structmatrix soverrelaxation(structmatrix *A, structmatrix *b){
const unsigned int MAXITER=100;
const double TOL=1e-6;
double *xp=calloc(A->nrows,sizeof(double));//init guess 0s
double *x= calloc(A->nrows,sizeof(double));//
structmatrix XP=creatematrix(xp
,A->nrows,1//solns in col vector
,endt(MATDOUBLE),rowmjr);
structmatrix X=creatematrix(x
,A->nrows,1//solns in col vector
,endt(MATDOUBLE),rowmjr);
fpidx idxA= getidxingfunc( A);
fpidx idxb= getidxingfunc( b);
fpidx idxX= getidxingfunc(&X);
fpidx idxXP=getidxingfunc(&XP);
#define Xv(ri,ci) *(double*) idxX( &ri,&ci,&X)
#define XPv(ri,ci) *(double*) idxXP(&ri,&ci,&XP)
#define Av(ri,ci) *(double*) idxA( &ri,&ci, A)
#define bv(ri,ci) *(double*) idxb( &ri,&ci, b)
unsigned int zero=0;
double omega=.5;//b/w 0 and 2
unsigned int k=0;
while(k<MAXITER){
unsigned ri;
for(ri=0;ri<A->nrows;ri++){
double newsumsoln=0;unsigned int sumi=0;
for(sumi=0;(sumi<(ri));sumi++)//tricky iter
{newsumsoln=newsumsoln-Av(ri,sumi)*Xv(sumi,zero);}
double oldsumsoln=0;
for(sumi=ri+1;(sumi<A->nrows);sumi++)
{oldsumsoln=oldsumsoln-Av(ri,sumi)*XPv(sumi,zero);}
Xv(ri,zero)=(1/Av(ri,ri))*(newsumsoln+oldsumsoln+bv(ri,zero))*omega
+(1-omega)*XPv(ri,zero);
}
double normofdiff=0;
for(ri=0;ri<X.nrows;ri++){
normofdiff+=pow((Xv(ri,zero)-XPv(ri,zero)),2);}
normofdiff=pow(normofdiff,.5);
if(normofdiff<TOL){printf("converged in %d iterations\n",k+1);return X;}
for(ri=0;ri<X.nrows;ri++){XPv(ri,zero)=Xv(ri,zero);}
k++; }
free(XP.data);
return X;
#undef Xv
#undef XPv
#undef Av
#undef bv
}
double l2r_l2_ranksvm_fun::fun(double *w)
{
int q,i,j;
double f = 0;
int l = prob->l;
int w_size = get_nr_variable();
selectiontree *T;
Xv(w,z);
for (q=0;q<nr_query;q++)
{
int *perm_q = &perm[start[q]];
id_and_value *order_perm_q = order_perm[q];
for (i=0;i<count[q];i++)
{
order_perm_q[i].id = perm_q[i];
order_perm_q[i].value = z[perm_q[i]];
}
qsort(order_perm_q, count[q], sizeof(id_and_value), compare_values);
T = new selectiontree(nr_class[q]);
j = 0;
for (i=0;i<count[q];i++)
{
while (j<count[q] && (1 - order_perm_q[j].value + order_perm_q[i].value>0))
{
T->insert_node(int_y[order_perm_q[j].id], order_perm_q[j].value);
j++;
}
T->larger(int_y[order_perm_q[i].id], &l_plus[order_perm_q[i].id], &alpha_plus[order_perm_q[i].id]);
}
delete T;
j = count[q] - 1;
T = new selectiontree(nr_class[q]);
for (i=count[q]-1;i>=0;i--)
{
while (j>=0 && (1 - order_perm_q[i].value + order_perm_q[j].value>0))
{
T->insert_node(int_y[order_perm_q[j].id], order_perm_q[j].value);
j--;
}
T->smaller(int_y[order_perm_q[i].id], &l_minus[order_perm_q[i].id], &alpha_minus[order_perm_q[i].id]);
}
delete T;
}
for(i=0;i<w_size;i++)
f += w[i] * w[i];
f /= 2.0;
for(i=0;i<l;i++)
f += C * (z[i] * ((l_plus[i] + l_minus[i]) * z[i] - alpha_minus[i] - alpha_plus[i] - 2 * (l_minus[i] - l_plus[i])) + l_minus[i]);
return(f);
}
void init_env(t_env *e)
{
int i;
struct rlimit rlp;
X(-1, getrlimit(RLIMIT_NOFILE, &rlp), "getrlimit");
e->maxfd = rlp.rlim_cur;
e->fds = (t_fd*)Xv(NULL, malloc(sizeof(*e->fds) * e->maxfd), "malloc");
i = 0;
while (i < e->maxfd)
{
clean_fd(&e->fds[i]);
i++;
}
}
void l2_lr_fun::Hv(double *s, double *Hs)
{
int i;
int l=prob->l;
int n=prob->n;
double *wa = new double[l];
Xv(s, wa);
for(i=0;i<l;i++)
wa[i] = C[i]*D[i]*wa[i];
XTv(wa, Hs);
for(i=0;i<n;i++)
Hs[i] = s[i] + Hs[i];
delete[] wa;
}
void l2r_lr_fun::Hv(double *s, double *Hs)
{
int i;
int l=prob->l;
int w_size=get_nr_variable();
double *wa = new double[l];
Xv(s, wa);
for(i=0;i<l;i++)
wa[i] = C[i]*D[i]*wa[i];
XTv(wa, Hs);
for(i=0;i<w_size;i++)
Hs[i] = s[i] + Hs[i];
delete[] wa;
}
void l2r_l2_ranksvm_fun::Hv(double *s, double *Hs)
{
int q,i,j;
int w_size = get_nr_variable();
int l = prob->l;
double *wa = new double[l];
selectiontree *T;
double* alpha_plus_minus;
alpha_plus_minus = new double[l];
Xv(s, wa);
for (q=0;q<nr_query;q++)
{
id_and_value *order_perm_q = order_perm[q];
T = new selectiontree(nr_class[q]);
j = 0;
for (i=0;i<count[q];i++)
{
while (j<count[q] && (1 - order_perm_q[j].value + order_perm_q[i].value>0))
{
T->insert_node(int_y[order_perm_q[j].id],wa[order_perm_q[j].id]);
j++;
}
alpha_plus_minus[order_perm_q[i].id] = T->xv_larger(int_y[order_perm_q[i].id]);
}
delete T;
j = count[q] - 1;
T = new selectiontree(nr_class[q]);
for (i=count[q]-1;i>=0;i--)
{
while (j>=0 && (1 - order_perm_q[i].value + order_perm_q[j].value>0))
{
T->insert_node(int_y[order_perm_q[j].id], wa[order_perm_q[j].id]);
j--;
}
alpha_plus_minus[order_perm_q[i].id] += T->xv_smaller(int_y[order_perm_q[i].id]);
}
delete T;
}
for (i=0;i<l;i++)
wa[i] = wa[i] * (l_plus[i] + l_minus[i]) - alpha_plus_minus[i];
delete[] alpha_plus_minus;
XTv(wa, Hs);
delete[] wa;
for(i=0;i<w_size;i++)
Hs[i] = s[i] + 2 * C * Hs[i];
}
void selection_rank_fun::Hv(double *s, double *Hs)
{
int i,j,k;
int w_size=get_nr_variable();
int l=prob->l;
double *wa = new double[l];
selectiontree *T;
double* alpha_plus_minus;
alpha_plus_minus = new double[l];
Xv(s, wa);
for (i=0;i<nr_subset;i++)
{
T=new selectiontree(nr_class[i]);
k=0;
for (j=0;j<count[i];j++)
{
while (k<count[i]&&(1-pi[i][j].value+pi[i][k].value>0))
{
T->insert_node(int_y[pi[i][k].id],wa[pi[i][k].id]);
k++;
}
alpha_plus_minus[pi[i][j].id]=T->vector_sum_smaller(int_y[pi[i][j].id]);
}
delete T;
k=count[i]-1;
T = new selectiontree(nr_class[i]);
for (j=count[i]-1;j>=0;j--)
{
while (k>=0&&(1+pi[i][j].value-pi[i][k].value>0))
{
T->insert_node(int_y[pi[i][k].id],wa[pi[i][k].id]);
k--;
}
alpha_plus_minus[pi[i][j].id]+=T->vector_sum_larger(int_y[pi[i][j].id]);
}
delete T;
}
for (i=0;i<l;i++)
wa[i]=wa[i]*((double)l_plus[i]+(double)l_minus[i])-alpha_plus_minus[i];
delete[] alpha_plus_minus;
XTv(wa, Hs);
delete[] wa;
for(i=0;i<w_size;i++)
Hs[i] = s[i] + 2*C*Hs[i];
}
double l2loss_svm_fun::fun(double *w)
{
int i;
double f=0;
int *y=prob->y;
int l=prob->l;
int n=prob->n;
Xv(w, z);
for(i=0;i<l;i++)
{
z[i] = y[i]*z[i];
double d = 1-z[i];
if (d > 0)
f += C[i]*d*d;
}
f = 2*f;
for(i=0;i<n;i++)
f += w[i]*w[i];
f /= 2.0;
return(f);
}
double l2r_l2_svc_fun::fun(double *w)
{
int i;
double f=0;
int *y=prob->y;
int l=prob->l;
int w_size=get_nr_variable();
Xv(w, z);
for(i=0;i<l;i++)
{
z[i] = y[i]*z[i];
double d = 1-z[i];
if (d > 0)
f += C[i]*d*d;
}
f = 2*f;
for(i=0;i<w_size;i++)
f += w[i]*w[i];
f /= 2.0;
return(f);
}
double l2_lr_fun::fun(double *w)
{
int i;
double f=0;
int *y=prob->y;
int l=prob->l;
int n=prob->n;
Xv(w, z);
for(i=0;i<l;i++)
{
double yz = y[i]*z[i];
if (yz >= 0)
f += C[i]*log(1 + exp(-yz));
else
f += C[i]*(-yz+log(1 + exp(yz)));
}
f = 2*f;
for(i=0;i<n;i++)
f += w[i]*w[i];
f /= 2.0;
return(f);
}
double l2r_lr_fun::fun(double *w)
{
int i;
double f=0;
int *y=prob->y;
int l=prob->l;
int w_size=get_nr_variable();
Xv(w, z);
for(i=0;i<l;i++)
{
double yz = y[i]*z[i];
if (yz >= 0)
f += C[i]*log(1 + exp(-yz));
else
f += C[i]*(-yz+log(1 + exp(yz)));
}
f = 2*f;
for(i=0;i<w_size;i++)
f += w[i]*w[i];
f /= 2.0;
return(f);
}
double selection_rank_fun::fun(double *w, long int *num_data)
{
int i,j,k;
double f=0.0;
int l=prob->l;
int w_size=get_nr_variable();
selectiontree *T;
Xv(w,z);
*num_data += l;
for (i=0;i<nr_subset;i++)
{
for (j=0;j<count[i];j++)
{
pi[i][j].id = perm[j+start[i]];
pi[i][j].value = z[perm[j+start[i]]];
}
qsort(pi[i], count[i], sizeof(id_and_value), compare_id_and_value);
T=new selectiontree(nr_class[i]);
k=0;
for (j=0;j<count[i];j++)
{
while (k<count[i]&&(1-pi[i][j].value+pi[i][k].value>0))
{
T->insert_node(int_y[pi[i][k].id],pi[i][k].value);
k++;
}
T->count_smaller(int_y[pi[i][j].id],&l_minus[pi[i][j].id], &alpha_minus[pi[i][j].id]);
}
delete T;
k=count[i]-1;
T = new selectiontree(nr_class[i]);
for (j=count[i]-1;j>=0;j--)
{
while (k>=0&&(1+pi[i][j].value-pi[i][k].value>0))
{
T->insert_node(int_y[pi[i][k].id],pi[i][k].value);
k--;
}
T->count_larger(int_y[pi[i][j].id],&l_plus[pi[i][j].id], &alpha_plus[pi[i][j].id]);
}
delete T;
}
long long nSV = 0;
for (i=0;i<l;i++)
nSV += l_plus[i];
//info("nSV = %ld\n",nSV);
for(i=0;i<w_size;i++)
{
f += w[i]*w[i];
}
f /= 2.0;
for(i=0;i<l;i++)
{
f += C*(z[i]*((l_plus[i]+l_minus[i])*z[i]-alpha_minus[i]-alpha_plus[i]-2*(l_minus[i]-l_plus[i]))+l_minus[i]);
}
return (f);
}
void selection_rank_fun::Hv(double *s, double *Hs)
{
int i,j,k;
int w_size=get_nr_variable();
int l=prob->l;
double *wa = new double[l];
selectiontree *T;
double* alpha_plus_minus;
alpha_plus_minus = new double[l];
double begin, end;
begin = omp_get_wtime();
Xv(s, wa);
end = omp_get_wtime();
Xviter++;
Xvtime += end-begin;
begin = omp_get_wtime();
#pragma omp parallel for default(shared) private(i, j, k, T)
for (i=0;i<nr_subset;i++)
{
T=new selectiontree(nr_class[i]);// nr_class[i]is the i-th query's number of different label
k=0;
for (j=0;j<count[i];j++)
{
while (k<count[i]&&(1-pi[i][j].value+pi[i][k].value>0))
{
T->insert_node(int_y[pi[i][k].id],wa[pi[i][k].id]);
k++;
}
alpha_plus_minus[pi[i][j].id]=T->vector_sum_smaller(int_y[pi[i][j].id]);
}
delete T;
k=count[i]-1;
T = new selectiontree(nr_class[i]);
for (j=count[i]-1;j>=0;j--)
{
while (k>=0&&(1+pi[i][j].value-pi[i][k].value>0))
{
T->insert_node(int_y[pi[i][k].id],wa[pi[i][k].id]);
k--;
}
alpha_plus_minus[pi[i][j].id]+=T->vector_sum_larger(int_y[pi[i][j].id]);
}
delete T;
}
end = omp_get_wtime();
AViter++;
AVtime += end-begin;
#pragma omp parallel for default(shared) private(i)
for (i=0;i<l;i++)
wa[i]=wa[i]*((double)l_plus[i]+(double)l_minus[i])-alpha_plus_minus[i];
delete[] alpha_plus_minus;
begin = omp_get_wtime();
XTv(wa, Hs);
end = omp_get_wtime();
XTviter++;
XTvtime += end-begin;
delete[] wa;
#pragma omp parallel for default(shared) private(i)
for(i=0;i<w_size;i++)
Hs[i] = s[i] + 2*C*Hs[i];
}
double selection_rank_fun::fun(double *w)
{
int i,j,k;
double f = 0.0;
int l=prob->l;
int w_size=get_nr_variable();
selectiontree *T;
double begin,end;
begin = omp_get_wtime();
Xv(w,z);
end = omp_get_wtime();
Xviter++;
Xvtime += end-begin;
begin = omp_get_wtime();
#pragma omp parallel for default(shared) private(i, j, k, T) //construct the OST
for (i=0;i<nr_subset;i++)
{
for (j=0;j<count[i];j++)
{
pi[i][j].id = perm[j+start[i]];
pi[i][j].value = z[perm[j+start[i]]];
}
qsort(pi[i], count[i], sizeof(id_and_value), compare_id_and_value);
T=new selectiontree(nr_class[i]);
k=0;
for (j=0;j<count[i];j++)
{
while (k<count[i]&&(1-pi[i][j].value+pi[i][k].value>0))
{
T->insert_node(int_y[pi[i][k].id],pi[i][k].value);
k++;
}
T->count_smaller(int_y[pi[i][j].id],&l_minus[pi[i][j].id], &alpha_minus[pi[i][j].id]);
}
delete T;
k=count[i]-1;
T = new selectiontree(nr_class[i]);
for (j=count[i]-1;j>=0;j--)
{
while (k>=0&&(1+pi[i][j].value-pi[i][k].value>0))
{
T->insert_node(int_y[pi[i][k].id],pi[i][k].value);
k--;
}
T->count_larger(int_y[pi[i][j].id],&l_plus[pi[i][j].id], &alpha_plus[pi[i][j].id]);
}
delete T;
}
end = omp_get_wtime();
AViter++;
AVtime += end-begin;
long long nSV = 0;
#pragma omp parallel for default(shared) reduction(+:nSV) private(i)
for (i=0;i<l;i++)
nSV += l_plus[i];
//info("nSV = %ld\n",nSV);
for(i=0;i<w_size;i++)
{
f += w[i]*w[i];
}
f /= 2.0;
#pragma omp parallel for default(shared) private(i) reduction(+:f)
for(i=0;i<l;i++)
{
f += C*(z[i]*((l_plus[i]+l_minus[i])*z[i]-alpha_minus[i]-alpha_plus[i]-2.0*(l_minus[i]-l_plus[i]))+l_minus[i]);
}
return (f);
}
//todo put convergence into one function
structmatrix conjugategradient(structmatrix *A,structmatrix *b){
const unsigned int MAXITER=100;
const MATDOUBLE TOL=1e-6;
MATDOUBLE *xp=calloc(A->nrows,sizeof(MATDOUBLE));//init guess 0s
MATDOUBLE *x= malloc(A->nrows*sizeof(MATDOUBLE));//
structmatrix XP=creatematrix(xp
,A->nrows,1//solns in col vector
,endt(MATDOUBLE),rowmjr);
structmatrix X=creatematrix(x
,A->nrows,1//solns in col vector
,endt(MATDOUBLE),rowmjr);
structmatrix rP=copymatrix(b); //previous error
structmatrix pP=copymatrix(b); //CG vec
structmatrix r=creatematrix(malloc(sizeof(MATDOUBLE)*rP.nrows)
,rP.nrows,1
,endt(MATDOUBLE),rowmjr);
structmatrix p=creatematrix(malloc(sizeof(MATDOUBLE)*pP.nrows)
,pP.nrows,1
,endt(MATDOUBLE),rowmjr);
fpidx idxA= getidxingfunc( A);
fpidx idxb= getidxingfunc( b);
fpidx idxX= getidxingfunc(&X);
fpidx idxXP=getidxingfunc(&XP);
fpidx idxrP=getidxingfunc(&rP);
fpidx idxpP=getidxingfunc(&pP);
fpidx idxr =getidxingfunc(&r );
fpidx idxp =getidxingfunc(&p );
#define Xv(ri,ci) *(double*) idxX( &ri,&ci,&X)
#define XPv(ri,ci) *(double*) idxXP(&ri,&ci,&XP)
#define Av(ri,ci) *(double*) idxA( &ri,&ci, A)
#define bv(ri,ci) *(double*) idxb( &ri,&ci, b)
#define rPv(ri,ci) *(double*) idxrP( &ri,&ci, &rP)
#define pPv(ri,ci) *(double*) idxb( &ri,&ci, &pP)
#define rv(ri,ci) *(double*) idxA( &ri,&ci, &r)
#define pv(ri,ci) *(double*) idxb( &ri,&ci, &p)
//result definition
#define ApPv(ri,ci) *(double*) idxApP(&ri,&ci,&ApP)
unsigned int zero=0;
unsigned int k=0;
while(k<MAXITER){
double alpha, beta;//scalars to compute in each interatin
structmatrix rPT=(vecT(&rP)),pPT=vecT(&pP);
structmatrix rPTrP=matrixmatrixmuldbl(&rPT,&rP);//1x1
structmatrix ApP=matrixmatrixmuldbl(A,&pP);// vec nrows
fpidx idxApP =getidxingfunc(&ApP);
double alphan=*(double*) rPTrP.data;
double alphad=*(double*) (matrixmatrixmuldbl(&pPT,&ApP)).data;
alpha=alphan/alphad;//alpha new
unsigned int ri;
for(ri=0;ri<XP.nrows;ri++){
Xv(ri,zero)=XPv(ri,zero)+alpha*pPv(ri,zero); //new x approx soln
rv(ri,zero)=rPv(ri,zero)-alpha*ApPv(ri,zero);//new r error
}
structmatrix rT=vecT(&r);
structmatrix rTr=matrixmatrixmuldbl(&rT,&r);
beta=(*(double*) rTr.data)/(*(double*) rPTrP.data); //scalar/scalar
for(ri=0;ri<p.nrows;ri++){
pv(ri,zero)=rv(ri,zero)+beta*pPv(ri,zero);
}
double normofr=0;
for(ri=0;ri<X.nrows;ri++){normofr+=pow(rv(ri,zero),2);}
normofr=pow(normofr,.5);
if(normofr<TOL){printf("converged\n in %d iterations\n",k+1);return X;}
//previous=current
for(ri=0;ri<X.nrows;ri++){
XPv(ri,zero)=Xv(ri,zero);
pPv(ri,zero)=pv(ri,zero);
rPv(ri,zero)=rv(ri,zero);
}
/* todo does not work if i add these free statements
does the memory get freed with each loop? i thought it would not!*/
/*
free(rPT.data);
free(rPTrP.data);
free(ApP.data);
free(rT.data);
free(rTr.data);
*/
k++;}
free(XP.data);
free(rP.data);
free(pP.data);
free(r.data);
free(p.data);
return X;
#undef Xv
#undef XPv
#undef Av
#undef bv
#undef rPv
#undef pPv
#undef rv
#undef pv
#undef ApPv
}
