void r_sum_w_x_xprime(double **x, double *w, int n, int p,
double **tmp, double **ans)
{
/*
// given a matrix x (n x p) and a vector w of n
// weights, it computes the matrix
// \sumin w_i x_i x_i'
// need space for p x p "doubles" in tmp
*/
void sum_mat(double **a, double **b, double **c, int n, int m);
void matias_vec_vec(double **a, double *v1, double *v2, int n);
void scalar_mat(double **a, double b, double **c, int n, int m);
void reset_mat(double **a, int n, int m);
register int i;
reset_mat(ans, p, p);
for(i=0; i<n; i++) {
matias_vec_vec(tmp, x[i], x[i], p);
scalar_mat(tmp, w[i], tmp, p, p);
sum_mat(ans, tmp, ans, p, p);
};
}
int main(int argc, char * argv[])
{
parse_args(argc, argv);
const int size = n * n;
int data_size_bytes = size * sizeof(float);
float *mat_a = malloc(data_size_bytes);
float *mat_b = malloc(data_size_bytes);
float *vector;
float *output = malloc(data_size_bytes);
float *expected = malloc(data_size_bytes);
generate_matrix(n, mat_a, range);
generate_matrix(n, mat_b, range);
timing_t timer;
timer_start(&timer);
float *mat_b_trans = malloc(data_size_bytes);
transpose(n, mat_b, mat_b_trans);
for (int i=0; i<n; ++i) {
vector = &mat_b_trans[n*i];
MatMatMultiply(n, mat_a, vector, &output[n*i]);
}
float *output_trans = malloc(data_size_bytes);
transpose(n, output, output_trans);
timer_stop(&timer);
float sum = sum_mat(size, output_trans);
printf("%d %f %ld %ld\n", n, sum, timer.realtime, timer.cputime);
int status = 0;
if (trace == 1) {
printf("\nMatrix A\n");
for (int i=0; i<n; i++){
for (int j=0; j<n; j++){
printf("%f " , mat_a[i*n+j]);
}
printf("\n");
}
printf("\nMatrix B \n");
for (int i=0; i<n; i++){
for (int j=0; j<n; j++){
printf("%f " , mat_b[i*n+j]);
}
printf("\n");
}
printf("\n\nResult\n");
for (int i=0; i<n; i++){
for (int j=0; j<n; j++){
printf("%f " , output[i*n+j]);
}
printf("\n");
}
}
else if (trace == 2) {
multiply_CPU_matrix(n, mat_a, mat_b, expected);
int status = check(size, output_trans, expected);
if (status) {
printf("Test failed.\n");
status = 1;
}
else
printf("Test passed OK!\n");
}
free(mat_a);
free(mat_b);
free(mat_b_trans);
free(output);
free(expected);
free(output_trans);
return status;
}
int main(int argc, char *argv[])
{
FILE *mat;
FILE *vec;
FILE *end;
double main_buf[MAXSIZE];
double main_vec_buf[MAXSIZE];
Cnum mat_buf[MAXSIZE];
Cnum vec_buf[MAXSIZE];
Cnum result[MAXSIZE];
double Row=0, Col=0;
double vec_row;
double mat_RC_data[6];
long mat_in=0;
int j=0;
int thread=atoi(argv[3]);
double final_result[2];
mat = fopen("matrix.dat","rb");
vec = fopen("vector_input.dat","rb");
end = fopen("vector_output.dat","wb");
// exe input number 검사
if (argc == 4 && atoi(argv[1]) && atoi(argv[2]))
printf("input = %d x %d, Thread = %d \n",atoi(argv[1]), atoi(argv[2]),atoi(argv[3]));
else
{
fputs("[Error] Not a correct input", stderr);
exit(1);
}
// 파일 유무 검사
if(mat==NULL)
{
fputs("Matrix File error", stderr);
exit(1);
}
if(vec==NULL)
{
fputs("Vector File error", stderr);
exit(1);
}
start_time_measurement(); //시간측정 시작
// 매트릭스 크기
int point;
for(int i=3;i>0;i--)
{
point = i*4*sizeof(double);
point = -point;
if(fseek(mat, point, SEEK_END)==-1)
{
printf("error\n");
}
fread(&mat_RC_data[j],sizeof(double),2,mat);
Row=mat_RC_data[j]+1;
j++;
Col=mat_RC_data[j]+1;
j++;
//printf("row : %f, col : %f\n",Row,Col);
}
// matrix.dat 행 열값 부분 오류 검사
if(mat_RC_data[4]-mat_RC_data[2]>1)
{
fputs("[ERROR] Matrix File ROW_DATA error", stderr);
exit(1);
}
if(mat_RC_data[2]-mat_RC_data[0]>1)
{
fputs("[ERROR] Matrix File ROW_DATA error", stderr);
exit(1);
}
if(mat_RC_data[5]-mat_RC_data[3]>2)
{
fputs("[ERROR] Matrix File ROW_DATA error", stderr);
exit(1);
}
if(mat_RC_data[3]-mat_RC_data[1]>2)
{
fputs("[ERROR] Matrix File ROW_DATA error", stderr);
exit(1);
}
//커맨드 입력 행열 과 입력받은 매트릭스 비교
if(atoi(argv[1])!=Row)
{
fputs("[ERROR] 입력한 행값과 매트릭스의 행값이 다릅니다.", stderr);
exit(1);
}
if(atoi(argv[2])!=Col)
{
fputs("[ERROR] 입력한 열값과 매트릭스의 열값이 다릅니다.", stderr);
exit(1);
}
printf("전체 열의 값 = %f\n전체 행의 값 = %f \n", Row, Col);
//vec 행렬 행 크기
fseek(vec,0,SEEK_END);
vec_row = ftell(vec)/(sizeof(double)*2);
printf("벡터행렬 행 값 = %f\n",vec_row);
//행렬 크기가 다를 시 오류 메세지 출력
if(Col!=vec_row)
{
fputs("[ERROR] Matrix and Vector are not same", stderr);
exit(1);
}
//행렬값 꺼내서 연산
j=0;
int button=0;
fseek(mat,0,SEEK_SET); //파일 포인터 위치 초기화
fseek(vec,0,SEEK_SET); //파일 포인터 위치 초기화
fseek(end,0,SEEK_SET); //파일 포인터 위치 초기화
for(int k=0; k<Row; k++)
{
//인덱스 초기화
button =0;
j=0;
fseek(vec,0,SEEK_SET); //파일 포인터 위치 초기화
//mat 행렬 가져와서 mat_buf[]에 저장 100개씩 -> ////vec 행의 갯수에 따라로 수정해야함 //// 일단은 100개단위로
for(int i=0; i<Col*4; i++)
{
fread(&main_buf[i], sizeof(double), 1, mat);
//printf("값 : %f ", main_buf[i]);
if(i>3 && i%4==0)
j++;
// 구조체에 값저장
if(button==2)
mat_buf[j].realnum=main_buf[i];
else if(button==3)
{
mat_buf[j].imanum=main_buf[i];
}
button++;
if(button==4)
button=0;
}
//vec 행렬 가져와서 vec_buf[]에 저장
j=0;
for(int y=0; y<Col*2; y++)
{
fread(&main_vec_buf[y],sizeof(double),1,vec);
if(y>1&&y%2==0)
j++;
if(y%2==0)
vec_buf[j].realnum = main_vec_buf[y];
else
{
vec_buf[j].imanum = main_vec_buf[y];
}
}
// mat * vec
/*
for(int i=0; i<Col; i++)
result[i]=mult(mat_buf[i],vec_buf[i]);
*/
mult_mat(mat_buf,vec_buf,result,(int)Col,thread);
result[0]=sum_mat(result,(int)Col);
/*
for(int i=1; i<Col; i++)
{
result[0]=sum(result[0],result[i]);
}
*/
fwrite(&result[0].realnum,sizeof(double),1,end);
fwrite(&result[0].imanum,sizeof(double),1,end);
//printf("%f, %f \n",final_result[0].realnum,final_result[0].imanum);
}
printf("Calculation Complete ");
end_time_measurement(); //시간 측정 끝
fclose(mat);
fclose(vec);
fclose(end);
return 0;
}
double R_rlm_rand(double *X, double *y, int *N, int *P,
int *Boot_Samp, int *Nres,
int *M, int *size_boot, double *ours, double *full,
double *Beta_m, double *Beta_s, double *Scale,
int *Seed, int *calc_full,
double *C, double *Psi_c, int *max_it,
int *converged_mm,
int *groups, int *n_group, int *k_fast_s)
{
void initialize_mat(double **a, int n, int m);
void initialize_vec(double *a, int n);
void R_S_rlm(double *X, double *y, int *n, int *P,
int *nres, int *max_it,
double *SCale, double *beta_s, double *beta_m,
int *converged_mm,
int *seed_rand, double *C, double *Psi_c,
int *Groups, int *N_group, int *K_fast_s);
double Psi_reg(double,double);
double Psi_reg_prime(double,double);
double Chi_prime(double,double);
double Chi(double,double);
void sampler_i(int, int, int *);
int inverse(double **,double **, int);
void matias_vec_vec(double **, double *, double *, int);
void scalar_mat(double **, double, double **, int, int);
void scalar_vec(double *, double, double *, int);
void sum_mat(double **,double **, double **, int, int);
void sum_vec(double *, double *, double *, int);
void dif_mat(double **, double **, double **, int , int );
void dif_vec(double *, double *, double *, int);
void mat_vec(double **, double *, double *, int, int);
void mat_mat(double **, double **, double **, int, int, int);
// void disp_vec(double *, int);
// void disp_mat(double **, int, int);
// void disp_mat_i(int **, int, int);
// void disp_vec(double *, int);
/* double **xb; */
double *Xb, **xb;
int **boot_samp;
double **x, **x2, **x3, **x4, *beta_m, *beta_s,*beta_aux;
double *Fi, *res, *res_s, *w, *ww, dummyscale, scale;
double *v, *v2, *v_aux, *yb; // , timefinish, timestart;
double u,u2,s,c,Psi_constant;
// double test_chi=0, test_psi=0;
int n,p,m,seed; // ,*indices;
int nboot=*size_boot;
// int fake_p = 0;
register int i,j,k;
setbuf(stdout,NULL);
c = *C; Psi_constant = *Psi_c;
n = *N; p = *P; m = *M; seed = *Seed;
boot_samp = (int **) malloc(m * sizeof(int*) );
for(i=0;i<m;i++)
boot_samp[i] = (int*) malloc(nboot *sizeof(int));
// indices = (int *) malloc( n * sizeof(int) );
v = (double *) malloc( p * sizeof(double) );
v2 = (double *) malloc( p * sizeof(double) );
v_aux = (double *) malloc( p * sizeof(double) );
yb = (double *) malloc( n * sizeof(double) );
Xb = (double*) malloc( n * p * sizeof(double) );
x = (double **) malloc ( n * sizeof(double *) );
xb = (double **) malloc ( n * sizeof(double *) );
Fi = (double *) malloc ( n * sizeof(double) );
res = (double *) malloc ( n * sizeof(double) );
res_s = (double *) malloc ( n * sizeof(double) );
ww = (double *) malloc ( n * sizeof(double) );
w = (double *) malloc ( n * sizeof(double) );
x2 = (double **) malloc ( p * sizeof(double *) );
x3 = (double **) malloc ( p * sizeof(double *) );
x4 = (double **) malloc ( p * sizeof(double *) );
beta_aux = (double *) malloc( p * sizeof(double) );
beta_m = (double *) malloc( p * sizeof(double) );
beta_s = (double *) malloc( p * sizeof(double) );
for(i=0;i<n;i++) {
x[i] = (double*) malloc (p * sizeof(double) );
xb[i] = (double*) malloc ((p+1) * sizeof(double) );
};
for(i=0;i<p;i++) {
x2[i] = (double*) malloc (p * sizeof(double) );
x3[i] = (double*) malloc (p * sizeof(double) );
x4[i] = (double*) malloc (p * sizeof(double) );
};
/* copy X into x for easier handling */
for(i=0;i<n;i++)
for(j=0;j<p;j++)
x[i][j]=X[j*n+i];
/* calculate robust regression estimates */
for(i=0;i<m;i++)
for(j=0;j<nboot;j++)
boot_samp[i][j]=Boot_Samp[j*m+i]-1;
R_S_rlm(X, y, N, P, Nres, max_it, &scale, Beta_s, Beta_m,
converged_mm, &seed, &c,
Psi_c, groups, n_group, k_fast_s);
*Scale = scale;
/* get M-fitted values in Fi */
mat_vec(x,Beta_m,Fi,n,p);
/* get residuals of M-est in res */
dif_vec(y,Fi,res,n);
/* get S-fitted values in res_s */
mat_vec(x,Beta_s,res_s,n,p);
/* get residuals of S-est in res_s */
dif_vec(y,res_s,res_s,n);
/* set auxiliary matrices to zero */
initialize_mat(x3, p, p);
initialize_mat(x4, p, p);
initialize_vec(v, p);
u2 = 0.0;
/* calculate correction matrix */
for(i=0;i<n;i++) {
u = res[i]/scale ;
w[i] = Psi_reg(u,Psi_constant)/res[i];
matias_vec_vec(x2,x[i],x[i],p);
scalar_mat(x2,Psi_reg_prime(u,Psi_constant),
x2,p,p);
sum_mat(x3,x2,x3,p,p);
matias_vec_vec(x2,x[i],x[i],p);
scalar_mat(x2,w[i],x2,p,p);
sum_mat(x4,x2,x4,p,p);
scalar_vec(x[i],Psi_reg_prime(u,Psi_constant)*u,v_aux,p);
sum_vec(v,v_aux,v,p);
u2 += Chi_prime(u, c) * u;
};
/* scalar_vec(v, .5 * (double) (n-p) * scale / u2 , v, p); */
scalar_vec(v, .5 * (double) n * scale / u2 , v, p);
inverse(x3,x2,p);
mat_mat(x2,x4,x3,p,p,p);
mat_vec(x2,v,v2,p,p);
scalar_mat(x3,scale,x3,p,p);
/* the correction matrix is now in x3 */
/* the correction vector is now in v2 */
/* start the bootstrap replications */
for(i=0;i<m;i++) {
/* change the seed! */
++seed;
// sampler_i(n,nboot,indices);
// for(j=0;j<nboot; j++)
// indices[j]=boot_samp[i][j];
/* get pseudo observed y's */
for(j=0;j<nboot;j++) /* xb[j][p] = */
yb[j] = y[boot_samp[i][j]];
for(j=0;j<nboot;j++)
for(k=0;k<p;k++) {
// xb[j][k] = x[boot_samp[i][j]][k];
// Xb[k*nboot+j] = X[k*n + indices[j]];
Xb[k*nboot+j] = x[boot_samp[i][j]][k];
xb[j][k] = Xb[k*nboot+j];
};
/* calculate full bootstrap estimate */
if( *calc_full == 1 )
R_S_rlm(Xb,yb,&nboot,P,Nres,max_it,&dummyscale,
beta_s,beta_m,converged_mm,&seed,&c,
Psi_c, groups, n_group, k_fast_s);
/* void R_S_rlm(double *X, double *y, int *n, int *P,
int *nres, int *max_it,
double *SCale, double *beta_s, double *beta_m,
int *converged_mm,
int *seed_rand, double *C, double *Psi_c,
int *Groups, int *N_group, int *K_fast_s) */
/* double *C, double *Psi_c, int *max_it,
int *groups, int *n_group, int *k_fast_s); */
// HERE
/* disp_mat(xb, nboot,p); */
// disp_vec(yb,nboot);
// Rprintf("\nfull scale: %f", dummyscale);
/* calculate robust bootsrap */
scalar_vec(v,0.0,v,p); /* v <- 0 */
scalar_mat(x2,0.0,x2,p,p); /* x2 <- 0 */
s = 0.0;
for(j=0;j<nboot;j++) {
scalar_vec(xb[j],yb[j]*w[boot_samp[i][j]],v_aux,p);
sum_vec(v,v_aux,v,p);
matias_vec_vec(x4,xb[j],xb[j],p);
scalar_mat(x4,w[boot_samp[i][j]],x4,p,p);
sum_mat(x2,x4,x2,p,p);
s += Chi(res_s[boot_samp[i][j]] / scale , c);
};
/* s = s * scale / .5 / (double) (nboot - p) ; */
s = s * scale / .5 / (double) n;
inverse(x2,x4,p); /* x4 <- x2^-1 */
mat_vec(x4,v,v_aux,p,p); /* v_aux <- x4 * v */
dif_vec(v_aux,Beta_m,v_aux,p); /* v_aux <- v_aux - beta_m */
/* v has the robust bootstrapped vector, correct it */
mat_vec(x3,v_aux,v,p,p); /* v <- x3 * v_aux */
scalar_vec(v2,s-scale,v_aux,p);
sum_vec(v_aux,v,v,p);
/* store the betas (splus-wise!) */
for(j=0;j<p;j++) {
ours[j*m+i]=v[j];
if( *calc_full == 1 )
// full[j*m+i]=beta_m[j]-Beta_m[j];
full[j*m+i]=beta_m[j];
};
};
for(i=0;i<m;i++)
free(boot_samp[i]);
free(boot_samp);
for(i=0;i<n;i++) {
free(x[i]);
free(xb[i]);
};
for(i=0;i<p;i++) {
free(x2[i]);
free(x3[i]);
free(x4[i]);
};
free(x) ;free(x2);free(xb);
free(x3);free(x4);
free(beta_aux);free(beta_m);free(beta_s);
free(w);free(ww);free(Fi);free(res);
free(v);free(v2);free(v_aux);free(yb);
free(res_s);
free(Xb);
return(0);
}
