aimsalgo  5.0.5
Neuroimaging image processing
LM2Gaussian< T > Class Template Reference

#include <aims/optimization/lm2gauss.h>

Inheritance diagram for LM2Gaussian< T >:
Collaboration diagram for LM2Gaussian< T >:

Public Member Functions

 LM2Gaussian (T k1=(T) 1.0, T m1=(T) 0.0, T s1=(T) 1.0, T k2=(T) 1.0, T m2=(T) 0.0, T s2=(T) 1.0)
 
apply (T)
 
eval (T)
 
- Public Member Functions inherited from LMFunction< T >
 LMFunction ()
 
 LMFunction (const LMFunction< T > &)
 
virtual ~LMFunction ()
 
std::vector< T > & param ()
 
std::vector< T > & derivative ()
 

Additional Inherited Members

- Protected Attributes inherited from LMFunction< T >
std::vector< T > par
 
std::vector< T > der
 

Detailed Description

template<class T>
class LM2Gaussian< T >

Definition at line 42 of file lm2gauss.h.

Constructor & Destructor Documentation

◆ LM2Gaussian()

template<class T >
LM2Gaussian< T >::LM2Gaussian ( k1 = (T)1.0,
m1 = (T)0.0,
s1 = (T)1.0,
k2 = (T)1.0,
m2 = (T)0.0,
s2 = (T)1.0 
)
inline

Definition at line 55 of file lm2gauss.h.

References LMFunction< T >::der, and LMFunction< T >::par.

Member Function Documentation

◆ apply()

template<class T >
T LM2Gaussian< T >::apply ( x)
inlinevirtual

Reimplemented from LMFunction< T >.

Definition at line 93 of file lm2gauss.h.

References LMFunction< T >::par.

◆ eval()

template<class T >
T LM2Gaussian< T >::eval ( x)
inlinevirtual

Reimplemented from LMFunction< T >.

Definition at line 71 of file lm2gauss.h.

References LMFunction< T >::der, and LMFunction< T >::par.


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