Struct smoothed_online_convex_optimization::model::data_center::DataCenterModelOutputSuccess

pub struct DataCenterModelOutputSuccess {
    pub energy_cost: f64,
    pub revenue_loss: f64,
    pub assignments: Vec<Vec<Vec<f64>>>,
}

Model result.

Fields

energy_cost: f64

Energy cost of model.

revenue_loss: f64

Revenue loss of model.

assignments: Vec<Vec<Vec<f64>>>

All possible assignments of fractions of loads to server types for each time slot.

Implementations

impl DataCenterModelOutputSuccess

pub fn new(energy_cost: f64, revenue_loss: f64, assignment: Vec<f64>) -> Self

Trait Implementations

impl Clone for DataCenterModelOutputSuccess

fn clone(&self) -> DataCenterModelOutputSuccess

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for DataCenterModelOutputSuccess

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'a> DefaultGivenOnlineProblem<i32, SmoothedBalancedLoadOptimization<'a, i32>, DataCenterModelOutputSuccess, DataCenterModelOutputFailure> for Memory<'a>

fn default(o: &Online<IntegralSmoothedBalancedLoadOptimization<'_>>) -> Self

impl<'de> Deserialize<'de> for DataCenterModelOutputSuccess

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl IntoPy<Py<PyAny>> for DataCenterModelOutputSuccess

fn into_py(self, py: Python<'_>) -> PyObject

Performs the conversion.

impl<'a, T> Model<T, SimplifiedSmoothedConvexOptimization<'a, T, DataCenterModelOutputSuccess, DataCenterModelOutputFailure>, DataCenterOfflineInput, DataCenterOnlineInput, DataCenterModelOutputSuccess, DataCenterModelOutputFailure> for DataCenterModel where
    T: Value<'a>, 

fn to(
    &self,
    _: DataCenterOfflineInput
) -> SimplifiedSmoothedConvexOptimization<'a, T, DataCenterModelOutputSuccess, DataCenterModelOutputFailure>

Generates an offline problem instance given some $input$ (with certainty).

fn update(
    &self,
    o: &mut Online<SimplifiedSmoothedConvexOptimization<'a, T, DataCenterModelOutputSuccess, DataCenterModelOutputFailure>>,
    _: DataCenterOnlineInput
)

Performs an online update of the given problem instance $o$ with some $input$ (which may be uncertain).

impl<'a, T> Model<T, SmoothedBalancedLoadOptimization<'a, T>, DataCenterOfflineInput, DataCenterOnlineInput, DataCenterModelOutputSuccess, DataCenterModelOutputFailure> for DataCenterModel where
    T: Value<'a>, 

fn to(
    &self,
    _: DataCenterOfflineInput
) -> SmoothedBalancedLoadOptimization<'a, T>

Notes:

• Only allows for a single location, source, and job type.

fn update(
    &self,
    o: &mut Online<SmoothedBalancedLoadOptimization<'a, T>>,
    _: DataCenterOnlineInput
)

Performs an online update of the given problem instance $o$ with some $input$ (which may be uncertain).

impl<'a, T> Model<T, SmoothedConvexOptimization<'a, T, DataCenterModelOutputSuccess, DataCenterModelOutputFailure>, DataCenterOfflineInput, DataCenterOnlineInput, DataCenterModelOutputSuccess, DataCenterModelOutputFailure> for DataCenterModel where
    T: Value<'a>, 

fn to(
    &self,
    input: DataCenterOfflineInput
) -> SmoothedConvexOptimization<'a, T, DataCenterModelOutputSuccess, DataCenterModelOutputFailure>

Generates an offline problem instance given some $input$ (with certainty).

fn update(
    &self,
    o: &mut Online<SmoothedConvexOptimization<'a, T, DataCenterModelOutputSuccess, DataCenterModelOutputFailure>>,
    _: DataCenterOnlineInput
)

Performs an online update of the given problem instance $o$ with some $input$ (which may be uncertain).

impl ModelOutputSuccess for DataCenterModelOutputSuccess

fn vertical_merge(self, output: Self) -> Self

Computes the mean energy cost and revenue loss.

fn horizontal_merge(self, output: Self) -> Self

Merge two outputs across time steps.

impl PartialEq<DataCenterModelOutputSuccess> for DataCenterModelOutputSuccess

fn eq(&self, other: &DataCenterModelOutputSuccess) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &DataCenterModelOutputSuccess) -> bool

This method tests for !=.

impl<'a, T> Problem<T, DataCenterModelOutputSuccess, DataCenterModelOutputFailure> for SmoothedBalancedLoadOptimization<'a, T> where
    T: Value<'a>, 

fn hit_cost(
    &self,
    t: i32,
    x: Config<T>
) -> Cost<DataCenterModelOutputSuccess, DataCenterModelOutputFailure>

Hitting cost.

fn movement(&self, prev_x: Config<T>, x: Config<T>, inverted: bool) -> N64

Movement cost.

fn objective_function<'a>(&self, xs: &Schedule<T>) -> Result<Cost<C, D>> where
    T: Value<'a>, 

Objective function. Calculates the cost of a schedule.

fn inverted_objective_function<'a>(
    &self,
    xs: &Schedule<T>
) -> Result<Cost<C, D>> where
    T: Value<'a>, 

Inverted Objective function. Calculates the cost of a schedule. Pays the switching cost for powering down rather than powering up.

fn alpha_unfair_objective_function<'a>(
    &self,
    xs: &Schedule<T>,
    alpha: f64
) -> Result<Cost<C, D>> where
    T: Value<'a>, 

$\alpha$-unfair Objective function. Calculates the cost of a schedule.

fn objective_function_with_default<'a>(
    &self,
    xs: &Schedule<T>,
    default: &Config<T>
) -> Result<Cost<C, D>> where
    T: Value<'a>, 

Objective function starting from an initial configuration other than $\mathbf{0}$.

fn _objective_function_with_default<'a>(
    &self,
    xs: &Schedule<T>,
    default: &Config<T>,
    alpha: f64,
    inverted: bool
) -> Result<Cost<C, D>> where
    T: Value<'a>, 

fn total_movement<'a>(&self, xs: &Schedule<T>, inverted: bool) -> Result<N64> where
    T: Value<'a>, 

Movement in the decision space.

fn _default_config<'a>(&self) -> Config<T> where
    T: Value<'a>, 

impl PyClass for DataCenterModelOutputSuccess

type Dict = PyClassDummySlot

Specify this class has #[pyclass(dict)] or not.

type WeakRef = PyClassDummySlot

Specify this class has #[pyclass(weakref)] or not.

type BaseNativeType = PyAny

The closest native ancestor. This is PyAny by default, and when you declare #[pyclass(extends=PyDict)], it’s PyDict.

impl PyClassDescriptors<DataCenterModelOutputSuccess> for PyClassImplCollector<DataCenterModelOutputSuccess>

fn py_class_descriptors(self) -> &'static [PyMethodDefType]

impl PyClassImpl for DataCenterModelOutputSuccess

const DOC: &'static str

Class doc string

const IS_GC: bool

#[pyclass(gc)]

const IS_BASETYPE: bool

#[pyclass(subclass)]

const IS_SUBCLASS: bool

#[pyclass(extends=…)]

type Layout = PyCell<Self>

Layout

type BaseType = PyAny

Base class

type ThreadChecker = ThreadCheckerStub<DataCenterModelOutputSuccess>

This handles following two situations:

fn for_each_method_def(visitor: &mut dyn FnMut(&[PyMethodDefType]))

fn get_new() -> Option<newfunc>

fn get_alloc() -> Option<allocfunc>

fn get_free() -> Option<freefunc>

fn get_call() -> Option<PyCFunctionWithKeywords>

fn for_each_proto_slot(visitor: &mut dyn FnMut(&[PyType_Slot]))

fn get_buffer() -> Option<&'static PyBufferProcs>

impl PyTypeInfo for DataCenterModelOutputSuccess

type AsRefTarget = PyCell<Self>

Utility type to make Py::as_ref work.

const NAME: &'static str

Class name.

const MODULE: Option<&'static str>

Module name, if any.

fn type_object_raw(py: Python<'_>) -> *mut PyTypeObject

PyTypeObject instance for this type.

fn is_type_of(object: &PyAny) -> bool

Checks if object is an instance of this type or a subclass of this type.

fn is_exact_type_of(object: &PyAny) -> bool

Checks if object is an instance of this type.

impl Serialize for DataCenterModelOutputSuccess

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where
    __S: Serializer, 

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for DataCenterModelOutputSuccess