#include "structs.h"

#include <math.h> // math functions

#include <gsl/gsl_rng.h> // random number generator functions

#include <gsl/gsl_randist.h> // random number distributions

#include <gsl/gsl_blas.h>

#include <gsl/gsl_matrix.h>

#include <gsl/gsl_vector.h>

#include <gsl/gsl_odeiv.h>

#include <gsl/gsl_errno.h>

double* predOnRes(struct foodweb nicheweb, const double y[], double* resPred)

{

int S = nicheweb.S;

int Y = nicheweb.Y;

int Rnum = nicheweb.Rnum;

gsl_vector *network = nicheweb.network; // Inhalt: A+linksA+Y+linksY+Massen+Trophische_Level = (Rnum+S)²+1+Y²+1+(Rnum+S)+S

double lambda = nicheweb.lambda;

double aij = nicheweb.aij;

double hand = nicheweb.hand;

int i,j,l;

/* Massen rausholen */

gsl_vector_view A_view = gsl_vector_subvector(network, 0, (Rnum+S)*(Rnum+S)); // Fressmatrix A als Vektor

gsl_matrix_view EA_mat = gsl_matrix_view_vector(&A_view.vector, (Rnum+S), (Rnum+S)); // A als Matrix_view

gsl_matrix *EAmat = &EA_mat.matrix; // A als Matrix

gsl_vector_view M_vec = gsl_vector_subvector(network, ((Rnum+S)*(Rnum+S))+1+(Y*Y)+1, (Rnum+S)); // Massenvektor

gsl_vector *Mvec = &M_vec.vector;

double ytemp[(Rnum+S)*Y]; // tempvector for populations and efforts

for(i=0;i<(Rnum+S)*Y;i++)

ytemp[i]=y[i];

/* Alles view_array */

/* Auslesen von ytemp = y[]; sind Population */

gsl_vector_view yfd_vec=gsl_vector_view_array(ytemp,(Rnum+S)*Y);

gsl_vector *yfdvec=&yfd_vec.vector; // populations and efforts for later use

/* Initialisierungen */

gsl_matrix *AFgsl=gsl_matrix_calloc(Rnum+S, Rnum+S); // matrix of foraging efforts

gsl_matrix *Emat=gsl_matrix_calloc(Rnum+S, Rnum+S); // gsl objects for calculations of populations

gsl_vector *tvec=gsl_vector_calloc(Rnum+S);

gsl_vector *rvec=gsl_vector_calloc(Rnum+S);

gsl_vector *svec=gsl_vector_calloc(Rnum+S);

gsl_vector *resPredTemp=gsl_vector_calloc(Rnum+S);

for(l=0;l<Y;l++) // start of patch solving

{

/* Initialisierungen */

gsl_matrix_set_zero(AFgsl); // reset gsl objects for every patch

gsl_matrix_set_zero(Emat);

gsl_vector_set_zero(tvec);

gsl_vector_set_zero(rvec);

gsl_vector_set_zero(svec);

/* Je Vektoren von (Res+S) Elementen */

/* yfdvec enthält die Population */

gsl_vector_view y_vec=gsl_vector_subvector(yfdvec,(Rnum+S)*l,(Rnum+S));

gsl_vector *yvecpre=&y_vec.vector;

/* Kopie von EAmat erstellen */

gsl_matrix_memcpy(AFgsl,EAmat);

for(i=0;i<Rnum+S;i++)

{

/* Nehme i-te Zeile aus A */

gsl_vector_view tempp=gsl_matrix_row(AFgsl,i);

/* Summiere Absolutwerte der Zeile */

double temp1;

temp1=gsl_blas_dasum(&tempp.vector);

if(temp1!=0)

{

/* Teile die Einträge, die nicht- Null sind durch Anzahl an nicht-Nullen in dieser Zeile*/

/* und setzte diesen Wert dann an den entsprechenden Platz */

/* Man erhält also eine prozentuale Verbindung */

for(j=0;j<Rnum+S;j++)

gsl_matrix_set(AFgsl,i,j,(gsl_matrix_get(AFgsl,i,j)/temp1));

}

}

/* aij ist Attackrate; AFgsl ist jetzt normiert- also fij */

gsl_matrix_memcpy(Emat,EAmat);

gsl_matrix_scale(Emat,aij); // Emat(i,j) = a(i,j)

gsl_matrix_mul_elements(Emat,AFgsl); // Emat(i,j) = a(i,j)*f(i,j)

/* hand = handling time */

/* Berechnung wie aus Paper */

gsl_vector_memcpy(svec,yvecpre); // s(i)=y(i)

gsl_vector_scale(svec, hand); // s(i)=y(i)*h

gsl_blas_dgemv(CblasNoTrans,1,Emat,svec,0,rvec); // r(i)=Sum_k h*a(i,k)*f(i,k)*y(k)

gsl_vector_add_constant(rvec,1); // r(i)=1+Sum_k h*a(i,k)*f(i,k)*y(k)

gsl_vector_memcpy(tvec,Mvec); // t(i)=masse(i)^(-0.25)

gsl_vector_div(tvec,rvec); // t(i)=masse(i)^(-0.25)/(1+Sum_k h*a(i,k)*f(i,k)*y(k))

gsl_vector_mul(tvec,yvecpre); // t(i)=masse(i)^(-0.25)*y(i)/(1+Sum_k h*a(i,k)*f(i,k)*y(k))

//gsl_vector_memcpy(ydottemp,ydotvec);

for(i=Rnum; i<Rnum+S; i++)

{

/* Benötige nur Resource */

gsl_vector_set(yvecpre,i,0);

}

gsl_blas_dgemv(CblasNoTrans,lambda,Emat,yvecpre,0,resPredTemp); // ydot(i) = Sum_j lambda*a(i,j)*f(i,j)*y(j)

gsl_vector_mul(resPredTemp,tvec); // ydot(i) = Sum_j lambda*a(i,j)*f(i,j)*y(j)*t(i)

resPred[l] = gsl_blas_dasum(resPredTemp); // PredOnRes = Sum_i ydot(i)

}

gsl_matrix_free(Emat);

gsl_matrix_free(AFgsl);

gsl_vector_free(tvec);

gsl_vector_free(rvec);

gsl_vector_free(svec);

gsl_vector_free(resPredTemp);

return 0;

}

double* intraguildPred(struct foodweb nicheweb, const double y[], double* intraPred)

{

int i,j,l;

int S = nicheweb.S;

int Y = nicheweb.Y;

int Rnum = nicheweb.Rnum;

gsl_vector *network = nicheweb.network; // Inhalt: A+linksA+Y+linksY+Massen+Trophische_Level = (Rnum+S)²+1+Y²+1+(Rnum+S)+S

double lambda = nicheweb.lambda;

double aij = nicheweb.aij;

double hand = nicheweb.hand;

/* Massen rausholen */

gsl_vector_view A_view = gsl_vector_subvector(network, 0, (Rnum+S)*(Rnum+S)); // Fressmatrix A als Vektor

gsl_matrix_view EA_mat = gsl_matrix_view_vector(&A_view.vector, (Rnum+S), (Rnum+S)); // A als Matrix_view

gsl_matrix *EAmat = &EA_mat.matrix; // A als Matrix

gsl_vector_view M_vec = gsl_vector_subvector(network, ((Rnum+S)*(Rnum+S))+1+(Y*Y)+1, (Rnum+S)); // Massenvektor

gsl_vector *Mvec = &M_vec.vector; // massvector: M(i)=m^(-0.25)

double ytemp[(Rnum+S)*Y]; // tempvector for populations and efforts

for(i=0;i<(Rnum+S)*Y;i++)

ytemp[i]=y[i];

/* Alles view_array */

/* Auslesen von ytemp = y[]; sind Population */

gsl_vector_view yfd_vec=gsl_vector_view_array(ytemp,(Rnum+S)*Y);

gsl_vector *yfdvec=&yfd_vec.vector; // populations and efforts for later use

/* Initialisierungen */

gsl_matrix *AFgsl=gsl_matrix_calloc(Rnum+S, Rnum+S); // matrix of foraging efforts

gsl_matrix *Emat=gsl_matrix_calloc(Rnum+S, Rnum+S); // gsl objects for calculations of populations

gsl_vector *tvec=gsl_vector_calloc(Rnum+S);

gsl_vector *rvec=gsl_vector_calloc(Rnum+S);

gsl_vector *svec=gsl_vector_calloc(Rnum+S);

gsl_vector *intraPredTemp=gsl_vector_calloc(Rnum+S);

for(l=0;l<Y;l++) // start of patch solving

{

/* Initialisierungen */

gsl_matrix_set_zero(AFgsl); // reset gsl objects for every patch

gsl_matrix_set_zero(Emat);

gsl_vector_set_zero(tvec);

gsl_vector_set_zero(rvec);

gsl_vector_set_zero(svec);

/* Je Vektoren von (Res+S) Elementen */

/* yfdvec enthält die Population */

gsl_vector_view y_vec=gsl_vector_subvector(yfdvec,(Rnum+S)*l,(Rnum+S));

gsl_vector *yvecint=&y_vec.vector;

/* Kopie von EAmat erstellen */

gsl_matrix_memcpy(AFgsl,EAmat);

for(i=0;i<Rnum+S;i++)

{

/* Nehme i-te Zeile aus A */

gsl_vector_view tempp=gsl_matrix_row(AFgsl,i);

/* Summiere Absolutwerte der Zeile */

double temp1;

temp1=gsl_blas_dasum(&tempp.vector);

if(temp1!=0)

{

/* Teile die Einträge, die nicht- Null sind durch Anzahl an nicht-Nullen in dieser Zeile*/

/* und setzte diesen Wert dann an den entsprechenden Platz */

/* Man erhält also eine prozentuale Verbindung */

for(j=0;j<Rnum+S;j++)

gsl_matrix_set(AFgsl,i,j,(gsl_matrix_get(AFgsl,i,j)/temp1));

}

}

/* aij ist Attackrate; AFgsl ist jetzt normiert- also fij */

gsl_matrix_memcpy(Emat,EAmat);

gsl_matrix_scale(Emat,aij); // Emat(i,j) = a(i,j)

gsl_matrix_mul_elements(Emat,AFgsl); // Emat(i,j) = a(i,j)*f(i,j)

/* hand = handling time */

/* Berechnung wie aus Paper */

gsl_vector_set(yvecint,0,0);

printf("y: %f\n",gsl_vector_get(yvecint,0));

gsl_vector_memcpy(svec,yvecint); // s(i)=y(i)

gsl_vector_scale(svec, hand); // s(i)=y(i)*h

gsl_blas_dgemv(CblasNoTrans,1,Emat,svec,0,rvec); // r(i)=Sum_k h*a(i,k)*f(i,k)*y(k)

gsl_vector_add_constant(rvec,1); // r(i)=1+Sum_k h*a(i,k)*f(i,k)*y(k)

gsl_vector_memcpy(tvec,Mvec); // t(i)=masse(i)^(-0.25)

gsl_vector_div(tvec,rvec); // t(i)=masse(i)^(-0.25)/(1+Sum_k h*a(i,k)*f(i,k)*y(k))

gsl_vector_mul(tvec,yvecint); // t(i)=masse(i)^(-0.25)*y(i)/(1+Sum_k h*a(i,k)*f(i,k)*y(k))

gsl_blas_dgemv(CblasNoTrans,lambda,Emat,yvecint,0,intraPredTemp); // ydot(i)=Sum_j lambda*a(i,j)*f(i,j)*y(j)

gsl_vector_mul(intraPredTemp,tvec);

intraPred[l] = gsl_blas_dasum(intraPredTemp);

}

/* Speicher befreien */

gsl_matrix_free(Emat);

gsl_matrix_free(AFgsl);

gsl_vector_free(tvec);

gsl_vector_free(rvec);

gsl_vector_free(svec);

gsl_vector_free(intraPredTemp);

return 0;

}

double* metabolicLoss(struct foodweb nicheweb, const double y[], double* metLoss)

{

int S = nicheweb.S;

int Y = nicheweb.Y;

int Rnum = nicheweb.Rnum;

double alpha = nicheweb.alpha;

gsl_vector *network = nicheweb.network; // Inhalt: A+linksA+Y+linksY+Massen+Trophische_Level = (Rnum+S)²+1+Y²+1+(Rnum+S)+S

int i,l;

/* Massen rausholen */

gsl_vector_view M_vec = gsl_vector_subvector(network, ((Rnum+S)*(Rnum+S))+1+(Y*Y)+1, (Rnum+S)); // Massenvektor

gsl_vector *Mvec = &M_vec.vector;

double ytemp[(Rnum+S)*Y]; // tempvector for populations and efforts

for(i=0;i<(Rnum+S)*Y;i++)

ytemp[i]=y[i];

/* Alles view_array */

/* Auslesen von ytemp = y[]; sind Population */

gsl_vector_view yfd_vec=gsl_vector_view_array(ytemp,(Rnum+S)*Y);

gsl_vector *yfdvec=&yfd_vec.vector; // populations and efforts for later use

/* Initialisierungen */

gsl_vector *svec=gsl_vector_calloc(Rnum+S);

for(l=0;l<Y;l++) // start of patch solving

{

/* Initialisierungen */

gsl_vector_set_zero(svec);

/* yfdvec enthält die Population */

gsl_vector_view y_vec=gsl_vector_subvector(yfdvec,(Rnum+S)*l,(Rnum+S));

gsl_vector *yvecmet=&y_vec.vector;

gsl_vector_memcpy(svec,Mvec);

//printf("svec vorher: %f\n",gsl_vector_get(svec,3));

gsl_vector_scale(svec,alpha); // s(i)=alpha*masse^(-0.25) [svec=Respiration bzw. Mortalitaet]

//printf("svec nachher: %f\n",gsl_vector_get(svec,3));

gsl_vector_set(yvecmet,0,0); // es wird nur der Fluss zur Ressource benötigt

gsl_vector_mul(svec,yvecmet); // s(i) = alpha*masse^(-0.25)*y(i)

metLoss[l] = gsl_blas_dasum(svec);

//printf("metloss %f\n",metLoss[0]);

}

/* Speicher befreien */

gsl_vector_free(svec);

return 0;

}

int kastenFunktion(double x, double y, double z)

{

int flag = 0;

if(x>=y&&x<=z)

{

flag = 1;

}

return(flag);

}

double* functionalDiversity(struct foodweb nicheweb, const double y[], double center[], double intervall[], double* funDiv)

{

int S = nicheweb.S;

int Y = nicheweb.Y;

int Rnum = nicheweb.Rnum;

int i,j,l,max;

double L=10;

double N = 1000;

double h= L/N;

double s;

double M_prey;

double C,I;

for(l=0; l<Y;l++)

{

// int k;

// k=0;

for(j=0;j<N;j++)

{

s=(j)*h-(2);

M_prey=s;

max = 0;

//printf("M_prey : %f\n", M_prey);

for(i=(Rnum+S)*l+Rnum; i<(Rnum+S)*l+(Rnum+S);i++)

{

if(y[i]>1e-5)

{

C = log10(center[i]);

I = log10(intervall[i]);

if(I>=0)

{

// if(M_prey>C-I && M_prey< C+I)

// {

// //printf("k : %i\n",k);

//

// k++;

// }

max += kastenFunktion(M_prey,C-I,C+I);

// printf("In Schleife für positive Intervalle\n");

// printf("kastenFunktion : %i\n", kastenFunktion(M_prey,C+I,C-I));

// printf("max : %i\n", max);

}

else

{

// if(M_prey<=C-I && M_prey>= C+I)

// {

// //printf("k : %i\n",k);

// k++;

// }

max += kastenFunktion(M_prey,C+I,C-I);

// printf("i : %i\n", i);

// if(kastenFunktion(M_prey,C+I,C-I)>0)

// {

// // printf("M_prey : %f\n", M_prey);

// }

}

}

}

//printf("k : %i\n",k);

//printf("max außen : %i\n", max);

if(max>0)

{

max =1;

}

//printf("max Ende: %i\n", max);

funDiv[l] += max*h;

//printf("funDiv: %f\n",funDiv[0]);

}

}

return 0;

}