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rawTherapee/rtengine/ipretinex.cc
luz.paz cc60ea2248 Fix source comment and misc. typos 
Found via `codespell -q 3 -I ../rawtherapy-whitelist.txt -S ./rtdata/languages -L hist,fo,reall,bloc,alph`
2019-06-03 17:38:50 -04:00

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/*
* 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/>.
* adaptation to RawTherapee
* 2015 Jacques Desmis <jdesmis@gmail.com>
* 2015 Ingo Weyrich <heckflosse67@gmx.de>
* D. J. Jobson, Z. Rahman, and G. A. Woodell. A multi-scale
* Retinex for bridging the gap between color images and the
* human observation of scenes. IEEE Transactions on Image Processing,
* 1997, 6(7): 965-976
* Fan Guo Zixing Cai Bin Xie Jin Tang
* School of Information Science and Engineering, Central South University Changsha, China
* Weixing Wang and Lian Xu
* College of Physics and Information Engineering, Fuzhou University, Fuzhou, China
* inspired from 2003 Fabien Pelisson <Fabien.Pelisson@inrialpes.fr>
* some ideas taken (use of mask) Russell Cottrell - The Retinex .8bf Plugin
*/
#include <cmath>
#include <cstdio>
#include <cstdlib>
#include <cstring>
#include "gauss.h"
#include "improcfun.h"
#include "median.h"
#include "opthelper.h"
#include "procparams.h"
#include "rawimagesource.h"
#include "rtengine.h"
#include "StopWatch.h"
#define clipretinex( val, minv, maxv ) (( val = (val < minv ? minv : val ) ) > maxv ? maxv : val )
namespace
{
void retinex_scales( float* scales, int nscales, int mode, int s, float high)
{
if ( nscales == 1 ) {
scales[0] = (float)s / 2.f;
} else if (nscales == 2) {
scales[1] = (float) s / 2.f;
scales[0] = (float) s;
} else {
float size_step = (float) s / (float) nscales;
if (mode == 0) {
for (int i = 0; i < nscales; ++i ) {
scales[nscales - i - 1] = 2.0f + (float)i * size_step;
}
} else if (mode == 1) {
size_step = (float)log(s - 2.0f) / (float) nscales;
for (int i = 0; i < nscales; ++i ) {
scales[nscales - i - 1] = 2.0f + (float)pow (10.f, (i * size_step) / log (10.f));
}
} else if (mode == 2) {
size_step = (float) log(s - 2.0f) / (float) nscales;
for ( int i = 0; i < nscales; ++i ) {
scales[i] = s - (float)pow (10.f, (i * size_step) / log (10.f));
}
} else if (mode == 3) {
size_step = (float) log(s - 2.0f) / (float) nscales;
for ( int i = 0; i < nscales; ++i ) {
scales[i] = high * s - (float)pow (10.f, (i * size_step) / log (10.f));
}
}
}
}
void mean_stddv2( float **dst, float &mean, float &stddv, int W_L, int H_L, float &maxtr, float &mintr)
{
// summation using double precision to avoid too large summation error for large pictures
double vsquared = 0.f;
double sum = 0.f;
maxtr = -999999.f;
mintr = 999999.f;
#ifdef _OPENMP
#pragma omp parallel
#endif
{
float lmax = -999999.f, lmin = 999999.f;
#ifdef _OPENMP
#pragma omp for reduction(+:sum,vsquared) nowait // this leads to differences, but parallel summation is more accurate
#endif
for (int i = 0; i < H_L; i++ )
for (int j = 0; j < W_L; j++) {
sum += dst[i][j];
vsquared += (dst[i][j] * dst[i][j]);
lmax = dst[i][j] > lmax ? dst[i][j] : lmax;
lmin = dst[i][j] < lmin ? dst[i][j] : lmin;
}
#ifdef _OPENMP
#pragma omp critical
#endif
{
maxtr = maxtr > lmax ? maxtr : lmax;
mintr = mintr < lmin ? mintr : lmin;
}
}
mean = sum / (double) (W_L * H_L);
vsquared /= (double) W_L * H_L;
stddv = ( vsquared - (mean * mean) );
stddv = (float)sqrt(stddv);
}
}
namespace rtengine
{
extern const Settings* settings;
void RawImageSource::MSR(float** luminance, float** originalLuminance, float **exLuminance, LUTf & mapcurve, bool &mapcontlutili, int width, int height, const RetinexParams &deh, const RetinextransmissionCurve & dehatransmissionCurve, const RetinexgaintransmissionCurve & dehagaintransmissionCurve, float &minCD, float &maxCD, float &mini, float &maxi, float &Tmean, float &Tsigma, float &Tmin, float &Tmax)
{
if (deh.enabled) {//enabled
float maxtr, mintr;
constexpr float eps = 2.f;
bool useHsl = deh.retinexcolorspace == "HSLLOG";
bool useHslLin = deh.retinexcolorspace == "HSLLIN";
float offse = (float) deh.offs; //def = 0 not use
int iter = deh.iter;
int gradient = deh.scal;
int scal = 3;//disabled scal
int nei = (int) (2.8f * deh.neigh); //def = 220
float vart = (float)deh.vart / 100.f;//variance
float gradvart = (float)deh.grad;
float gradstr = (float)deh.grads;
float strength = (float) deh.str / 100.f; // Blend with original L channel data
float limD = (float) deh.limd;
limD = pow(limD, 1.7f);//about 2500 enough
limD *= useHslLin ? 10.f : 1.f;
float ilimD = 1.f / limD;
float hig = ((float) deh.highl) / 100.f;
scal = deh.skal;
int H_L = height;
int W_L = width;
float *tran[H_L] ALIGNED16;
float *tranBuffer = nullptr;
constexpr float elogt = 2.71828f;
bool lhutili = false;
FlatCurve* shcurve = new FlatCurve(deh.lhcurve); //curve L=f(H)
if (!shcurve || shcurve->isIdentity()) {
if (shcurve) {
delete shcurve;
shcurve = nullptr;
}
} else {
lhutili = true;
}
bool higplus = false ;
int moderetinex = 2; // default to 2 ( deh.retinexMethod == "high" )
if(deh.retinexMethod == "highliplus") {
higplus = true;
moderetinex = 3;
} else if (deh.retinexMethod == "uni") {
moderetinex = 0;
} else if (deh.retinexMethod == "low") {
moderetinex = 1;
} else { /*if (deh.retinexMethod == "highli") */
moderetinex = 3;
}
constexpr float aahi = 49.f / 99.f; ////reduce sensibility 50%
constexpr float bbhi = 1.f - aahi;
for(int it = 1; it < iter + 1; it++) { //iter nb max of iterations
float high = bbhi + aahi * (float) deh.highl;
float grad = 1.f;
float sc = scal;
if(gradient == 0) {
grad = 1.f;
sc = 3.f;
} else if(gradient == 1) {
grad = 0.25f * it + 0.75f;
sc = -0.5f * it + 4.5f;
} else if(gradient == 2) {
grad = 0.5f * it + 0.5f;
sc = -0.75f * it + 5.75f;
} else if(gradient == 3) {
grad = 0.666f * it + 0.333f;
sc = -0.75f * it + 5.75f;
} else if(gradient == 4) {
grad = 0.8f * it + 0.2f;
sc = -0.75f * it + 5.75f;
} else if(gradient == 5) {
if(moderetinex != 3) {
grad = 2.5f * it - 1.5f;
} else {
float aa = (11.f * high - 1.f) / 4.f;
float bb = 1.f - aa;
grad = aa * it + bb;
}
sc = -0.75f * it + 5.75f;
} else if(gradient == 6) {
if(moderetinex != 3) {
grad = 5.f * it - 4.f;
} else {
float aa = (21.f * high - 1.f) / 4.f;
float bb = 1.f - aa;
grad = aa * it + bb;
}
sc = -0.75f * it + 5.75f;
}
else if(gradient == -1) {
grad = -0.125f * it + 1.125f;
sc = 3.f;
}
if(iter == 1) {
sc = scal;
} else {
//adjust sc in function of choice of scale by user if iterations
if(scal < 3) {
sc -= 1;
if(sc < 1.f) {//avoid 0
sc = 1.f;
}
}
if(scal > 4) {
sc += 1;
}
}
float varx = vart;
float limdx = limD;
float ilimdx = ilimD;
if(gradvart != 0) {
if(gradvart == 1) {
varx = vart * (-0.125f * it + 1.125f);
limdx = limD * (-0.125f * it + 1.125f);
ilimdx = 1.f / limdx;
} else if(gradvart == 2) {
varx = vart * (-0.2f * it + 1.2f);
limdx = limD * (-0.2f * it + 1.2f);
ilimdx = 1.f / limdx;
} else if(gradvart == -1) {
varx = vart * (0.125f * it + 0.875f);
limdx = limD * (0.125f * it + 0.875f);
ilimdx = 1.f / limdx;
} else if(gradvart == -2) {
varx = vart * (0.4f * it + 0.6f);
limdx = limD * (0.4f * it + 0.6f);
ilimdx = 1.f / limdx;
}
}
scal = round(sc);
float ks = 1.f;
if(gradstr != 0) {
if(gradstr == 1) {
if(it <= 3) {
ks = -0.3f * it + 1.6f;
} else {
ks = 0.5f;
}
} else if(gradstr == 2) {
if(it <= 3) {
ks = -0.6f * it + 2.2f;
} else {
ks = 0.3f;
}
} else if(gradstr == -1) {
if(it <= 3) {
ks = 0.2f * it + 0.6f;
} else {
ks = 1.2f;
}
} else if(gradstr == -2) {
if(it <= 3) {
ks = 0.4f * it + 0.2f;
} else {
ks = 1.5f;
}
}
}
float strengthx = ks * strength;
constexpr auto maxRetinexScales = 8;
float RetinexScales[maxRetinexScales];
retinex_scales( RetinexScales, scal, moderetinex, nei / grad, high );
float *src[H_L] ALIGNED16;
float *srcBuffer = new float[H_L * W_L];
for (int i = 0; i < H_L; i++) {
src[i] = &srcBuffer[i * W_L];
}
int h_th = 0, s_th = 0;
int shHighlights = deh.highlights;
int shShadows = deh.shadows;
int mapmet = 0;
if(deh.mapMethod == "map") {
mapmet = 2;
} else if(deh.mapMethod == "mapT") {
mapmet = 3;
} else if(deh.mapMethod == "gaus") {
mapmet = 4;
}
const double shradius = mapmet == 4 ? (double) deh.radius : 40.;
int viewmet = 0;
if(deh.viewMethod == "mask") {
viewmet = 1;
} else if(deh.viewMethod == "tran") {
viewmet = 2;
} else if(deh.viewMethod == "tran2") {
viewmet = 3;
} else if(deh.viewMethod == "unsharp") {
viewmet = 4;
}
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int i = 0; i < H_L; i++)
for (int j = 0; j < W_L; j++) {
src[i][j] = luminance[i][j] + eps;
luminance[i][j] = 0.f;
}
float *out[H_L] ALIGNED16;
float *outBuffer = new float[H_L * W_L];
for (int i = 0; i < H_L; i++) {
out[i] = &outBuffer[i * W_L];
}
if(viewmet == 3 || viewmet == 2) {
tranBuffer = new float[H_L * W_L];
for (int i = 0; i < H_L; i++) {
tran[i] = &tranBuffer[i * W_L];
}
}
const float logBetaGain = xlogf(16384.f);
float pond = logBetaGain / (float) scal;
if(!useHslLin) {
pond /= log(elogt);
}
auto shmap = ((mapmet == 2 || mapmet == 3 || mapmet == 4) && it == 1) ? new SHMap (W_L, H_L) : nullptr;
float *buffer = new float[W_L * H_L];;
for ( int scale = scal - 1; scale >= 0; scale-- ) {
#ifdef _OPENMP
#pragma omp parallel
#endif
{
if(scale == scal - 1)
{
gaussianBlur (src, out, W_L, H_L, RetinexScales[scale], buffer);
} else { // reuse result of last iteration
// out was modified in last iteration => restore it
if((((mapmet == 2 && scale > 1) || mapmet == 3 || mapmet == 4) || (mapmet > 0 && mapcontlutili)) && it == 1)
{
#ifdef _OPENMP
#pragma omp for
#endif
for (int i = 0; i < H_L; i++) {
for (int j = 0; j < W_L; j++) {
out[i][j] = buffer[i * W_L + j];
}
}
}
gaussianBlur (out, out, W_L, H_L, sqrtf(SQR(RetinexScales[scale]) - SQR(RetinexScales[scale + 1])), buffer);
}
if((((mapmet == 2 && scale > 2) || mapmet == 3 || mapmet == 4) || (mapmet > 0 && mapcontlutili)) && it == 1 && scale > 0)
{
// out will be modified => store it for use in next iteration. We even don't need a new buffer because 'buffer' is free after gaussianBlur :)
#ifdef _OPENMP
#pragma omp for
#endif
for (int i = 0; i < H_L; i++) {
for (int j = 0; j < W_L; j++) {
buffer[i * W_L + j] = out[i][j];
}
}
}
}
if(((mapmet == 2 && scale > 2) || mapmet == 3 || mapmet == 4) && it == 1) {
shmap->updateL (out, shradius, true, 1);
h_th = shmap->max_f - deh.htonalwidth * (shmap->max_f - shmap->avg) / 100;
s_th = deh.stonalwidth * (shmap->avg - shmap->min_f) / 100;
}
#ifdef __SSE2__
vfloat pondv = F2V(pond);
vfloat limMinv = F2V(ilimdx);
vfloat limMaxv = F2V(limdx);
#endif
if(mapmet > 0 && mapcontlutili && it == 1) {
// TODO: When rgbcurvespeedup branch is merged into master we can simplify the code by
// 1) in rawimagesource.retinexPrepareCurves() insert
// mapcurve *= 0.5f;
// after
// CurveFactory::mapcurve (mapcontlutili, retinexParams.mapcurve, mapcurve, 1, lhist16RETI, histLRETI);
// 2) remove the division by 2.f from the code 7 lines below this line
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int i = 0; i < H_L; i++) {
for (int j = 0; j < W_L; j++) {
out[i][j] = mapcurve[2.f * out[i][j]] / 2.f;
}
}
}
if(((mapmet == 2 && scale > 2) || mapmet == 3 || mapmet == 4) && it == 1) {
float hWeight = (100.f - shHighlights) / 100.f;
float sWeight = (100.f - shShadows) / 100.f;
#ifdef _OPENMP
#pragma omp parallel for schedule(dynamic,16)
#endif
for (int i = 0; i < H_L; i++) {
for (int j = 0; j < W_L; j++) {
float mapval = 1.f + shmap->map[i][j];
float factor = 1.f;
if (mapval > h_th) {
factor = (h_th + hWeight * (mapval - h_th)) / mapval;
} else if (mapval < s_th) {
factor = (s_th - sWeight * (s_th - mapval)) / mapval;
}
out[i][j] *= factor;
}
}
}
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int i = 0; i < H_L; i++) {
int j = 0;
#ifdef __SSE2__
if(useHslLin) {
for (; j < W_L - 3; j += 4) {
_mm_storeu_ps(&luminance[i][j], LVFU(luminance[i][j]) + pondv * (vclampf(LVFU(src[i][j]) / LVFU(out[i][j]), limMinv, limMaxv) ));
}
} else {
for (; j < W_L - 3; j += 4) {
_mm_storeu_ps(&luminance[i][j], LVFU(luminance[i][j]) + pondv * xlogf(vclampf(LVFU(src[i][j]) / LVFU(out[i][j]), limMinv, limMaxv) ));
}
}
#endif
if(useHslLin) {
for (; j < W_L; j++) {
luminance[i][j] += pond * (LIM(src[i][j] / out[i][j], ilimdx, limdx));
}
} else {
for (; j < W_L; j++) {
luminance[i][j] += pond * xlogf(LIM(src[i][j] / out[i][j], ilimdx, limdx)); // /logt ?
}
}
}
}
if(mapmet > 1) {
if(shmap) {
delete shmap;
}
}
shmap = nullptr;
delete [] buffer;
delete [] srcBuffer;
float mean = 0.f;
float stddv = 0.f;
// I call mean_stddv2 instead of mean_stddv ==> logBetaGain
mean_stddv2( luminance, mean, stddv, W_L, H_L, maxtr, mintr);
//printf("mean=%f std=%f delta=%f maxtr=%f mintr=%f\n", mean, stddv, delta, maxtr, mintr);
//mean_stddv( luminance, mean, stddv, W_L, H_L, logBetaGain, maxtr, mintr);
if (dehatransmissionCurve && mean != 0.f && stddv != 0.f) { //if curve
float asig = 0.166666f / stddv;
float bsig = 0.5f - asig * mean;
float amax = 0.333333f / (maxtr - mean - stddv);
float bmax = 1.f - amax * maxtr;
float amin = 0.333333f / (mean - stddv - mintr);
float bmin = -amin * mintr;
asig *= 500.f;
bsig *= 500.f;
amax *= 500.f;
bmax *= 500.f;
amin *= 500.f;
bmin *= 500.f;
#ifdef _OPENMP
#pragma omp parallel
#endif
{
float absciss;
#ifdef _OPENMP
#pragma omp for schedule(dynamic,16)
#endif
for (int i = 0; i < H_L; i++ )
for (int j = 0; j < W_L; j++) { //for mintr to maxtr evalate absciss in function of original transmission
if (LIKELY(fabsf(luminance[i][j] - mean) < stddv)) {
absciss = asig * luminance[i][j] + bsig;
} else if (luminance[i][j] >= mean) {
absciss = amax * luminance[i][j] + bmax;
} else { /*if(luminance[i][j] <= mean - stddv)*/
absciss = amin * luminance[i][j] + bmin;
}
//TODO : move multiplication by 4.f and subtraction of 1.f inside the curve
luminance[i][j] *= (-1.f + 4.f * dehatransmissionCurve[absciss]); //new transmission
if(viewmet == 3 || viewmet == 2) {
tran[i][j] = luminance[i][j];
}
}
}
// median filter on transmission ==> reduce artifacts
if (deh.medianmap && it == 1) { //only one time
int wid = W_L;
int hei = H_L;
float *tmL[hei] ALIGNED16;
float *tmLBuffer = new float[wid * hei];
int borderL = 1;
for (int i = 0; i < hei; i++) {
tmL[i] = &tmLBuffer[i * wid];
}
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int i = borderL; i < hei - borderL; i++) {
for (int j = borderL; j < wid - borderL; j++) {
tmL[i][j] = median(luminance[i][j], luminance[i - 1][j], luminance[i + 1][j], luminance[i][j + 1], luminance[i][j - 1], luminance[i - 1][j - 1], luminance[i - 1][j + 1], luminance[i + 1][j - 1], luminance[i + 1][j + 1]); //3x3
}
}
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int i = borderL; i < hei - borderL; i++ ) {
for (int j = borderL; j < wid - borderL; j++) {
luminance[i][j] = tmL[i][j];
}
}
delete [] tmLBuffer;
}
// I call mean_stddv2 instead of mean_stddv ==> logBetaGain
//mean_stddv( luminance, mean, stddv, W_L, H_L, 1.f, maxtr, mintr);
mean_stddv2( luminance, mean, stddv, W_L, H_L, maxtr, mintr);
}
float epsil = 0.1f;
mini = mean - varx * stddv;
if (mini < mintr) {
mini = mintr + epsil;
}
maxi = mean + varx * stddv;
if (maxi > maxtr) {
maxi = maxtr - epsil;
}
float delta = maxi - mini;
//printf("maxi=%f mini=%f mean=%f std=%f delta=%f maxtr=%f mintr=%f\n", maxi, mini, mean, stddv, delta, maxtr, mintr);
if ( !delta ) {
delta = 1.0f;
}
float cdfactor = 32768.f / delta;
maxCD = -9999999.f;
minCD = 9999999.f;
// coeff for auto "transmission" with 2 sigma #95% data
float aza = 16300.f / (2.f * stddv);
float azb = -aza * (mean - 2.f * stddv);
float bza = 16300.f / (2.f * stddv);
float bzb = 16300.f - bza * (mean);
//prepare work for curve gain
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int i = 0; i < H_L; i++) {
for (int j = 0; j < W_L; j++) {
luminance[i][j] = luminance[i][j] - mini;
}
}
mean = 0.f;
stddv = 0.f;
// I call mean_stddv2 instead of mean_stddv ==> logBetaGain
mean_stddv2( luminance, mean, stddv, W_L, H_L, maxtr, mintr);
float asig = 0.f, bsig = 0.f, amax = 0.f, bmax = 0.f, amin = 0.f, bmin = 0.f;
if (dehagaintransmissionCurve && mean != 0.f && stddv != 0.f) { //if curve
asig = 0.166666f / stddv;
bsig = 0.5f - asig * mean;
amax = 0.333333f / (maxtr - mean - stddv);
bmax = 1.f - amax * maxtr;
amin = 0.333333f / (mean - stddv - mintr);
bmin = -amin * mintr;
asig *= 500.f;
bsig *= 500.f;
amax *= 500.f;
bmax *= 500.f;
amin *= 500.f;
bmin *= 500.f;
}
#ifdef _OPENMP
#pragma omp parallel
#endif
{
float cdmax = -999999.f, cdmin = 999999.f;
#ifdef _OPENMP
#pragma omp for schedule(dynamic,16) nowait
#endif
for ( int i = 0; i < H_L; i ++ )
for (int j = 0; j < W_L; j++) {
float gan;
if (dehagaintransmissionCurve && mean != 0.f && stddv != 0.f) {
float absciss;
if (LIKELY(fabsf(luminance[i][j] - mean) < stddv)) {
absciss = asig * luminance[i][j] + bsig;
} else if (luminance[i][j] >= mean) {
absciss = amax * luminance[i][j] + bmax;
} else { /*if(luminance[i][j] <= mean - stddv)*/
absciss = amin * luminance[i][j] + bmin;
}
// float cd = cdfactor * ( luminance[i][j] - mini ) + offse;
// TODO : move multiplication by 2.f inside the curve
gan = 2.f * (dehagaintransmissionCurve[absciss]); //new gain function transmission
} else {
gan = 0.5f;
}
float cd = gan * cdfactor * ( luminance[i][j] ) + offse;
cdmax = cd > cdmax ? cd : cdmax;
cdmin = cd < cdmin ? cd : cdmin;
float str = strengthx;
if(lhutili && it == 1) { // S=f(H)
{
float HH = exLuminance[i][j];
float valparam;
if(useHsl || useHslLin) {
valparam = float((shcurve->getVal(HH) - 0.5f));
} else {
valparam = float((shcurve->getVal(Color::huelab_to_huehsv2(HH)) - 0.5f));
}
str *= (1.f + 2.f * valparam);
}
}
if(higplus && exLuminance[i][j] > 65535.f * hig) {
str *= hig;
}
if(viewmet == 0) {
luminance[i][j] = intp(str, clipretinex( cd, 0.f, 32768.f ), originalLuminance[i][j]);
} else if(viewmet == 1) {
luminance[i][j] = out[i][j];
} else if(viewmet == 4) {
luminance[i][j] = originalLuminance[i][j] + str * (originalLuminance[i][j] - out[i][j]);//unsharp
} else if(viewmet == 2) {
if(tran[i][j] <= mean) {
luminance[i][j] = azb + aza * tran[i][j]; //auto values
} else {
luminance[i][j] = bzb + bza * tran[i][j];
}
} else { /*if(viewmet == 3) */
luminance[i][j] = 1000.f + tran[i][j] * 700.f; //arbitrary values to help display log values which are between -20 to + 30 - usage values -4 + 5
}
}
#ifdef _OPENMP
#pragma omp critical
#endif
{
maxCD = maxCD > cdmax ? maxCD : cdmax;
minCD = minCD < cdmin ? minCD : cdmin;
}
}
delete [] outBuffer;
outBuffer = nullptr;
//printf("cdmin=%f cdmax=%f\n",minCD, maxCD);
Tmean = mean;
Tsigma = stddv;
Tmin = mintr;
Tmax = maxtr;
if (shcurve) {
delete shcurve;
shcurve = nullptr;
}
}
if(tranBuffer) {
delete [] tranBuffer;
}
}
}
}
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