ommx.v1.parametric_instance_pb2

Classes

`Parameter`	Placeholder of a parameter in a parametrized optimization problem
`ParametricInstance`	Optimization problem including parameter, variables varying while solving the problem like penalty weights or dual variables.

Module Contents

class ommx.v1.parametric_instance_pb2.Parameter(*, id: int = ..., name: str | None = ..., subscripts: collections.abc.Iterable[int] | None = ..., parameters: collections.abc.Mapping[str, str] | None = ..., description: str | None = ...)

Placeholder of a parameter in a parametrized optimization problem

class ParametersEntry(*, key: str = ..., value: str = ...)

ClearField(field_name: Literal['key', b'key', 'value', b'value']) → None

KEY_FIELD_NUMBER: int

VALUE_FIELD_NUMBER: int

key: str

value: str

ClearField(field_name: Literal['_description', b'_description', '_name', b'_name', 'description', b'description', 'id', b'id', 'name', b'name', 'parameters', b'parameters', 'subscripts', b'subscripts']) → None

HasField(field_name: Literal['_description', b'_description', '_name', b'_name', 'description', b'description', 'name', b'name']) → bool

WhichOneof(oneof_group: Literal['_description', b'_description']) → Literal['description'] | None
WhichOneof(oneof_group: Literal['_name', b'_name']) → Literal['name'] | None

DESCRIPTION_FIELD_NUMBER: int

ID_FIELD_NUMBER: int

NAME_FIELD_NUMBER: int

PARAMETERS_FIELD_NUMBER: int

SUBSCRIPTS_FIELD_NUMBER: int

description: str: Human-readable description for the parameter

id: int

ID for the parameter

IDs are not required to be sequential.
The ID must be unique within the instance including the decision variables.

name: str: Name of the parameter. e.g. x

property parameters: google.protobuf.internal.containers.ScalarMap[str, str]: Additional metadata for the parameter, same usage as DecisionVariable.parameters

property subscripts: google.protobuf.internal.containers.RepeatedScalarFieldContainer[int]: Subscripts of the parameter, same usage as DecisionVariable.subscripts

class ommx.v1.parametric_instance_pb2.ParametricInstance(*, description: ommx.v1.instance_pb2.Instance.Description | None = ..., decision_variables: collections.abc.Iterable[ommx.v1.decision_variables_pb2.DecisionVariable] | None = ..., parameters: collections.abc.Iterable[global___Parameter] | None = ..., objective: ommx.v1.function_pb2.Function | None = ..., constraints: collections.abc.Iterable[ommx.v1.constraint_pb2.Constraint] | None = ..., sense: ommx.v1.instance_pb2.Instance.Sense.ValueType = ..., constraint_hints: ommx.v1.constraint_hints_pb2.ConstraintHints | None = ..., removed_constraints: collections.abc.Iterable[ommx.v1.constraint_pb2.RemovedConstraint] | None = ..., decision_variable_dependency: collections.abc.Mapping[int, ommx.v1.function_pb2.Function] | None = ..., named_functions: collections.abc.Iterable[ommx.v1.named_function_pb2.NamedFunction] | None = ...)

Optimization problem including parameter, variables varying while solving the problem like penalty weights or dual variables. These parameters are not decision variables.

class DecisionVariableDependencyEntry(*, key: int = ..., value: ommx.v1.function_pb2.Function | None = ...)

ClearField(field_name: Literal['key', b'key', 'value', b'value']) → None

HasField(field_name: Literal['value', b'value']) → bool

KEY_FIELD_NUMBER: int

VALUE_FIELD_NUMBER: int

key: int

property value: ommx.v1.function_pb2.Function

ClearField(field_name: Literal['constraint_hints', b'constraint_hints', 'constraints', b'constraints', 'decision_variable_dependency', b'decision_variable_dependency', 'decision_variables', b'decision_variables', 'description', b'description', 'named_functions', b'named_functions', 'objective', b'objective', 'parameters', b'parameters', 'removed_constraints', b'removed_constraints', 'sense', b'sense']) → None

HasField(field_name: Literal['constraint_hints', b'constraint_hints', 'description', b'description', 'objective', b'objective']) → bool

CONSTRAINTS_FIELD_NUMBER: int

CONSTRAINT_HINTS_FIELD_NUMBER: int

DECISION_VARIABLES_FIELD_NUMBER: int

DECISION_VARIABLE_DEPENDENCY_FIELD_NUMBER: int

DESCRIPTION_FIELD_NUMBER: int

NAMED_FUNCTIONS_FIELD_NUMBER: int

OBJECTIVE_FIELD_NUMBER: int

PARAMETERS_FIELD_NUMBER: int

REMOVED_CONSTRAINTS_FIELD_NUMBER: int

SENSE_FIELD_NUMBER: int

property constraint_hints: ommx.v1.constraint_hints_pb2.ConstraintHints: Constraint hints to be used by solver to gain performance. They are derived from one-or-more constraints in the instance and typically contains information of special types of constraints (e.g. one-hot, SOS, …).

property constraints: google.protobuf.internal.containers.RepeatedCompositeFieldContainer[ommx.v1.constraint_pb2.Constraint]: Constraints of the optimization problem. This may contain parameters in addition to the decision variables.

property decision_variable_dependency: google.protobuf.internal.containers.MessageMap[int, ommx.v1.function_pb2.Function]: When a decision variable is dependent on another decision variable as polynomial, this map contains the ID of the dependent decision variable as key and the polynomial as value.

property decision_variables: google.protobuf.internal.containers.RepeatedCompositeFieldContainer[ommx.v1.decision_variables_pb2.DecisionVariable]: Decision variables used in this instance

property description: ommx.v1.instance_pb2.Instance.Description

property named_functions: google.protobuf.internal.containers.RepeatedCompositeFieldContainer[ommx.v1.named_function_pb2.NamedFunction]

property objective: ommx.v1.function_pb2.Function: Objective function of the optimization problem. This may contain parameters in addition to the decision variables.

property parameters: google.protobuf.internal.containers.RepeatedCompositeFieldContainer[global___Parameter]

Parameters of this instance

The ID must be unique within the instance including the decision variables.

property removed_constraints: google.protobuf.internal.containers.RepeatedCompositeFieldContainer[ommx.v1.constraint_pb2.RemovedConstraint]: Constraints removed via preprocessing. These are restored when evaluated into ommx.v1.Solution.

sense: ommx.v1.instance_pb2.Instance.Sense.ValueType: The sense of this problem, i.e. minimize the objective or maximize it.