/*
 *  This file is part of RawTherapee.
 *
 *  Copyright (c) 2004-2010 Gabor Horvath <hgabor@rawtherapee.com>
 *
 *  RawTherapee is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU General Public License as published by
 *  the Free Software Foundation, either version 3 of the License, or
 *  (at your option) any later version.
 *
 *  RawTherapee is distributed in the hope that it will be useful,
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *  GNU General Public License for more details.
 *
 *  You should have received a copy of the GNU General Public License
 *  along with RawTherapee.  If not, see <http://www.gnu.org/licenses/>.
 */
#include "shmap.h"
#include "gauss.h"
#include "rtengine.h"
#include "rt_math.h"
#include "rawimagesource.h"
#undef THREAD_PRIORITY_NORMAL
#include "opthelper.h"

namespace rtengine {

extern const Settings* settings;

SHMap::SHMap (int w, int h, bool multiThread) : W(w), H(h), multiThread(multiThread) {

    map = new float*[H];
    for (int i=0; i<H; i++)
        map[i] = new float[W];

}

SHMap::~SHMap () {

    for (int i=0; i<H; i++)
        delete [] map[i];
    delete [] map;
}

void SHMap::fillLuminance( Imagefloat * img, float **luminance, double lumi[3] ) // fill with luminance
{

#ifdef _OPENMP
#pragma omp parallel for
#endif
    for (int i=0; i<H; i++)
        for (int j=0; j<W; j++) {
            luminance[i][j] = lumi[0]*std::max(img->r(i,j),0.f) + lumi[1]*std::max(img->g(i,j),0.f) + lumi[2]*std::max(img->b(i,j),0.f);
		}
	
}

void SHMap::update (Imagefloat* img, double radius, double lumi[3], bool hq, int skip) {

    if (!hq) {
		fillLuminance( img, map, lumi);

#ifdef _OPENMP
#pragma omp parallel
#endif
{
        AlignedBufferMP<double>* pBuffer = new AlignedBufferMP<double> (max(W,H));
    	gaussHorizontal<float> (map, map, *pBuffer, W, H, radius);
		gaussVertical<float>   (map, map, *pBuffer, W, H, radius);
        delete pBuffer;
}
    }

    else {
		//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
		//experimental dirpyr shmap

		float thresh = (100.f*radius);//1000;

		// set up range function
		// calculate size of Lookup table. That's possible because from a value k for all i>=k rangefn[i] will be exp(-10)
		// So we use this fact and the automatic clip of lut to reduce the size of lut and the number of calculations to fill the lut
		// In past this lut had only integer precision with rangefn[i] = 0 for all i>=k
		// We set the last element to a small epsilon 1e-15 instead of zero to avoid divisions by zero
		const int lutSize = thresh * sqrtf(10.f) + 1;
		thresh *= thresh;
		LUTf rangefn(lutSize);
		for (int i=0; i<lutSize-1; i++) {
			rangefn[i] = xexpf(-min(10.f,(static_cast<float>(i)*i) / thresh ));//*intfactor;
		}
		rangefn[lutSize-1] = 1e-15f;
		
		// We need one temporary buffer
		float ** buffer = allocArray<float> (W, H);
		
		// the final result has to be in map
		// for an even number of levels that means: map => buffer, buffer => map
		// for an odd number of levels that means: buffer => map, map => buffer, buffer => map
		// so let's calculate the number of levels first
		// There are at least two levels
		int numLevels=2;
		int scale=2;
		while (skip*scale<16) {
			scale *= 2;
			numLevels++;
		}

		float ** dirpyrlo[2];
		if(numLevels&1) { // odd number of levels, start with buffer
			dirpyrlo[0] = buffer;
			dirpyrlo[1] = map;
		} else { // even number of levels, start with map
			dirpyrlo[0] = map;
			dirpyrlo[1] = buffer;
		}

		fillLuminance( img, dirpyrlo[0], lumi);

		scale = 1;
		int level=0;
		int indx=0;
		dirpyr_shmap(dirpyrlo[indx], dirpyrlo[1-indx], W, H, rangefn, level, scale );
		scale *= 2;
		level ++;
		indx = 1-indx;
		while (skip*scale<16) {
			dirpyr_shmap(dirpyrlo[indx], dirpyrlo[1-indx], W, H, rangefn, level, scale );
			scale *= 2;
			level ++;
			indx = 1-indx;
		}

		dirpyr_shmap(dirpyrlo[indx], dirpyrlo[1-indx], W, H, rangefn, level, scale );

		freeArray<float>(buffer, H);

		//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
/*
        // anti-alias filtering the result
#ifdef _OPENMP
#pragma omp for
#endif
        for (int i=0; i<H; i++)
            for (int j=0; j<W; j++)
                if (i>0 && j>0 && i<H-1 && j<W-1)
                    map[i][j] = (buffer[i-1][j-1]+buffer[i-1][j]+buffer[i-1][j+1]+buffer[i][j-1]+buffer[i][j]+buffer[i][j+1]+buffer[i+1][j-1]+buffer[i+1][j]+buffer[i+1][j+1])/9;
                else
                    map[i][j] = buffer[i][j];
*/

    }
    // update average, minimum, maximum
    double _avg = 0.0f;	// use double precision to gain precision especially at systems with few cores and big pictures (error for 36 MPixel on single core was about 8% with float)
    min_f = 65535;
    max_f = 0;
#ifdef _OPENMP
#pragma omp parallel
#endif
{
    float _min_f = 65535.0f;
    float _max_f = 0.0f;
    float _val;
#ifdef _OPENMP
#pragma omp for reduction(+:_avg) schedule(dynamic,16) nowait
#endif
    for (int i=0; i<H; i++)
        for (int j=0; j<W; j++) {
            _val = map[i][j];
            if (_val < _min_f)
                _min_f = _val;
            if (_val > _max_f)
                _max_f = _val;
            _avg += _val;
        }
#ifdef _OPENMP
#pragma omp critical
#endif
{
	if(_min_f < min_f )
		min_f = _min_f;
	if(_max_f > max_f )
		max_f = _max_f;
}
}
    _avg /= ((H)*(W));
    avg = _avg;

}

void SHMap::forceStat (float max_, float min_, float avg_) {

    max_f = max_;
    min_f = min_;
    avg = avg_;
}

SSEFUNCTION void SHMap::dirpyr_shmap(float ** data_fine, float ** data_coarse, int width, int height, LUTf & rangefn, int level, int scale)
{
	//scale is spacing of directional averaging weights

	//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	// calculate weights, compute directionally weighted average

	int scalewin, halfwin;

	if(level < 2) {
		halfwin = 1;
		scalewin = halfwin*scale;

#ifdef _OPENMP
#pragma omp parallel
#endif
{
#if defined( __SSE2__ ) && defined( __x86_64__ )
	__m128 dirwtv, valv, normv, dftemp1v, dftemp2v;
#endif // __SSE2__
	int j;
#ifdef _OPENMP
#pragma omp for
#endif
	for(int i = 0; i < height; i++) {
		float dirwt;
		for(j = 0; j < scalewin; j++) {
			float val=0.f;
			float norm=0.f;
			for(int inbr=max(i-scalewin,i%scale); inbr<=min(i+scalewin, height-1); inbr+=scale) {
				for (int jnbr=j%scale; jnbr<=j+scalewin; jnbr+=scale) {
					dirwt = ( rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
					val += dirwt*data_fine[inbr][jnbr];
					norm += dirwt;
				}
			}
			data_coarse[i][j] = val/norm; // low pass filter
		}
#if defined( __SSE2__ ) && defined( __x86_64__ )
		int inbrMin = max(i-scalewin,i%scale);
		for(; j < (width-scalewin)-3; j+=4) {
			valv= _mm_setzero_ps();
			normv= _mm_setzero_ps();
			dftemp1v = LVFU(data_fine[i][j]);
			for(int inbr=inbrMin; inbr<=min(i+scalewin, height-1); inbr+=scale) {
				for (int jnbr=j-scalewin; jnbr<=j+scalewin; jnbr+=scale) {
					dftemp2v = LVFU(data_fine[inbr][jnbr]);
					dirwtv = ( rangefn[_mm_cvttps_epi32(vabsf(dftemp2v-dftemp1v))] );
					valv += dirwtv*dftemp2v;
					normv += dirwtv;
				}
			}
			_mm_storeu_ps( &data_coarse[i][j], valv/normv);
		}
		for(; j < width-scalewin; j++) {
			float val=0.f;
			float norm=0.f;
			for(int inbr=inbrMin; inbr<=min(i+scalewin, height-1); inbr+=scale) {
				for (int jnbr=j-scalewin; jnbr<=j+scalewin; jnbr+=scale) {
					dirwt = ( rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
					val += dirwt*data_fine[inbr][jnbr];
					norm += dirwt;
				}
			}
			data_coarse[i][j] = val/norm; // low pass filter
		}

#else
		for(; j < width-scalewin; j++) {
			float val=0.f;
			float norm=0.f;
			for(int inbr=max(i-scalewin,i%scale); inbr<=min(i+scalewin, height-1); inbr+=scale) {
				for (int jnbr=j-scalewin; jnbr<=j+scalewin; jnbr+=scale) {
					dirwt = ( rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
					val += dirwt*data_fine[inbr][jnbr];
					norm += dirwt;
				}
			}
			data_coarse[i][j] = val/norm; // low pass filter
		}
#endif
		for(; j < width; j++) {
			float val=0.f;
			float norm=0.f;
			for(int inbr=max(i-scalewin,i%scale); inbr<=min(i+scalewin, height-1); inbr+=scale) {
				for (int jnbr=j-scalewin; jnbr<width; jnbr+=scale) {
					dirwt = ( rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
					val += dirwt*data_fine[inbr][jnbr];
					norm += dirwt;
				}
			}
			data_coarse[i][j] = val/norm; // low pass filter
		}
	}
}
}
else {
	halfwin=2;
	scalewin = halfwin*scale;
	int domker[5][5] = {{1,1,1,1,1},{1,2,2,2,1},{1,2,2,2,1},{1,2,2,2,1},{1,1,1,1,1}};
	//generate domain kernel

#ifdef _OPENMP
#pragma omp parallel
#endif
{
#if defined( __SSE2__ ) && defined( __x86_64__ )
	__m128 dirwtv, valv, normv, dftemp1v, dftemp2v;
	float domkerv[5][5][4] __attribute__ ((aligned (16))) = {{{1,1,1,1},{1,1,1,1},{1,1,1,1},{1,1,1,1},{1,1,1,1}},{{1,1,1,1},{2,2,2,2},{2,2,2,2},{2,2,2,2},{1,1,1,1}},{{1,1,1,1},{2,2,2,2},{2,2,2,2},{2,2,2,2},{1,1,1,1}},{{1,1,1,1},{2,2,2,2},{2,2,2,2},{2,2,2,2},{1,1,1,1}},{{1,1,1,1},{1,1,1,1},{1,1,1,1},{1,1,1,1},{1,1,1,1}}};

#endif // __SSE2__
	int j;
#ifdef _OPENMP
#pragma omp for schedule(dynamic,16)
#endif
	for(int i = 0; i < height; i++) {
		float dirwt;
		for(j = 0; j < scalewin; j++) {
			float val=0.f;
			float norm=0.f;
			for(int inbr=max(i-scalewin,i%scale); inbr<=min(i+scalewin, height-1); inbr+=scale) {
				for (int jnbr=j%scale; jnbr<=j+scalewin; jnbr+=scale) {
					dirwt = ( domker[(inbr-i)/scale+halfwin][(jnbr-j)/scale+halfwin] * rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
					val += dirwt*data_fine[inbr][jnbr];
					norm += dirwt;
				}
			}
			data_coarse[i][j] = val/norm; // low pass filter
		}
#if defined( __SSE2__ ) && defined( __x86_64__ )
		for(; j < width-scalewin-3; j+=4) {
			valv = _mm_setzero_ps();
			normv = _mm_setzero_ps();
			dftemp1v = LVFU(data_fine[i][j]);
			for(int inbr=max(i-scalewin,i%scale); inbr<=MIN(i+scalewin, height-1); inbr+=scale) {
				int indexihlp = (inbr-i)/scale+halfwin;
				for (int jnbr=j-scalewin,indexjhlp = 0; jnbr<=j+scalewin; jnbr+=scale,indexjhlp++) {
					dftemp2v = LVFU(data_fine[inbr][jnbr]);
					dirwtv = ( _mm_load_ps((float*)&domkerv[indexihlp][indexjhlp]) * rangefn[_mm_cvttps_epi32(vabsf(dftemp2v-dftemp1v))] );
					valv += dirwtv*dftemp2v;
					normv += dirwtv;
				}
			}
			_mm_storeu_ps( &data_coarse[i][j], valv/normv);
		}
		for(; j < width-scalewin; j++) {
			float val=0;
			float norm=0;
			for(int inbr=max(i-scalewin,i%scale); inbr<=min(i+scalewin, height-1); inbr+=scale) {
				for (int jnbr=j-scalewin; jnbr<=j+scalewin; jnbr+=scale) {
					dirwt = ( domker[(inbr-i)/scale+halfwin][(jnbr-j)/scale+halfwin] * rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
					val += dirwt*data_fine[inbr][jnbr];
					norm += dirwt;
				}
			}
			data_coarse[i][j] = val/norm; // low pass filter
		}

#else
		for(; j < width-scalewin; j++) {
			float val=0;
			float norm=0;
			for(int inbr=max(i-scalewin,i%scale); inbr<=min(i+scalewin, height-1); inbr+=scale) {
				for (int jnbr=j-scalewin; jnbr<=j+scalewin; jnbr+=scale) {
					dirwt = ( domker[(inbr-i)/scale+halfwin][(jnbr-j)/scale+halfwin] * rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
					val += dirwt*data_fine[inbr][jnbr];
					norm += dirwt;
				}
			}
			data_coarse[i][j] = val/norm; // low pass filter
		}
#endif
		for(; j < width; j++) {
			float val=0;
			float norm=0;
			for(int inbr=max(i-scalewin,i%scale); inbr<=min(i+scalewin, height-1); inbr+=scale) {
				for (int jnbr=j-scalewin; jnbr<width; jnbr+=scale) {
					dirwt = ( domker[(inbr-i)/scale+halfwin][(jnbr-j)/scale+halfwin] * rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
					val += dirwt*data_fine[inbr][jnbr];
					norm += dirwt;
				}
			}
			data_coarse[i][j] = val/norm; // low pass filter
		}
	}
}

}

}

}//end of SHMap
