void model_parameters::init_states(void)
{
K=mfexp(lnK);
halfk = K/2;
MSY=mfexp(lnMSY);
// calc z, zMSY, and meanP
z=(1/(n-1))*pow(n,(n/(n-1)));
zMSY=z*MSY;
meanP=mean(Pobs);
}
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);
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 model_parameters::initialization(void)
{
NAreaAge.initialize();
CatchAreaAge.initialize();
CatchNatAge.initialize();
Nage(1,1) = So*Bo/(1+beta*Bo);
for(int i=sage+1 ; i <= nage ; i++)
{
Nage(1,i) = Nage(1,i-1) * mfexp(-za(i-1));
}
VulB(1) = elem_prod(elem_prod(Nage(1),va),wa);
SB(1) = elem_prod(Nage(1),fa)*wa/2;
tBo = Nage(1)*wa;
calcmaxpos(tBo);
varPos = maxPos*cvPos;
PosX(1) = minPos + (maxPos - minPos) * (0.5+0.5*sin(indmonth(1)*PI/6 - mo*PI/6));
VBarea(1,sarea) = VulB(1)* (cnorm(areas(sarea)+0.5,PosX(1),varPos));
for(int r=sarea+1 ; r <= narea-1 ; r++)
{
VBarea(1,r) = VulB(1)* (cnorm(areas(r)+0.5,PosX(1),varPos)-cnorm(areas(r)-0.5,PosX(1),varPos));
NAreaAge(1)(r) = elem_prod(Nage(1)(sage,nage),(cnorm(areas(r)+0.5,PosX(1),varPos)-cnorm(areas(r)-0.5,PosX(1),varPos)));
}
//VBarea(1,narea) = VulB(1)* (1.0-cnorm(areas(narea)-0.5,PosX(1),varPos));
NationVulB(1,1) = sum(VBarea(1)(sarea,sarea+nationareas(1)-1));
NationVulB(1,2) = sum(VBarea(1)(sarea+nationareas(1),narea));
dvar_vector tmp1(sarea,narea);
dvar_vector tmp2(sarea,narea);
dvar_vector tmp3(sarea,narea);
for(int rr= sarea; rr<=narea; rr++)
{
tmp1(rr)= VBarea(1)(rr)/ (NationVulB(1)(indnatarea(rr)) + 0.0001);
tmp2(rr) = tmp1(rr)*TotEffyear(indnatarea(rr))(indyr(1));
Effarea(1)(rr) = tmp2(rr)*TotEffmonth(indnatarea(rr))(indmonth(1));
}
for(int a= sage; a<= nage;a++)
{
dvar_vector propVBarea(sarea,narea);
for(int rr =sarea; rr<=narea; rr++)
{
propVBarea(rr) = (cnorm(areas(rr)+0.5,PosX(1),varPos)-cnorm(areas(rr)-0.5,PosX(1),varPos))(a-sage+1);
CatchAreaAge(1)(rr)(a) = q*Effarea(1)(rr)*va(a)/(q*Effarea(1)(rr)*va(a)+m)*(1-mfexp(-(q*Effarea(1)(rr)*va(a)+m)))*NAreaAge(1)(rr)(a);
CatchNatAge(1)(indnatarea(rr))(a) += CatchAreaAge(1)(rr)(a);
EffNatAge(indnatarea(rr))(1)(sage-2) = 1;
EffNatAge(indnatarea(rr))(1)(sage-1) = indnatarea(rr);
EffNatAge(indnatarea(rr))(1)(a) += Effarea(1)(rr)*propVBarea(rr);
}
//cout<<"propVBarea "<<propVBarea<<endl;
//cout<<"Effarea(1) "<<Effarea(1)<<endl;
Effage(1)(a) = Effarea(1)* propVBarea;
}
}
const T coefficients(const T &x, const T &sel_coeffs)
{
int x1 = x.indexmin();
int x2 = x.indexmax();
int y2 = sel_coeffs.indexmax();
T y(x1,x2);
for ( int i = x1; i < y2; i++ )
{
//y(i) = exp(sel_coeffs(i)) / (1.0 + exp(sel_coeffs(i)));
y(i) = mfexp(sel_coeffs(i));
}
//y(y2,x2) = exp(sel_coeffs(y2)) / (1.0 + exp(sel_coeffs(y2)));
y(y2,x2) = mfexp(sel_coeffs(y2));
return y;
}
LRGS::LRGS(sLRGSdata& data,sLRGSparameters& pars)
{
cout<<"The other constructor"<<endl;
m_syr = data.syr;
m_nyr = data.nyr;
m_agek = data.agek;
m_ct = data.ct;
m_it = data.it;
m_bo = mfexp(pars.log_bo);
m_h = pars.h;
m_s = pars.s;
m_sig = sqrt(1.0/mfexp(pars.log_sigma));
m_tau = sqrt(1.0/mfexp(pars.log_tau));
m_wt = pars.wt;
}
inline
const T plogis(const T &x, const T2 &mean, const T2 &sd)
{
//typedef typename logisticTrait<T>::plogisT plogisT;
T selex = T2(1.0)/(T2(1.0)+mfexp(-(x-mean)/sd));
//selex /= selex(selex.indexmax());
return selex;
}
void model_parameters::preliminary_calculations(void)
{
admaster_slave_variable_interface(*this);
int X;
double pi = 3.14159265358979323844;
MatDelta = L95 - L50;
Mat = 1.0/(1+mfexp(-log(19)*(LenMids-L50)/MatDelta));
Fec = elem_prod(Mat, pow(LenMids, FecB));
Fec = Fec/max(Fec);
SDLinf = CVLinf * Linf;
LinfdL = ((Linf + MaxSD * SDLinf) - (Linf - MaxSD * SDLinf))/(NGTG-1);
for (X=0;X<NGTG;X++) {
DiffLinfs(X+1) = (Linf - MaxSD * SDLinf) + X * LinfdL;
}
RecProbs = 1/(sqrt(2*pi*SDLinf*SDLinf)) * mfexp(-(elem_prod((DiffLinfs-Linf),(DiffLinfs-Linf)))/(2*SDLinf*SDLinf));
RecProbs = RecProbs/sum(RecProbs);
cout << "damnit" << endl;
}
dvar_vector model_parameters::calcmaxpos(const dvariable& tb)
{
int pp = tb > 0.5*tBo?1:2;
//cout<<"tb "<<tb<<endl;
//cout<<"0.7tBo "<<0.7*tBo<<endl;
//cout<<"pp "<<pp<<endl;
switch (pp) {
case 1:
maxPos(sage,nage) = 1./(1.+mfexp(-(age-maxPos501)/maxPossd1));
maxPos(sage,nage) *= (narea-sarea);
maxPos(sage,nage) += sarea;
cout<<"high B"<<endl;
break;
case 2:
maxPos(sage,nage) = 1./(1.+mfexp(-(age-maxPos502)/maxPossd2));
maxPos(sage,nage) *= (narea-sarea);
maxPos(sage,nage) += sarea;
cout<<"low B"<<endl;
break;
}
return(maxPos);
}
const T nonparametric(const T &x, const T &selparms)
{
int x2 = x.indexmax();
dvar_vector selex(1,x2);
for ( int i = 1; i <= x2; i++ )
{
//selex(i) = 1.0 / (1.0 + mfexp(-selparms(i)));
//selex(i) = mfexp(selparms(i)) / (1.0 + mfexp(selparms(i)));
selex(i) = mfexp(selparms(i));
}
//dvariable temp = selex(x2);
dvariable temp = max(selex);
//selex /= temp;
return selex;
}
dvariable mult_likelihood(const dmatrix &o, const dvar_matrix &p, dvar_matrix &nu,
const dvariable &log_vn)
{
// kludge to ensure observed and predicted matrixes are the same size
if(o.colsize()!=p.colsize() || o.rowsize()!=p.rowsize())
{
cerr<<"Error in multivariate_t_likelihood, observed and predicted matrixes"
" are not the same size\n";
ad_exit(1);
}
dvariable vn = mfexp(log_vn);
dvariable ff = 0.0;
int r1 = o.rowmin();
int r2 = o.rowmax();
int c1 = o.colmin();
int c2 = o.colmax();
for(int i = r1; i <= r2; i++ )
{
dvar_vector sobs = vn * o(i)/sum(o(i)); //scale observed numbers by effective sample size.
ff -= gammln(vn);
for(int j = c1; j <= c2; j++ )
{
if( value(sobs(j)) > 0.0 )
ff += gammln(sobs(j));
}
ff -= sobs * log(TINY + p(i));
dvar_vector o1=o(i)/sum(o(i));
dvar_vector p1=p(i)/sum(p(i));
nu(i) = elem_div(o1-p1,sqrt(elem_prod(p1,1.-p1)/vn));
}
// exit(1);
return ff;
}
// Half normal.
// Order of detpars: g0, sigma.
dvariable detfn_hn (double x, const dvar_vector &detpars, dvariable ss_resid)
{
return detpars(1)*mfexp(-square(x)/(2*square(detpars(2))));
}
// Log-link threshold.
// Order of detpars: shape1, shape2, scale.
dvariable detfn_logth (double x, const dvar_vector &detpars, dvariable ss_resid)
{
return 0.5 - 0.5*(2*cumd_norm((detpars(1) - mfexp(detpars(2) - detpars(3)*x))*pow(2,0.5)) - 1);
}
// Hazard rate.
// Order of detpars: g0, sigma, z.
dvariable detfn_hr (double x, const dvar_vector &detpars, dvariable ss_resid)
{
return detpars(1)*(1 - mfexp(-pow(x/detpars(2),-detpars(3))));
}
void model_parameters::move_grow_die(void)
{
dvariable tB;
for(int i=2;i<=ntstp;i++)
{
//if(i>12)exit(1);
switch (indmonth(i)) {
case 1:
Nage(i)(sage) = (So*SB(i-nmon)/(1.+beta*SB(i-nmon)))*mfexp(wt(indyr(i))*err);
for(int a = sage+1;a<=nage;a++)
{
Nage(i)(a) = Nage(i-1)(a-1)*mfexp(-(m+q*Effage(i-1)(a-1)*va(a-1))/12);
}
break;
default:
Nage(i) = elem_prod(Nage(i-1),mfexp(-(m+q*elem_prod(Effage(i-1),va))/12));
break;
}
VulB(i) = elem_prod(elem_prod(Nage(i),va),wa);
SB(i) = elem_prod(Nage(i),fa)*wa/2;
maxPos.initialize();
tB = Nage(i)*wa;
calcmaxpos(tB);
//cout<<"maxPos "<<maxPos<<endl;
varPos = maxPos*cvPos;
PosX(i) = minPos + (maxPos - minPos) * (0.5+0.5*sin(indmonth(i)*PI/6 - mo*PI/6));
VBarea(i,sarea) = VulB(i)* (cnorm(areas(sarea)+0.5,PosX(i),varPos));
for(int r = sarea+1;r <= narea;r++)
{
VBarea(i)(r) = VulB(i)* (cnorm(areas(r)+0.5,PosX(i),varPos)-cnorm(areas(r)-0.5,PosX(i),varPos));
NAreaAge(i)(r) = elem_prod(Nage(i)(sage,nage),(cnorm(areas(r)+0.5,PosX(i),varPos)-cnorm(areas(r)-0.5,PosX(i),varPos)));
}
//VBarea(i,narea) = VulB(i)* (1.0-cnorm(areas(narea)-0.5,PosX(i),varPos));
NationVulB(i,1) = sum(VBarea(i)(sarea,sarea+nationareas(1)-1));
NationVulB(i,2) = sum(VBarea(i)(sarea+nationareas(1),narea));
dvar_vector tmp1(sarea,narea);
dvar_vector tmp2(sarea,narea);
for(int rr= sarea; rr<=narea; rr++)
{
tmp1(rr)= VBarea(i)(rr)/ (NationVulB(i)(indnatarea(rr)) + 1);
tmp2(rr) = tmp1(rr)*TotEffyear(indnatarea(rr))(indyr(i));
Effarea(i)(rr) = tmp2(rr)*TotEffmonth(indnatarea(rr))(indmonth(i));
}
for(int a = sage; a<=nage;a++)
{
dvar_vector propVBarea(sarea,narea);
for(int rr =sarea; rr<=narea; rr++)
{
propVBarea(rr) = (cnorm(areas(rr)+0.5,PosX(i),varPos)-cnorm(areas(rr)-0.5,PosX(i),varPos))(a-sage+1);
EffNatAge(indnatarea(rr))(i)(sage-2) = i;
EffNatAge(indnatarea(rr))(i)(sage-1) = indnatarea(rr);
EffNatAge(indnatarea(rr))(i)(a) += Effarea(i)(rr)* propVBarea(rr);
}
//cout<<"propVBarea "<<propVBarea<<endl;
//cout<<"Effarea(1) "<<Effarea(1)<<endl;
Effage(i)(a) = Effarea(i)*propVBarea;
}
for(int r = sarea+1;r <= narea-1;r++)
{
for(int a = sage; a<=nage;a++)
{
CatchAreaAge(i)(r)(a) = q*Effarea(i)(r)*va(a)/(q*Effarea(i)(r)*va(a)+m)*(1-mfexp(-(q*Effarea(i)(r)*va(a)+m)))*NAreaAge(i)(r)(a);
CatchNatAge(i)(indnatarea(r))(a)+= CatchAreaAge(i)(r)(a);
}
}
}
}
const T logSelexMeanOne(const T &x) const
{
T y = log(gsm::coefficients(x, this->GetSelCoeffs()));
y -= log(mean(mfexp(y)));
return y;
}
const T logSelexMeanOne(const T &x) const
{
T y = log(gsm::pdubnorm<T>(x, this->GetSL(), this->GetS50(), this->GetSR()));
y -= log(mean(mfexp(y)));
return y;
}
const T logSelexMeanOne(const T &x) const
{
T y = log(gsm::plogis95<T>(x, this->GetS50(), this->GetS95()));
y -= log(mean(mfexp(y)));
return y;
}
const T logSelexMeanOne(const T &x) const
{
T y = log(gsm::plogis(x, this->GetMean(), this->GetStd()));
y -= log(mean(mfexp(y)));
return y;
}
