gm_to_dirac_short< T > Class Template Reference

Inheritance diagram for gm_to_dirac_short< T >:

Public Types
using	GSLVectorType = typename gm_to_dirac_approx_i< T >::GSLVectorType
using	GSLVectorViewType = typename gm_to_dirac_approx_i< T >::GSLVectorViewType
using	GSLMatrixType = typename gm_to_dirac_approx_i< T >::GSLMatrixType
Public Types inherited from gm_to_dirac_approx_i< T >
using	GSLVectorType = typename GSLTemplateTypeAlias< T >::VectorType
using	GSLVectorViewType = typename GSLTemplateTypeAlias< T >::VectorViewType
using	GSLMatrixType = typename GSLTemplateTypeAlias< T >::MatrixType

Public Member Functions
bool	approximate (const T *covDiag, size_t L, size_t N, size_t bMax, T *x, const T *wX=nullptr, GslminimizerResult *result=nullptr, const ApproximateOptions &options=ApproximateOptions{}) override
	approximate using raw pointers
void	modified_van_mises_distance_sq (const T *covDiag, T *distance, size_t L, size_t N, size_t bMax, T *x, const T *wX) override
	calculate modified van mises distance based on standard normal deviation and x
void	modified_van_mises_distance_sq_derivative (const T *covDiag, T *gradient, size_t L, size_t N, size_t bMax, T *x, const T *wX) override
	calculate modified van mises distance based on standard normal deviation and x
bool	approximate (const GSLVectorType *covDiag, size_t L, size_t N, size_t bMax, GSLVectorType *x, const GSLVectorType *wX=nullptr, GslminimizerResult *result=nullptr, const ApproximateOptions &options=ApproximateOptions{}) override
	approximate using gsl vectors
void	modified_van_mises_distance_sq (const GSLVectorType *covDiag, T *distance, size_t L, size_t N, size_t bMax, GSLVectorType *x, const GSLVectorType *wX) override
	calculate modified van mises distance based on standard normal deviation and x
void	modified_van_mises_distance_sq_derivative (const GSLVectorType *covDiag, GSLVectorType *gradient, size_t L, size_t N, size_t bMax, GSLVectorType *x, const GSLVectorType *wX) override
	calculate modified van mises distance based on standard normal deviation and x
bool	approximate (const GSLVectorType *covDiag, size_t L, size_t N, size_t bMax, GSLMatrixType *x, const GSLVectorType *wX=nullptr, GslminimizerResult *result=nullptr, const ApproximateOptions &options=ApproximateOptions{}) override
	approximate using gsl vectors
void	modified_van_mises_distance_sq (const GSLVectorType *covDiag, T *distance, size_t L, size_t N, size_t bMax, GSLMatrixType *x, const GSLVectorType *wX) override
	calculate modified van mises distance based on standard normal deviation and x
void	modified_van_mises_distance_sq_derivative (const GSLVectorType *covDiag, GSLMatrixType *gradient, size_t L, size_t N, size_t bMax, GSLMatrixType *x, const GSLVectorType *wX) override
	calculate modified van mises distance based on standard normal deviation and x
bool	approximate (const gsl_vector_float *covDiag, size_t L, size_t N, size_t bMax, gsl_vector_float *x, const gsl_vector_float *wX, GslminimizerResult *result, const ApproximateOptions &options)
bool	approximate (const gsl_vector *covDiag, size_t L, size_t N, size_t bMax, gsl_vector *x, const gsl_vector *wX, GslminimizerResult *result, const ApproximateOptions &options)
void	modified_van_mises_distance_sq (const gsl_vector_float *covDiag, float *distance, size_t L, size_t N, size_t bMax, gsl_vector_float *x, const gsl_vector_float *wX)
void	modified_van_mises_distance_sq (const gsl_vector *covDiag, double *distance, size_t L, size_t N, size_t bMax, gsl_vector *x, const gsl_vector *wX)
void	modified_van_mises_distance_sq_derivative (const gsl_vector_float *covDiag, gsl_vector_float *gradient, size_t L, size_t N, size_t bMax, gsl_vector_float *x, const gsl_vector_float *wX)
void	modified_van_mises_distance_sq_derivative (const gsl_vector *covDiag, gsl_vector *gradient, size_t L, size_t N, size_t bMax, gsl_vector *x, const gsl_vector *wX)
bool	approximate (const gsl_vector_float *covDiag, size_t L, size_t N, size_t bMax, gsl_vector_float *x, const gsl_vector_float *wX, GslminimizerResult *result, const ApproximateOptions &options)
bool	approximate (const gsl_vector *covDiag, size_t L, size_t N, size_t bMax, gsl_vector *x, const gsl_vector *wX, GslminimizerResult *result, const ApproximateOptions &options)
void	modified_van_mises_distance_sq (const gsl_vector_float *covDiag, float *distance, size_t L, size_t N, size_t bMax, gsl_vector_float *x, const gsl_vector_float *wX)
void	modified_van_mises_distance_sq (const gsl_vector *covDiag, double *distance, size_t L, size_t N, size_t bMax, gsl_vector *x, const gsl_vector *wX)
void	modified_van_mises_distance_sq_derivative (const gsl_vector_float *covDiag, gsl_vector_float *gradient, size_t L, size_t N, size_t bMax, gsl_vector_float *x, const gsl_vector_float *wX)
void	modified_van_mises_distance_sq_derivative (const gsl_vector *covDiag, gsl_vector *gradient, size_t L, size_t N, size_t bMax, gsl_vector *x, const gsl_vector *wX)

Friends
class	benchmark_gm_to_dirac_short

Member Function Documentation

approximate() [1/3]

template<typename T >

bool gm_to_dirac_short< T >::approximate ( const GSLVectorType *  covDiag, size_t  L, size_t  N, size_t  bMax, GSLMatrixType *  x, const GSLVectorType *  wX = nullptr, GslminimizerResult *  result = nullptr, const ApproximateOptions &  options = ApproximateOptions{}  )

overridevirtual

approximate using gsl vectors

Parameters

covDiag	covariance matrix diagonal
L	number of data points for apprioximation
N	dimension of the data
bMax	bMax
x	first guess for the approximation and return value
wX	weights for the x data points
result	minimizer result
options	options for minimizer

Returns

true, on success, false otherwise

Implements gm_to_dirac_approx_i< T >.

approximate() [2/3]

template<typename T >

bool gm_to_dirac_short< T >::approximate ( const GSLVectorType *  covDiag, size_t  L, size_t  N, size_t  bMax, GSLVectorType *  x, const GSLVectorType *  wX = nullptr, GslminimizerResult *  result = nullptr, const ApproximateOptions &  options = ApproximateOptions{}  )

overridevirtual

approximate using gsl vectors

Parameters

covDiag	covariance matrix diagonal
L	number of data points for apprioximation
N	dimension of the data
bMax	bMax
x	first guess for the approximation and return value
wX	weights for the x data points
result	minimizer result
options	options for minimizer

Returns

true, on success, false otherwise

Implements gm_to_dirac_approx_i< T >.

approximate() [3/3]

template<typename T >

bool gm_to_dirac_short< T >::approximate ( const T *  covDiag, size_t  L, size_t  N, size_t  bMax, T *  x, const T *  wX = nullptr, GslminimizerResult *  result = nullptr, const ApproximateOptions &  options = ApproximateOptions{}  )

overridevirtual

approximate using raw pointers

Parameters

covDiag	covariance matrix diagonal
L	number of data points for apprioximation
N	dimension of the data
bMax	bMax
x	first guess for the approximation and return value
result	minimizer result
options	options for minimizer

Returns

true, on success, false otherwise

Implements gm_to_dirac_approx_i< T >.

modified_van_mises_distance_sq() [1/3]

template<typename T >

void gm_to_dirac_short< T >::modified_van_mises_distance_sq ( const GSLVectorType *  covDiag, T *  distance, size_t  L, size_t  N, size_t  bMax, GSLMatrixType *  x, const GSLVectorType *  wX  )

overridevirtual

calculate modified van mises distance based on standard normal deviation and x

Parameters

distance	pointer to distance value to be calculated
L	number of data points for approximation
N	dimension of the data
bMax	bMax
x	first guess for the approximation and return value
result	minimizer result
options	options for minimizer

Returns

true, on success, false otherwise

Implements gm_to_dirac_approx_i< T >.

modified_van_mises_distance_sq() [2/3]

template<typename T >

void gm_to_dirac_short< T >::modified_van_mises_distance_sq ( const GSLVectorType *  covDiag, T *  distance, size_t  L, size_t  N, size_t  bMax, GSLVectorType *  x, const GSLVectorType *  wX  )

overridevirtual

calculate modified van mises distance based on standard normal deviation and x

Parameters

distance	pointer to distance value to be calculated
L	number of data points for approximation
N	dimension of the data
bMax	bMax
x	first guess for the approximation and return value
result	minimizer result
options	options for minimizer

Returns

true, on success, false otherwise

Implements gm_to_dirac_approx_i< T >.

modified_van_mises_distance_sq() [3/3]

template<typename T >

void gm_to_dirac_short< T >::modified_van_mises_distance_sq ( const T *  covDiag, T *  distance, size_t  L, size_t  N, size_t  bMax, T *  x, const T *  wX  )

overridevirtual

calculate modified van mises distance based on standard normal deviation and x

Parameters

distance	pointer to distance value to be calculated
L	number of data points for approximation
N	dimension of the data
bMax	bMax
x	first guess for the approximation and return value
result	minimizer result
options	options for minimizer

Returns

true, on success, false otherwise

Implements gm_to_dirac_approx_i< T >.

modified_van_mises_distance_sq_derivative() [1/3]

template<typename T >

void gm_to_dirac_short< T >::modified_van_mises_distance_sq_derivative ( const GSLVectorType *  covDiag, GSLMatrixType *  gradient, size_t  L, size_t  N, size_t  bMax, GSLMatrixType *  x, const GSLVectorType *  wX  )

overridevirtual

calculate modified van mises distance based on standard normal deviation and x

Parameters

gradient	pointer to gradient to be calculated
L	number of data points for approximation
N	dimension of the data
bMax	bMax
x	first guess for the approximation and return value
result	minimizer result
options	options for minimizer

Returns

true, on success, false otherwise

Implements gm_to_dirac_approx_i< T >.

modified_van_mises_distance_sq_derivative() [2/3]

template<typename T >

void gm_to_dirac_short< T >::modified_van_mises_distance_sq_derivative ( const GSLVectorType *  covDiag, GSLVectorType *  gradient, size_t  L, size_t  N, size_t  bMax, GSLVectorType *  x, const GSLVectorType *  wX  )

overridevirtual

calculate modified van mises distance based on standard normal deviation and x

Parameters

gradient	pointer to gradient to be calculated
L	number of data points for approximation
N	dimension of the data
bMax	bMax
x	first guess for the approximation and return value
result	minimizer result
options	options for minimizer

Returns

true, on success, false otherwise

Implements gm_to_dirac_approx_i< T >.

modified_van_mises_distance_sq_derivative() [3/3]

template<typename T >

void gm_to_dirac_short< T >::modified_van_mises_distance_sq_derivative ( const T *  covDiag, T *  gradient, size_t  L, size_t  N, size_t  bMax, T *  x, const T *  wX  )

overridevirtual

calculate modified van mises distance based on standard normal deviation and x

Parameters

gradient	pointer to gradient to be calculated
L	number of data points for approximation
N	dimension of the data
bMax	bMax
x	first guess for the approximation and return value
result	minimizer result
options	options for minimizer

Returns

true, on success, false otherwise

Implements gm_to_dirac_approx_i< T >.

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

• lib/gm_to_dirac/gm_to_dirac_short.h
• lib/gm_to_dirac/gm_to_dirac_short.cpp