Name 

Description 

 

InverseHess 

Returns the inverse of Hessian matrix. 

 

Iterations 

Returns number of optimization algorithm iterations. 

 

MinValue 

Stores value of the objective function, evaluated at minimum. 

 

Name 

Description 

 

AllowStreaming 

Returns the negatated value of BlockAssign. 

 

Assign 

Assign values of all published properties from Source. 

 

AssignTemplate 

Assign values of "template-like" published properties from Source. 

 

Create 

This is Create, a member of class TMtxOptimization. 

 

Destroy 

This is Destroy, a member of class TMtxOptimization. 

 

LoadTemplateFromFile 

Load a template from file. 

 

LoadTemplateFromStream 

Load a template from stream. 

 

Recalculate 

Triggers TMtxOptimization recalculation. 

 

Reset 

Reset is called after loading the data from stream or file.  

 

SaveTemplateToFile 

Save template to file. 

 

SaveTemplateToStream 

Save template to stream. 

 

SetObjects 

Define any additional Object constant parameters in the RealFunction. 

 

Name 

Description 

 

Dirty 

Becomes true after any of the properties have changed. 

 

EditorActive 

Returns True, if the component editor is displayed. 

 

GradHessProcedure 

Defines the gradient vector and Hessian matrix calculation routine. 

 

GradProcedure 

Defines the gradient vector calculation routine. 

 

RealFunction 

Defines the function to be minimized. 

 

Reference 

Stores a list of components that have to be notified, when this component is destroyed. 

 

StopReason 

Stop reason for optimization algorithm. 

 

Verbose 

If not nil then the optimization method uses it for logging each optimization step. 

 

Name 

Description 

 

AutoUpdate 

Automatic recalculation. 

 

ConstantParameters 

set/read the additional constants used in minimized function. 

 

GradTolerance 

The precision for numeric gradient and/or Hessian matrix calculation. 

 

Lambda0 

Initial lambda step used in Marquardt optimization algorithm. 

 

MaxIterations 

maximum number of iterations allowed for minimum search. 

 

NumericGradMethod 

Defines which gradient numerical approximation method will be used to to evaluate gradient. 

 

OptimizationMethod 

Optimization algorithm used for minimum search. 

 

SoftSearch 

Internal line search algorithm. 

 

Tolerance 

Precision. 

 

VariableParameters 

Set/read the variables in minimized function.