[ VIGRA Homepage | Function Index | Class Index | Namespaces | File List | Main Page ]

details Matrix Functions VIGRA

Basic matrix algebra, element-wise mathematical functions, row and columns statistics, data normalization etc. More...

Functions

template<class T , class C >
linalg::TemporaryMatrix< T > abs (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C >
linalg::TemporaryMatrix< T > acos (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C1 , class C2 , class C3 >
void add (const MultiArrayView< 2, T, C1 > &a, const MultiArrayView< 2, T, C2 > &b, MultiArrayView< 2, T, C3 > &r)
 
template<class T , class C >
int argMax (MultiArrayView< 2, T, C > const &a)
 Find the index of the maximum element in a matrix. More...
 
template<class T , class C , class UnaryFunctor >
int argMaxIf (MultiArrayView< 2, T, C > const &a, UnaryFunctor condition)
 Find the index of the maximum element in a matrix subject to a condition. More...
 
template<class T , class C >
int argMin (MultiArrayView< 2, T, C > const &a)
 Find the index of the minimum element in a matrix. More...
 
template<class T , class C , class UnaryFunctor >
int argMinIf (MultiArrayView< 2, T, C > const &a, UnaryFunctor condition)
 Find the index of the minimum element in a matrix subject to a condition. More...
 
template<class T , class C >
linalg::TemporaryMatrix< T > asin (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C >
linalg::TemporaryMatrix< T > atan (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C >
linalg::TemporaryMatrix< T > ceil (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C >
MultiArrayIndex columnCount (const MultiArrayView< 2, T, C > &x)
 
template<... >
void columnStatistics (...)
 
template<class T , class C >
MultiArrayView< 2, T, C > columnVector (MultiArrayView< 2, T, C > const &m, MultiArrayIndex d)
 
template<class T , class C >
MultiArrayView< 2, T, C > columnVector (MultiArrayView< 2, T, C > const &m, MultiArrayShape< 2 >::type first, int end)
 
template<class T , class C >
linalg::TemporaryMatrix< T > cos (MultiArrayView< 2, T, C > const &v)
 
template<class T1 , class C1 , class T2 , class C2 >
void covarianceMatrixOfColumns (MultiArrayView< 2, T1, C1 > const &features, MultiArrayView< 2, T2, C2 > &covariance)
 Compute the covariance matrix between the columns of a matrix features. More...
 
template<class T , class C >
TemporaryMatrix< T > covarianceMatrixOfColumns (MultiArrayView< 2, T, C > const &features)
 Compute the covariance matrix between the columns of a matrix features. More...
 
template<class T1 , class C1 , class T2 , class C2 >
void covarianceMatrixOfRows (MultiArrayView< 2, T1, C1 > const &features, MultiArrayView< 2, T2, C2 > &covariance)
 Compute the covariance matrix between the rows of a matrix features. More...
 
template<class T , class C >
TemporaryMatrix< T > covarianceMatrixOfRows (MultiArrayView< 2, T, C > const &features)
 Compute the covariance matrix between the rows of a matrix features. More...
 
template<class T , class C1 , class C2 , class C3 >
void cross (const MultiArrayView< 1, T, C1 > &x, const MultiArrayView< 1, T, C2 > &y, MultiArrayView< 1, T, C3 > &r)
 
template<class T , class C1 , class C2 , class C3 >
void cross (const MultiArrayView< 2, T, C1 > &x, const MultiArrayView< 2, T, C2 > &y, MultiArrayView< 2, T, C3 > &r)
 
template<class T , class C1 , class C2 >
TemporaryMatrix< T > cross (const MultiArrayView< 2, T, C1 > &x, const MultiArrayView< 2, T, C2 > &y)
 
template<class T , class C1 , class C2 >
void diagonalMatrix (MultiArrayView< 2, T, C1 > const &v, MultiArrayView< 2, T, C2 > &r)
 
template<class T , class C >
TemporaryMatrix< T > diagonalMatrix (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C1 , class C2 >
NormTraits< T >::SquaredNormType dot (const MultiArrayView< 2, T, C1 > &x, const MultiArrayView< 2, T, C2 > &y)
 
template<class T , class C1 , class C2 >
NormTraits< T >::SquaredNormType dot (const MultiArrayView< 1, T, C1 > &x, const MultiArrayView< 1, T, C2 > &y)
 
template<class T , class C >
linalg::TemporaryMatrix< T > exp (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C >
linalg::TemporaryMatrix< T > floor (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C >
void identityMatrix (MultiArrayView< 2, T, C > &r)
 
template<class T >
TemporaryMatrix< T > identityMatrix (MultiArrayIndex size)
 
template<class T , class C >
bool isSymmetric (const MultiArrayView< 2, T, C > &v)
 
template<class T , class C1 , class C2 >
TemporaryMatrix< T > joinHorizontally (const MultiArrayView< 2, T, C1 > &a, const MultiArrayView< 2, T, C2 > &b)
 
template<class T , class C1 , class C2 >
TemporaryMatrix< T > joinVertically (const MultiArrayView< 2, T, C1 > &a, const MultiArrayView< 2, T, C2 > &b)
 
template<class T , class C >
linalg::TemporaryMatrix< T > log (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C >
linalg::TemporaryMatrix< T > log10 (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C1 , class C2 , class C3 >
void mmul (const MultiArrayView< 2, T, C1 > &a, const MultiArrayView< 2, T, C2 > &b, MultiArrayView< 2, T, C3 > &r)
 
template<class T , class C1 , class C2 >
TemporaryMatrix< T > mmul (const MultiArrayView< 2, T, C1 > &a, const MultiArrayView< 2, T, C2 > &b)
 
template<class T , class ALLOC >
Matrix< T, ALLLOC >::NormType norm (const Matrix< T, ALLLOC > &a)
 
template<class T >
TemporaryMatrix< T > ones (MultiArrayIndex rows, MultiArrayIndex cols)
 
template<class T , class C , class U >
TemporaryMatrix< T > operator* (const MultiArrayView< 2, T, C > &a, PointWise< U > b)
 
template<class T , class C >
TemporaryMatrix< T > operator* (const MultiArrayView< 2, T, C > &a, T b)
 
template<class T , class C >
TemporaryMatrix< T > operator* (T a, const MultiArrayView< 2, T, C > &b)
 
template<class T , class A , int N, class DATA , class DERIVED >
TinyVector< T, N > operator* (const Matrix< T, A > &a, const TinyVectorBase< T, N, DATA, DERIVED > &b)
 
template<class T , int N, class DATA , class DERIVED , class A >
TinyVector< T, N > operator* (const TinyVectorBase< T, N, DATA, DERIVED > &a, const Matrix< T, A > &b)
 
template<class T , class C1 , class C2 >
TemporaryMatrix< T > operator* (const MultiArrayView< 2, T, C1 > &a, const MultiArrayView< 2, T, C2 > &b)
 
template<class T , class C1 , class C2 >
TemporaryMatrix< T > operator+ (const MultiArrayView< 2, T, C1 > &a, const MultiArrayView< 2, T, C2 > &b)
 
template<class T , class C >
TemporaryMatrix< T > operator+ (const MultiArrayView< 2, T, C > &a, T b)
 
template<class T , class C >
TemporaryMatrix< T > operator+ (T a, const MultiArrayView< 2, T, C > &b)
 
template<class T , class C1 , class C2 >
TemporaryMatrix< T > operator- (const MultiArrayView< 2, T, C1 > &a, const MultiArrayView< 2, T, C2 > &b)
 
template<class T , class C >
TemporaryMatrix< T > operator- (const MultiArrayView< 2, T, C > &a)
 
template<class T , class C >
TemporaryMatrix< T > operator- (const MultiArrayView< 2, T, C > &a, T b)
 
template<class T , class C >
TemporaryMatrix< T > operator- (T a, const MultiArrayView< 2, T, C > &b)
 
template<class T , class C , class U >
TemporaryMatrix< T > operator/ (const MultiArrayView< 2, T, C > &a, PointWise< U > b)
 
template<class T , class C >
TemporaryMatrix< T > operator/ (const MultiArrayView< 2, T, C > &a, T b)
 
template<class T , class C >
TemporaryMatrix< T > operator/ (T a, const MultiArrayView< 2, T, C > &b)
 
template<class T , class C >
ostream & operator<< (ostream &s, const vigra::MultiArrayView< 2, T, C > &m)
 
template<class T , class C1 , class C2 , class C3 >
void outer (const MultiArrayView< 2, T, C1 > &x, const MultiArrayView< 2, T, C2 > &y, MultiArrayView< 2, T, C3 > &r)
 
template<class T , class C1 , class C2 >
TemporaryMatrix< T > outer (const MultiArrayView< 2, T, C1 > &x, const MultiArrayView< 2, T, C2 > &y)
 
template<class T , class C >
TemporaryMatrix< T > outer (const MultiArrayView< 2, T, C > &x)
 
template<class T , int N>
TemporaryMatrix< T > outer (const TinyVector< T, N > &x)
 
template<class T , class C1 , class C2 , class C3 >
void pdiv (const MultiArrayView< 2, T, C1 > &a, const MultiArrayView< 2, T, C2 > &b, MultiArrayView< 2, T, C3 > &r)
 
template<class T , class C1 , class C2 >
TemporaryMatrix< T > pdiv (const MultiArrayView< 2, T, C1 > &a, const MultiArrayView< 2, T, C2 > &b)
 
template<class T , class C1 , class C2 , class C3 >
void pmul (const MultiArrayView< 2, T, C1 > &a, const MultiArrayView< 2, T, C2 > &b, MultiArrayView< 2, T, C3 > &r)
 
template<class T , class C1 , class C2 >
TemporaryMatrix< T > pmul (const MultiArrayView< 2, T, C1 > &a, const MultiArrayView< 2, T, C2 > &b)
 
template<class T , class C >
linalg::TemporaryMatrix< T > pow (MultiArrayView< 2, T, C > const &v, T exponent)
 
template<... >
void prepareColumns (...)
 Standardize the columns of a matrix according to given DataPreparationGoals. More...
 
template<... >
void prepareRows (...)
 Standardize the rows of a matrix according to given DataPreparationGoals. More...
 
template<class T , class C1 , class C2 >
void repeatMatrix (MultiArrayView< 2, T, C1 > const &v, MultiArrayView< 2, T, C2 > &r, unsigned int verticalCount, unsigned int horizontalCount)
 
template<class T , class C >
TemporaryMatrix< T > repeatMatrix (MultiArrayView< 2, T, C > const &v, unsigned int verticalCount, unsigned int horizontalCount)
 
template<class T , class C >
linalg::TemporaryMatrix< T > round (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C >
MultiArrayIndex rowCount (const MultiArrayView< 2, T, C > &x)
 
template<... >
void rowStatistics (...)
 
template<class T , class C >
MultiArrayView< 2, T, C > rowVector (MultiArrayView< 2, T, C > const &m, MultiArrayIndex d)
 
template<class T , class C >
MultiArrayView< 2, T, C > rowVector (MultiArrayView< 2, T, C > const &m, MultiArrayShape< 2 >::type first, MultiArrayIndex end)
 
template<class T , class C1 , class C2 >
void sdiv (const MultiArrayView< 2, T, C1 > &a, T b, MultiArrayView< 2, T, C2 > &r)
 
template<class T , class C >
linalg::TemporaryMatrix< T > sign (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C >
linalg::TemporaryMatrix< T > sin (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C1 , class C2 >
void smul (const MultiArrayView< 2, T, C1 > &a, T b, MultiArrayView< 2, T, C2 > &r)
 
template<class T , class C2 , class C3 >
void smul (T a, const MultiArrayView< 2, T, C2 > &b, MultiArrayView< 2, T, C3 > &r)
 
template<class T , class C >
linalg::TemporaryMatrix< T > sq (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C >
linalg::TemporaryMatrix< T > sqrt (MultiArrayView< 2, T, C > const &v)
 
template<class T , class ALLOC >
Matrix< T, ALLLOC >
::SquaredNormType 
squaredNorm (const Matrix< T, ALLLOC > &a)
 
template<class T , class C1 , class C2 , class C3 >
void sub (const MultiArrayView< 2, T, C1 > &a, const MultiArrayView< 2, T, C2 > &b, MultiArrayView< 2, T, C3 > &r)
 
template<class T , class C >
MultiArrayView< 2, T, C > subVector (MultiArrayView< 2, T, C > const &m, int first, int end)
 
template<class T , class C >
linalg::TemporaryMatrix< T > tan (MultiArrayView< 2, T, C > const &v)
 
template<class T , class C >
NumericTraits< T >::Promote trace (MultiArrayView< 2, T, C > const &m)
 
template<class T , class C1 , class C2 >
void transpose (const MultiArrayView< 2, T, C1 > &v, MultiArrayView< 2, T, C2 > &r)
 
template<class T , class C >
MultiArrayView< 2, T,
StridedArrayTag > 
transpose (MultiArrayView< 2, T, C > const &v)
 

Detailed Description

Basic matrix algebra, element-wise mathematical functions, row and columns statistics, data normalization etc.

Function Documentation

MultiArrayIndex rowCount ( const MultiArrayView< 2, T, C > &  x)

Number of rows of a matrix represented as a MultiArrayView<2, ...>

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

MultiArrayIndex columnCount ( const MultiArrayView< 2, T, C > &  x)

Number of columns of a matrix represented as a MultiArrayView<2, ...>

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

MultiArrayView< 2, T, C > rowVector ( MultiArrayView< 2, T, C > const &  m,
MultiArrayIndex  d 
)

Create a row vector view for row d of the matrix m

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

MultiArrayView<2, T, C> vigra::linalg::rowVector ( MultiArrayView< 2, T, C > const &  m,
MultiArrayShape< 2 >::type  first,
MultiArrayIndex  end 
)

Create a row vector view of the matrix m starting at element first and ranging to column end (non-inclusive).

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

MultiArrayView< 2, T, C > columnVector ( MultiArrayView< 2, T, C > const &  m,
MultiArrayIndex  d 
)

Create a column vector view for column d of the matrix m

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

MultiArrayView<2, T, C> vigra::linalg::columnVector ( MultiArrayView< 2, T, C > const &  m,
MultiArrayShape< 2 >::type  first,
int  end 
)

Create a column vector view of the matrix m starting at element first and ranging to row end (non-inclusive).

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

MultiArrayView<2, T, C> vigra::linalg::subVector ( MultiArrayView< 2, T, C > const &  m,
int  first,
int  end 
)

Create a sub vector view of the vector m starting at element first and ranging to row end (non-inclusive).

Note: This function may only be called when either rowCount(m) == 1 or columnCount(m) == 1, i.e. when m really represents a vector. Otherwise, a PreconditionViolation exception is raised.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

bool isSymmetric ( MultiArrayView< 2, T, C > const &  m)

Check whether matrix m is symmetric.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

NumericTraits<T>::Promote vigra::linalg::trace ( MultiArrayView< 2, T, C > const &  m)

Compute the trace of a square matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

Matrix<T, ALLLOC>::SquaredNormType vigra::linalg::squaredNorm ( const Matrix< T, ALLLOC > &  a)

calculate the squared Frobenius norm of a matrix. Equal to the sum of squares of the matrix elements.

#include <vigra/matrix.hxx> Namespace: vigra

Matrix<T, ALLLOC>::NormType vigra::linalg::norm ( const Matrix< T, ALLLOC > &  a)

calculate the Frobenius norm of a matrix. Equal to the root of the sum of squares of the matrix elements.

#include <vigra/matrix.hxx> Namespace: vigra

void vigra::linalg::identityMatrix ( MultiArrayView< 2, T, C > &  r)

initialize the given square matrix as an identity matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

TemporaryMatrix<T> vigra::linalg::identityMatrix ( MultiArrayIndex  size)

create an identity matrix of the given size. Usage:

vigra::Matrix<double> m = vigra::identityMatrix<double>(size);

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

TemporaryMatrix<T> vigra::linalg::ones ( MultiArrayIndex  rows,
MultiArrayIndex  cols 
)

create matrix of ones of the given size. Usage:

vigra::Matrix<double> m = vigra::ones<double>(rows, cols);

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

void vigra::linalg::diagonalMatrix ( MultiArrayView< 2, T, C1 > const &  v,
MultiArrayView< 2, T, C2 > &  r 
)

make a diagonal matrix from a vector. The vector is given as matrix v, which must either have a single row or column. The result is written into the square matrix r.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

TemporaryMatrix<T> vigra::linalg::diagonalMatrix ( MultiArrayView< 2, T, C > const &  v)

create a diagonal matrix from a vector. The vector is given as matrix v, which must either have a single row or column. The result is returned as a temporary matrix. Usage:

vigra::Matrix<double> v(1, len);
v = ...;
vigra::Matrix<double> m = diagonalMatrix(v);

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

void transpose ( const MultiArrayView< 2, T, C1 > &  v,
MultiArrayView< 2, T, C2 > &  r 
)

transpose matrix v. The result is written into r which must have the correct (i.e. transposed) shape.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

Examples:
nnlsq.cxx.
MultiArrayView<2, T, StridedArrayTag> vigra::linalg::transpose ( MultiArrayView< 2, T, C > const &  v)

create the transpose of matrix v. This does not copy any data, but only creates a transposed view to the original matrix. A copy is only made when the transposed view is assigned to another matrix. Usage:

vigra::Matrix<double> v(rows, cols);
v = ...;
vigra::Matrix<double> m = transpose(v);

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

TemporaryMatrix<T> vigra::linalg::joinVertically ( const MultiArrayView< 2, T, C1 > &  a,
const MultiArrayView< 2, T, C2 > &  b 
)

Create new matrix by concatenating two matrices a and b vertically, i.e. on top of each other. The two matrices must have the same number of columns. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::joinHorizontally ( const MultiArrayView< 2, T, C1 > &  a,
const MultiArrayView< 2, T, C2 > &  b 
)

Create new matrix by concatenating two matrices a and b horizontally, i.e. side by side. The two matrices must have the same number of rows. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

void vigra::linalg::repeatMatrix ( MultiArrayView< 2, T, C1 > const &  v,
MultiArrayView< 2, T, C2 > &  r,
unsigned int  verticalCount,
unsigned int  horizontalCount 
)

Initialize a matrix with repeated copies of a given matrix.

Matrix r will consist of verticalCount downward repetitions of v, and horizontalCount side-by-side repetitions. When v has size m by n, r must have size (m*verticalCount) by (n*horizontalCount).

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::repeatMatrix ( MultiArrayView< 2, T, C > const &  v,
unsigned int  verticalCount,
unsigned int  horizontalCount 
)

Create a new matrix by repeating a given matrix.

The resulting matrix r will consist of verticalCount downward repetitions of v, and horizontalCount side-by-side repetitions, i.e. it will be of size (m*verticalCount) by (n*horizontalCount) when v has size m by n. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

void vigra::linalg::add ( const MultiArrayView< 2, T, C1 > &  a,
const MultiArrayView< 2, T, C2 > &  b,
MultiArrayView< 2, T, C3 > &  r 
)

add matrices a and b. The result is written into r. All three matrices must have the same shape.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::operator+ ( const MultiArrayView< 2, T, C1 > &  a,
const MultiArrayView< 2, T, C2 > &  b 
)

add matrices a and b. The two matrices must have the same shape. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::operator+ ( const MultiArrayView< 2, T, C > &  a,
b 
)

add scalar b to every element of the matrix a. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::operator+ ( a,
const MultiArrayView< 2, T, C > &  b 
)

add scalar a to every element of the matrix b. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

void vigra::linalg::sub ( const MultiArrayView< 2, T, C1 > &  a,
const MultiArrayView< 2, T, C2 > &  b,
MultiArrayView< 2, T, C3 > &  r 
)

subtract matrix b from a. The result is written into r. All three matrices must have the same shape.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::operator- ( const MultiArrayView< 2, T, C1 > &  a,
const MultiArrayView< 2, T, C2 > &  b 
)

subtract matrix b from a. The two matrices must have the same shape. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::operator- ( const MultiArrayView< 2, T, C > &  a)

negate matrix a. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::operator- ( const MultiArrayView< 2, T, C > &  a,
b 
)

subtract scalar b from every element of the matrix a. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::operator- ( a,
const MultiArrayView< 2, T, C > &  b 
)

subtract every element of the matrix b from scalar a. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

NormTraits<T>::SquaredNormType vigra::linalg::dot ( const MultiArrayView< 2, T, C1 > &  x,
const MultiArrayView< 2, T, C2 > &  y 
)

calculate the inner product of two matrices representing vectors. Typically, matrix x has a single row, and matrix y has a single column, and the other dimensions match. In addition, this function handles the cases when either or both of the two inputs are transposed (e.g. it can compute the dot product of two column vectors). A PreconditionViolation exception is thrown when the shape conditions are violated.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

NormTraits<T>::SquaredNormType vigra::linalg::dot ( const MultiArrayView< 1, T, C1 > &  x,
const MultiArrayView< 1, T, C2 > &  y 
)

calculate the inner product of two vectors. The vector lengths must match.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

void vigra::linalg::cross ( const MultiArrayView< 1, T, C1 > &  x,
const MultiArrayView< 1, T, C2 > &  y,
MultiArrayView< 1, T, C3 > &  r 
)

calculate the cross product of two vectors of length 3. The result is written into r.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

void vigra::linalg::cross ( const MultiArrayView< 2, T, C1 > &  x,
const MultiArrayView< 2, T, C2 > &  y,
MultiArrayView< 2, T, C3 > &  r 
)

calculate the cross product of two matrices representing vectors. That is, x, y, and r must have a single column of length 3. The result is written into r.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

TemporaryMatrix<T> vigra::linalg::cross ( const MultiArrayView< 2, T, C1 > &  x,
const MultiArrayView< 2, T, C2 > &  y 
)

calculate the cross product of two matrices representing vectors. That is, x, and y must have a single column of length 3. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

void vigra::linalg::outer ( const MultiArrayView< 2, T, C1 > &  x,
const MultiArrayView< 2, T, C2 > &  y,
MultiArrayView< 2, T, C3 > &  r 
)

calculate the outer product of two matrices representing vectors. That is, matrix x must have a single column, and matrix y must have a single row, and the other dimensions must match. The result is written into r.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

TemporaryMatrix<T> vigra::linalg::outer ( const MultiArrayView< 2, T, C1 > &  x,
const MultiArrayView< 2, T, C2 > &  y 
)

calculate the outer product of two matrices representing vectors. That is, matrix x must have a single column, and matrix y must have a single row, and the other dimensions must match. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

TemporaryMatrix<T> vigra::linalg::outer ( const MultiArrayView< 2, T, C > &  x)

calculate the outer product of a matrix (representing a vector) with itself. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

TemporaryMatrix<T> vigra::linalg::outer ( const TinyVector< T, N > &  x)

calculate the outer product of a TinyVector with itself. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

void vigra::linalg::smul ( const MultiArrayView< 2, T, C1 > &  a,
b,
MultiArrayView< 2, T, C2 > &  r 
)

multiply matrix a with scalar b. The result is written into r. a and r must have the same shape.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

void vigra::linalg::smul ( a,
const MultiArrayView< 2, T, C2 > &  b,
MultiArrayView< 2, T, C3 > &  r 
)

multiply scalar a with matrix b. The result is written into r. b and r must have the same shape.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

void vigra::linalg::mmul ( const MultiArrayView< 2, T, C1 > &  a,
const MultiArrayView< 2, T, C2 > &  b,
MultiArrayView< 2, T, C3 > &  r 
)

perform matrix multiplication of matrices a and b. The result is written into r. The three matrices must have matching shapes.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::mmul ( const MultiArrayView< 2, T, C1 > &  a,
const MultiArrayView< 2, T, C2 > &  b 
)

perform matrix multiplication of matrices a and b. a and b must have matching shapes. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

void vigra::linalg::pmul ( const MultiArrayView< 2, T, C1 > &  a,
const MultiArrayView< 2, T, C2 > &  b,
MultiArrayView< 2, T, C3 > &  r 
)

multiply two matrices a and b pointwise. The result is written into r. All three matrices must have the same shape.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::pmul ( const MultiArrayView< 2, T, C1 > &  a,
const MultiArrayView< 2, T, C2 > &  b 
)

multiply matrices a and b pointwise. a and b must have matching shapes. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::operator* ( const MultiArrayView< 2, T, C > &  a,
PointWise< U >  b 
)

multiply matrices a and b pointwise. a and b must have matching shapes. The result is returned as a temporary matrix.

Usage:

Matrix<double> a(m,n), b(m,n);
Matrix<double> c = a * pointWise(b);
// is equivalent to
// Matrix<double> c = pmul(a, b);

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::operator* ( const MultiArrayView< 2, T, C > &  a,
b 
)

multiply matrix a with scalar b. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::operator* ( a,
const MultiArrayView< 2, T, C > &  b 
)

multiply scalar a with matrix b. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TinyVector<T, N> vigra::linalg::operator* ( const Matrix< T, A > &  a,
const TinyVectorBase< T, N, DATA, DERIVED > &  b 
)

multiply matrix a with TinyVector b. a must be of size N x N. Vector b and the result vector are interpreted as column vectors.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TinyVector<T, N> vigra::linalg::operator* ( const TinyVectorBase< T, N, DATA, DERIVED > &  a,
const Matrix< T, A > &  b 
)

multiply TinyVector a with matrix b. b must be of size N x N. Vector a and the result vector are interpreted as row vectors.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::operator* ( const MultiArrayView< 2, T, C1 > &  a,
const MultiArrayView< 2, T, C2 > &  b 
)

perform matrix multiplication of matrices a and b. a and b must have matching shapes. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

void vigra::linalg::sdiv ( const MultiArrayView< 2, T, C1 > &  a,
b,
MultiArrayView< 2, T, C2 > &  r 
)

divide matrix a by scalar b. The result is written into r. a and r must have the same shape.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

void vigra::linalg::pdiv ( const MultiArrayView< 2, T, C1 > &  a,
const MultiArrayView< 2, T, C2 > &  b,
MultiArrayView< 2, T, C3 > &  r 
)

divide two matrices a and b pointwise. The result is written into r. All three matrices must have the same shape.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::pdiv ( const MultiArrayView< 2, T, C1 > &  a,
const MultiArrayView< 2, T, C2 > &  b 
)

divide matrices a and b pointwise. a and b must have matching shapes. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::operator/ ( const MultiArrayView< 2, T, C > &  a,
PointWise< U >  b 
)

divide matrices a and b pointwise. a and b must have matching shapes. The result is returned as a temporary matrix.

Usage:

Matrix<double> a(m,n), b(m,n);
Matrix<double> c = a / pointWise(b);
// is equivalent to
// Matrix<double> c = pdiv(a, b);

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::operator/ ( const MultiArrayView< 2, T, C > &  a,
b 
)

divide matrix a by scalar b. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

TemporaryMatrix<T> vigra::linalg::operator/ ( a,
const MultiArrayView< 2, T, C > &  b 
)

Create a matrix whose elements are the quotients between scalar a and matrix b. The result is returned as a temporary matrix.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: vigra::linalg

int vigra::linalg::argMin ( MultiArrayView< 2, T, C > const &  a)

Find the index of the minimum element in a matrix.

The function returns the index in column-major scan-order sense, i.e. according to the order used by MultiArrayView::operator[]. If the matrix is actually a vector, this is just the row or columns index. In case of a truly 2-dimensional matrix, the index can be converted to an index pair by calling MultiArrayView::scanOrderIndexToCoordinate()

Required Interface:

bool f = a[0] < NumericTraits<T>::max();

#include <vigra/matrix.hxx>
Namespace: vigra

int vigra::linalg::argMax ( MultiArrayView< 2, T, C > const &  a)

Find the index of the maximum element in a matrix.

The function returns the index in column-major scan-order sense, i.e. according to the order used by MultiArrayView::operator[]. If the matrix is actually a vector, this is just the row or columns index. In case of a truly 2-dimensional matrix, the index can be converted to an index pair by calling MultiArrayView::scanOrderIndexToCoordinate()

Required Interface:

bool f = NumericTraits<T>::min() < a[0];

#include <vigra/matrix.hxx>
Namespace: vigra

int vigra::linalg::argMinIf ( MultiArrayView< 2, T, C > const &  a,
UnaryFunctor  condition 
)

Find the index of the minimum element in a matrix subject to a condition.

The function returns -1 if no element conforms to condition. Otherwise, the index of the maximum element is returned in column-major scan-order sense, i.e. according to the order used by MultiArrayView::operator[]. If the matrix is actually a vector, this is just the row or columns index. In case of a truly 2-dimensional matrix, the index can be converted to an index pair by calling MultiArrayView::scanOrderIndexToCoordinate()

Required Interface:

bool c = condition(a[0]);
bool f = a[0] < NumericTraits<T>::max();

#include <vigra/matrix.hxx>
Namespace: vigra

int vigra::linalg::argMaxIf ( MultiArrayView< 2, T, C > const &  a,
UnaryFunctor  condition 
)

Find the index of the maximum element in a matrix subject to a condition.

The function returns -1 if no element conforms to condition. Otherwise, the index of the maximum element is returned in column-major scan-order sense, i.e. according to the order used by MultiArrayView::operator[]. If the matrix is actually a vector, this is just the row or columns index. In case of a truly 2-dimensional matrix, the index can be converted to an index pair by calling MultiArrayView::scanOrderIndexToCoordinate()

Required Interface:

bool c = condition(a[0]);
bool f = NumericTraits<T>::min() < a[0];

#include <vigra/matrix.hxx>
Namespace: vigra

linalg::TemporaryMatrix<T> vigra::linalg::pow ( MultiArrayView< 2, T, C > const &  v,
exponent 
)

Matrix point-wise power.

linalg::TemporaryMatrix<T> vigra::linalg::sqrt ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise sqrt.

linalg::TemporaryMatrix<T> vigra::linalg::exp ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise exp.

linalg::TemporaryMatrix<T> vigra::linalg::log ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise log.

linalg::TemporaryMatrix<T> vigra::linalg::log10 ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise log10.

linalg::TemporaryMatrix<T> vigra::linalg::sin ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise sin.

linalg::TemporaryMatrix<T> vigra::linalg::asin ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise asin.

linalg::TemporaryMatrix<T> vigra::linalg::cos ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise cos.

linalg::TemporaryMatrix<T> vigra::linalg::acos ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise acos.

linalg::TemporaryMatrix<T> vigra::linalg::tan ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise tan.

linalg::TemporaryMatrix<T> vigra::linalg::atan ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise atan.

linalg::TemporaryMatrix<T> vigra::linalg::round ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise round.

linalg::TemporaryMatrix<T> vigra::linalg::floor ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise floor.

linalg::TemporaryMatrix<T> vigra::linalg::ceil ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise ceil.

linalg::TemporaryMatrix<T> vigra::linalg::abs ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise abs.

linalg::TemporaryMatrix<T> vigra::linalg::sq ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise square.

linalg::TemporaryMatrix<T> vigra::linalg::sign ( MultiArrayView< 2, T, C > const &  v)

Matrix point-wise sign.

ostream& std::operator<< ( ostream &  s,
const vigra::MultiArrayView< 2, T, C > &  m 
)

print a matrix m to the stream s.

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespace: std

void vigra::linalg::columnStatistics (   ...)

Compute statistics of every column of matrix A.

The result matrices must be row vectors with as many columns as A.

Declarations:

compute only the mean:

namespace vigra { namespace linalg {
template <class T1, class C1, class T2, class C2>
void
columnStatistics(MultiArrayView<2, T1, C1> const & A,
MultiArrayView<2, T2, C2> & mean);
} }

compute mean and standard deviation:

namespace vigra { namespace linalg {
template <class T1, class C1, class T2, class C2, class T3, class C3>
void
columnStatistics(MultiArrayView<2, T1, C1> const & A,
MultiArrayView<2, T2, C2> & mean,
MultiArrayView<2, T3, C3> & stdDev);
} }

compute mean, standard deviation, and norm:

namespace vigra { namespace linalg {
template <class T1, class C1, class T2, class C2, class T3, class C3, class T4, class C4>
void
columnStatistics(MultiArrayView<2, T1, C1> const & A,
MultiArrayView<2, T2, C2> & mean,
MultiArrayView<2, T3, C3> & stdDev,
MultiArrayView<2, T4, C4> & norm);
} }

Usage:

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

Matrix A(rows, columns);
.. // fill A
Matrix columnMean(1, columns), columnStdDev(1, columns), columnNorm(1, columns);
columnStatistics(A, columnMean, columnStdDev, columnNorm);
void vigra::linalg::rowStatistics (   ...)

Compute statistics of every row of matrix A.

The result matrices must be column vectors with as many rows as A.

Declarations:

compute only the mean:

namespace vigra { namespace linalg {
template <class T1, class C1, class T2, class C2>
void
rowStatistics(MultiArrayView<2, T1, C1> const & A,
MultiArrayView<2, T2, C2> & mean);
} }

compute mean and standard deviation:

namespace vigra { namespace linalg {
template <class T1, class C1, class T2, class C2, class T3, class C3>
void
rowStatistics(MultiArrayView<2, T1, C1> const & A,
MultiArrayView<2, T2, C2> & mean,
MultiArrayView<2, T3, C3> & stdDev);
} }

compute mean, standard deviation, and norm:

namespace vigra { namespace linalg {
template <class T1, class C1, class T2, class C2, class T3, class C3, class T4, class C4>
void
rowStatistics(MultiArrayView<2, T1, C1> const & A,
MultiArrayView<2, T2, C2> & mean,
MultiArrayView<2, T3, C3> & stdDev,
MultiArrayView<2, T4, C4> & norm);
} }

Usage:

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

Matrix A(rows, columns);
.. // fill A
Matrix rowMean(rows, 1), rowStdDev(rows, 1), rowNorm(rows, 1);
rowStatistics(a, rowMean, rowStdDev, rowNorm);
void vigra::linalg::covarianceMatrixOfColumns ( MultiArrayView< 2, T1, C1 > const &  features,
MultiArrayView< 2, T2, C2 > &  covariance 
)

Compute the covariance matrix between the columns of a matrix features.

The result matrix covariance must by a square matrix with as many rows and columns as the number of columns in matrix features.

#include <vigra/matrix.hxx>
Namespace: vigra

TemporaryMatrix<T> vigra::linalg::covarianceMatrixOfColumns ( MultiArrayView< 2, T, C > const &  features)

Compute the covariance matrix between the columns of a matrix features.

The result is returned as a square temporary matrix with as many rows and columns as the number of columns in matrix features.

#include <vigra/matrix.hxx>
Namespace: vigra

void vigra::linalg::covarianceMatrixOfRows ( MultiArrayView< 2, T1, C1 > const &  features,
MultiArrayView< 2, T2, C2 > &  covariance 
)

Compute the covariance matrix between the rows of a matrix features.

The result matrix covariance must by a square matrix with as many rows and columns as the number of rows in matrix features.

#include <vigra/matrix.hxx>
Namespace: vigra

TemporaryMatrix<T> vigra::linalg::covarianceMatrixOfRows ( MultiArrayView< 2, T, C > const &  features)

Compute the covariance matrix between the rows of a matrix features.

The result is returned as a square temporary matrix with as many rows and columns as the number of rows in matrix features.

#include <vigra/matrix.hxx>
Namespace: vigra

void vigra::linalg::prepareColumns (   ...)

Standardize the columns of a matrix according to given DataPreparationGoals.

For every column of the matrix A, this function computes mean, standard deviation, and norm. It then applies a linear transformation to the values of the column according to these statistics and the given DataPreparationGoals. The result is returned in matrix res which must have the same size as A. Optionally, the transformation applied can also be returned in the matrices offset and scaling (see below for an example how these matrices can be used to standardize more data according to the same transformation).

The following DataPreparationGoals are supported:

ZeroMean
Subtract the column mean form every column if the values in the column are not constant. Do nothing in a constant column.
UnitSum
Scale the columns so that the their sum is one if the sum was initially non-zero. Do nothing in a zero-sum column.
UnitVariance
Divide by the column standard deviation if the values in the column are not constant. Do nothing in a constant column.
UnitNorm
Divide by the column norm if it is non-zero.
ZeroMean | UnitVariance
First subtract the mean and then divide by the standard deviation, unless the column is constant (in which case the column remains unchanged).
ZeroMean | UnitNorm
If the column is non-constant, subtract the mean. Then divide by the norm of the result if the norm is non-zero.

Declarations:

Standardize the matrix and return the parameters of the linear transformation. The matrices offset and scaling must be row vectors with as many columns as A.

namespace vigra { namespace linalg {
template <class T, class C1, class C2, class C3, class C4>
void
prepareColumns(MultiArrayView<2, T, C1> const & A,
MultiArrayView<2, T, C2> & res,
MultiArrayView<2, T, C3> & offset,
MultiArrayView<2, T, C4> & scaling,
DataPreparationGoals goals = ZeroMean | UnitVariance);
} }

Only standardize the matrix.

namespace vigra { namespace linalg {
template <class T, class C1, class C2>
void
prepareColumns(MultiArrayView<2, T, C1> const & A,
MultiArrayView<2, T, C2> & res,
DataPreparationGoals goals = ZeroMean | UnitVariance);
} }

Usage:

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

Matrix A(rows, columns);
.. // fill A
Matrix standardizedA(rows, columns), offset(1, columns), scaling(1, columns);
prepareColumns(A, standardizedA, offset, scaling, ZeroMean | UnitNorm);
// use offset and scaling to prepare additional data according to the same transformation
Matrix newData(nrows, columns);
Matrix standardizedNewData = (newData - repeatMatrix(offset, nrows, 1)) * pointWise(repeatMatrix(scaling, nrows, 1));
void vigra::linalg::prepareRows (   ...)

Standardize the rows of a matrix according to given DataPreparationGoals.

This algorithm works in the same way as prepareColumns() (see there for detailed documentation), but is applied to the rows of the matrix A instead. Accordingly, the matrices holding the parameters of the linear transformation must be column vectors with as many rows as A.

Declarations:

Standardize the matrix and return the parameters of the linear transformation. The matrices offset and scaling must be column vectors with as many rows as A.

namespace vigra { namespace linalg {
template <class T, class C1, class C2, class C3, class C4>
void
prepareRows(MultiArrayView<2, T, C1> const & A,
MultiArrayView<2, T, C2> & res,
MultiArrayView<2, T, C3> & offset,
MultiArrayView<2, T, C4> & scaling,
DataPreparationGoals goals = ZeroMean | UnitVariance)´ } };
} }

Only standardize the matrix.

namespace vigra { namespace linalg {
template <class T, class C1, class C2>
void
prepareRows(MultiArrayView<2, T, C1> const & A,
MultiArrayView<2, T, C2> & res,
DataPreparationGoals goals = ZeroMean | UnitVariance);
} }

Usage:

#include <vigra/matrix.hxx> or
#include <vigra/linear_algebra.hxx>
Namespaces: vigra and vigra::linalg

Matrix A(rows, columns);
.. // fill A
Matrix standardizedA(rows, columns), offset(rows, 1), scaling(rows, 1);
prepareRows(A, standardizedA, offset, scaling, ZeroMean | UnitNorm);
// use offset and scaling to prepare additional data according to the same transformation
Matrix newData(rows, ncolumns);
Matrix standardizedNewData = (newData - repeatMatrix(offset, 1, ncolumns)) * pointWise(repeatMatrix(scaling, 1, ncolumns));

© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de)
Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany

html generated using doxygen and Python
vigra 1.11.1 (Fri May 19 2017)