/usr/include/sopt/wavelets/indirect.h is in libsopt-dev 2.0.0-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 | #ifndef SOPT_WAVELET_INDIRECT_H
#define SOPT_WAVELET_INDIRECT_H
#include "sopt/config.h"
#include "sopt/types.h"
#include "sopt/wavelets/innards.impl.h"
#include "sopt/wavelets/wavelet_data.h"
// Function inside anonymouns namespace won't appear in library
namespace sopt {
namespace wavelets {
namespace {
//! Single-level 1d indirect transform
//! \param[in] coeffs_: input coefficients
//! \param[out] signal: output with the reconstituted signal
//! \param[in] wavelet: contains wavelet coefficients
template <class T0, class T1>
typename std::enable_if<T1::IsVectorAtCompileTime, void>::type
indirect_transform_impl(Eigen::ArrayBase<T0> const &coeffs, Eigen::ArrayBase<T1> const &signal_,
WaveletData const &wavelet) {
Eigen::ArrayBase<T1> &signal = const_cast<Eigen::ArrayBase<T1> &>(signal_);
assert(coeffs.size() == signal.size());
assert(coeffs.size() % 2 == 0);
up_convolve_sum(signal, coeffs, wavelet.indirect_filter.low_even, wavelet.indirect_filter.low_odd,
wavelet.indirect_filter.high_even, wavelet.indirect_filter.high_odd);
}
//! Single-level 2d indirect transform
//! \param[in] coeffs_: input coefficients
//! \param[out] signal: output with the reconstituted signal
//! \param[in] wavelet: contains wavelet coefficients
template <class T0, class T1>
typename std::enable_if<not T1::IsVectorAtCompileTime, void>::type
indirect_transform_impl(Eigen::ArrayBase<T0> const &coeffs_, Eigen::ArrayBase<T1> const &signal_,
WaveletData const &wavelet) {
Eigen::ArrayBase<T0> &coeffs = const_cast<Eigen::ArrayBase<T0> &>(coeffs_);
Eigen::ArrayBase<T1> &signal = const_cast<Eigen::ArrayBase<T1> &>(signal_);
assert(coeffs.rows() == signal.rows() and coeffs.cols() == signal.cols());
assert(coeffs.rows() % 2 == 0 and coeffs.cols() % 2 == 0);
for(typename T0::Index i(0); i < signal.rows(); ++i)
indirect_transform_impl(coeffs.row(i).transpose(), signal.row(i).transpose(), wavelet);
coeffs = signal;
for(typename T0::Index j(0); j < signal.cols(); ++j)
indirect_transform_impl(coeffs.col(j), signal.col(j), wavelet);
}
}
//! \brief N-levels 1d indirect transform
//! \param[in] coeffs_: input coefficients
//! \param[out] signal: output with the reconstituted signal
//! \param[in] wavelet: contains wavelet coefficients
//! \note The size of the coefficients should a multiple of $2^l$ where $l$ is the number of
//! levels.
template <class T0, class T1>
typename std::enable_if<T1::IsVectorAtCompileTime, void>::type
indirect_transform(Eigen::ArrayBase<T0> const &coeffs, Eigen::ArrayBase<T1> &signal, t_uint levels,
WaveletData const &wavelet) {
if(levels == 0)
return;
assert(coeffs.rows() == signal.rows());
assert(coeffs.cols() == signal.cols());
assert(coeffs.size() % (1u << levels) == 0);
auto input = copy(coeffs);
for(t_uint level(levels - 1); level > 0; --level) {
auto const N = static_cast<t_uint>(signal.size()) >> level;
indirect_transform_impl(input.head(N), signal.head(N), wavelet);
input.head(N) = signal.head(N);
}
indirect_transform_impl(input, signal, wavelet);
}
//! \brief N-levels 2d indirect transform
//! \param[in] coeffs_: input coefficients
//! \param[out] signal: output with the reconstituted signal
//! \param[in] wavelet: contains wavelet coefficients
//! \note The size of the signal and coefficients should a multiple of $2^l$ where $l$ is the
//! number of levels.
template <class T0, class T1>
typename std::enable_if<not T1::IsVectorAtCompileTime, void>::type
indirect_transform(Eigen::ArrayBase<T0> const &coeffs_, Eigen::ArrayBase<T1> const &signal_,
t_uint levels, WaveletData const &wavelet) {
Eigen::ArrayBase<T0> &coeffs = const_cast<Eigen::ArrayBase<T0> &>(coeffs_);
Eigen::ArrayBase<T1> &signal = const_cast<Eigen::ArrayBase<T1> &>(signal_);
assert(coeffs.rows() == signal.rows());
assert(coeffs.cols() == signal.cols());
assert(coeffs.size() % (1u << levels) == 0);
if(levels == 0) {
signal = coeffs_;
return;
}
auto input = copy(coeffs);
for(t_uint level(levels - 1); level > 0; --level) {
auto const Nx = static_cast<t_uint>(signal.rows()) >> level;
auto const Ny = static_cast<t_uint>(signal.cols()) >> level;
indirect_transform_impl(input.topLeftCorner(Nx, Ny), signal.topLeftCorner(Nx, Ny), wavelet);
input.topLeftCorner(Nx, Ny) = signal.topLeftCorner(Nx, Ny);
}
indirect_transform_impl(input, signal, wavelet);
}
//! Indirect 1d and 2d transform
//! \param[in] coeffs_: input coefficients
//! \param[in] wavelet: contains wavelet coefficients
//! \returns the reconstituted signal
//! \note The size of the coefficients should a multiple of $2^l$ where $l$ is the number of
//! levels.
template <class T0>
auto indirect_transform(Eigen::ArrayBase<T0> const &coeffs, t_uint levels,
WaveletData const &wavelet) -> decltype(copy(coeffs)) {
auto result = copy(coeffs);
indirect_transform(coeffs, result, levels, wavelet);
return result;
}
}
}
#endif
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