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MultiValueParameter class

Bases: Parameter

A data class representing a multi-value parameter in an optimization model.

The MultiValueParameter class is a subclass of Parameter and is used to represent parameters with multiple values in an optimization model. It provides properties to access the set of parameter values, lower bounds, and upper bounds.

Source code in pyorlib/structures/parameters/multi_value_parameter.py 
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@dataclass(frozen=True)
class MultiValueParameter(Parameter):
    """
    A data class representing a multi-value parameter in an optimization model.

    The `MultiValueParameter` class is a subclass of `Parameter` and is used to represent parameters with multiple
    values in an optimization model. It provides properties to access the set of parameter values, lower bounds,
    and upper bounds.
    """

    values: Tuple[float, ...] | None = None
    """ A tuple containing the parameter values, or None if no values are specified. """

    lower_bounds: Tuple[float, ...] | None = None
    """ A tuple containing the lower bounds for each parameter value, or None if no lower bounds are specified. """

    upper_bounds: Tuple[float, ...] | None = None
    """ A tuple containing the upper bounds for each parameter value, or None if no upper bounds are specified. """

    def __post_init__(self) -> None:
        # Parameter Validations
        if self.value_type is None:
            raise ValueError("Parameter value type is required.")

        if self.parameter_type == ParameterType.FIXED and self.values is not None:
            if self.lower_bounds is not None or self.upper_bounds is not None:
                raise ValueError("Parameters with values cannot have bounds.")
            if len(self.values) == 0:
                raise ValueError("Parameter values cannot be empty.")
            for val in self.values:
                if val >= 1e20 or val <= -1e20:
                    raise ValueError("Parameter values cannot be [+/-]infinity.")

                # Value and Value Type validations
                if self.value_type == ValueType.BINARY and not ValueTypeValidator.is_binary(val):
                    raise ValueError("Parameter set values must be valid integer numbers.")
                elif self.value_type == ValueType.INTEGER and not ValueTypeValidator.is_integer(val):
                    raise ValueError("Parameter set values must be valid integer numbers.")
        elif (
            self.parameter_type == ParameterType.BOUNDED
            and self.lower_bounds is not None
            and self.upper_bounds is not None
        ):
            if self.values is not None:
                raise ValueError("Parameters with bounds cannot have a value.")
            if len(self.lower_bounds) != len(self.upper_bounds):
                raise ValueError("Parameters bounds must have the same length.")
            if len(self.lower_bounds) == 0:
                raise ValueError("Parameters bounds cannot be empty.")
            for i in range(0, len(self.lower_bounds)):
                lb = self.lower_bounds[i]
                ub = self.upper_bounds[i]
                if lb > ub:
                    raise ValueError("Parameters lower bounds cannot be greater than upper bounds.")

                if ub >= 1e20 or lb < -1e20:
                    raise ValueError("Parameter upper and lower bounds cannot be [+/-]infinity.")

                # lb and ub values and value type validation
                if self.value_type == ValueType.BINARY and (
                    not ValueTypeValidator.is_binary(lb) or not ValueTypeValidator.is_binary(ub)
                ):
                    raise ValueError("Parameter lower and upper bound values must be valid binary numbers.")
                elif self.value_type == ValueType.INTEGER and (
                    not ValueTypeValidator.is_integer(lb) or not ValueTypeValidator.is_integer(ub)
                ):
                    raise ValueError("Parameter lower and upper bound values must be valid integer numbers.")
        else:
            raise ValueError("Invalid parameter")

Attributes

parameter_type instance-attribute 

parameter_type: ParameterType

The type of the parameter.

value_type instance-attribute 

value_type: ValueType

The value type of the parameter values.

is_bounded property 

is_bounded: bool

Returns a boolean indicating whether the parameter is bounded.

RETURNS DESCRIPTION
bool

True if the parameter is bounded, False otherwise.

values class-attribute instance-attribute 

values: Tuple[float, ...] | None = None

A tuple containing the parameter values, or None if no values are specified.

lower_bounds class-attribute instance-attribute 

lower_bounds: Tuple[float, ...] | None = None

A tuple containing the lower bounds for each parameter value, or None if no lower bounds are specified.

upper_bounds class-attribute instance-attribute 

upper_bounds: Tuple[float, ...] | None = None

A tuple containing the upper bounds for each parameter value, or None if no upper bounds are specified.

Functions

__init__ 

__init__(parameter_type: ParameterType, value_type: ValueType, values: Tuple[float, ...] | None = None, lower_bounds: Tuple[float, ...] | None = None, upper_bounds: Tuple[float, ...] | None = None) -> None