void model_parameters::userfunction(void)
{
obj_fun =0.0;
int Gtype, L;
FMpar = mfexp(logFM); // estimated F/M
SL50 = mfexp(logSL50);
Delta = mfexp(logDelta);
Vul = 1.0/(1+mfexp(-log(19)*(LenBins-SL50)/Delta));
MkL = Mk * pow(Linf/LenBins, Mpow);
FkL = FMpar * Mk * Vul;
for (Gtype=1;Gtype<=NGTG;Gtype++) {
MKLMat(Gtype) = MkL + kslope*(DiffLinfs(Gtype) - Linf);
ZKLMat(Gtype) = MKLMat(Gtype) + FkL;
currMkL = MKLMat(Gtype);
currZkL = ZKLMat(Gtype);
PUnFished = 0;
PFished = 0;
NUnFished = 0;
NFished = 0 ;
PUnFished(1) = RecProbs(Gtype);
PFished(1) = RecProbs(Gtype);
GTGLinf = DiffLinfs(Gtype);
for (L=2;L<=NLenMids+1;L++) {
if (LenBins(L) < GTGLinf) {
PUnFished(L) = PUnFished(L-1) * pow(((GTGLinf-LenBins(L))/(GTGLinf-LenBins(L-1))),currMkL(L-1));
PFished(L) = PFished(L-1) * pow(((GTGLinf-LenBins(L))/(GTGLinf-LenBins(L-1))),currZkL(L-1));
}
if (LenBins(L) >= GTGLinf) {
PUnFished(L) = 0;
PFished(L) = 0;
}
}
for (L=1;L<=NLenMids;L++) {
NUnFished(L) = (PUnFished(L) - PUnFished(L+1))/currMkL(L);
NFished(L) = (PFished(L) - PFished(L+1))/currZkL(L);
}
UnfishedMatrix(Gtype) = NUnFished;
FishedMatrix(Gtype) = NFished;
EP0_gtg(Gtype) = sum(elem_prod(NUnFished, Fec));
EPf_gtg(Gtype) = sum(elem_prod(NFished, Fec));
}
EP0 = sum(EP0_gtg);
EPf = sum(EPf_gtg);
SPR = EPf/EP0;
PredUnfishedComp = colsum(UnfishedMatrix);
PredUnfishedComp = PredUnfishedComp/sum(PredUnfishedComp);
// cout<<"hello"<<endl;
PredFishedComp = colsum(FishedMatrix);
PredFishedComp = PredFishedComp/sum(PredFishedComp);
PredLenComp = colsum(FishedMatrix);
PredLenComp = elem_prod(PredLenComp, 1.0/(1+mfexp(-log(19)*(LenMids-SL50)/Delta)));
PredLenComp = PredLenComp/sum(PredLenComp);
SL95 = SL50 + Delta;
obj_fun = -sum(elem_prod(ObsLength, log(elem_div(PredLenComp+0.00000001,ObsLength+0.00000001)))); // AP from ADMB living doc
}
void SetNewExtraColumnCount()
{
int newcount;
GetVisColumns();
newcount=colsum(0,EXTRACOLUMNCOUNT-1);
DBWriteContactSettingByte(NULL,CLUIFrameModule,"EnabledColumnCount",(BYTE)newcount);
EnabledColumnCount=newcount;
SendMessage(pcli->hwndContactTree,CLM_SETEXTRACOLUMNS,EnabledColumnCount,0);
}
void SetNewExtraColumnCount()
{
int newcount;
LoadPositionsFromDB(ExtraOrder);
GetVisColumns();
newcount=colsum(0,EXTRACOLUMNCOUNT-1);
ModernWriteSettingByte(NULL,CLUIFrameModule,"EnabledColumnCount",(BYTE)newcount);
EnabledColumnCount=newcount;
SendMessage(pcli->hwndContactTree,CLM_SETEXTRACOLUMNS,EnabledColumnCount,0);
};
void ContingencyTable_entropies (ContingencyTable me, double *h, double *hx, double *hy, double *hygx, double *hxgy, double *uygx, double *uxgy, double *uxy) {
*h = *hx = *hy = *hxgy = *hygx = *uygx = *uxgy = *uxy = 0;
autoNUMvector<double> rowsum (1, my numberOfRows);
autoNUMvector<double> colsum (1, my numberOfColumns);
// row and column totals
double sum = 0.0;
for (long i = 1; i <= my numberOfRows; i++) {
for (long j = 1; j <= my numberOfColumns; j++) {
rowsum[i] += my data[i][j];
colsum[j] += my data[i][j];
}
sum += rowsum[i];
}
// Entropy of x distribution
for (long j = 1; j <= my numberOfColumns; j++) {
if (colsum[j] > 0.0) {
double p = colsum[j] / sum;
*hx -= p * NUMlog2 (p);
}
}
// Entropy of y distribution
for (long i = 1; i <= my numberOfRows; i++) {
if (rowsum[i] > 0.0) {
double p = rowsum[i] / sum;
*hy -= p * NUMlog2 (p);
}
}
// Total entropy
for (long i = 1; i <= my numberOfRows; i++) {
for (long j = 1; j <= my numberOfColumns; j++) {
if (my data[i][j] > 0.0) {
double p = my data[i][j] / sum;
*h -= p * NUMlog2 (p);
}
}
}
// Conditional entropies
*hygx = *h - *hx;
*hxgy = *h - *hy;
*uygx = (*hy - *hygx) / (*hy + TINY);
*uxgy = (*hx - *hxgy) / (*hx + TINY);
*uxy = 2.0 * (*hx + *hy - *h) / (*hx + *hy + TINY);
}
int ExtraToColumnNum(int extra)
{
int cnt=EnabledColumnCount-1;
int extracnt=EXTRACOLUMNCOUNT-1;
switch(extra)
{
case EXTRA_ICON_WEB: if (!visar[0])return(-1);break;
case EXTRA_ICON_ADV1: if (!visar[1])return(-1);break;
case EXTRA_ICON_ADV2: if (!visar[2])return(-1);break;
case EXTRA_ICON_SMS: if (!visar[3])return(-1);break;
case EXTRA_ICON_EMAIL: if (!visar[4])return(-1);break;
case EXTRA_ICON_PROTO: if (!visar[5])return(-1);break;
case EXTRA_ICON_CLIENT: if (!visar[6])return(-1);break;
};
switch(extra)
{
case EXTRA_ICON_WEB: if (extracnt-5>=0) return(cnt-colsum(extracnt-5,extracnt));
case EXTRA_ICON_ADV1: if (extracnt-4>=0) return(cnt-colsum(extracnt-4,extracnt));
case EXTRA_ICON_ADV2: if (extracnt-3>=0) return(cnt-colsum(extracnt-3,extracnt));
case EXTRA_ICON_SMS: if (extracnt-2>=0) return(cnt-colsum(extracnt-2,extracnt));
case EXTRA_ICON_EMAIL: if (extracnt-1>=0) return(cnt-colsum(extracnt-1,extracnt));
case EXTRA_ICON_PROTO: return(cnt-colsum(extracnt,extracnt));
case EXTRA_ICON_CLIENT: return(cnt);
};
return(-1);
};
Mat calculateImageSymmetryScore(const Mat& image) {
Mat gray_img ;
if (image.channels() == 3) {
cvtColor(image, gray_img, CV_BGR2GRAY);
} else {
gray_img = image.clone();
}
// gray_img = magicEqualHist(gray_img);
// imshow("histed",gray_img);
if (gray_img.cols %2 == 1) {
hconcat(gray_img, gray_img.col(gray_img.cols-1), gray_img);
}
gray_img.convertTo(gray_img, CV_32FC1);
Mat score(gray_img.cols,gray_img.cols,CV_32FC1,Scalar::all(0));
Mat temp(1,1,CV_32FC1), base(1,1,CV_32FC1),colsum(1,1,CV_32FC1);
for (int i = 0 ; i < gray_img.cols/2; i++) {
temp = gray_img.colRange(0, i+1).clone();
flip(temp, temp, 1);
base = gray_img.colRange(i+1, gray_img.cols).clone();
base.colRange(0, temp.cols) += temp;
reduce(base, colsum, 0, CV_REDUCE_SUM,CV_32FC1);
colsum = colsum.t();
colsum.copyTo(score.colRange(i, i+1).rowRange(0, colsum.rows));
}
flip(score, score, 1);
flip(gray_img, gray_img, 1);
for (int i = 0 ; i < gray_img.cols/2; i++) {
temp = gray_img.colRange(0, i+1).clone();
flip(temp, temp, 1);
base = gray_img.colRange(i+1, gray_img.cols).clone();
base.colRange(0, temp.cols) += temp;
reduce(base, colsum, 0, CV_REDUCE_SUM,CV_32FC1);
colsum = colsum.t();
colsum.copyTo(score.colRange(i, i+1).rowRange(0, colsum.rows));
}
flip(score, score, 1);
gray_img.release();
base.release();
temp.release();
return score;
}
int ExtraImage_ExtraIDToColumnNum(int extra)
{
if (HasExtraIconsService())
{
if (extra < 1 || extra > EXTRACOLUMNCOUNT)
return -1;
else
return extra-1;
}
int ord=ExtraOrder[extra-1];
if (!visar[ord]) return -1;
return (colsum(0,ord)-1);
};
void ContingencyTable_chisq (ContingencyTable me, double *chisq, long *df) {
long nr = my numberOfRows, nc = my numberOfColumns;
*chisq = 0; *df = 0;
autoNUMvector<double> rowsum (1, nr);
autoNUMvector<double> colsum (1, nc);
/*
row and column marginals
*/
double sum = 0;
for (long i = 1; i <= my numberOfRows; i++) {
for (long j = 1; j <= my numberOfColumns; j++) {
rowsum[i] += my data[i][j];
colsum[j] += my data[i][j];
}
sum += rowsum[i];
}
for (long i = 1; i <= my numberOfRows; i++) {
if (rowsum[i] == 0) {
--nr;
}
}
for (long j = 1; j <= my numberOfColumns; j++) {
if (colsum[j] == 0) {
--nc;
}
}
*df = (nr - 1) * (nc - 1);
for (long i = 1; i <= my numberOfRows; i++) {
if (rowsum[i] == 0) {
continue;
}
for (long j = 1; j <= my numberOfColumns; j++) {
if (colsum[j] == 0) {
continue;
}
double expt = rowsum[i] * colsum[j] / sum;
double tmp = my data[i][j] - expt;
*chisq += tmp * tmp / expt;
}
}
}
int ExtraToColumnNum(int extra)
{
if (HasExtraIconsService())
{
if (extra < 1 || extra > EXTRACOLUMNCOUNT)
return -1;
else
return extra-1;
}
else
{
int cnt=EnabledColumnCount;
int extracnt=EXTRACOLUMNCOUNT-1;
int ord=ExtraOrder[extra-1];
if (!visar[ord]) return -1;
return (colsum(0,ord)-1);
}
};
