JDFTx  1.1.1
InverseKohnSham Class Reference
Inheritance diagram for InverseKohnSham:
Minimizable< ScalarFieldArray >

Public Member Functions

 InverseKohnSham (Everything &)
 
void step (const ScalarFieldArray &dir, double alpha)
 Move the state in parameter space along direction dir with scale alpha.
 
double compute (ScalarFieldArray *grad)
 Returns the objective function at the current state and store the gradient in grad, if non-null.
 
ScalarFieldArray precondition (const ScalarFieldArray &grad)
 
void constrain (ScalarFieldArray &dir)
 
bool report (int iter)
 
double sync (double x) const
 All processes minimize together; make sure scalars are in sync to round-off error.
 
- Public Member Functions inherited from Minimizable< ScalarFieldArray >
double minimize (const MinimizeParams &params)
 Minimize this objective function with algorithm controlled by params and return the minimized value.
 
void fdTest (const MinimizeParams &params)
 

Member Function Documentation

void InverseKohnSham::constrain ( ScalarFieldArray )
virtual

Constrain an arbitrary vector to the space of free directions for minimize. Used only to generate a random direction for fdTest within the valid minimization subspace.

Reimplemented from Minimizable< ScalarFieldArray >.

ScalarFieldArray InverseKohnSham::precondition ( const ScalarFieldArray grad)
virtual

Override to enable preconditioning: return the preconditioned gradient, given the gradient The last call to compute() is guaranteed to be at the same position, so a cached result may be returned

Reimplemented from Minimizable< ScalarFieldArray >.

bool InverseKohnSham::report ( int  iter)
virtual

Override for optional processing/reporting after each/every few iterations It should return whether the state was modified

Reimplemented from Minimizable< ScalarFieldArray >.


The documentation for this class was generated from the following file: