

check_constraints(values: Values) → list[tuple[Constraint, bool]]¶

Test every input constraint against the values.

Parameters:: values – The values to substitute, such as result.best.values.
Returns:: One pair of a constraint and a bool for each input constraint. The bool says whether the values satisfy that constraint.

property input_constraints: ConstraintList¶

The constraints that the model received.

Returns:: The constraints of the model, before the conversion.

property input_matrix¶

The objective function as a matrix. Removed in v1.7.0.

Use input_poly. A model holds its objective function as a Poly.

Raises:: NotImplementedError – Always.

property input_poly: Poly | None¶

The objective function that the model received.

Returns:: The objective function, or None when the model has none.

property logical_mapping: IntermediateMapping¶

The map from the input variables to the intermediate variables.

Returns:: The mapping that the conversion to the intermediate model made.

property logical_matrix¶

The intermediate model as a matrix. Removed in v1.7.0.

Use logical_model_poly. A model holds its objective function as a Poly.

Raises:: NotImplementedError – Always.

property logical_model_matrix¶

The unconstrained intermediate model as a matrix. Obsolete.

Use logical_model_poly.

Raises:: NotImplementedError – Always.

property logical_model_poly: Poly¶

The intermediate model as one polynomial with no constraint.

Returns:: The objective function of the intermediate model, with the penalty function of every constraint added to it.

property logical_poly: Poly | None¶

The objective function of the intermediate model.

The constraints are not in it. Use logical_model_poly to get them too.

Returns:: The objective function, or None when the intermediate model has none.

property num_input_vars: int¶

The number of the variables that the input model uses.

Returns:: The count.

property num_logical_vars: int¶

The number of the variables that the intermediate model uses.

The quadratization adds a variable, so this count is not less than num_input_vars.

Returns:: The count.

property substitution_multiplier: float¶

The multiplier of the penalty that the quadratization adds.

The conversion to the intermediate model multiplies the penalty function of a substitution by this value. Raise it when the solution breaks a substitution. The setter raises ValueError when the value is not a positive float.

Returns:: The multiplier. It is positive.