// Copyright (C) 2011  Davis E. King (davis@dlib.net)
#undef DLIB_MATRIx_CONV_ABSTRACT_Hh_
#ifdef DLIB_MATRIx_CONV_ABSTRACT_Hh_

#include "matrix_abstract.h"

namespace dlib
{

// ----------------------------------------------------------------------------------------

const matrix_exp conv (
const matrix_exp& m1,
const matrix_exp& m2
);
/*!
requires
- m1 and m2 both contain elements of the same type
ensures
- returns a matrix R such that:
- R is the convolution of m1 with m2.  In particular, this function is
equivalent to performing the following in matlab: R = conv2(m1,m2).
- R::type == the same type that was in m1 and m2.
- R.nr() == m1.nr()+m2.nr()-1
- R.nc() == m1.nc()+m2.nc()-1
!*/

// ----------------------------------------------------------------------------------------

const matrix_exp xcorr (
const matrix_exp& m1,
const matrix_exp& m2
);
/*!
requires
- m1 and m2 both contain elements of the same type
ensures
- returns a matrix R such that:
- R is the cross-correlation of m1 with m2.  In particular, this
function returns conv(m1,flip(m2)) if the matrices contain real
elements and conv(m1,flip(conj(m2))) if they are complex.
- R::type == the same type that was in m1 and m2.
- R.nr() == m1.nr()+m2.nr()-1
- R.nc() == m1.nc()+m2.nc()-1
!*/

// ----------------------------------------------------------------------------------------

const matrix_exp xcorr_fft (
const matrix_exp& m1,
const matrix_exp& m2
);
/*!
requires
- m1 and m2 both contain elements of the same type
- m1 and m2 contain real or complex values and must be double, float, or long
double valued. (e.g. not integers)
ensures
- This function is identical to xcorr() except that it uses a fast Fourier
transform to do the convolution and is therefore much faster when both m1 and
m2 are large.
!*/

// ----------------------------------------------------------------------------------------

const matrix_exp conv_same (
const matrix_exp& m1,
const matrix_exp& m2
);
/*!
requires
- m1 and m2 both contain elements of the same type
ensures
- returns a matrix R such that:
- R is the convolution of m1 with m2.  In particular, this function is
equivalent to performing the following in matlab: R = conv2(m1,m2,'same').
In particular, this means the result will have the same dimensions as m1 and will
contain the central part of the full convolution.  Therefore, conv_same(m1,m2) is
equivalent to subm(conv(m1,m2), m2.nr()/2, m2.nc()/2, m1.nr(), m1.nc()).
- R::type == the same type that was in m1 and m2.
- R.nr() == m1.nr()
- R.nc() == m1.nc()
!*/

// ----------------------------------------------------------------------------------------

const matrix_exp xcorr_same (
const matrix_exp& m1,
const matrix_exp& m2
);
/*!
requires
- m1 and m2 both contain elements of the same type
ensures
- returns a matrix R such that:
- R is the cross-correlation of m1 with m2.  In particular, this
function returns conv_same(m1,flip(m2)) if the matrices contain real
elements and conv_same(m1,flip(conj(m2))) if they are complex.
- R::type == the same type that was in m1 and m2.
- R.nr() == m1.nr()
- R.nc() == m1.nc()
!*/

// ----------------------------------------------------------------------------------------

const matrix_exp conv_valid (
const matrix_exp& m1,
const matrix_exp& m2
);
/*!
requires
- m1 and m2 both contain elements of the same type
ensures
- returns a matrix R such that:
- R is the convolution of m1 with m2.  In particular, this function is
equivalent to performing the following in matlab: R = conv2(m1,m2,'valid').
In particular, this means only elements of the convolution which don't require
zero padding are included in the result.
- R::type == the same type that was in m1 and m2.
- if (m1 has larger dimensions than m2) then
- R.nr() == m1.nr()-m2.nr()+1
- R.nc() == m1.nc()-m2.nc()+1
- else
- R.nr() == 0
- R.nc() == 0
!*/

// ----------------------------------------------------------------------------------------

const matrix_exp xcorr_valid (
const matrix_exp& m1,
const matrix_exp& m2
);
/*!
requires
- m1 and m2 both contain elements of the same type
ensures
- returns a matrix R such that:
- R is the cross-correlation of m1 with m2.  In particular, this
function returns conv_valid(m1,flip(m2)) if the matrices contain real
elements and conv_valid(m1,flip(conj(m2))) if they are complex.
- R::type == the same type that was in m1 and m2.
- if (m1 has larger dimensions than m2) then
- R.nr() == m1.nr()-m2.nr()+1
- R.nc() == m1.nc()-m2.nc()+1
- else
- R.nr() == 0
- R.nc() == 0
!*/

// ----------------------------------------------------------------------------------------

}

#endif // DLIB_MATRIx_CONV_ABSTRACT_Hh_