Index (java-trust-constr 1.0.0 API)

A B C D E F G H I J K L M N O P Q R S T U V X Z
All Classes and Interfaces|All Packages

A

A - Variable in class de.labathome.trustconstr.LinearVectorFunction: Constraint matrix; mirrors scipy's self.J.
A() - Method in class de.labathome.trustconstr.records.Sparsity
abs() - Method in class de.labathome.trustconstr.matrix.DenseMatrix
abs() - Method in class de.labathome.trustconstr.matrix.Matrix
abs() - Method in class de.labathome.trustconstr.matrix.SparseMatrix
absInPlace() - Method in class de.labathome.trustconstr.matrix.DenseMatrix: In-place absolute value.
absInPlace() - Method in class de.labathome.trustconstr.matrix.Matrix: In-place absolute value.
absStep() - Method in class de.labathome.trustconstr.records.FiniteDifferenceOptions
absStep(Matrix) - Method in class de.labathome.trustconstr.records.FiniteDifferenceOptions.FiniteDifferenceOptionsFactory
AdjustedDifferencingScheme - Class in de.labathome.trustconstr.records: Output of NumDiff.adjustSchemeToBounds(de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, int, de.labathome.trustconstr.enums.FiniteDifferenceMethod, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix): the per-dimension finite-difference step (with sign flips and clamping applied so each step lands inside the user-provided bounds) plus a per- dimension flag indicating whether the central scheme had to be downgraded to a one-sided scheme.
AdjustedDifferencingScheme(Matrix, boolean[]) - Constructor for class de.labathome.trustconstr.records.AdjustedDifferencingScheme
adjustSchemeToBounds(Matrix, Matrix, int, FiniteDifferenceMethod, Matrix, Matrix) - Static method in class de.labathome.trustconstr.NumDiff: Adjust finite-difference step sizes so that the perturbed point stays within [lb, ub] per dimension, flipping direction or switching forward / backward as needed.
allVecs - Variable in class de.labathome.trustconstr.records.CGInfo: All intermediate iterates, when returnAll=true; otherwise null.
apply(Matrix) - Method in interface de.labathome.trustconstr.interfaces.LinearOperator: Apply the linear operator to a given vector.
apply(Matrix, double[], double[]) - Method in interface de.labathome.trustconstr.CanonicalConstraint.HessianFn
apply(Matrix, double[], double[]) - Method in class de.labathome.trustconstr.LagrangianHessian
apply(Matrix, double[], double[]) - Method in interface de.labathome.trustconstr.LagrangianHessian.ConstraintHessian
apply(Matrix, Matrix, Object) - Method in interface de.labathome.trustconstr.interfaces.HessianProduct
apply(Matrix, Object) - Method in class de.labathome.trustconstr.FullHessianUpdateStrategy
apply(Matrix, Object) - Method in class de.labathome.trustconstr.HessianLinearOperator
approxDerivative(BiFunction<Matrix, Object, Matrix>, Matrix, Matrix, FiniteDifferenceOptions, Object) - Static method in class de.labathome.trustconstr.NumDiff: Finite-difference Jacobian of a vector-valued function with extra args.
approxDerivative(DoubleUnaryOperator, double, FiniteDifferenceOptions) - Static method in class de.labathome.trustconstr.NumDiff: Finite-difference gradient of a scalar function of a scalar argument.
approxDerivative(Function<Matrix, Matrix>, Matrix, Matrix, FiniteDifferenceOptions) - Static method in class de.labathome.trustconstr.NumDiff: Finite-difference Jacobian of a vector-valued function.
approxDerivative(ToDoubleFunction<Matrix>, double, double, FiniteDifferenceOptions) - Static method in class de.labathome.trustconstr.NumDiff: Finite-difference gradient of a scalar function of a scalar argument with a precomputed f0.
approxDerivative(ToDoubleFunction<Matrix>, double, FiniteDifferenceOptions) - Static method in class de.labathome.trustconstr.NumDiff: Finite-difference gradient of a ToDoubleFunction of a scalar argument.
approxDerivative(ToDoubleFunction<Matrix>, Matrix, double, FiniteDifferenceOptions) - Static method in class de.labathome.trustconstr.NumDiff: Finite-difference gradient of a real-valued function of a vector argument.
approxDerivativeAsLinearOperator(BiFunction<Matrix, Object, Matrix>, Matrix, Matrix, FiniteDifferenceOptions, Object) - Static method in class de.labathome.trustconstr.NumDiff: Strict scipy approx_derivative(..., as_linear_operator=True) counterpart: returns a matrix-free LinearOperator that applies the FD Jacobian J(x0) * p on demand.
approxDerivativeFullOutput(BiFunction<Matrix, Object, Matrix>, Matrix, Matrix, FiniteDifferenceOptions, Object) - Static method in class de.labathome.trustconstr.NumDiff: Strict scipy approx_derivative(..., full_output=True) counterpart: returns the FD Jacobian alongside an info dict carrying metadata about the computation.
ApproxDerivativeResult - Record Class in de.labathome.trustconstr.records: Output shape of NumDiff.approxDerivativeFullOutput(java.util.function.BiFunction<de.labathome.trustconstr.matrix.Matrix, java.lang.Object, de.labathome.trustconstr.matrix.Matrix>, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.records.FiniteDifferenceOptions, java.lang.Object).
ApproxDerivativeResult(Matrix, Map<String, Object>) - Constructor for record class de.labathome.trustconstr.records.ApproxDerivativeResult: Creates an instance of a ApproxDerivativeResult record class.
approxDerivativeWithWorkers(BiFunction<Matrix, Object, Matrix>, Matrix, Matrix, FiniteDifferenceOptions, Object, ExecutorService) - Static method in class de.labathome.trustconstr.NumDiff: Strict scipy approx_derivative(..., workers=...) counterpart: computes a dense FD Jacobian column-by-column with the per-column evaluations dispatched in parallel through executor.
approxType - Variable in class de.labathome.trustconstr.FullHessianUpdateStrategy: Whether FullHessianUpdateStrategy.B (HESSIAN) or FullHessianUpdateStrategy.H (INV_HESSIAN) is being approximated.
args(Object) - Method in class de.labathome.trustconstr.ScalarFunction.ScalarFunctionFactory: Provide any additional fixed parameters needed to specify the scalar function (the args argument forwarded to fun/grad/hess).
asLinearOperator() - Method in class de.labathome.trustconstr.records.FiniteDifferenceOptions
asLinearOperator(boolean) - Method in class de.labathome.trustconstr.records.FiniteDifferenceOptions.FiniteDifferenceOptionsFactory
assembleJacobianWithSlacks(CSRMatrix, CSRMatrix, double[]) - Static method in class de.labathome.trustconstr.sparse.SparseAssembly: Build the augmented Jacobian used inside the interior-point method:
AUGMENTED_SYSTEM - Enum constant in enum class de.labathome.trustconstr.enums.ProjectionMethod: The operators will be computed using the so-called augmented system approach explained in [1]_.
autoScale(Matrix, Matrix) - Method in class de.labathome.trustconstr.FullHessianUpdateStrategy: Heuristic scaling factor for the initial Hessian (or inverse-Hessian) approximation, based on Nocedal & Wright (2006), p.143 formula (6.20).

B

B - Variable in class de.labathome.trustconstr.FullHessianUpdateStrategy: Hessian approximation (used when approxType == HESSIAN).
barrierParameter - Variable in class de.labathome.trustconstr.records.OptimizeResult: Barrier parameter at the last iteration.
barrierParameter - Variable in class de.labathome.trustconstr.records.StateIP: Current log-barrier coefficient.
BarrierSubproblem - Class in de.labathome.trustconstr: Barrier optimization problem:
BarrierSubproblem(Matrix, Matrix, ToDoubleBiFunction<Matrix, Object>, BiFunction<Matrix, Object, Matrix>, LagrangeHessian, long, long, long, Constraint, Jacobian, double, double, boolean[], GlobalStoppingCriteria, double, double, Matrix, Matrix, Matrix, Matrix, Matrix) - Constructor for class de.labathome.trustconstr.BarrierSubproblem: Construct the barrier subproblem at a starting iterate.
barrierTolerance - Variable in class de.labathome.trustconstr.records.OptimizeResult: Tolerance for the barrier subproblem at the last iteration.
barrierTolerance - Variable in class de.labathome.trustconstr.records.StateIP: Current barrier-subproblem tolerance.
BasicReport - Class in de.labathome.trustconstr.report: Basic 7-column progress report used for bound-constrained problems.
BasicReport() - Constructor for class de.labathome.trustconstr.report.BasicReport
BFGS - Class in de.labathome.trustconstr: Broyden-Fletcher-Goldfarb-Shanno (BFGS) Hessian update strategy.
BFGS.BFGSFactory - Class in de.labathome.trustconstr: Builder for BFGS; configure via BFGS.FACTORY.
BFGSFactory() - Constructor for class de.labathome.trustconstr.BFGS.BFGSFactory: Public so callers can construct a fresh factory per build instead of mutating the shared BFGS.FACTORY singleton (whose state leaks across calls and tests).
blockArray(CSRMatrix[][]) - Static method in class de.labathome.trustconstr.sparse.SparseAssembly: 2D block assembly.
bounds() - Method in class de.labathome.trustconstr.LinearConstraint
bounds() - Method in class de.labathome.trustconstr.NonlinearConstraint
bounds() - Method in class de.labathome.trustconstr.records.FiniteDifferenceOptions
bounds() - Method in class de.labathome.trustconstr.records.PreparedConstraint
bounds(FiniteDifferenceBounds) - Method in class de.labathome.trustconstr.records.FiniteDifferenceOptions.FiniteDifferenceOptionsFactory
Bounds - Class in de.labathome.trustconstr.records: Box bounds lb ≤ x ≤ ub on the optimisation variable, plus a global keepFeasible flag controlling whether the algorithm is allowed to step outside the box during line-searches and trial steps.
Bounds(Matrix, Matrix, boolean) - Constructor for class de.labathome.trustconstr.records.Bounds
boxIntersections(double[], double[], double[], double[]) - Static method in class de.labathome.trustconstr.QPSubproblem: Find the intersection of a segment (or line) with the rectangular box lb ≤ x ≤ ub, where the segment is parameterised as x(t) = z + t*d.
boxIntersections(double[], double[], double[], double[], boolean) - Static method in class de.labathome.trustconstr.QPSubproblem: Find the intersection of a segment (or line) with the rectangular box lb ≤ x ≤ ub, where the segment is parameterised as x(t) = z + t*d.
boxSphereIntersections(double[], double[], double[], double[], double) - Static method in class de.labathome.trustconstr.QPSubproblem: Convenience overload of QPSubproblem.boxSphereIntersections(double[], double[], double[], double[], double, boolean) with entireLine = false.
boxSphereIntersections(double[], double[], double[], double[], double, boolean) - Static method in class de.labathome.trustconstr.QPSubproblem: Find the intersection of a segment (or line) with both a box lb ≤ x ≤ ub and a ball ||x|| ≤ trustRadius.
boxSphereIntersectionsWithExtraInfo(double[], double[], double[], double[], double) - Static method in class de.labathome.trustconstr.QPSubproblem: Convenience overload of QPSubproblem.boxSphereIntersectionsWithExtraInfo(double[], double[], double[], double[], double, boolean) with entireLine = false.
boxSphereIntersectionsWithExtraInfo(double[], double[], double[], double[], double, boolean) - Static method in class de.labathome.trustconstr.QPSubproblem: Find the intersection between segment (or line) and box/sphere constraints.
build() - Method in class de.labathome.trustconstr.BFGS.BFGSFactory: Build a configured BFGS instance.
build() - Method in class de.labathome.trustconstr.records.FiniteDifferenceOptions.FiniteDifferenceOptionsFactory
build() - Method in class de.labathome.trustconstr.ScalarFunction.ScalarFunctionFactory
build() - Method in class de.labathome.trustconstr.sparse.CSRMatrix.Builder: Compress the DOK contents into a canonical CSR representation (column indices sorted within each row, no duplicates, no explicit zeros).
build() - Method in class de.labathome.trustconstr.SR1.SR1Factory: Build a configured SR1 instance.
build() - Method in class de.labathome.trustconstr.VectorFunction.VectorFunctionFactory
builder(int, int) - Static method in class de.labathome.trustconstr.sparse.CSRMatrix: Start an incremental DOK-style build.

C

c() - Method in class de.labathome.trustconstr.records.FunctionAndConstraint
CanonicalConstraint - Class in de.labathome.trustconstr: Canonical-form constraint
CanonicalConstraint.HessianFn - Interface in de.labathome.trustconstr: Functional interface for the constraint Hessian-of-Lagrangian: Sum_i v_eq[i] * H_{eq,i}(x) + Sum_j v_ineq[j] * H_{ineq,j}(x).
CanonicalConstraint.InitialCanonical - Record Class in de.labathome.trustconstr: Output shape of CanonicalConstraint.initialConstraintsAsCanonical(int, java.util.List<de.labathome.trustconstr.CanonicalConstraint>, de.labathome.trustconstr.matrix.Matrix, boolean): the four arrays (cEq, cIneq, JEq, JIneq) returned as a record.
cEq() - Method in record class de.labathome.trustconstr.CanonicalConstraint.InitialCanonical: Returns the value of the cEq record component.
CGInfo - Class in de.labathome.trustconstr.records: Result of a projected-CG inner solve from QPSubproblem.projectedCG(de.labathome.trustconstr.interfaces.LinearOperator, de.labathome.trustconstr.matrix.Matrix, java.lang.Object, java.lang.Object, de.labathome.trustconstr.matrix.Matrix).
CGInfo() - Constructor for class de.labathome.trustconstr.records.CGInfo
cgIter - Variable in class de.labathome.trustconstr.records.OptimizeResult: Total number of the conjugate gradient method iterations.
cgNIter - Variable in class de.labathome.trustconstr.records.State: Number of CG iterations performed in the most recent inner solve.
cgStopCond - Variable in class de.labathome.trustconstr.records.OptimizeResult: Reason for CG subproblem termination at the last iteration: 0 : CG subproblem not evaluated. 1 : Iteration limit was reached. 2 : Reached the trust-region boundary. 3 : Negative curvature detected. 4 : Tolerance was satisfied.
cgStopCond - Variable in class de.labathome.trustconstr.records.State: Why the most recent CG inner solve terminated.
cholesky(DenseMatrix) - Static method in class de.labathome.trustconstr.matrix.LinAlg: Cholesky factorisation of an SPD matrix via dpotrf, upper triangle.
CholResult - Record Class in de.labathome.trustconstr.matrix: Cholesky factorisation of a symmetric positive-definite matrix.
CholResult(double[], int, boolean) - Constructor for record class de.labathome.trustconstr.matrix.CholResult: Creates an instance of a CholResult record class.
cIneq() - Method in record class de.labathome.trustconstr.CanonicalConstraint.InitialCanonical: Returns the value of the cIneq record component.
cols() - Method in class de.labathome.trustconstr.matrix.DenseMatrix
cols() - Method in class de.labathome.trustconstr.sparse.CSCMatrix
cols() - Method in class de.labathome.trustconstr.sparse.CSRMatrix.Builder
cols() - Method in class de.labathome.trustconstr.sparse.CSRMatrix
column(double...) - Static method in class de.labathome.trustconstr.matrix.DenseMatrix
columnNames() - Method in class de.labathome.trustconstr.report.BasicReport
columnNames() - Method in class de.labathome.trustconstr.report.IPReport
columnNames() - Method in class de.labathome.trustconstr.report.ReportBase
columnNames() - Method in class de.labathome.trustconstr.report.SQPReport
columnWidths() - Method in class de.labathome.trustconstr.report.BasicReport
columnWidths() - Method in class de.labathome.trustconstr.report.IPReport
columnWidths() - Method in class de.labathome.trustconstr.report.ReportBase
columnWidths() - Method in class de.labathome.trustconstr.report.SQPReport
CombinedConstraint - Class in de.labathome.trustconstr: Concatenation of several LinearConstraint / NonlinearConstraint objects into a single Constraint + Jacobian that the orchestrator can pass straight to EqualityConstrainedSQP.eqSQP(de.labathome.trustconstr.interfaces.IFunctionAndConstraint, de.labathome.trustconstr.interfaces.IGradientAndJacobian, de.labathome.trustconstr.interfaces.LagrangeHessian, de.labathome.trustconstr.matrix.Matrix, double, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.interfaces.StoppingCriterion, de.labathome.trustconstr.records.State, double, double, de.labathome.trustconstr.enums.ProjectionMethod, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.interfaces.LinearOperator) or TrustRegionInteriorPoint.trustRegionInteriorPoint(java.util.function.ToDoubleBiFunction<de.labathome.trustconstr.matrix.Matrix, java.lang.Object>, java.util.function.BiFunction<de.labathome.trustconstr.matrix.Matrix, java.lang.Object, de.labathome.trustconstr.matrix.Matrix>, de.labathome.trustconstr.interfaces.LagrangeHessian, int, int, int, de.labathome.trustconstr.interfaces.Constraint, de.labathome.trustconstr.interfaces.Jacobian, de.labathome.trustconstr.matrix.Matrix, double, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.interfaces.GlobalStoppingCriteria, boolean[], double, de.labathome.trustconstr.records.State, double, double, double, double, de.labathome.trustconstr.enums.ProjectionMethod).
CombinedConstraint(Object[], int) - Constructor for class de.labathome.trustconstr.CombinedConstraint
CombinedConstraint(List<C>, int) - Constructor for class de.labathome.trustconstr.CombinedConstraint: Convenience constructor accepting a List of source constraints.
COMPLEX_STEP - Enum constant in enum class de.labathome.trustconstr.enums.FiniteDifferenceMethod: Complex-step differentiation (scipy 'cs').
computeAbsoluteStep(Matrix, Matrix, Matrix, FiniteDifferenceMethod) - Static method in class de.labathome.trustconstr.NumDiff: Compute the absolute finite-difference step from a relative step.
concatenate(List<CanonicalConstraint>, boolean) - Static method in class de.labathome.trustconstr.CanonicalConstraint: Concatenate a list of canonical constraints into one.
constr - Variable in class de.labathome.trustconstr.records.OptimizeResult: List of constraint values at the solution.
constr - Variable in class de.labathome.trustconstr.records.State: Constraint residual vectors, one entry per constraint source.
Constraint - Interface in de.labathome.trustconstr.interfaces: Evaluator for the canonical-form constraints of the optimization problem: constr_eq(x) = 0 and constr_ineq(x) ≤ 0.
constraintPenalty - Variable in class de.labathome.trustconstr.records.OptimizeResult: Penalty parameter at the last iteration, see `initial_constr_penalty`.
constraintPenalty - Variable in class de.labathome.trustconstr.records.State: Current merit-function penalty (the rho in f(x) + rho ||c(x)||).
constraintViolation - Variable in class de.labathome.trustconstr.records.OptimizeResult: Maximum constraint violation at the solution.
constrEq(Matrix) - Method in class de.labathome.trustconstr.CombinedConstraint
constrEq(Matrix) - Method in interface de.labathome.trustconstr.interfaces.Constraint
constrEq(Matrix) - Method in class de.labathome.trustconstr.LinearConstraint
constrEq(Matrix) - Method in class de.labathome.trustconstr.NonlinearConstraint
constrEq(Matrix) - Method in class de.labathome.trustconstr.SparsityForcedConstraint
constrIneq(Matrix) - Method in class de.labathome.trustconstr.CombinedConstraint
constrIneq(Matrix) - Method in interface de.labathome.trustconstr.interfaces.Constraint
constrIneq(Matrix) - Method in class de.labathome.trustconstr.LinearConstraint
constrIneq(Matrix) - Method in class de.labathome.trustconstr.NonlinearConstraint
constrIneq(Matrix) - Method in class de.labathome.trustconstr.SparsityForcedConstraint
constrViolation - Variable in class de.labathome.trustconstr.records.State: Infinity-norm of the constraint residual at the current iterate.
copy() - Method in class de.labathome.trustconstr.matrix.DenseMatrix
copy() - Method in class de.labathome.trustconstr.matrix.Matrix
copy() - Method in class de.labathome.trustconstr.matrix.SparseMatrix
copyFromMatrix(Matrix) - Static method in class de.labathome.trustconstr.matrix.DenseMatrix: Densify any Matrix: if m is already a DenseMatrix, return a DenseMatrix.copy(); otherwise materialise via DenseMatrix.getAsDouble(long, long).
copyFromMatrix(Matrix) - Static method in class de.labathome.trustconstr.matrix.DenseMatrix.Factory
copyFromMatrix(Matrix) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory
copyFromMatrix(Matrix) - Static method in class de.labathome.trustconstr.matrix.SparseMatrix.Factory
CSCMatrix - Class in de.labathome.trustconstr.sparse: Compressed Sparse Column matrix.
CSCMatrix(int, int, int[], int[], double[]) - Constructor for class de.labathome.trustconstr.sparse.CSCMatrix: Construct from raw CSC triplets.
CSRMatrix - Class in de.labathome.trustconstr.sparse: Compressed Sparse Row matrix.
CSRMatrix(int, int, int[], int[], double[]) - Constructor for class de.labathome.trustconstr.sparse.CSRMatrix: Construct from raw CSR triplets.
CSRMatrix.Builder - Class in de.labathome.trustconstr.sparse: Incremental builder for CSRMatrix using a Dictionary-of-Keys (DOK) representation under the hood.

D

DAMP_UPDATE - Enum constant in enum class de.labathome.trustconstr.enums.ExceptionStrategy: Damp the update by interpolating with the previous matrix (scipy 'damp_update').
data() - Method in class de.labathome.trustconstr.matrix.DenseMatrix: The underlying column-major buffer.
data() - Method in class de.labathome.trustconstr.sparse.CSCMatrix
data() - Method in class de.labathome.trustconstr.sparse.CSRMatrix
de.labathome.trustconstr - package de.labathome.trustconstr
de.labathome.trustconstr.demo - package de.labathome.trustconstr.demo
de.labathome.trustconstr.enums - package de.labathome.trustconstr.enums
de.labathome.trustconstr.interfaces - package de.labathome.trustconstr.interfaces
de.labathome.trustconstr.matrix - package de.labathome.trustconstr.matrix
de.labathome.trustconstr.records - package de.labathome.trustconstr.records
de.labathome.trustconstr.report - package de.labathome.trustconstr.report
de.labathome.trustconstr.sparse - package de.labathome.trustconstr.sparse
defaultScaling(long) - Static method in class de.labathome.trustconstr.EqualityConstrainedSQP: Default scaling: returns the n x n identity, i.e. an unscaled SQP step.
DenseMatrix - Class in de.labathome.trustconstr.matrix: Dense matrix backed by a column-major double[] buffer of length rows * cols.
DenseMatrix(int, int) - Constructor for class de.labathome.trustconstr.matrix.DenseMatrix: Allocate a fresh rows x cols zero-filled DenseMatrix.
DenseMatrix.Factory - Class in de.labathome.trustconstr.matrix: Backwards-compatible nested factory class.
DenseSolve - Class in de.labathome.trustconstr.sparse: Thin wrapper around LAPACK direct linear solvers for the trust-constr KKT path.
DenseSolve.LUFactor - Class in de.labathome.trustconstr.sparse: Factorisation of a square matrix A ready to repeatedly DenseSolve.LUFactor.solve(double[]) against right-hand sides.
diag(double[]) - Static method in class de.labathome.trustconstr.matrix.MatrixOps: Build a sparse diagonal matrix with the given entries on the diagonal.
divide(double) - Method in class de.labathome.trustconstr.matrix.DenseMatrix
divide(double) - Method in class de.labathome.trustconstr.matrix.Matrix
divide(double) - Method in class de.labathome.trustconstr.matrix.SparseMatrix
divide(Matrix) - Method in class de.labathome.trustconstr.matrix.DenseMatrix
divide(Matrix) - Method in class de.labathome.trustconstr.matrix.Matrix
divide(Matrix) - Method in class de.labathome.trustconstr.matrix.SparseMatrix
dot(double[], double[]) - Static method in class de.labathome.trustconstr.matrix.MatrixOps: Dot product of two equal-length vectors.
doubleValue() - Method in class de.labathome.trustconstr.matrix.Matrix: Extract the single scalar value of a 1 x 1 matrix.

E

empty(int) - Static method in class de.labathome.trustconstr.CanonicalConstraint: Construct an empty canonical constraint -- zero rows of each kind.
enforceFeasibilityIneq() - Method in class de.labathome.trustconstr.CombinedConstraint: Concatenated per-canonical-inequality-row enforceFeasibility flags across all sources, in the same order they appear in CombinedConstraint.constrIneq(Matrix).
enforceFeasibilityIneq() - Method in class de.labathome.trustconstr.LinearConstraint: Per-canonical-inequality-row enforceFeasibility flags derived from the user-supplied keep_feasible.
enforceFeasibilityIneq() - Method in class de.labathome.trustconstr.NonlinearConstraint: Per-canonical-inequality-row enforceFeasibility flags derived from the user-supplied keep_feasible.
enforceFeasibilityIneq() - Method in class de.labathome.trustconstr.SparsityForcedConstraint: Pass-through to the source's enforce-feasibility flags.
epsForMethod(Class<?>, Class<?>, FiniteDifferenceMethod) - Static method in class de.labathome.trustconstr.NumDiff: Calculate the relative EPS step for a given data type and FD method.
epsilon(Matrix) - Method in class de.labathome.trustconstr.ScalarFunction.ScalarFunctionFactory: Absolute step size for FD gradient/Hessian, taking precedence over the relative step.
eq() - Method in record class de.labathome.trustconstr.records.EqIneqSplit: Returns the value of the eq record component.
EqIneqSplit - Record Class in de.labathome.trustconstr.records: Pair of canonical equality and inequality components produced by a CanonicalConstraint's fun(x) or jac(x).
EqIneqSplit(Matrix, Matrix) - Constructor for record class de.labathome.trustconstr.records.EqIneqSplit: Creates an instance of a EqIneqSplit record class.
eqpKktFact(Matrix, Matrix, Matrix, Matrix) - Static method in class de.labathome.trustconstr.QPSubproblem: Solve the equality-constrained quadratic program
eqSQP(IFunctionAndConstraint, IGradientAndJacobian, LagrangeHessian, Matrix, double, Matrix, Matrix, Matrix, StoppingCriterion, State, double, double, ProjectionMethod, Matrix, Matrix, LinearOperator) - Static method in class de.labathome.trustconstr.EqualityConstrainedSQP: Solve a nonlinear equality-constrained problem using trust-region SQP.
EQUALITY_CONSTRAINED_SQP - Enum constant in enum class de.labathome.trustconstr.enums.TrustConstrMethod: Trust-region equality-constrained SQP (scipy equality_constrained_sqp).
EqualityConstrainedSQP - Class in de.labathome.trustconstr: Byrd-Omojokun Trust-Region SQP method
EqualityConstrainedSQP() - Constructor for class de.labathome.trustconstr.EqualityConstrainedSQP
equals(Object) - Method in record class de.labathome.trustconstr.CanonicalConstraint.InitialCanonical: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class de.labathome.trustconstr.matrix.CholResult: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class de.labathome.trustconstr.matrix.QRResult: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class de.labathome.trustconstr.matrix.SVDResult: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class de.labathome.trustconstr.records.ApproxDerivativeResult: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class de.labathome.trustconstr.records.EqIneqSplit: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class de.labathome.trustconstr.records.Residual: Indicates whether some other object is "equal to" this one.
equalsContent(Matrix) - Method in class de.labathome.trustconstr.matrix.Matrix
exceptionStrategy(ExceptionStrategy) - Method in class de.labathome.trustconstr.BFGS.BFGSFactory: Choose how to proceed when the curvature condition is violated: SKIP_UPDATE skips the update entirely; DAMP_UPDATE interpolates between the actual BFGS result and the unmodified matrix.
ExceptionStrategy - Enum Class in de.labathome.trustconstr.enums: What BFGS / SR1 should do when the curvature condition (delta_grad * delta_x) ≤ threshold is violated.
executionTime - Variable in class de.labathome.trustconstr.records.OptimizeResult: Total execution time in nanoseconds.
executionTime - Variable in class de.labathome.trustconstr.records.State: Wall-clock time elapsed since the start of the run, in nanoseconds.
eye(int) - Static method in class de.labathome.trustconstr.matrix.DenseMatrix
eye(int) - Static method in class de.labathome.trustconstr.sparse.CSCMatrix: n x n identity in CSC.
eye(int) - Static method in class de.labathome.trustconstr.sparse.CSRMatrix: n x n identity in CSR.
eye(long, long) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory

F

f - Variable in class de.labathome.trustconstr.LinearVectorFunction: Cached A x at LinearVectorFunction.x; null until first call.
f() - Method in interface de.labathome.trustconstr.interfaces.VectorFunctionLike
f() - Method in class de.labathome.trustconstr.LinearVectorFunction
f() - Method in class de.labathome.trustconstr.NonlinearVectorFunction
f() - Method in class de.labathome.trustconstr.records.FunctionAndConstraint
f() - Method in class de.labathome.trustconstr.ScalarFunction
f() - Method in class de.labathome.trustconstr.VectorFunction
factor() - Method in record class de.labathome.trustconstr.matrix.CholResult: Returns the value of the factor record component.
factor(double[][]) - Static method in class de.labathome.trustconstr.sparse.DenseSolve: Factor a dense n x n matrix A via LAPACK dgetrf.
FACTORY - Static variable in class de.labathome.trustconstr.BFGS: Default BFGS factory; configure with chained setters then call BFGS.BFGSFactory.build().
FACTORY - Static variable in class de.labathome.trustconstr.records.FiniteDifferenceOptions: Default factory; build via FiniteDifferenceOptions.FiniteDifferenceOptionsFactory.build().
FACTORY - Static variable in class de.labathome.trustconstr.ScalarFunction: Default ScalarFunction.ScalarFunctionFactory; create one and call ScalarFunction.ScalarFunctionFactory.build().
FACTORY - Static variable in class de.labathome.trustconstr.SR1: Default SR1 factory; configure with chained setters then call SR1.SR1Factory.build().
FACTORY - Static variable in class de.labathome.trustconstr.VectorFunction: Default VectorFunction.VectorFunctionFactory.
fill(double) - Method in class de.labathome.trustconstr.matrix.Matrix: In-place fill with the given scalar.
fill(double, long, long) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory
finiteDiffBounds(FiniteDifferenceBounds) - Method in class de.labathome.trustconstr.ScalarFunction.ScalarFunctionFactory: Bounds within which FD perturbations must stay.
finiteDiffBounds(FiniteDifferenceBounds) - Method in class de.labathome.trustconstr.VectorFunction.VectorFunctionFactory: Bounds within which FD perturbations must stay.
FiniteDifferenceBounds - Class in de.labathome.trustconstr.records: Box bounds lb ≤ x ≤ ub used by NumDiff.approxDerivative(java.util.function.DoubleUnaryOperator, double, de.labathome.trustconstr.records.FiniteDifferenceOptions) to clamp finite-difference perturbations.
FiniteDifferenceBounds(Matrix, Matrix, boolean) - Constructor for class de.labathome.trustconstr.records.FiniteDifferenceBounds
FiniteDifferenceMethod - Enum Class in de.labathome.trustconstr.enums: Finite-difference scheme used by NumDiff.approxDerivative(java.util.function.DoubleUnaryOperator, double, de.labathome.trustconstr.records.FiniteDifferenceOptions).
FiniteDifferenceOptions - Class in de.labathome.trustconstr.records: Configuration for NumDiff.approxDerivative(java.util.function.DoubleUnaryOperator, double, de.labathome.trustconstr.records.FiniteDifferenceOptions).
FiniteDifferenceOptions.FiniteDifferenceOptionsFactory - Class in de.labathome.trustconstr.records: Builder for FiniteDifferenceOptions.
FiniteDifferenceOptionsFactory() - Constructor for class de.labathome.trustconstr.records.FiniteDifferenceOptions.FiniteDifferenceOptionsFactory: Default-construct a fresh factory (THREE_POINT, unbounded).
finiteDiffJacSparsity(Matrix) - Method in class de.labathome.trustconstr.VectorFunction.VectorFunctionFactory: Specify a Jacobian sparsity pattern: a matrix with non-zero elements exactly where non-zero Jacobian entries are expected.
finiteDiffRelStep(Matrix) - Method in class de.labathome.trustconstr.ScalarFunction.ScalarFunctionFactory: Per-component relative step size for the FD gradient/Hessian.
finiteDiffRelStep(Matrix) - Method in class de.labathome.trustconstr.VectorFunction.VectorFunctionFactory: Per-component relative step size for the FD Jacobian/Hessian.
firstIteration - Variable in class de.labathome.trustconstr.FullHessianUpdateStrategy: true until the first FullHessianUpdateStrategy.update(Matrix, Matrix) call has been performed.
forMatvec(CSCMatrix) - Static method in class de.labathome.trustconstr.sparse.SparseLinearOperator
forMatvec(CSRMatrix) - Static method in class de.labathome.trustconstr.sparse.SparseLinearOperator
forRmatvec(CSCMatrix) - Static method in class de.labathome.trustconstr.sparse.SparseLinearOperator
forRmatvec(CSRMatrix) - Static method in class de.labathome.trustconstr.sparse.SparseLinearOperator
fromBounds(Bounds) - Static method in class de.labathome.trustconstr.CanonicalConstraint: Promote Bounds into a canonical constraint via LinearConstraint.fromBounds(Bounds).
fromBounds(Bounds) - Static method in class de.labathome.trustconstr.LinearConstraint: Build a LinearConstraint from variable Bounds, i.e. the trivial linear constraint lb <= x <= ub with A = I.
fromColumnMajor(int, int, double[]) - Static method in class de.labathome.trustconstr.matrix.DenseMatrix: Wrap an already-column-major buffer without copying.
fromDense(double[][]) - Static method in class de.labathome.trustconstr.sparse.CSCMatrix: Build CSC from a dense 2D array; column-major scan, but the input is still given as row-major dense[i][j].
fromDense(double[][]) - Static method in class de.labathome.trustconstr.sparse.CSRMatrix: Build a CSR matrix from a row-major dense double[][].
fromLinearConstraint(LinearConstraint) - Static method in class de.labathome.trustconstr.CanonicalConstraint: Wrap a LinearConstraint as a canonical constraint.
fromMatrix(Matrix) - Static method in class de.labathome.trustconstr.sparse.CSRMatrix: Build from any Matrix.
fromNonlinearConstraint(NonlinearConstraint, int) - Static method in class de.labathome.trustconstr.CanonicalConstraint: Wrap a NonlinearConstraint as a canonical constraint.
fromPreparedConstraint(PreparedConstraint) - Static method in class de.labathome.trustconstr.CanonicalConstraint: Build a canonical constraint from a PreparedConstraint.
fromRows(double[][]) - Static method in class de.labathome.trustconstr.matrix.DenseMatrix: Repack a row-major double[][] into a fresh column-major DenseMatrix.
FullHessianUpdateStrategy - Class in de.labathome.trustconstr: Hessian update strategy with full dimensional internal representation.
FullHessianUpdateStrategy(boolean, double) - Constructor for class de.labathome.trustconstr.FullHessianUpdateStrategy
FullHessianUpdateStrategy.FullHessianUpdateStrategyFactory<T extends FullHessianUpdateStrategy.FullHessianUpdateStrategyFactory<T>> - Class in de.labathome.trustconstr: Shared base factory for BFGS.BFGSFactory and SR1.SR1Factory.
FullHessianUpdateStrategyFactory() - Constructor for class de.labathome.trustconstr.FullHessianUpdateStrategy.FullHessianUpdateStrategyFactory: Default-construct: initial scale is auto-derived.
fun - Variable in class de.labathome.trustconstr.records.OptimizeResult: Objective function at the solution.
fun - Variable in class de.labathome.trustconstr.records.State: Objective value f(x) at the current iterate.
fun() - Method in class de.labathome.trustconstr.records.PreparedConstraint
fun(Matrix) - Method in class de.labathome.trustconstr.CanonicalConstraint: Evaluate the canonical equality and inequality residuals at x.
fun(Matrix) - Method in interface de.labathome.trustconstr.interfaces.VectorFunctionLike: Evaluate the function at x, updating any internal cache.
fun(Matrix) - Method in class de.labathome.trustconstr.LinearVectorFunction
fun(Matrix) - Method in class de.labathome.trustconstr.NonlinearVectorFunction
fun(Matrix) - Method in class de.labathome.trustconstr.ScalarFunction
fun(Matrix) - Method in class de.labathome.trustconstr.VectorFunction
fun(Function<Matrix, Matrix>) - Method in class de.labathome.trustconstr.VectorFunction.VectorFunctionFactory: Set the vector-valued function to evaluate.
fun(ToDoubleBiFunction<Matrix, Object>) - Method in class de.labathome.trustconstr.ScalarFunction.ScalarFunctionFactory: Set the objective function to optimize.
funAndConstr(Matrix) - Method in class de.labathome.trustconstr.BarrierSubproblem: Evaluate the barrier function and the augmented constraints at a given augmented iterate z = [x; s]:
funAndConstr(Matrix) - Method in interface de.labathome.trustconstr.interfaces.IFunctionAndConstraint
FunctionAndConstraint - Class in de.labathome.trustconstr.records: Bundle of an objective value f(x) and a constraint vector c(x).
FunctionAndConstraint(double, Matrix) - Constructor for class de.labathome.trustconstr.records.FunctionAndConstraint
fUpdated - Variable in class de.labathome.trustconstr.LinearVectorFunction: true when LinearVectorFunction.f matches the current LinearVectorFunction.x.

G

g() - Method in class de.labathome.trustconstr.ScalarFunction: DANGER ZONE: returns the live internal gradient buffer; callers must not mutate it.
get(int, int) - Method in class de.labathome.trustconstr.matrix.DenseMatrix
get(int, int) - Method in class de.labathome.trustconstr.sparse.CSRMatrix.Builder: Read back the value at (i, j); defaults to 0.0.
getA() - Method in class de.labathome.trustconstr.LinearConstraint
getAsDouble(long, long) - Method in class de.labathome.trustconstr.matrix.DenseMatrix
getAsDouble(long, long) - Method in class de.labathome.trustconstr.matrix.Matrix
getAsDouble(long, long) - Method in class de.labathome.trustconstr.matrix.SparseMatrix
getColumnCount() - Method in class de.labathome.trustconstr.matrix.DenseMatrix
getColumnCount() - Method in class de.labathome.trustconstr.matrix.Matrix
getColumnCount() - Method in class de.labathome.trustconstr.matrix.SparseMatrix
getMatrix() - Method in class de.labathome.trustconstr.FullHessianUpdateStrategy
getMatrix() - Method in interface de.labathome.trustconstr.interfaces.HessianUpdateStrategy: Return current internal matrix.
getRowCount() - Method in class de.labathome.trustconstr.matrix.DenseMatrix
getRowCount() - Method in class de.labathome.trustconstr.matrix.Matrix
getRowCount() - Method in class de.labathome.trustconstr.matrix.SparseMatrix
getScaling(Matrix) - Method in class de.labathome.trustconstr.BarrierSubproblem: Returns the diagonal scaling matrix diag([1...1, s]) that decouples the variable rows from the slack rows in the trust-region step.
getSize() - Method in class de.labathome.trustconstr.matrix.Matrix
getSlack(Matrix) - Method in class de.labathome.trustconstr.BarrierSubproblem: Slice off the nIneq x 1 slack block from an augmented iterate z = [x; s].
getVariables(Matrix) - Method in class de.labathome.trustconstr.BarrierSubproblem: Slice off the nVars x 1 variable block from an augmented iterate z = [x; s].
GlobalStoppingCriteria - Interface in de.labathome.trustconstr.interfaces: Termination predicate consulted by the trust-region SQP and interior-point loops once per outer iteration.
grad - Variable in class de.labathome.trustconstr.records.OptimizeResult: [n] Gradient of the objective function at the solution.
grad - Variable in class de.labathome.trustconstr.records.State: Gradient gradf(x) at the current iterate.
grad() - Method in class de.labathome.trustconstr.records.GradientAndJacobian
grad(FiniteDifferenceMethod) - Method in class de.labathome.trustconstr.ScalarFunction.ScalarFunctionFactory: Compute the gradient by finite differences instead of analytically.
grad(Matrix) - Method in class de.labathome.trustconstr.ScalarFunction
grad(BiFunction<Matrix, Object, Matrix>) - Method in class de.labathome.trustconstr.ScalarFunction.ScalarFunctionFactory: Provide an analytic gradient grad(x, args) -> gradf(x).
gradAndJac(Matrix) - Method in class de.labathome.trustconstr.BarrierSubproblem: Returns the scaled gradient and Jacobian for the augmented system:
gradAndJac(Matrix) - Method in interface de.labathome.trustconstr.interfaces.IGradientAndJacobian
GradientAndJacobian - Class in de.labathome.trustconstr.records: Bundle of a gradient gradf(x) and a Jacobian dc/dx.
GradientAndJacobian(Matrix, Matrix) - Constructor for class de.labathome.trustconstr.records.GradientAndJacobian
groupColumns(Matrix) - Static method in class de.labathome.trustconstr.NumDiff: Group columns of a 2-D matrix for sparse finite differencing.
groupColumns(Matrix, int[]) - Static method in class de.labathome.trustconstr.NumDiff: Group columns of a 2-D matrix for sparse FD with a user-supplied permutation that controls greedy-grouping order.

H

H - Variable in class de.labathome.trustconstr.FullHessianUpdateStrategy: Inverse-Hessian approximation (used when approxType == INV_HESSIAN).
H - Variable in class de.labathome.trustconstr.LinearVectorFunction: Constant zero Hessian (n x n); shared across calls.
H() - Method in class de.labathome.trustconstr.ScalarFunction: DANGER ZONE: returns the live internal Hessian buffer; callers must not mutate it.
H() - Method in class de.labathome.trustconstr.VectorFunction
hAdjusted() - Method in class de.labathome.trustconstr.records.AdjustedDifferencingScheme
hashCode() - Method in record class de.labathome.trustconstr.CanonicalConstraint.InitialCanonical: Returns a hash code value for this object.
hashCode() - Method in record class de.labathome.trustconstr.matrix.CholResult: Returns a hash code value for this object.
hashCode() - Method in record class de.labathome.trustconstr.matrix.QRResult: Returns a hash code value for this object.
hashCode() - Method in record class de.labathome.trustconstr.matrix.SVDResult: Returns a hash code value for this object.
hashCode() - Method in record class de.labathome.trustconstr.records.ApproxDerivativeResult: Returns a hash code value for this object.
hashCode() - Method in record class de.labathome.trustconstr.records.EqIneqSplit: Returns a hash code value for this object.
hashCode() - Method in record class de.labathome.trustconstr.records.Residual: Returns a hash code value for this object.
hess(FiniteDifferenceMethod) - Method in class de.labathome.trustconstr.ScalarFunction.ScalarFunctionFactory: Compute the Hessian by finite differences instead of analytically.
hess(FiniteDifferenceMethod) - Method in class de.labathome.trustconstr.VectorFunction.VectorFunctionFactory: Compute the Hessian by finite differences instead of analytically.
hess(HessianUpdateStrategy) - Method in class de.labathome.trustconstr.ScalarFunction.ScalarFunctionFactory: Approximate the Hessian via a quasi-Newton update strategy (e.g.
hess(HessianUpdateStrategy) - Method in class de.labathome.trustconstr.VectorFunction.VectorFunctionFactory: Approximate the Hessian via a quasi-Newton update strategy (e.g.
hess(Matrix) - Method in class de.labathome.trustconstr.ScalarFunction
hess(Matrix, double[], double[]) - Method in class de.labathome.trustconstr.CanonicalConstraint: Evaluate the constraint Hessian-of-Lagrangian at x.
hess(Matrix, Matrix) - Method in interface de.labathome.trustconstr.interfaces.VectorFunctionLike: Evaluate the constraint Hessian-of-Lagrangian Sum_i v[i] * H_{f_i}(x) at x for the given multiplier vector v.
hess(Matrix, Matrix) - Method in class de.labathome.trustconstr.LinearVectorFunction
hess(Matrix, Matrix) - Method in class de.labathome.trustconstr.NonlinearVectorFunction
hess(Matrix, Matrix) - Method in class de.labathome.trustconstr.VectorFunction
hess(BiFunction<Matrix, Matrix, Matrix>) - Method in class de.labathome.trustconstr.VectorFunction.VectorFunctionFactory: Provide an analytic constraint Hessian-of-Lagrangian (x, v) -> Sum v[i] H_{c_i}(x).
hess(BiFunction<Matrix, Object, Matrix>) - Method in class de.labathome.trustconstr.ScalarFunction.ScalarFunctionFactory: Provide an analytic Hessian hess(x, args) -> grad^2f(x).
HESSIAN - Enum constant in enum class de.labathome.trustconstr.enums.HessianApproximationType: Approximate the Hessian B ~= grad^2f (scipy 'hess').
HessianApproximationType - Enum Class in de.labathome.trustconstr.enums: Whether a Hessian-update strategy approximates the Hessian or its inverse.
HessianLinearOperator - Class in de.labathome.trustconstr: Adapter that exposes a matrix-free HessianProduct as a BiFunction returning an explicit Hessian Matrix.
HessianLinearOperator(HessianProduct, long) - Constructor for class de.labathome.trustconstr.HessianLinearOperator
HessianProduct - Interface in de.labathome.trustconstr.interfaces: A matrix-free Hessian: given the current point x and a vector p, return H(x) p.
HessianUpdateStrategy - Interface in de.labathome.trustconstr.interfaces: Interface for implementing Hessian update strategies.
hitsBoundary - Variable in class de.labathome.trustconstr.records.CGInfo: true iff the returned step lies on the trust-region boundary.
hstack(CSRMatrix...) - Static method in class de.labathome.trustconstr.sparse.SparseAssembly: Horizontal stack of CSR matrices: columns are concatenated, rows must agree.

I

IdentityVectorFunction - Class in de.labathome.trustconstr: Identity vector function f(x) = x (Jacobian I).
IdentityVectorFunction(Matrix, Optional<Boolean>) - Constructor for class de.labathome.trustconstr.IdentityVectorFunction: Build an identity vector function sized for the iterate x0.
IFunctionAndConstraint - Interface in de.labathome.trustconstr.interfaces: Combined evaluator returning (f(x), constr(x)) in a single call.
IGradientAndJacobian - Interface in de.labathome.trustconstr.interfaces: Combined evaluator returning (gradf(x), gradconstr(x)) in a single call.
importFromArray(double[]) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory: Wrap a 1-D array as a 1 x n row matrix (the row-vector counterpart of Matrix.Factory.linkToArray(double[])).
importFromArray(double[][]) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory: Alias for Matrix.Factory.linkToArray(double[][]).
indices() - Method in class de.labathome.trustconstr.sparse.CSCMatrix
indices() - Method in class de.labathome.trustconstr.sparse.CSRMatrix
indptr() - Method in class de.labathome.trustconstr.sparse.CSCMatrix
indptr() - Method in class de.labathome.trustconstr.sparse.CSRMatrix
ineq() - Method in record class de.labathome.trustconstr.records.EqIneqSplit: Returns the value of the ineq record component.
info() - Method in record class de.labathome.trustconstr.records.ApproxDerivativeResult: Returns the value of the info record component.
initalScale(double) - Method in class de.labathome.trustconstr.FullHessianUpdateStrategy.FullHessianUpdateStrategyFactory: Pin the initial Hessian scale to a user-supplied value.
InitialCanonical(Matrix, Matrix, Matrix, Matrix) - Constructor for record class de.labathome.trustconstr.CanonicalConstraint.InitialCanonical: Creates an instance of a InitialCanonical record class.
initialConstraintsAsCanonical(int, List<CanonicalConstraint>, Matrix, boolean) - Static method in class de.labathome.trustconstr.CanonicalConstraint: Stack the canonical residuals and Jacobians of every constraint in canonicals at the starting iterate x0.
initialConstraintsAsCanonical(int, List<PreparedConstraint>, boolean) - Static method in class de.labathome.trustconstr.CanonicalConstraint: scipy-shape overload taking a list of PreparedConstraints.
initialize(long, HessianApproximationType) - Method in class de.labathome.trustconstr.FullHessianUpdateStrategy
initialize(long, HessianApproximationType) - Method in interface de.labathome.trustconstr.interfaces.HessianUpdateStrategy: Initialize internal matrix.
initialScale - Variable in class de.labathome.trustconstr.FullHessianUpdateStrategy.FullHessianUpdateStrategyFactory: User-specified initial scale, used when FullHessianUpdateStrategy.FullHessianUpdateStrategyFactory.initialScaleAuto is false.
initialScaleAuto - Variable in class de.labathome.trustconstr.FullHessianUpdateStrategy.FullHessianUpdateStrategyFactory: Whether the initial Hessian scale is auto-derived from the first step.
initialScaleAuto() - Method in class de.labathome.trustconstr.FullHessianUpdateStrategy.FullHessianUpdateStrategyFactory: Use the auto-derived initial scale (the default).
insideBoxBoundaries(double[], double[], double[]) - Static method in class de.labathome.trustconstr.QPSubproblem: Check whether lb ≤ x ≤ ub elementwise.
intersect() - Method in class de.labathome.trustconstr.records.IntersectionResult
IntersectionResult - Class in de.labathome.trustconstr.records: Result of intersecting a parametric segment x(t) = z + t*d with a trust-region or box constraint.
IntersectionResult(double, double, boolean) - Constructor for class de.labathome.trustconstr.records.IntersectionResult
INV_HESSIAN - Enum constant in enum class de.labathome.trustconstr.enums.HessianApproximationType: Approximate the inverse Hessian H ~= (grad^2f)^-^1 (scipy 'inv_hess').
IPReport - Class in de.labathome.trustconstr.report: Trust-region interior-point progress report (10 columns).
IPReport() - Constructor for class de.labathome.trustconstr.report.IPReport
isColumnVector() - Method in class de.labathome.trustconstr.matrix.Matrix
isRowVector() - Method in class de.labathome.trustconstr.matrix.Matrix: Lenient shape predicate: returns true if either dimension is 1 -- i.e. the matrix is shaped like a vector (row, column, or 1×1 scalar).
isSparse() - Method in class de.labathome.trustconstr.matrix.Matrix
isSparse() - Method in class de.labathome.trustconstr.matrix.SparseMatrix
ITER_LIMIT_REACHED - Enum constant in enum class de.labathome.trustconstr.enums.PCGStoppingCondition: 1: Iteration limit was reached.
IterationCallback - Interface in de.labathome.trustconstr.interfaces: Caller-supplied hook invoked once per outer iteration of the trust-constr orchestrator.
iterationFormats() - Method in class de.labathome.trustconstr.report.BasicReport
iterationFormats() - Method in class de.labathome.trustconstr.report.IPReport
iterationFormats() - Method in class de.labathome.trustconstr.report.ReportBase: Per-column Formatter format specs (e.g.
iterationFormats() - Method in class de.labathome.trustconstr.report.SQPReport

J

J() - Method in interface de.labathome.trustconstr.interfaces.VectorFunctionLike
J() - Method in class de.labathome.trustconstr.LinearVectorFunction
J() - Method in class de.labathome.trustconstr.NonlinearVectorFunction
J() - Method in class de.labathome.trustconstr.VectorFunction
jac - Variable in class de.labathome.trustconstr.records.OptimizeResult: List of the Jacobian matrices of the constraints at the solution.
jac - Variable in class de.labathome.trustconstr.records.State: Constraint Jacobians, one entry per constraint source.
jac() - Method in class de.labathome.trustconstr.records.GradientAndJacobian
jac(FiniteDifferenceMethod) - Method in class de.labathome.trustconstr.VectorFunction.VectorFunctionFactory: Compute the Jacobian by finite differences instead of analytically.
jac(Matrix) - Method in class de.labathome.trustconstr.CanonicalConstraint: Evaluate the canonical equality and inequality Jacobians at x.
jac(Matrix) - Method in interface de.labathome.trustconstr.interfaces.VectorFunctionLike: Evaluate the Jacobian at x, updating any internal cache.
jac(Matrix) - Method in class de.labathome.trustconstr.LinearVectorFunction
jac(Matrix) - Method in class de.labathome.trustconstr.NonlinearVectorFunction
jac(Matrix) - Method in class de.labathome.trustconstr.VectorFunction
jac(Function<Matrix, Matrix>) - Method in class de.labathome.trustconstr.VectorFunction.VectorFunctionFactory: Provide an analytic Jacobian.
jacEq(Matrix) - Method in class de.labathome.trustconstr.CombinedConstraint
jacEq(Matrix) - Method in interface de.labathome.trustconstr.interfaces.Jacobian
jacEq(Matrix) - Method in class de.labathome.trustconstr.LinearConstraint
jacEq(Matrix) - Method in class de.labathome.trustconstr.NonlinearConstraint
jacEq(Matrix) - Method in class de.labathome.trustconstr.SparsityForcedConstraint
jacEqCSR() - Method in class de.labathome.trustconstr.LinearConstraint: Sparse Jacobian for equality rows: a CSRMatrix built directly from the row-selected non-zeros of A, without going through a dense intermediate.
jacIneq(Matrix) - Method in class de.labathome.trustconstr.CombinedConstraint
jacIneq(Matrix) - Method in interface de.labathome.trustconstr.interfaces.Jacobian
jacIneq(Matrix) - Method in class de.labathome.trustconstr.LinearConstraint
jacIneq(Matrix) - Method in class de.labathome.trustconstr.NonlinearConstraint
jacIneq(Matrix) - Method in class de.labathome.trustconstr.SparsityForcedConstraint
jacIneqCSR() - Method in class de.labathome.trustconstr.LinearConstraint: Sparse Jacobian for inequality rows: a CSRMatrix (with the appropriate per-row sign flips for one-sided lower-bound rows).
jacobian() - Method in record class de.labathome.trustconstr.records.ApproxDerivativeResult: Returns the value of the jacobian record component.
Jacobian - Interface in de.labathome.trustconstr.interfaces: Jacobian evaluator paired with Constraint: returns the partial derivatives of the canonical-form equality and inequality constraint vectors with respect to x.
JEq() - Method in record class de.labathome.trustconstr.CanonicalConstraint.InitialCanonical: Returns the value of the JEq record component.
JIneq() - Method in record class de.labathome.trustconstr.CanonicalConstraint.InitialCanonical: Returns the value of the JIneq record component.

K

keepFeasible - Variable in class de.labathome.trustconstr.CanonicalConstraint: Per-canonical-inequality-row strict-feasibility flags (length CanonicalConstraint.nIneq).
keepFeasible() - Method in class de.labathome.trustconstr.LinearConstraint
keepFeasible() - Method in class de.labathome.trustconstr.NonlinearConstraint
keepFeasible() - Method in class de.labathome.trustconstr.records.Bounds
keepFeasible() - Method in class de.labathome.trustconstr.records.FiniteDifferenceBounds
keepFeasible() - Method in class de.labathome.trustconstr.records.PreparedConstraint

L

LagrangeHessian - Interface in de.labathome.trustconstr.interfaces: Hessian of the Lagrangian L(x, v) = f(x) + Sum v_i c_i(x) with respect to x, returned as a LinearOperator so callers can apply it to vectors without materialising the full n × n matrix.
lagrangianContribution(Matrix, double[], double[]) - Method in class de.labathome.trustconstr.CombinedConstraint: Sum of constraint-Hessian-of-Lagrangian contributions across all sources.
lagrangianContribution(Matrix, double[], double[]) - Method in class de.labathome.trustconstr.NonlinearConstraint: Constraint Hessian-of-Lagrangian Sum_i v[i] * H_{c_i}(x), combining equality and inequality multipliers into a single Hessian contribution.
lagrangianContribution(Matrix, double[], double[]) - Method in class de.labathome.trustconstr.SparsityForcedConstraint: Pass-through to the source's Lagrangian-Hessian contribution.
lagrangianGrad - Variable in class de.labathome.trustconstr.records.OptimizeResult: [n] Gradient of the Lagrangian function at the solution.
lagrangianGrad - Variable in class de.labathome.trustconstr.records.State: Lagrangian gradient gradf(x) + Sum v_i gradc_i(x) at the current iterate.
lagrangianHessian(Matrix, Matrix) - Method in class de.labathome.trustconstr.BarrierSubproblem: Full augmented Lagrangian Hessian, block-diagonal:
LagrangianHessian - Class in de.labathome.trustconstr: Lagrangian Hessian H_obj(x) + Sum_i v_i * H_{c_i}(x) as a matrix-free LinearOperator-builder.
LagrangianHessian(int, Function<Matrix, Matrix>, LagrangianHessian.ConstraintHessian) - Constructor for class de.labathome.trustconstr.LagrangianHessian: Build a Lagrangian Hessian for an n-variable problem.
LagrangianHessian.ConstraintHessian - Interface in de.labathome.trustconstr: Constraint Hessian-of-Lagrangian: Sum_i v_eq[i] * H_{eq,i}(x) + Sum_j v_ineq[j] * H_{ineq,j}(x).
lagrHess(Matrix, Matrix) - Method in interface de.labathome.trustconstr.interfaces.LagrangeHessian
lagrHessS(Matrix, Matrix) - Method in class de.labathome.trustconstr.BarrierSubproblem: Scaled Lagrangian Hessian with respect to the slacks s, i.e.
lagrHessX(Matrix, Matrix) - Method in class de.labathome.trustconstr.BarrierSubproblem: Lagrangian Hessian with respect to x (the Hx block).
lb() - Method in class de.labathome.trustconstr.LinearConstraint
lb() - Method in class de.labathome.trustconstr.NonlinearConstraint
lb() - Method in class de.labathome.trustconstr.records.Bounds
lb() - Method in class de.labathome.trustconstr.records.FiniteDifferenceBounds
lb() - Method in class de.labathome.trustconstr.records.PreparedConstraint
LinAlg - Class in de.labathome.trustconstr.matrix: Thin static facade over dev.ludovic.netlib BLAS / LAPACK kernels, specialised to DenseMatrix (column-major double[]).
LinearConstraint - Class in de.labathome.trustconstr: Linear constraint of the form
LinearConstraint(Matrix, double[], double[]) - Constructor for class de.labathome.trustconstr.LinearConstraint: Convenience overload: equivalent to LinearConstraint(Matrix, double[], double[], boolean[]) with keepFeasible = null.
LinearConstraint(Matrix, double[], double[], boolean[]) - Constructor for class de.labathome.trustconstr.LinearConstraint: Build a linear constraint lb ≤ A x ≤ ub.
LinearOperator - Interface in de.labathome.trustconstr.interfaces: Matrix-free linear operator: applies an underlying linear map to a vector without materialising the matrix.
linearOperatorDifference(Function<Matrix, Matrix>, Matrix, Matrix, Matrix, FiniteDifferenceMethod) - Static method in class de.labathome.trustconstr.NumDiff: Build a LinearOperator that applies the FD Jacobian J(x0)*p on demand, without materialising the full Jacobian.
LinearVectorFunction - Class in de.labathome.trustconstr: Linear vector function f(x) = A x and its derivatives.
LinearVectorFunction(Matrix, Matrix, Optional<Boolean>) - Constructor for class de.labathome.trustconstr.LinearVectorFunction: Build a linear vector function f(x) = A x.
linkToArray(double[]) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory: Wrap a 1-D array as an n x 1 column vector.
linkToArray(double[][]) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory
linkToArray(int[][]) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory: int[][] input -- promoted to double for test fixtures.
lowestF() - Method in class de.labathome.trustconstr.ScalarFunction
lowestX() - Method in class de.labathome.trustconstr.ScalarFunction

M

m - Variable in class de.labathome.trustconstr.LinearVectorFunction: Output dimension (A.rows).
m() - Method in interface de.labathome.trustconstr.interfaces.VectorFunctionLike
m() - Method in class de.labathome.trustconstr.LinearVectorFunction
m() - Method in class de.labathome.trustconstr.NonlinearVectorFunction
m() - Method in class de.labathome.trustconstr.records.PreparedConstraint
m() - Method in class de.labathome.trustconstr.VectorFunction
main(String[]) - Static method in class de.labathome.trustconstr.demo.SpectralCondensation
mapAdd(double) - Method in class de.labathome.trustconstr.matrix.Matrix: Helper used by Matrix.plus(double) and Matrix.minus(double): returns a fresh dense matrix with scalar added to every entry.
Matrix - Class in de.labathome.trustconstr.matrix: Abstract dense/sparse matrix base.
Matrix() - Constructor for class de.labathome.trustconstr.matrix.Matrix
Matrix.Factory - Class in de.labathome.trustconstr.matrix: Static constructors.
MatrixOps - Class in de.labathome.trustconstr.matrix: Small static helpers that operate on double[] vectors and Matrix instances.
matvec(double[]) - Method in class de.labathome.trustconstr.sparse.CSCMatrix: Matrix-vector product y = A x.
matvec(double[]) - Method in class de.labathome.trustconstr.sparse.CSRMatrix: Matrix-vector product y = A x.
message - Variable in class de.labathome.trustconstr.records.OptimizeResult: Termination message.
method - Variable in class de.labathome.trustconstr.records.OptimizeResult: Optimization method used.
method() - Method in class de.labathome.trustconstr.records.FiniteDifferenceOptions
method(FiniteDifferenceMethod) - Method in class de.labathome.trustconstr.records.FiniteDifferenceOptions.FiniteDifferenceOptionsFactory
minCurvature(double) - Method in class de.labathome.trustconstr.BFGS.BFGSFactory: Minimum curvature dot(delta_grad, delta_x) (scaled by a normalization factor) allowed to bypass the exception strategy.
minDenominator(double) - Method in class de.labathome.trustconstr.SR1.SR1Factory: Set the minimum denominator magnitude allowed in the update, scaled by a normalization factor.
minimize(Function<Matrix, Double>, Matrix, C, int, double, double) - Static method in class de.labathome.trustconstr.MinimizeTrustConstr: Most general convenience overload: only the objective function is supplied.
minimize(Function<Matrix, Double>, Function<Matrix, Matrix>, HessianUpdateStrategy, Matrix, C, int, double, double) - Static method in class de.labathome.trustconstr.MinimizeTrustConstr: Convenience overload accepting any HessianUpdateStrategy (BFGS, SR1, custom).
minimize(Function<Matrix, Double>, Function<Matrix, Matrix>, Matrix, C, int, double, double) - Static method in class de.labathome.trustconstr.MinimizeTrustConstr: Convenience overload that approximates the objective Hessian via a fresh BFGS update strategy -- the scipy-default behaviour when hess is omitted from the user call.
minimize(Function<Matrix, Double>, Function<Matrix, Matrix>, Function<Matrix, Matrix>, Matrix, C, int, double, double) - Static method in class de.labathome.trustconstr.MinimizeTrustConstr: General-purpose entry point: routes to MinimizeTrustConstr.minimizeEqualityConstrained(java.util.function.Function<de.labathome.trustconstr.matrix.Matrix, java.lang.Double>, java.util.function.Function<de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix>, java.util.function.Function<de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix>, de.labathome.trustconstr.matrix.Matrix, C, int, double, double) when the constraint has only equality rows, and to a TrustRegionInteriorPoint-driven path when any inequality rows are present.
minimize(Function<Matrix, Double>, Function<Matrix, Matrix>, Function<Matrix, Matrix>, Matrix, Object[], int, double, double) - Static method in class de.labathome.trustconstr.MinimizeTrustConstr: Multi-constraint entry point: combines the supplied constraints into a CombinedConstraint and dispatches as in the single-constraint overload.
minimizeEqualityConstrained(Function<Matrix, Double>, Function<Matrix, Matrix>, Function<Matrix, Matrix>, Matrix, C, int, double, double) - Static method in class de.labathome.trustconstr.MinimizeTrustConstr: Convenience entry point covering the equality-constrained slice of the trust-constr API: a scalar objective with an explicit gradient and Hessian, subject to optional pure-equality constraints from a single LinearConstraint or NonlinearConstraint.
minimizeTrustConstr(ToDoubleBiFunction<Matrix, Object>, Matrix, Object, BiFunction<Matrix, Object, Matrix>, BiFunction<Matrix, Object, Matrix>, HessianProduct, Bounds, Object, double, double, double, Optional<Boolean>, IterationCallback, int, int, Matrix, double, double, double, double, ProjectionMethod, boolean) - Static method in class de.labathome.trustconstr.MinimizeTrustConstr: Minimize a scalar function subject to constraints.
minimizeTrustConstr(ToDoubleBiFunction<Matrix, Object>, Matrix, Object, BiFunction<Matrix, Object, Matrix>, BiFunction<Matrix, Object, Matrix>, HessianProduct, Bounds, Object, double, double, double, Optional<Boolean>, IterationCallback, int, int, Matrix, double, double, double, double, ProjectionMethod, boolean, ExecutorService) - Static method in class de.labathome.trustconstr.MinimizeTrustConstr: Strict scipy _minimize_trustregion_constr(..., workers=N) counterpart.
MinimizeTrustConstr - Class in de.labathome.trustconstr: Java port of scipy.optimize.minimize(method='trust-constr')
MinimizeTrustConstr() - Constructor for class de.labathome.trustconstr.MinimizeTrustConstr
minus(double) - Method in class de.labathome.trustconstr.matrix.Matrix
minus(Matrix) - Method in class de.labathome.trustconstr.matrix.DenseMatrix
minus(Matrix) - Method in class de.labathome.trustconstr.matrix.Matrix
minus(Matrix) - Method in class de.labathome.trustconstr.matrix.SparseMatrix
modifiedDogleg(Matrix, Object, Matrix, double, double[], double[]) - Static method in class de.labathome.trustconstr.QPSubproblem: Approximately minimize 1/2 ||A x + b||^2 subject to ||x|| < Delta and lb ≤ x ≤ ub using a modified dogleg approach.
mtimes(Matrix) - Method in class de.labathome.trustconstr.matrix.DenseMatrix
mtimes(Matrix) - Method in class de.labathome.trustconstr.matrix.Matrix
mtimes(Matrix) - Method in class de.labathome.trustconstr.matrix.SparseMatrix
multiply(double) - Method in class de.labathome.trustconstr.sparse.CSCMatrix: Element-wise scalar multiply (allocates a new matrix).
multiply(double) - Method in class de.labathome.trustconstr.sparse.CSRMatrix: Element-wise scalar multiply (allocates a new matrix).

N

n - Variable in class de.labathome.trustconstr.FullHessianUpdateStrategy: Problem dimension.
n - Variable in class de.labathome.trustconstr.LinearVectorFunction: Input dimension (A.cols).
n() - Method in interface de.labathome.trustconstr.interfaces.VectorFunctionLike
n() - Method in class de.labathome.trustconstr.LagrangianHessian
n() - Method in class de.labathome.trustconstr.LinearVectorFunction
n() - Method in record class de.labathome.trustconstr.matrix.CholResult: Returns the value of the n record component.
n() - Method in class de.labathome.trustconstr.NonlinearVectorFunction
n() - Method in class de.labathome.trustconstr.records.PreparedConstraint
n() - Method in class de.labathome.trustconstr.sparse.DenseSolve.LUFactor
n() - Method in class de.labathome.trustconstr.VectorFunction
NEGATIVE_CURVATURE - Enum constant in enum class de.labathome.trustconstr.enums.PCGStoppingCondition: 3: Negative curvature detected.
nEq - Variable in class de.labathome.trustconstr.CanonicalConstraint: Number of canonical equality rows.
nEq() - Method in class de.labathome.trustconstr.CombinedConstraint
nEq() - Method in class de.labathome.trustconstr.LinearConstraint
nEq() - Method in class de.labathome.trustconstr.NonlinearConstraint
nEq() - Method in class de.labathome.trustconstr.SparsityForcedConstraint
nIneq - Variable in class de.labathome.trustconstr.CanonicalConstraint: Number of canonical inequality rows.
nIneq() - Method in class de.labathome.trustconstr.CombinedConstraint
nIneq() - Method in class de.labathome.trustconstr.LinearConstraint
nIneq() - Method in class de.labathome.trustconstr.NonlinearConstraint
nIneq() - Method in class de.labathome.trustconstr.SparsityForcedConstraint
niter - Variable in class de.labathome.trustconstr.records.CGInfo: Number of CG iterations performed.
nIter - Variable in class de.labathome.trustconstr.records.OptimizeResult: Total number of iterations.
nIter - Variable in class de.labathome.trustconstr.records.State: Number of completed outer iterations.
nnz() - Method in class de.labathome.trustconstr.matrix.SparseMatrix
nnz() - Method in class de.labathome.trustconstr.sparse.CSCMatrix
nnz() - Method in class de.labathome.trustconstr.sparse.CSRMatrix.Builder
nnz() - Method in class de.labathome.trustconstr.sparse.CSRMatrix
NonlinearConstraint - Class in de.labathome.trustconstr: Nonlinear constraint of the form
NonlinearConstraint(Function<Matrix, Matrix>, double[], double[]) - Constructor for class de.labathome.trustconstr.NonlinearConstraint
NonlinearConstraint(Function<Matrix, Matrix>, double[], double[], boolean[]) - Constructor for class de.labathome.trustconstr.NonlinearConstraint
NonlinearConstraint(Function<Matrix, Matrix>, Function<Matrix, Matrix>, double[], double[]) - Constructor for class de.labathome.trustconstr.NonlinearConstraint: Convenience overload with neither constraint Hessian nor keepFeasible flags.
NonlinearConstraint(Function<Matrix, Matrix>, Function<Matrix, Matrix>, double[], double[], boolean[]) - Constructor for class de.labathome.trustconstr.NonlinearConstraint: Convenience overload: as NonlinearConstraint(Function, Function, BiFunction, double[], double[], boolean[]) with no constraint Hessian.
NonlinearConstraint(Function<Matrix, Matrix>, Function<Matrix, Matrix>, BiFunction<Matrix, Matrix, Matrix>, double[], double[], boolean[]) - Constructor for class de.labathome.trustconstr.NonlinearConstraint: Build a nonlinear constraint with explicit constraint Hessian.
NonlinearVectorFunction - Class in de.labathome.trustconstr: Light-weight nonlinear vector function carrier for use inside PreparedConstraint.
NonlinearVectorFunction(Function<Matrix, Matrix>, Function<Matrix, Matrix>, BiFunction<Matrix, Matrix, Matrix>, Matrix, Optional<Boolean>) - Constructor for class de.labathome.trustconstr.NonlinearVectorFunction: Build a nonlinear vector function and cache f, J at x0.
norm2() - Method in class de.labathome.trustconstr.matrix.DenseMatrix
norm2() - Method in class de.labathome.trustconstr.matrix.Matrix
norm2() - Method in class de.labathome.trustconstr.matrix.SparseMatrix
norm2(double[]) - Static method in class de.labathome.trustconstr.matrix.MatrixOps: Euclidean (2-)norm of a vector.
NORMAL_EQUATION - Enum constant in enum class de.labathome.trustconstr.enums.ProjectionMethod: The operators will be computed using the so-called normal equation approach explained in [1]_.
normF() - Method in class de.labathome.trustconstr.matrix.Matrix
normInf() - Method in class de.labathome.trustconstr.matrix.DenseMatrix
normInf() - Method in class de.labathome.trustconstr.matrix.Matrix
normInf() - Method in class de.labathome.trustconstr.matrix.SparseMatrix
NOT_EVALUATED - Enum constant in enum class de.labathome.trustconstr.enums.PCGStoppingCondition: 0: CG subproblem not evaluated.
numConstraintEval - Variable in class de.labathome.trustconstr.records.OptimizeResult: Number of constraint evaluations for each of the constraints.
numConstraintEval - Variable in class de.labathome.trustconstr.records.State: Per-constraint count of constraint evaluations.
numConstraintHessianEval - Variable in class de.labathome.trustconstr.records.OptimizeResult: Number of Hessian evaluations for each of the constraints.
numConstraintHessianEval - Variable in class de.labathome.trustconstr.records.State: Per-constraint count of constraint Hessian evaluations.
numConstraintJacobianEval - Variable in class de.labathome.trustconstr.records.OptimizeResult: Number of Jacobian matrix evaluations for each of the constraints.
numConstraintJacobianEval - Variable in class de.labathome.trustconstr.records.State: Per-constraint count of constraint Jacobian evaluations.
NumDiff - Class in de.labathome.trustconstr: Finite-difference Jacobians and gradients (mirrors scipy _numdiff.approx_derivative).
NumDiff() - Constructor for class de.labathome.trustconstr.NumDiff
numEval - Variable in class de.labathome.trustconstr.records.State: Number of objective evaluations so far.
numFunctionEval - Variable in class de.labathome.trustconstr.records.OptimizeResult: Number of the objective function evaluations.
numFunctionEvals() - Method in interface de.labathome.trustconstr.interfaces.VectorFunctionLike
numFunctionEvals() - Method in class de.labathome.trustconstr.NonlinearVectorFunction
numFunctionEvals() - Method in class de.labathome.trustconstr.ScalarFunction
numFunctionEvals() - Method in class de.labathome.trustconstr.VectorFunction
numGradientEval - Variable in class de.labathome.trustconstr.records.State: Number of gradient evaluations so far.
numGradientEvals() - Method in class de.labathome.trustconstr.ScalarFunction
numHessianEval - Variable in class de.labathome.trustconstr.records.OptimizeResult: Number of the objective function Hessian evaluations.
numHessianEval - Variable in class de.labathome.trustconstr.records.State: Number of Hessian evaluations so far.
numHessianEvals() - Method in interface de.labathome.trustconstr.interfaces.VectorFunctionLike
numHessianEvals() - Method in class de.labathome.trustconstr.NonlinearVectorFunction
numHessianEvals() - Method in class de.labathome.trustconstr.ScalarFunction
numHessianEvals() - Method in class de.labathome.trustconstr.VectorFunction
numJacobianEval - Variable in class de.labathome.trustconstr.records.OptimizeResult: Number of the objective function gradient evaluations.
numJacobianEvals() - Method in interface de.labathome.trustconstr.interfaces.VectorFunctionLike
numJacobianEvals() - Method in class de.labathome.trustconstr.NonlinearVectorFunction
numJacobianEvals() - Method in class de.labathome.trustconstr.VectorFunction

O

of(Matrix) - Static method in class de.labathome.trustconstr.records.Sparsity: Convenience factory: derive the column grouping from A via NumDiff.groupColumns(Matrix).
of(Matrix, int[]) - Static method in class de.labathome.trustconstr.records.Sparsity: Convenience factory with a user-supplied column ordering.
ONE_SIDED - Enum constant in enum class de.labathome.trustconstr.enums.FiniteDifferenceMethod: One-sided perturbation (forward or backward, picked per dimension).
ones(long[]) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory
ones(long, long) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory
optimality - Variable in class de.labathome.trustconstr.records.OptimizeResult: Infinity norm of the Lagrangian gradient at the solution.
optimality - Variable in class de.labathome.trustconstr.records.State: KKT optimality measure (infinity-norm of the Lagrangian gradient).
OptimizeResult - Class in de.labathome.trustconstr.records: Mutable output of MinimizeTrustConstr.minimize(java.util.function.Function<de.labathome.trustconstr.matrix.Matrix, java.lang.Double>, java.util.function.Function<de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix>, java.util.function.Function<de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix>, de.labathome.trustconstr.matrix.Matrix, C, int, double, double).
OptimizeResult() - Constructor for class de.labathome.trustconstr.records.OptimizeResult
orthogonality(Matrix, Matrix) - Static method in class de.labathome.trustconstr.Projections: Measure orthogonality between a vector and the null space of a matrix.

P

PCGStoppingCondition - Enum Class in de.labathome.trustconstr.enums: Why projected-CG terminated on the most recent inner solve.
plus(double) - Method in class de.labathome.trustconstr.matrix.Matrix
plus(Matrix) - Method in class de.labathome.trustconstr.matrix.DenseMatrix
plus(Matrix) - Method in class de.labathome.trustconstr.matrix.Matrix
plus(Matrix) - Method in class de.labathome.trustconstr.matrix.SparseMatrix
PreparedConstraint - Class in de.labathome.trustconstr.records: User-facing constraint prepared for use by the trust-constr orchestrator.
PreparedConstraint(LinearConstraint, Matrix, Optional<Boolean>) - Constructor for class de.labathome.trustconstr.records.PreparedConstraint: Prepare a LinearConstraint.
PreparedConstraint(NonlinearConstraint, Matrix, Optional<Boolean>, FiniteDifferenceBounds) - Constructor for class de.labathome.trustconstr.records.PreparedConstraint: Prepare a NonlinearConstraint.
PreparedConstraint(Bounds, Matrix, Optional<Boolean>) - Constructor for class de.labathome.trustconstr.records.PreparedConstraint: Prepare Bounds (folding them into the constraint set as the trivial linear constraint lb ≤ x ≤ ub with A = I).
printFooter() - Method in class de.labathome.trustconstr.report.ReportBase: Print a blank line as the report footer.
printFooter(PrintStream) - Method in class de.labathome.trustconstr.report.ReportBase: Print the footer to a specified target (used by tests).
printHeader() - Method in class de.labathome.trustconstr.report.ReportBase: Print the column header line and a separator.
printHeader(PrintStream) - Method in class de.labathome.trustconstr.report.ReportBase: Print the column header to a specified target (used by tests).
printIteration(PrintStream, Object...) - Method in class de.labathome.trustconstr.report.ReportBase: Print a single iteration row to a specified target (used by tests).
printIteration(Object...) - Method in class de.labathome.trustconstr.report.ReportBase: Print a single iteration row to System.out.
projectedCG(LinearOperator, Matrix, Object, Object, Matrix) - Static method in class de.labathome.trustconstr.QPSubproblem: Solve the equality-constrained quadratic program
projectedCG(LinearOperator, Matrix, Object, Object, Matrix, double, double[], double[], double) - Static method in class de.labathome.trustconstr.QPSubproblem: Solve EQP problem with projected CG method.
projectedCG(LinearOperator, Matrix, Object, Object, Matrix, double, double[], double[], double, long, long, boolean) - Static method in class de.labathome.trustconstr.QPSubproblem: Solve the equality-constrained quadratic program
ProjectionMethod - Enum Class in de.labathome.trustconstr.enums: How Projections.projections(de.labathome.trustconstr.matrix.Matrix) should factor the constraint Jacobian to build the null-space / least-squares / row-space projectors.
projections(Matrix) - Static method in class de.labathome.trustconstr.Projections: Convenience overload: auto-select factorisation method, defaults for orthogonality / refinement / numerical-zero tolerances.
projections(Matrix, ProjectionMethod) - Static method in class de.labathome.trustconstr.Projections: Convenience overload with an explicit factorisation method.
projections(Matrix, ProjectionMethod, double) - Static method in class de.labathome.trustconstr.Projections: Convenience overload exposing the orthogonality tolerance.
projections(Matrix, ProjectionMethod, double, int) - Static method in class de.labathome.trustconstr.Projections: Convenience overload exposing the maximum number of refinement iterations.
projections(Matrix, ProjectionMethod, double, int, double) - Static method in class de.labathome.trustconstr.Projections: Return three linear operators related with a given matrix A.
Projections - Class in de.labathome.trustconstr: Linear operators that project onto the null space, range, and least-squares solution set of a constraint Jacobian.
Projections() - Constructor for class de.labathome.trustconstr.Projections

Q

Q() - Method in record class de.labathome.trustconstr.matrix.QRResult: Returns the value of the Q record component.
QPSubproblem - Class in de.labathome.trustconstr: Quadratic-programming subproblem helpers used inside the trust-region SQP / IP loops: the projected-CG inner solver, the equality-constrained KKT direct factorization, the modified-dogleg trust-region step, and the segment/box/sphere intersection routines that drive trust-region step acceptance.
QPSubproblem() - Constructor for class de.labathome.trustconstr.QPSubproblem
qr(DenseMatrix) - Static method in class de.labathome.trustconstr.matrix.LinAlg: QR factorisation via dgeqrf + dorgqr.
QR_FACTORIZATION - Enum constant in enum class de.labathome.trustconstr.enums.ProjectionMethod: Compute projections using QR factorization.
QRResult - Record Class in de.labathome.trustconstr.matrix: QR factorisation of a tall-or-square matrix A (m x n with m >= n): A = Q R with Q (m x n) having orthonormal columns and R (n x n) upper triangular.
QRResult(DenseMatrix, DenseMatrix) - Constructor for record class de.labathome.trustconstr.matrix.QRResult: Creates an instance of a QRResult record class.

R

R() - Method in record class de.labathome.trustconstr.matrix.QRResult: Returns the value of the R record component.
randn(long, long) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory: Random normal matrix with mean 0 and stddev 1.
rank() - Method in class de.labathome.trustconstr.matrix.Matrix: Rank computed via SVD: count singular values strictly greater than the default LAPACK numerical-zero threshold max(m,n) * ulp(sigma_max).
rank(double) - Method in record class de.labathome.trustconstr.matrix.SVDResult: Number of singular values strictly greater than tol.
reciprocalSingularValues() - Method in record class de.labathome.trustconstr.matrix.SVDResult: Element-wise reciprocal of the singular values, with values at or below the LAPACK numerical-zero threshold max(m,n) * ulp(sigma_max) mapped to 0.
reinforceBoxBoundaries(double[], double[], double[]) - Static method in class de.labathome.trustconstr.QPSubproblem: Return clipped value of x.
relStep() - Method in class de.labathome.trustconstr.records.FiniteDifferenceOptions
relStep(Matrix) - Method in class de.labathome.trustconstr.records.FiniteDifferenceOptions.FiniteDifferenceOptionsFactory
ReportBase - Class in de.labathome.trustconstr.report: Abstract base for trust-constr per-iteration progress reports.
ReportBase() - Constructor for class de.labathome.trustconstr.report.ReportBase
residual(Matrix) - Method in class de.labathome.trustconstr.LinearConstraint: Lower and upper residuals at x: sl = A x - lb (positive iff lower bound satisfied), sb = ub - A x (positive iff upper bound satisfied).
residual(Matrix) - Method in class de.labathome.trustconstr.records.Bounds: Lower and upper residuals at x: sl = x - lb (positive iff lower bound satisfied), sb = ub - x (positive iff upper bound satisfied).
Residual - Record Class in de.labathome.trustconstr.records: Lower and upper residuals for a two-sided constraint lb ≤ f(x) ≤ ub.
Residual(double[], double[]) - Constructor for record class de.labathome.trustconstr.records.Residual: Creates an instance of a Residual record class.
rmatvec(double[]) - Method in class de.labathome.trustconstr.sparse.CSCMatrix: Transposed matrix-vector product y = A^T x.
rmatvec(double[]) - Method in class de.labathome.trustconstr.sparse.CSRMatrix: Transposed matrix-vector product y = A^T x.
row(double...) - Static method in class de.labathome.trustconstr.matrix.DenseMatrix
rows() - Method in class de.labathome.trustconstr.matrix.DenseMatrix
rows() - Method in class de.labathome.trustconstr.sparse.CSCMatrix
rows() - Method in class de.labathome.trustconstr.sparse.CSRMatrix.Builder
rows() - Method in class de.labathome.trustconstr.sparse.CSRMatrix

S

s() - Method in record class de.labathome.trustconstr.matrix.SVDResult: Returns the value of the s record component.
sb() - Method in record class de.labathome.trustconstr.records.Residual: Returns the value of the sb record component.
ScalarFunction - Class in de.labathome.trustconstr: Scalar function and its derivatives.
ScalarFunction.ScalarFunctionFactory - Class in de.labathome.trustconstr: Builder for ScalarFunction.
ScalarFunctionFactory() - Constructor for class de.labathome.trustconstr.ScalarFunction.ScalarFunctionFactory: Default-construct an empty factory.
scale - Variable in class de.labathome.trustconstr.FullHessianUpdateStrategy: Current scaling factor applied to the Hessian (or its inverse).
scaleInPlace(double) - Method in class de.labathome.trustconstr.matrix.DenseMatrix: In-place scaling.
selectColumns(int...) - Method in class de.labathome.trustconstr.matrix.DenseMatrix: Pick an arbitrary subset of columns into a fresh DenseMatrix.
selectColumns(long) - Method in class de.labathome.trustconstr.matrix.Matrix
selectRows(int...) - Method in class de.labathome.trustconstr.matrix.DenseMatrix: Pick an arbitrary subset of rows into a fresh DenseMatrix.
self() - Method in class de.labathome.trustconstr.FullHessianUpdateStrategy.FullHessianUpdateStrategyFactory
set(int, int, double) - Method in class de.labathome.trustconstr.matrix.DenseMatrix
set(int, int, double) - Method in class de.labathome.trustconstr.sparse.CSRMatrix.Builder: Store v at (i, j).
setAsDouble(double, long, long) - Method in class de.labathome.trustconstr.matrix.DenseMatrix
setAsDouble(double, long, long) - Method in class de.labathome.trustconstr.matrix.Matrix
setAsDouble(double, long, long) - Method in class de.labathome.trustconstr.matrix.SparseMatrix
setRandSeed(long) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory: Set the seed of the RNG underlying Matrix.Factory.randn(long, long) so results become reproducible.
shouldStop(State, Matrix, boolean, double, double, double, double, CGInfo) - Method in interface de.labathome.trustconstr.interfaces.StoppingCriterion
shouldStop(State, Matrix, boolean, double, double, double, double, CGInfo, double, double) - Method in interface de.labathome.trustconstr.interfaces.GlobalStoppingCriteria
shouldTerminate(State) - Method in interface de.labathome.trustconstr.interfaces.IterationCallback
SKIP_UPDATE - Enum constant in enum class de.labathome.trustconstr.enums.ExceptionStrategy: Skip the Hessian update entirely (scipy 'skip_update').
sl() - Method in record class de.labathome.trustconstr.records.Residual: Returns the value of the sl record component.
solve(double[]) - Method in class de.labathome.trustconstr.sparse.DenseSolve.LUFactor: Solve A x = b reusing the captured LU.
solve(DenseMatrix) - Method in record class de.labathome.trustconstr.matrix.CholResult: Solve A x = rhs where A is the original SPD matrix factored into CholResult.factor().
solve(DenseMatrix) - Method in record class de.labathome.trustconstr.matrix.QRResult: Least-squares solve: returns the n x p matrix x that minimises ||A x - rhs||_2, where A = Q R was the original input.
solve(DenseMatrix, DenseMatrix) - Static method in class de.labathome.trustconstr.matrix.LinAlg: Solve A x = b via LAPACK dgesv (general LU with partial pivoting).
solve(Matrix) - Method in class de.labathome.trustconstr.matrix.Matrix: Solve this * x = rhs via LAPACK dgesv (general LU).
solveLU(double[][], double[]) - Static method in class de.labathome.trustconstr.sparse.DenseSolve: Convenience: factor and solve in one step.
source() - Method in class de.labathome.trustconstr.records.PreparedConstraint
source() - Method in class de.labathome.trustconstr.SparsityForcedConstraint
sparse(Matrix) - Static method in class de.labathome.trustconstr.matrix.MatrixOps: Materialise the non-zero entries of a possibly-dense matrix into a SparseMatrix (DOK-backed).
SparseAssembly - Class in de.labathome.trustconstr.sparse: Sparse-aware structured assembly: vstack, hstack, blockArray, and the specialised KKT/Jacobian builders that trust-constr relies on.
sparseJacobian - Variable in class de.labathome.trustconstr.LinearVectorFunction: true if A is stored as a SparseMatrix.
sparseJacobian() - Method in class de.labathome.trustconstr.LinearVectorFunction
sparseJacobian() - Method in class de.labathome.trustconstr.NonlinearVectorFunction
sparseJacobian() - Method in class de.labathome.trustconstr.VectorFunction
sparseJacobian() - Method in class de.labathome.trustconstr.VectorFunction.VectorFunctionFactory: Force the Jacobian return type to a sparse representation.
SparseLinearOperator - Class in de.labathome.trustconstr.sparse: Adapter from a CSRMatrix or CSCMatrix to the existing LinearOperator interface used throughout the algorithm.
SparseMatrix - Class in de.labathome.trustconstr.matrix: Sparse matrix backed by a Dictionary-of-Keys (DOK) representation: a HashMap keyed by the encoded (row, col) index.
SparseMatrix(int, int) - Constructor for class de.labathome.trustconstr.matrix.SparseMatrix: Allocate a fresh empty sparse matrix.
SparseMatrix.Factory - Class in de.labathome.trustconstr.matrix: Static factories that produce SparseMatrix instances.
sparsity() - Method in class de.labathome.trustconstr.records.FiniteDifferenceOptions
sparsity(Sparsity) - Method in class de.labathome.trustconstr.records.FiniteDifferenceOptions.FiniteDifferenceOptionsFactory
Sparsity - Class in de.labathome.trustconstr.records: Pairing of a sparsity-pattern matrix A with a precomputed Curtis-Powell-Reid column grouping.
Sparsity(Matrix, int[]) - Constructor for class de.labathome.trustconstr.records.Sparsity
SparsityForcedConstraint - Class in de.labathome.trustconstr: Decorator that wraps a Constraint + Jacobian source and forces the jacEq / jacIneq return values to a specific sparsity.
SparsityForcedConstraint(Object, boolean) - Constructor for class de.labathome.trustconstr.SparsityForcedConstraint
sparsityGroups() - Method in class de.labathome.trustconstr.records.Sparsity
SpectralCondensation - Class in de.labathome.trustconstr.demo: Demo: spectral condensation of a 2D closed curve.
sphereIntersections(double[], double[], double) - Static method in class de.labathome.trustconstr.QPSubproblem: Find the intersection between segment (or line) and spherical constraints.
sphereIntersections(double[], double[], double, boolean) - Static method in class de.labathome.trustconstr.QPSubproblem: Find the intersection of a segment (or line) with the ball ||x|| ≤ trustRadius, where the segment is parameterised as x(t) = z + t*d.
SQPReport - Class in de.labathome.trustconstr.report: Equality-constrained SQP progress report (9 columns).
SQPReport() - Constructor for class de.labathome.trustconstr.report.SQPReport
SR1 - Class in de.labathome.trustconstr: Symmetric-rank-1 (SR1) Hessian update strategy.
SR1(boolean, double, double) - Constructor for class de.labathome.trustconstr.SR1
SR1.SR1Factory - Class in de.labathome.trustconstr: Builder for SR1; configure via SR1.FACTORY.
SR1Factory() - Constructor for class de.labathome.trustconstr.SR1.SR1Factory: Public so callers can construct a fresh factory per build instead of mutating the shared SR1.FACTORY singleton (whose state leaks across calls and tests).
state() - Method in class de.labathome.trustconstr.records.StatefulResult
State - Class in de.labathome.trustconstr.records: Mutable state threaded through the equality-path SQP outer loop.
State() - Constructor for class de.labathome.trustconstr.records.State: Default-construct a State with all fields at their zero/null defaults.
StatefulResult - Class in de.labathome.trustconstr.records: Inner-loop result from EqualityConstrainedSQP.eqSQP(de.labathome.trustconstr.interfaces.IFunctionAndConstraint, de.labathome.trustconstr.interfaces.IGradientAndJacobian, de.labathome.trustconstr.interfaces.LagrangeHessian, de.labathome.trustconstr.matrix.Matrix, double, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.interfaces.StoppingCriterion, de.labathome.trustconstr.records.State, double, double, de.labathome.trustconstr.enums.ProjectionMethod, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.interfaces.LinearOperator) and TrustRegionInteriorPoint.trustRegionInteriorPoint(java.util.function.ToDoubleBiFunction<de.labathome.trustconstr.matrix.Matrix, java.lang.Object>, java.util.function.BiFunction<de.labathome.trustconstr.matrix.Matrix, java.lang.Object, de.labathome.trustconstr.matrix.Matrix>, de.labathome.trustconstr.interfaces.LagrangeHessian, int, int, int, de.labathome.trustconstr.interfaces.Constraint, de.labathome.trustconstr.interfaces.Jacobian, de.labathome.trustconstr.matrix.Matrix, double, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.matrix.Matrix, de.labathome.trustconstr.interfaces.GlobalStoppingCriteria, boolean[], double, de.labathome.trustconstr.records.State, double, double, double, double, de.labathome.trustconstr.enums.ProjectionMethod).
StatefulResult(Matrix, State) - Constructor for class de.labathome.trustconstr.records.StatefulResult
StatefulResult(Matrix, State, Matrix) - Constructor for class de.labathome.trustconstr.records.StatefulResult
StateIP - Class in de.labathome.trustconstr.records: IP-path extension of State: adds the log-barrier coefficient and the barrier-subproblem inner-loop tolerance carried alongside the standard outer-iteration fields.
StateIP() - Constructor for class de.labathome.trustconstr.records.StateIP
status - Variable in class de.labathome.trustconstr.records.OptimizeResult: {0, 1, 2, 3}: Termination status: 0 : The maximum number of function evaluations is exceeded. 1 : `gtol` termination condition is satisfied. 2 : `xtol` termination condition is satisfied. 3 : `callback` function requested termination.
stopCond - Variable in class de.labathome.trustconstr.records.CGInfo: Why CG terminated (residual met tolerance, hit boundary, etc.).
stoppingCriteria(State, Matrix, boolean, double, double, double, double, CGInfo) - Method in class de.labathome.trustconstr.BarrierSubproblem: Stopping criterion for the barrier subproblem; mirrors formula (2.3) from Byrd-Hribar-Nocedal (1999), p.879.
StoppingCriterion - Interface in de.labathome.trustconstr.interfaces: Termination predicate consulted by the inner SQP loop.
StrictBounds - Class in de.labathome.trustconstr.records: FiniteDifferenceBounds variant constructed from a Bounds record, propagating the keep_feasible flag.
StrictBounds(Bounds) - Constructor for class de.labathome.trustconstr.records.StrictBounds
subMatrix(int, int, int, int) - Method in class de.labathome.trustconstr.matrix.DenseMatrix: Inclusive submatrix slice rows[r0..r1] x cols[c0..c1].
subMatrix(long, long, long, long) - Method in class de.labathome.trustconstr.matrix.Matrix: Slice rows [r0..r1] and columns [c0..c1] (inclusive).
success - Variable in class de.labathome.trustconstr.records.OptimizeResult: Whether the optimizer reports success.
svd(DenseMatrix) - Static method in class de.labathome.trustconstr.matrix.LinAlg: Full SVD via dgesvd (jobu='A', jobvt='A'): A = U * diag(s) * V^T.
SVD_FACTORIZATION - Enum constant in enum class de.labathome.trustconstr.enums.ProjectionMethod: Compute projections using SVD factorization.
SVDResult - Record Class in de.labathome.trustconstr.matrix: Singular-value decomposition A = U * diag(s) * V^T.
SVDResult(DenseMatrix, double[], DenseMatrix) - Constructor for record class de.labathome.trustconstr.matrix.SVDResult: Creates an instance of a SVDResult record class.
syr(DenseMatrix, double, double[]) - Static method in class de.labathome.trustconstr.matrix.LinAlg: In-place rank-1 symmetric update: A := A + alpha x x^T.
syr2(DenseMatrix, double, double[], double[]) - Static method in class de.labathome.trustconstr.matrix.LinAlg: In-place rank-2 symmetric update: A := A + alpha (x y^T + y x^T).

T

tA() - Method in class de.labathome.trustconstr.records.IntersectionResult
tB() - Method in class de.labathome.trustconstr.records.IntersectionResult
THREE_POINT - Enum constant in enum class de.labathome.trustconstr.enums.FiniteDifferenceMethod: Central difference (scipy '3-point').
times(double) - Method in class de.labathome.trustconstr.matrix.DenseMatrix
times(double) - Method in class de.labathome.trustconstr.matrix.Matrix
times(double) - Method in class de.labathome.trustconstr.matrix.SparseMatrix
times(Matrix) - Method in class de.labathome.trustconstr.matrix.DenseMatrix
times(Matrix) - Method in class de.labathome.trustconstr.matrix.Matrix
times(Matrix) - Method in class de.labathome.trustconstr.matrix.SparseMatrix
toColumnArray() - Method in class de.labathome.trustconstr.matrix.DenseMatrix
toColumnArray() - Method in class de.labathome.trustconstr.matrix.Matrix
toCSC() - Method in class de.labathome.trustconstr.sparse.CSRMatrix: Convert to CSC of the same matrix (not the transpose).
toCSR() - Method in class de.labathome.trustconstr.matrix.SparseMatrix: Materialise this sparse matrix to a CSRMatrix (canonical CSR form: column indices sorted within each row, no explicit zeros).
toCSR() - Method in class de.labathome.trustconstr.sparse.CSCMatrix: Convert to CSR of the same matrix (not the transpose).
toDense() - Method in class de.labathome.trustconstr.sparse.CSCMatrix: Materialise as a dense [rows][cols] array.
toDense() - Method in class de.labathome.trustconstr.sparse.CSRMatrix: Materialize as a dense [rows][cols] array.
toDoubleArray() - Method in class de.labathome.trustconstr.matrix.DenseMatrix
toDoubleArray() - Method in class de.labathome.trustconstr.matrix.Matrix
TOLERANCE_SATISFIED - Enum constant in enum class de.labathome.trustconstr.enums.PCGStoppingCondition: 4: Tolerance was satisfied.
toRowMajor() - Method in class de.labathome.trustconstr.matrix.DenseMatrix
toString() - Method in record class de.labathome.trustconstr.CanonicalConstraint.InitialCanonical: Returns a string representation of this record class.
toString() - Method in record class de.labathome.trustconstr.matrix.CholResult: Returns a string representation of this record class.
toString() - Method in class de.labathome.trustconstr.matrix.DenseMatrix
toString() - Method in record class de.labathome.trustconstr.matrix.QRResult: Returns a string representation of this record class.
toString() - Method in record class de.labathome.trustconstr.matrix.SVDResult: Returns a string representation of this record class.
toString() - Method in record class de.labathome.trustconstr.records.ApproxDerivativeResult: Returns a string representation of this record class.
toString() - Method in record class de.labathome.trustconstr.records.EqIneqSplit: Returns a string representation of this record class.
toString() - Method in class de.labathome.trustconstr.records.OptimizeResult: One-line summary suitable for println(result): success flag, status, method, x, fun, optimality, constraint violation, iteration counters.
toString() - Method in record class de.labathome.trustconstr.records.Residual: Returns a string representation of this record class.
transpose() - Method in class de.labathome.trustconstr.matrix.DenseMatrix
transpose() - Method in class de.labathome.trustconstr.matrix.Matrix
transpose() - Method in class de.labathome.trustconstr.matrix.SparseMatrix
transpose() - Method in class de.labathome.trustconstr.sparse.CSCMatrix: Transpose.
transpose() - Method in class de.labathome.trustconstr.sparse.CSRMatrix: Transpose: returns a CSC matrix with the same non-zeros, rows/columns swapped.
TRUST_REGION_BOUNDARY_REACHED - Enum constant in enum class de.labathome.trustconstr.enums.PCGStoppingCondition: 2: Reached the trust-region boundary.
TRUST_REGION_INTERIOR_POINT - Enum constant in enum class de.labathome.trustconstr.enums.TrustConstrMethod: Trust-region interior-point method (scipy tr_interior_point).
TrustConstrMethod - Enum Class in de.labathome.trustconstr.enums: Which dispatch path actually ran inside MinimizeTrustConstr: reported back to the caller via OptimizeResult.method.
trustRadius - Variable in class de.labathome.trustconstr.records.OptimizeResult: Radius of the trust region at the last iteration.
trustRadius - Variable in class de.labathome.trustconstr.records.State: Current trust-region radius.
trustRegionInteriorPoint(ToDoubleBiFunction<Matrix, Object>, BiFunction<Matrix, Object, Matrix>, LagrangeHessian, int, int, int, Constraint, Jacobian, Matrix, double, Matrix, Matrix, Matrix, Matrix, Matrix, GlobalStoppingCriteria, boolean[], double, State, double, double, double, double, ProjectionMethod) - Static method in class de.labathome.trustconstr.TrustRegionInteriorPoint: Trust-region interior-point solve.
TrustRegionInteriorPoint - Class in de.labathome.trustconstr: Trust-region interior-point method.
TrustRegionInteriorPoint() - Constructor for class de.labathome.trustconstr.TrustRegionInteriorPoint
TWO_POINT - Enum constant in enum class de.labathome.trustconstr.enums.FiniteDifferenceMethod: Forward difference (scipy '2-point').
TWO_SIDED - Enum constant in enum class de.labathome.trustconstr.enums.FiniteDifferenceMethod: Two-sided central perturbation.

U

U() - Method in record class de.labathome.trustconstr.matrix.SVDResult: Returns the value of the U record component.
ub() - Method in class de.labathome.trustconstr.LinearConstraint
ub() - Method in class de.labathome.trustconstr.NonlinearConstraint
ub() - Method in class de.labathome.trustconstr.records.Bounds
ub() - Method in class de.labathome.trustconstr.records.FiniteDifferenceBounds
ub() - Method in class de.labathome.trustconstr.records.PreparedConstraint
unbounded(long) - Static method in class de.labathome.trustconstr.records.FiniteDifferenceBounds: Convenience factory for the bound-free case: -inf ≤ x ≤ +inf.
update(double, double) - Method in class de.labathome.trustconstr.BarrierSubproblem: Refresh the barrier coefficient and inner-loop tolerance for the next outer iteration.
update(Matrix, Matrix) - Method in class de.labathome.trustconstr.FullHessianUpdateStrategy
update(Matrix, Matrix) - Method in interface de.labathome.trustconstr.interfaces.HessianUpdateStrategy: Update internal matrix.
updateState(State, Matrix, boolean, ScalarFunction, PreparedConstraint[], long, double, double, CGInfo) - Static method in class de.labathome.trustconstr.MinimizeTrustConstr: Refresh the equality-path State record after an outer iteration (the function value, gradient, optimality, constraint violation, trust-region and CG fields).
updateStateIP(StateIP, Matrix, boolean, ScalarFunction, PreparedConstraint[], long, double, double, CGInfo, double, double) - Static method in class de.labathome.trustconstr.MinimizeTrustConstr: Refresh the IP-path StateIP record after an outer iteration: delegates to MinimizeTrustConstr.updateState(de.labathome.trustconstr.records.State, de.labathome.trustconstr.matrix.Matrix, boolean, de.labathome.trustconstr.ScalarFunction, de.labathome.trustconstr.records.PreparedConstraint[], long, double, double, de.labathome.trustconstr.records.CGInfo) and then sets the barrier-specific fields.
upper() - Method in record class de.labathome.trustconstr.matrix.CholResult: Returns the value of the upper record component.
useOneSided() - Method in class de.labathome.trustconstr.records.AdjustedDifferencingScheme
userFun() - Method in class de.labathome.trustconstr.NonlinearConstraint
userHess() - Method in class de.labathome.trustconstr.NonlinearConstraint
userJac() - Method in class de.labathome.trustconstr.NonlinearConstraint

V

v - Variable in class de.labathome.trustconstr.LinearVectorFunction: Most recently set Lagrange multipliers (from LinearVectorFunction.hess(Matrix, Matrix)).
v - Variable in class de.labathome.trustconstr.records.OptimizeResult: List of the Lagrange multipliers for the constraints at the solution.
v - Variable in class de.labathome.trustconstr.records.State: Lagrange multipliers, one entry per constraint source.
v() - Method in interface de.labathome.trustconstr.interfaces.VectorFunctionLike
v() - Method in class de.labathome.trustconstr.LinearVectorFunction
v() - Method in class de.labathome.trustconstr.NonlinearVectorFunction
v() - Method in class de.labathome.trustconstr.records.StatefulResult: Final Lagrange multiplier vector from the inner SQP loop.
v() - Method in class de.labathome.trustconstr.VectorFunction
validateKeepFeasibleAtStart(Matrix) - Method in class de.labathome.trustconstr.CombinedConstraint: Walk all sources and validate that any row marked keep_feasible=True is satisfied at x0.
validateKeepFeasibleAtStart(Matrix) - Method in class de.labathome.trustconstr.LinearConstraint: Throws IllegalArgumentException if any row marked keepFeasible[i] == true is violated at the supplied starting point.
validateKeepFeasibleAtStart(Matrix) - Method in class de.labathome.trustconstr.NonlinearConstraint: Throws IllegalArgumentException if any row marked keepFeasible[i] == true is violated at the supplied starting point.
validateKeepFeasibleAtStart(Matrix) - Method in class de.labathome.trustconstr.SparsityForcedConstraint: Pass-through to the source's keep-feasible-at-start validation.
valueOf(String) - Static method in enum class de.labathome.trustconstr.enums.ExceptionStrategy: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class de.labathome.trustconstr.enums.FiniteDifferenceMethod: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class de.labathome.trustconstr.enums.HessianApproximationType: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class de.labathome.trustconstr.enums.PCGStoppingCondition: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class de.labathome.trustconstr.enums.ProjectionMethod: Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class de.labathome.trustconstr.enums.TrustConstrMethod: Returns the enum constant of this class with the specified name.
values() - Static method in enum class de.labathome.trustconstr.enums.ExceptionStrategy: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class de.labathome.trustconstr.enums.FiniteDifferenceMethod: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class de.labathome.trustconstr.enums.HessianApproximationType: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class de.labathome.trustconstr.enums.PCGStoppingCondition: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class de.labathome.trustconstr.enums.ProjectionMethod: Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class de.labathome.trustconstr.enums.TrustConstrMethod: Returns an array containing the constants of this enum class, in the order they are declared.
VectorFunction - Class in de.labathome.trustconstr: Vector function and its derivatives.
VectorFunction.VectorFunctionFactory - Class in de.labathome.trustconstr: Builder for VectorFunction.
VectorFunctionFactory() - Constructor for class de.labathome.trustconstr.VectorFunction.VectorFunctionFactory: Public so callers can construct a fresh factory per build instead of mutating the shared VectorFunction.FACTORY singleton.
VectorFunctionLike - Interface in de.labathome.trustconstr.interfaces: Common surface implemented by every vector-valued function carrier the trust-constr code passes around: the full VectorFunction (objective wrapper with caching and finite-difference fallbacks), LinearVectorFunction (constant Jacobian A), and IdentityVectorFunction (Jacobian I).
vertCat(Matrix...) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory: Vertical concatenation: stack the input matrices on top of each other.
violation(Matrix) - Method in class de.labathome.trustconstr.records.PreparedConstraint: Compute the per-row constraint violation at x.
vstack(CSRMatrix...) - Static method in class de.labathome.trustconstr.sparse.SparseAssembly: Vertical stack of CSR matrices: rows are concatenated, columns must agree.
Vt() - Method in record class de.labathome.trustconstr.matrix.SVDResult: Returns the value of the Vt record component.

X

x - Variable in class de.labathome.trustconstr.LinearVectorFunction: Most recently evaluated point.
x - Variable in class de.labathome.trustconstr.records.CGInfo: Solution vector of the EQP problem (n x 1).
x - Variable in class de.labathome.trustconstr.records.OptimizeResult: [n] Solution found.
x - Variable in class de.labathome.trustconstr.records.State: Current iterate (n x 1).
x() - Method in class de.labathome.trustconstr.records.StatefulResult
x0() - Method in class de.labathome.trustconstr.records.PreparedConstraint
x0(Matrix) - Method in class de.labathome.trustconstr.ScalarFunction.ScalarFunctionFactory: Provide the initial point for evaluating fun.
x0(Matrix) - Method in class de.labathome.trustconstr.VectorFunction.VectorFunctionFactory: Provide the initial point.

Z

zeros(int, int) - Static method in class de.labathome.trustconstr.matrix.DenseMatrix
zeros(int, int) - Static method in class de.labathome.trustconstr.sparse.SparseAssembly
zeros(long[]) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory
zeros(long[]) - Static method in class de.labathome.trustconstr.matrix.SparseMatrix.Factory
zeros(long, long) - Static method in class de.labathome.trustconstr.matrix.Matrix.Factory
zeros(long, long) - Static method in class de.labathome.trustconstr.matrix.SparseMatrix.Factory

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