-- Created on: 1991-05-14
-- Created by: Laurent PAINNOT
-- Copyright (c) 1991-1999 Matra Datavision
-- Copyright (c) 1999-2012 OPEN CASCADE SAS
--
-- The content of this file is subject to the Open CASCADE Technology Public
-- License Version 6.5 (the "License"). You may not use the content of this file
-- except in compliance with the License. Please obtain a copy of the License
-- at http://www.opencascade.org and read it completely before using this file.
--
-- The Initial Developer of the Original Code is Open CASCADE S.A.S., having its
-- main offices at: 1, place des Freres Montgolfier, 78280 Guyancourt, France.
--
-- The Original Code and all software distributed under the License is
-- distributed on an "AS IS" basis, without warranty of any kind, and the
-- Initial Developer hereby disclaims all such warranties, including without
-- limitation, any warranties of merchantability, fitness for a particular
-- purpose or non-infringement. Please see the License for the specific terms
-- and conditions governing the rights and limitations under the License.




class FRPR from math
    	---Purpose:
    	-- this class implements the Fletcher-Reeves-Polak_Ribiere minimization 
    	-- algorithm of a function of multiple variables.
    	-- Knowledge of the function's gradient is required.

uses Vector from math, Matrix from math, 
     MultipleVarFunctionWithGradient from math,
     Status from math,
     OStream from Standard
     
raises DimensionError from Standard,
       NotDone from StdFail

is

    Create(F: in out MultipleVarFunctionWithGradient;
    	   StartingPoint: Vector; Tolerance: Real;
	   NbIterations: Integer=200; ZEPS: Real=1.0e-12)
    	---Purpose:	  Computes FRPR minimization function F from input vector
    	-- StartingPoint. The solution F = Fi is found when 2.0 *
    	-- abs(Fi - Fi-1) <= Tolerance * (abs(Fi) + abs(Fi-1) +
    	-- ZEPS). The maximum number of iterations allowed is given
    	-- by NbIterations.
    returns FRPR;
    
    
    Create(F: in out MultipleVarFunctionWithGradient;
    	   Tolerance: Real;
	   NbIterations: Integer = 200;
	   ZEPS: Real = 1.0e-12)
    	---Purpose: Purpose
    	-- Initializes the computation of the minimum of F.
    	-- Warning
    	-- A call to the Perform method must be made after this
    	-- initialization to compute the minimum of the function.
    returns FRPR;


    Delete(me:out) is virtual;
    ---C++: alias "Standard_EXPORT virtual ~math_FRPR(){Delete();}"
    
    Perform(me: in out; F: in out MultipleVarFunctionWithGradient; 
    	    StartingPoint: Vector)
	---Purpose: Use this method after a call to the initialization constructor
    	-- to compute the minimum of function F.
    	-- Warning
    	-- The initialization constructor must have been called before
    	-- the Perform method is called

    is static;


    IsSolutionReached(me: in out; F: in out MultipleVarFunctionWithGradient)
    	---Purpose:
    	-- The solution F = Fi is found when :
    	--   2.0 * abs(Fi - Fi-1) <= Tolerance * (abs(Fi) + abs(Fi-1)) + ZEPS.
    	-- The maximum number of iterations allowed is given by NbIterations.
    
    returns Boolean
    is virtual;
    
    
    IsDone(me)
    	---Purpose: Returns true if the computations are successful, otherwise returns false.
        ---C++: inline
    returns Boolean
    is static;
    
    

    Location(me)
    	---Purpose: returns the location vector of the minimum.
        -- Exception NotDone is raised if the minimum was not found.
        ---C++: inline
        ---C++: return const&
    
    returns Vector
    raises NotDone
    is static;


    Location(me; Loc: out Vector)
    	---Purpose: outputs the location vector of the minimum in Loc.
    	-- Exception NotDone is raised if the minimum was not found.
    	-- Exception DimensionError is raised if the range of Loc is not
    	-- equal to the range of the StartingPoint.
        ---C++: inline
    raises DimensionError,
    	   NotDone
    is static;
    

    Minimum(me)
       	---Purpose: returns the value of the minimum.
       	-- Exception NotDone is raised if the minimum was not found.
       	---C++: inline
    returns Real
    raises NotDone
    is static;
    
    
    Gradient(me)
       ---Purpose: returns the gradient vector at the minimum.
       -- Exception NotDone is raised if the minimum was not found.
       ---C++: inline
       ---C++: return const&
    returns Vector
    raises NotDone
    is static;
    
    
    Gradient(me; Grad: out Vector)
    	---Purpose: outputs the gradient vector at the minimum in Grad.
        -- Exception NotDone is raised if the minimum was not found.
        -- Exception DimensionError is raised if the range of Grad is not
        -- equal to the range of the StartingPoint.
        ---C++: inline
    
    raises DimensionError,
    	   NotDone
    is static;
    
    
    
    NbIterations(me)
	---Purpose: returns the number of iterations really done during the
        -- computation of the minimum.
        -- Exception NotDone is raised if the minimum was not found.
        ---C++: inline
    
    returns Integer
    raises NotDone
    is static;
    

    Dump(me; o: in out OStream)
	---Purpose: Prints on the stream o information on the current state 
    	--          of the object.
    	--          Is used to redefine the operator <<.

    is static;



fields
Done:            Boolean;
TheLocation:     Vector is protected;
TheGradient:     Vector is protected;
TheMinimum:      Real is protected;
PreviousMinimum: Real is protected;
Iter:            Integer;
State:           Integer;
XTol:            Real is protected;
EPSZ:            Real is protected;
TheStatus:       Status;
Itermax:         Integer;

end FRPR;