class
SpectralProjectedGradient[T, -DF <: DiffFunction[T]] extends FirstOrderMinimizer[T, DF] with Projecting[T] with Logging
Instance Constructors
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new
SpectralProjectedGradient(projection: (T) ⇒ T = ((t: T) => t), tolerance: Double = 1.0E-6, suffDec: Double = 1.0E-4, minImprovementWindow: Int = 10, alphaMax: Double = 1.0E10, alphaMin: Double = 1.0E-10, maxIter: Int = 500, testOpt: Boolean = true, initFeas: Boolean = false, maxSrchIt: Int = 30)(implicit coord: MutableCoordinateSpace[T, Double])
Type Members
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type
History = Double
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case class
State(x: T, value: Double, grad: T, adjustedValue: Double, adjustedGradient: T, iter: Int, initialAdjVal: Double, history: History, fVals: IndexedSeq[Double] = ..., numImprovementFailures: Int = 0, searchFailed: Boolean = false) extends Product with Serializable
Value Members
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final
def
!=(arg0: AnyRef): Boolean
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: AnyRef): Boolean
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final
def
==(arg0: Any): Boolean
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def
adjust(newX: T, newGrad: T, newVal: Double): (Double, T)
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val
alphaMax: Double
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val
alphaMin: Double
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final
def
asInstanceOf[T0]: T0
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def
calculateObjective(f: DF, x: T, history: History): (Double, T)
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def
chooseDescentDirection(state: State, f: DF): T
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def
clone(): AnyRef
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def
determineStepSize(state: State, f: DF, direction: T): Double
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
finalize(): Unit
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final
def
getClass(): Class[_]
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def
hashCode(): Int
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val
initFeas: Boolean
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def
initialHistory(f: DF, init: T): History
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def
initialState(f: DF, init: T): State
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final
def
isInstanceOf[T0]: Boolean
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def
iteratingShouldStop(state: State): Boolean
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def
iterations(f: DF, init: T): Iterator[State]
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lazy val
logger: Logger
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val
maxSrchIt: Int
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def
minimize(f: DF, init: T): T
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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val
numberOfImprovementFailures: Int
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def
projectedVector(x: T, g: T)(implicit vspace: NormedVectorSpace[T, Double]): T
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val
projection: (T) ⇒ T
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val
suffDec: Double
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
takeStep(state: State, dir: T, stepSize: Double): T
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val
testOpt: Boolean
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def
toString(): String
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def
updateFValWindow(oldState: State, newAdjVal: Double): IndexedSeq[Double]
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def
updateHistory(newX: T, newGrad: T, newVal: Double, f: DF, oldState: State): History
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
Inherited from Logging
Inherited from AnyRef
Inherited from Any
SPG is a Spectral Projected Gradient minimizer; it minimizes a differentiable function subject to the optimum being in some set, given by the projection operator projection
vector type