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/* Copyright (c) 2008-2022 the MRtrix3 contributors.
*
* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
* file, You can obtain one at http://mozilla.org/MPL/2.0/.
*
* Covered Software is provided under this License on an "as is"
* basis, without warranty of any kind, either expressed, implied, or
* statutory, including, without limitation, warranties that the
* Covered Software is free of defects, merchantable, fit for a
* particular purpose or non-infringing.
* See the Mozilla Public License v. 2.0 for more details.
*
* For more details, see http://www.mrtrix.org/.
*/
#ifndef __algo_histogram_h__
#define __algo_histogram_h__
#include <cmath>
#include "image_helpers.h"
#include "types.h"
#include "adapter/replicate.h"
#include "algo/loop.h"
namespace MR
{
namespace Algo
{
namespace Histogram
{
extern const App::OptionGroup Options;
class Calibrator
{ MEMALIGN (Calibrator)
public:
Calibrator (const size_t number_of_bins = 0, const bool ignorezero = false) :
min (std::numeric_limits<default_type>::infinity()),
max (-std::numeric_limits<default_type>::infinity()),
bin_width (NaN),
num_bins (number_of_bins),
ignore_zero (ignorezero) { }
template <typename value_type>
typename std::enable_if<std::is_arithmetic<value_type>::value, bool>::type operator() (const value_type val) {
if (std::isfinite(val) && !(ignore_zero && val == 0.0)) {
min = std::min (min, default_type(val));
max = std::max (max, default_type(val));
if (!num_bins)
data.push_back (default_type(val));
}
return true;
}
template <class T>
FORCE_INLINE typename std::enable_if<!std::is_arithmetic<T>::value, bool>::type operator() (const T& val) {
return (*this) (typename T::value_type (val));
}
void from_file (const std::string&);
void finalize (const size_t num_volumes, const bool is_integer);
default_type get_bin_centre (const size_t i) const {
assert (i < num_bins);
return get_min() + (get_bin_width() * (i + 0.5));
}
default_type get_bin_width() const { return bin_width; }
size_t get_num_bins() const { return num_bins; }
default_type get_min() const { return min; }
default_type get_max() const { return max; }
bool get_ignore_zero() const { return ignore_zero; }
private:
default_type min, max, bin_width;
size_t num_bins;
const bool ignore_zero;
vector<default_type> data;
default_type get_iqr();
};
class Data
{ MEMALIGN (Data)
public:
using vector_type = Eigen::Array<size_t, Eigen::Dynamic, 1>;
using cdf_type = Eigen::Array<default_type, Eigen::Dynamic, 1>;
Data (const Calibrator& calibrate) :
info (calibrate),
list (vector_type::Zero (info.get_num_bins())) { }
template <typename value_type>
bool operator() (const value_type val) {
if (std::isfinite(val) && !(info.get_ignore_zero() && val == 0.0)) {
const size_t pos = bin (val);
if (pos != size_t(list.size()))
++list[pos];
}
return true;
}
template <typename value_type>
size_t bin (const value_type val) const {
size_t pos = std::floor ((val - info.get_min()) / info.get_bin_width());
if (pos > size_t(list.size())) return size();
return pos;
}
size_t operator[] (const size_t index) const {
assert (index < size_t(list.size()));
return list[index];
}
size_t size() const {
return list.size();
}
const Calibrator& get_calibration() const { return info; }
const vector_type& pdf() const { return list; }
cdf_type cdf() const;
default_type first_min () const;
default_type entropy () const;
protected:
const Calibrator info;
vector_type list;
friend class Kernel;
};
// Convenience functions for calibrating (& histograming) basic input images
template <class ImageType>
void calibrate (Calibrator& result, ImageType& image)
{
for (auto l = Loop(image) (image); l; ++l)
result (image.value());
result.finalize (image.ndim() > 3 ? image.size(3) : 1, std::is_integral<typename ImageType::value_type>::value);
}
template <class ImageType, class MaskType>
void calibrate (Calibrator& result, ImageType& image, MaskType& mask)
{
if (!mask.valid()) {
calibrate (result, image);
return;
}
if (!dimensions_match (image, mask, 0, 3))
throw Exception ("Image and mask for histogram calibration do not match");
Adapter::Replicate<MaskType> mask_replicate (mask, image);
for (auto l = Loop(image) (image, mask_replicate); l; ++l) {
if (mask_replicate.value())
result (image.value());
}
result.finalize (image.ndim() > 3 ? image.size(3) : 1, std::is_integral<typename ImageType::value_type>::value);
}
template <class ImageType>
Data generate (ImageType& image, const size_t num_bins, const bool ignore_zero = false)
{
Calibrator calibrator (num_bins, ignore_zero);
calibrate (calibrator, image);
return generate (calibrator, image);
}
template <class ImageType, class MaskType>
Data generate (ImageType& image, MaskType& mask, const size_t num_bins, const bool ignore_zero = false)
{
Calibrator calibrator (num_bins, ignore_zero);
calibrate (calibrator, image, mask);
return generate (calibrator, image, mask);
}
template <class ImageType>
Data generate (const Calibrator& calibrator, ImageType& image)
{
Data result (calibrator);
for (auto l = Loop(image) (image); l; ++l)
result (typename ImageType::value_type (image.value()));
return result;
}
template <class ImageType, class MaskType>
Data generate (const Calibrator& calibrator, ImageType& image, MaskType& mask)
{
if (!mask.valid())
return generate (calibrator, image);
if (!dimensions_match (image, mask, 0, 3))
throw Exception ("Image and mask for histogram generation do not match");
Data result (calibrator);
Adapter::Replicate<MaskType> mask_replicate (mask, image);
for (auto l = Loop(image) (image, mask_replicate); l; ++l) {
if (mask_replicate.value())
result (typename ImageType::value_type (image.value()));
}
return result;
}
class Matcher
{ MEMALIGN (Matcher)
using vector_type = Eigen::Array<default_type, Eigen::Dynamic, 1>;
public:
Matcher (const Data& input, const Data& target);
default_type operator() (const default_type) const;
private:
const Calibrator calib_input, calib_target;
vector_type mapping;
};
}
}
}
#endif
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