HCL_Adjoint_dHCL_Adjoint_d creates the adjoint operator of a
HCL_LinearOpAdj_d as an operator in its own right
HCL_ALFcnlGrad_dHCL_ALFcnlGrad_d implements an Augmented Lagrangian functional; it is
itended for use with HCL_CMinAL_d
HCL_ALFcnlHess_dHCL_ALFcnlHess_d implements an Augmented Lagrangian functional; it is
itended for use with HCL_CMinAL_d
HCL_BandedMat_dHCL_BandedMat_d is the HCL object representing banded matrices
HCL_BandedMatInv_dHCL_BandedMatInv_d is the HCL object representing banded matrices
HCL_BaseHCL_Base is the base class for all HCL classes
HCL_BiLinearOp_dHCL_BiLinearOp_d is the base class for bilinear operators
HCL_BiLinearOpAdj_dHCL_BiLinearOpAdj_d is the base class for bilinear operators which
can compute various adjoint operators
HCL_BlockLinearOp_dHCL_BlockLinearOp_d implements an array of linear operators
acting on a product vector space
HCL_BlockLinearOpAdj_dHCL_BlockLinearOpAdj_d implements an array of linear operators
(with adjoints) acting on a product vector space
HCL_CG_dHCL_CG_d implements the (unpreconditioned) conjugate gradients algorithm
for solving a linear operator equation with a symmetric positive
definite operator
HCL_CMinALGrad_dHCL_CMinALGrad_d implements the Augmented Lagrangian algorithm
HCL_CMinALHess_dHCL_CMinALHess_d implements the Augmented Lagrangian algorithm
HCL_ColOperator_dHCL_ColOperator_d implements a linear operator from
Euclidean $n$-space into an abstract vector space $X$
HCL_CompLinearOp_dHCL_CompLinearOp_d is a concrete class implementing a composition
of two or more linear operators
HCL_CompLinearOpNormal_dHCL_CompLinearOpNormal_d is a concrete class implementing a composition
of two or more linear operators with adjoint operators
HCL_DiagBlockLinearOp_dHCL_DiagBlockLinearOp_d implements a diagonal array of linear operators
acting on a product vector space
HCL_DiagBlockLinearOpAdj_dHCL_DiagBlockLinearOpAdj_d implements a diagonal array of linear
operators (with adjoints) acting on a product vector space
HCL_DiagBlockLinearOpAdjInv_dHCL_DiagBlockLinearOpAdj_d implements a diagonal array of linear
operators (with adjoints and inverses) acting on a product vector space
HCL_DiagBlockLinearSolver_dHCL_DiagBlockLinearSolver_d implements a solver for a decoupled
system of linear operator equations
HCL_DiagFunctional_dHCL_DiagFunctional_d implements a separable function defined on a
product space
HCL_DiagFunctionalGrad_dHCL_DiagFunctionalGrad_d implements a separable function defined on a
product space
HCL_DiagFunctionalHess_dHCL_DiagFunctionalHess_d implements a separable function defined on a
product space
HCL_DiagScaleLinearOp_dHCL_DiagScaleLinearOp_d is a class implementing the linear operator
mapping x to a*x, where x and a are EuclideanVectors and
the multiplication is done componentwise
HCL_EuclideanVector_dHCL_EuclideanVector_d is the base class for vectors permitting componentwise operations
HCL_EuclideanVectorSpace_dHCL_EuclideanVectorSpace_d is the base class for all Euclidean
vector spaces in HCL, i
HCL_EvalALFcnlGrad_dHCL_EvalALFcnlGrad_d is the evaluation object for the class
HCL_ALFcnlGrad_d, which implements an Augmented Lagrangian functional
with gradient
HCL_EvalALFcnlHess_dHCL_EvalALFcnlHess_d is the evaluation object for the class
HCL_ALFcnlHess_d, which implements an Augmented Lagrangian functional
with gradient and Hessian
HCL_EvalDiagFcnlGrad_dHCL_EvalDiagFcnlGrad_d is the evaluation object for
HCL_DiagFunctionalGrad_d
HCL_EvalDiagFcnlHess_dHCL_EvalDiagFcnlHess_d is the evaluation object for
HCL_DiagFunctionalHess_d
HCL_EvalFunctionalProductDomainGrad_dHCL_EvalFunctionalProductDomainGrad_d is the base class for
the evaluation object created by an object of type
HCL_FunctionalProductDomainGrad_, a real-valued function
defined on a product vector space
HCL_EvalRestrictedFunctionalGrad_dHCL_EvalRestrictedFunctionalGrad_d is the evaluation class for
HCL_RestrictedFunctionalGrad_d, which is the concrete class
which turns a functional defined on a product space into an ordinary
functional by fixing all but one of the components
HCL_EvalRestrictedFunctionalHess_dHCL_EvalRestrictedFunctionalHess_d is the evaluation class for
HCL_RestrictedFunctionalHess_d, which is the concrete class
which turns a functional defined on a product space into an ordinary
functional by fixing all but one of the components
HCL_EvaluateFunctionalGrad_dThis class represents an "evaluation" object that will be created
by a HCL_FunctionalGrad_d object to implement the value and
gradient of the functional at a point
HCL_EvaluateFunctionalHess_dThis class represents an "evaluation" object that will be created
by a HCL_FunctionalHess_d object to implement the value, gradient,
and Hessian of the functional at a point
HCL_EvaluateOpDeriv2Adj_dThis class represents an "evaluation" object that will be created
by a HCL_OpDeriv2Adj_d object to implement the image and derivative
of the operator at a point
HCL_EvaluateOpDerivAdj_dThis class represents an "evaluation" object that will be created
by a HCL_OpDerivAdj_d object to implement the image and derivative
of the operator at a point
HCL_FPArch_dHCL_FPArch_d is an interface class to the LAPACK DLAMCH,
which determines the floating point characteristics of machine
on which the code is running
HCL_Functional_dHCL_Functional_d is the base class for all real-valued functions
HCL_FunctionalGrad_dHCL_FunctionalGrad_d is the base class for all real-valued
functions which can compute their gradients
HCL_FunctionalHess_dHCL_FunctionalHess_d is the base class for all real-valued
functions which can compute their gradients and Hessians
HCL_FunctionalProductDomainGrad_dHCL_FunctionalProductDomainGrad_d represents a functional
with gradient whose domain is a product space
HCL_GMRES_dHCL_GMRES_d implements the preconditioned Generalized Minimal
Residual (GMRES) algorithm for solving a linear operator equation
with a (possibly) non-symmetric operator (See Golub and VanLoan [1996])
HCL_InvLinearOp_dHCL_InvLinearOp_d creates the inverse operator of a
HCL_LinearOp_d or a HCL_LinearOpInv_d as an operator
in its own right
HCL_InvLinearOpAdj_dHCL_InvLinearOpAdj_d creates the inverse operator of a
HCL_LinearOpAdjInv_d as an operator in its own right
HCL_IRArnoldi_dHCL_IRArnoldi_d implements the implicitly restarted Arnoldi algorithm
for solving the (generalized) eigenvalue problem
HCL_ItEigSolver_dAbstract base class for iterative eigenvalue solvers
HCL_LeastSquaresFcnlGrad_dHCL_LeastSquaresFcnlGrad creates least squares objective functions
from operators and data
HCL_LeastSquaresFcnlHess_dHCL_LeastSquaresFcnlHess creates least squares objective functions
from operators and data
HCL_LinCombFcnlGrad_dHCL_LinCombFcnlGrad_d represents a linear combination of
real-valued functions with gradients
HCL_LinCombFcnlHess_dHCL_LinCombFcnlHess_d represents a linear combination of
real-valued functions with gradients and Hessians
HCL_LinCombLinearOp_dHCL_LinCombLinearOp_d is a concrete class implementing a linear
combination of one or more linear operators
HCL_LinCombLinearOpAdj_dHCL_LinCombLinearOpAdj_d is a concrete class implementing a linear
combination of one or more linear operators, each with adjoint
HCL_LinCombLinearOpNormal_dHCL_LinCombLinearOpNormal_d is a concrete class implementing a
linear combination of one or more linear operators, each with adjoint
and normal
HCL_LinearOp_dHCL_LinearOp_d is the base class for all linear operators
HCL_LinearOpAdj_dHCL_LinearOpAdj_d is the base class for all linear operators
with adjoints
HCL_LinearOpAdjEucRange_dHCL_LinearOpAdjEucRange_d is an abstract base class which is
almost identical to HCL_LinearOpAdj_d, from which it is derived,
except that the range of the linear operator is required to be a
HCL_EuclideanVectorSpace_d
HCL_LinearOpAdjInv_dHCL_LinearOpAdjInv_d represents a linear operator which knows how
to compute both its adjoint and its inverse (or an approximation to it)
HCL_LinearOpInv_dHCL_LinearOpInv_d represents a linear operator which knows how
to compute its inverse (or an approximation to it)
HCL_LinearOpNormal_dHCL_LinearOpNormal_d is the base class for all linear operators
with adjoint and normal operators
HCL_LinearSolver_dHCL_LinearSolver_d is the base class for linear solvers, that is, for
objects representing algorithms for solving linear operator equations
HCL_LineSearch_DS_dAn implementation of a backtracking
line search algorithm using cubic interpolation
(See Dennis and Schnabel, "Numerical Methods for Unconstrained
Optimization and Nonlinear Equations", Prentice-Hall (1983))
HCL_LineSearch_Fl_dAn implementation of a backtracking
line search algorithm using cubic and quadratic interpolation
(See Fletcher, "Practical Methods of Optimization" (2nd edition),
Wiley, (1987))
HCL_LineSearch_MT_dAn implementation of the More' and Thuente line search algorithm
(See More' and Thuente, "Line Search Algorithms with Guaranteed
Sufficient Decrease", ACM TOMS, Vol
HCL_lmbfgsOp_dHCL_lmbfgsOp_d implements the limited memory BFGS approximation to
the inverse Hessian of a twice-differentiable function
HCL_Matrix_dHCL_Matrix_d is the base class for all sparse and
dense matrices
HCL_MatTR_dHCL_MatTR_d implements an algorithm for solving the
trust region subproblem in the case in which the operator is
represented by a symmetric matrix
HCL_NonSymMat_dHCL_NonSymMat_d is the HCL object representing
nonsymmetric dense matrices
HCL_NonSymMatInv_dHCL_NonSymMatInv_d is the HCL object representing
nonsymmetric dense matrices
HCL_NonSymSparseMat_dHCL_NonSymSparseMat_d is the HCL object representing nonsymmetric
sparse matrices
HCL_Normal_dHCL_Normal_d creates the normal operator of a
HCL_LinearOpAdj_d or HCL_LinearOpNormal_d as an
operator in its own right
HCL_Op_dHCL_Op_d is the base class for (presumably nonlinear) operators
HCL_OpDeriv2Adj_dHCL_OpDeriv2Adj_d is the base class for (presumably nonlinear)
operators which know how to compute their first and second derivatives; the
first and second derivatives know how to compute the appropriate
adjoints
HCL_OpDerivAdj_dHCL_OpDerivAdj_d is the base class for (presumably nonlinear)
operators which know how to compute their derivatives as linear operators with
adjoints
HCL_PCG_dHCL_PCG_d implements the preconditioned conjugate gradients algorithm
for solving a linear operator equation with a symmetric positive
definite operator
HCL_ProductVector_dHCL_ProductVector_d represents a vector from a product space
HCL_ProductVectorSpace_dHCL_ProductVectorSpace_d represents a vector space which is
defined as a product of several given vector spaces
HCL_QuadRegFunctional_dHCL_QuadRegFunctional_d implements a quadratic functional defined by
a linear operator A as follows:
x |---> 0
HCL_RestrictedFunctionalGrad_dHCL_RestrictedFunctionalGrad_d is a concrete class which
creates a functional with gradient from a functional defined
on a product space, by fixing all but one of the components of the
independent variable
HCL_RestrictedFunctionalHess_dHCL_RestrictedFunctionalHess_d is a concrete class which
creates a functional with gradient and Hessian from a functional defined
on a product space, by fixing all but one of the components of the
independent variable
HCL_RnSpace_dHCL_RnSpace_d is the HCL object representing the vector space Rn
HCL_RnVector_dHCL_RnVector_d is a memory-based vector class representing vectors in Rn
HCL_RowOperator_dHCL_RowOperator_d implements a linear operator from
an abstract vector space $X$ into Euclidean $n$-space
HCL_ScaleLinearOp_dHCL_ScaleLinearOp_d is a class implementing the linear operator
mapping x to a*x, where a is a scalar
HCL_ScaleLinearOpAdjInv_dHCL_ScaleLinearOpAdjInv_d is a class implementing the linear operator
mapping x to a*x, where a is a scalar
HCL_SymMat_dHCL_SymMat_d is the HCL object representing symetrical matrices
HCL_TRCG_dThe class HCL_TRCG_d is an implentation of the Steihaug-Toint algorithm
for approximately solving the trust region subproblem
HCL_TRSSOp_dThe class HCL_TRSSOp_d defines the bordered operator used
by HCL_TrustRegion_SS_d
HCL_TrustRegion_SS_dThe class HCL_TrustRegion_SS_d is an implementation of the
Santosa-Sorensen algorithm for solving the trust region subproblem
HCL_TrustRegionSolver_dThe class HCL_TrustRegionSolver_d is an abstract base clase for
algorithms for solving the trust region subproblem:
min q(s) = <g,s> + 1/2<s,Bs>
s
HCL_UMin_lbfgs_dHCL_UMin_lbfgs_d implements the limited memory BFGS algorithm
for unconstrained minimization
HCL_UMinGrad_dHCL_UMinGrad_d is the abstract base class for unconstrained
minimizers which use first derivatives
HCL_UMinGradMethod_dHCL_UMinGradMethod provides easy access to the UMinGrad methods
HCL_UMinHess_dHCL_UMinHess_d is the base class for unconstrained minimizers which
use first and second derivatives
HCL_UMinHessMethod_dHCL_UMinHessMethod provides easy access to the UMinHess methods
HCL_UMinNLCG_dHCL_UMinNLCG_d implements the nonlinear conjugate gradient
algorithm (Polak-Ribiere form) for unconstrained minimization
HCL_UMinProductDomainGrad_dHCL_UMinProductDomainGrad_d is the abstract base class for
unconstrained minimization algorithms designed for problems in which
the objective function is defined on a product space
HCL_UMinProductDomainHess_dHCL_UMinProductDomainHess_d is the abstract base class for
unconstrained minimization algorithms designed for problems in which
the objective function is defined on a product space
HCL_UMinTR_dThe class HCL_UMinTR_d implements a generic algorithm for solving
unconstrained minimization problems using a trust region method
HCL_Vector_dHCL_Vector_d is the base class for all vectors in HCL
HCL_VectorSpace_dHCL_VectorSpace_d is the base class for all vector spaces in HCL
HCL_ZeroLinearOp_dHCL_ZeroLinearOp_d is a class implementing the zero linear operator
SGFSpace_dSGFSpaces define the geometry and attributes of uniform rectilinear grids
SGFVector_dSGFVector is an out-of-core vector class, implementing sampled functions
on a uniform rectilinear grid as HCL_Vectors
Functions, Macros
HCL_deleteTo be called in place of the operator delete (for HCL objects only)
