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-- File: SVD.cdl
-- Created: Mon May 13 14:35:56 1991
-- Author: Laurent PAINNOT
-- <lpa@topsn3>
---Copyright: Matra Datavision 1991, 1992
class SVD from math
---Purpose: SVD implements the solution of a set of N linear equations
-- of M unknowns without condition on N or M. The Singular
-- Value Decomposition algorithm is used. For singular or
-- nearly singular matrices SVD is a better choice than Gauss
-- or GaussLeastSquare.
uses Matrix from math,
Vector from math,
OStream from Standard
raises NotDone from StdFail,
DimensionError from Standard
is
Create(A: Matrix)
---Purpose:
-- Given as input an n X m matrix A with n < m, n = m or n > m
-- this constructor performs the Singular Value Decomposition.
returns SVD;
IsDone(me)
---Purpose: Returns true if the computations are successful, otherwise returns false.
---C++: inline
returns Boolean
is static;
Solve(me; B: Vector; X: out Vector; Eps: Real = 1.0e-6)
---Purpose:
-- Given the input Vector B this routine solves the set of linear
-- equations A . X = B.
-- Exception NotDone is raised if the decomposition of A was not done
-- successfully.
-- Exception DimensionError is raised if the range of B is not
-- equal to the rowrange of A.
-- Exception DimensionError is raised if the range of X is not
-- equal to the colrange of A.
raises NotDone,
DimensionError
is static;
PseudoInverse(me; Inv : out Matrix; Eps: Real= 1.0e-6)
---Purpose: Computes the inverse Inv of matrix A such as A * Inverse = Identity.
-- Exceptions
-- StdFail_NotDone if the algorithm fails (and IsDone returns false).
-- Standard_DimensionError if the ranges of Inv are
-- compatible with the ranges of A.
raises NotDone
is static;
Dump(me; o: in out OStream)
---Purpose: Prints information on the current state of the object.
-- Is used to redefine the operator <<.
is static;
fields
Done: Boolean;
Singular: Boolean;
U: Matrix;
V: Matrix;
Diag: Vector;
RowA: Integer;
end SVD;
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