int model::load_training_data(const dataset &ds)
{
int nrow, ncol;
nrow = ds.ins_num();
ncol = ds.fea_num();
if (nrow <= 0 || ncol < 1) {
ULIB_FATAL("invalid training data dimensions");
return -1;
}
if (nrow > FLAGS_max_num_examples)
nrow = FLAGS_max_num_examples;
if (alloc_training_data(nrow, ncol)) {
ULIB_FATAL("couldn't allocate training data");
return -1;
}
double tavg = 0;
double tvar = 0;
for (int i = 0; i < nrow; ++i) {
double t = ds.get_tgv(i);
tavg += t;
tvar += t*t;
gsl_vector_set(_tv, i, t);
for (int j = 0; j < ncol; ++j)
gsl_matrix_set(_fm, i, j, ds.get_fea(i, j));
}
_t_avg = tavg/nrow;
_t_std = sqrt(tvar/nrow - _t_avg*_t_avg);
return 0;
}
void line2list(struct list_head *head, const char *file)
{
FILE *fp;
struct str_ent *p;
char *line = NULL;
size_t n;
int nl = 0;
fp = fopen(file, "r");
if (fp == NULL) {
ULIB_FATAL("cannot open %s", file);
exit(EXIT_FAILURE);
}
while (getline(&line, &n, fp) > 0) {
p = (struct str_ent *) malloc(sizeof(struct str_ent));
if (p == NULL) {
ULIB_FATAL("cannot new entry");
exit(EXIT_FAILURE);
}
list_add_tail(&p->aaa, head);
p->str = line;
line = NULL;
++nl;
}
free(line);
fclose(fp);
ULIB_NOTICE("%d line(s) has been loaded", nl);
}
int model::get_col_mean()
{
size_t nrow = _fm->size1;
size_t ncol = _fm->size2;
gsl_vector_free(_col_mean);
gsl_vector *mean = gsl_vector_alloc(ncol);
if (mean == NULL) {
ULIB_FATAL("couldn't allocate vector");
return -1;
}
for (size_t j = 0; j < ncol; ++j) {
double sum = 0;
for (size_t i = 0; i < nrow; ++i)
sum += gsl_matrix_get(_fm, i, j);
sum /= nrow;
gsl_vector_set(mean, j, sum);
}
_col_mean = mean;
return 0;
}
int model::alloc_training_data(int nrow, int ncol)
{
gsl_vector_free(_tv);
gsl_matrix_free(_fm);
_tv = gsl_vector_alloc(nrow);
if (_tv == NULL) {
ULIB_FATAL("couldn't allocate target value vector");
return -1;
}
_fm = gsl_matrix_alloc(nrow, ncol);
if (_fm == NULL) {
ULIB_FATAL("couldn't allocate feature matrix");
_tv = NULL;
return -1;
}
return 0;
}
int main()
{
ULIB_DEBUG("debug log");
ULIB_WARNING("warning log");
ULIB_NOTICE("notice log");
ULIB_FATAL("fatal log");
printf("passed\n");
return 0;
}
int dataset::get_target(gsl_vector *v) const
{
int nrow = ins_num();
if ((int)v->size != nrow) {
ULIB_FATAL("dataset dims do not match the target vector");
return -1;
}
for (int i = 0; i < nrow; ++i)
gsl_vector_set(v, i, get_tgv(i));
return 0;
}
int dataset::get_matrix(gsl_matrix *m) const
{
int nrow = ins_num();
int ncol = fea_num();
if ((int)m->size1 != nrow
|| (int)m->size2 != ncol) {
ULIB_FATAL("dataset dims do not match the output matrix");
return -1;
}
for (int i = 0; i < nrow; ++i)
for (int j = 0; j < ncol; ++j)
gsl_matrix_set(m, i, j, get_fea(i, j));
return 0;
}
int model::get_col_sd()
{
size_t nrow = _fm->size1;
size_t ncol = _fm->size2;
gsl_vector_free(_col_sd);
gsl_vector *sd = gsl_vector_alloc(ncol);
if (sd == NULL) {
ULIB_FATAL("couldn't allocate vector");
return -1;
}
double k = sqrt(nrow);
for (size_t j = 0; j < ncol; ++j) {
gsl_vector_const_view cv = gsl_matrix_const_column(_fm, j);
double d = gsl_blas_dnrm2(&cv.vector);
gsl_vector_set(sd, j, d/k);
}
_col_sd = sd;
return 0;
}
int model::predict(const dataset &tds, gsl_matrix **pp)
{
int ret = -1;
gsl_matrix *mat = NULL;
gsl_matrix *ptv = NULL;
gsl_matrix *km1 = NULL;
gsl_matrix *km2 = NULL;
gsl_matrix *res = NULL;
gsl_matrix *stm = NULL;
gsl_vector_view avg_col;
gsl_vector_view dv;
if (tds.ins_num() <= 0 || tds.fea_num() != (int)_col_mean->size) {
ULIB_FATAL("invalid test dimensions, (ins_num=%d,fea_num=%d)",
tds.ins_num(), tds.fea_num());
goto done;
}
mat = gsl_matrix_alloc(tds.ins_num(), tds.fea_num());
if (mat == NULL) {
ULIB_FATAL("couldn't allocate test feature matrix");
goto done;
}
ptv = gsl_matrix_alloc(tds.ins_num(), 2);
if (ptv == NULL) {
ULIB_FATAL("couldn't allocate prediction matrix");
goto done;
}
if (tds.get_matrix(mat)) {
ULIB_FATAL("couldn't get test matrix");
goto done;
}
dbg_print_mat(mat, "Test Matrix:");
zero_out_mat(mat);
norm_mat(mat);
dbg_print_mat(mat, "Normalized Test Matrix:");
km1 = comp_kern_mat(mat, _fm, _kern);
if (km1 == NULL) {
ULIB_FATAL("couldn't compute test1 kernel matrix");
goto done;
}
dbg_print_mat(km1, "Test Kernel Matrix:");
km2 = comp_kern_mat(mat, mat, _kern);
if (km2 == NULL) {
ULIB_FATAL("couldn't compute test2 kernel matrix");
goto done;
}
dbg_print_mat(km1, "Test Kernel Matrix:");
dv = gsl_matrix_diagonal(km2);
res = gsl_matrix_alloc(km1->size1, _ikm->size2);
if (res == NULL) {
ULIB_FATAL("couldn't allocate temporary matrix");
goto done;
}
stm = gsl_matrix_alloc(km2->size1, km2->size2);
if (stm == NULL) {
ULIB_FATAL("couldn't allocate std matrix");
goto done;
}
gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, km1, _ikm, 0.0, res);
gsl_blas_dgemm(CblasNoTrans, CblasTrans, 1.0, res, km1, 0.0, stm);
gsl_matrix_sub(km2, stm);
dbg_print_mat(res, "Predictive Matrix:");
avg_col = gsl_matrix_column(ptv, 0);
gsl_blas_dgemv(CblasNoTrans, 1.0, res, _tv, 0.0, &avg_col.vector);
gsl_vector_add_constant(&avg_col.vector, _t_avg);
gsl_matrix_scale(km2, _t_std*_t_std);
gsl_vector_add_constant(&dv.vector, _noise_var);
for (size_t i = 0; i < km2->size1; ++i)
gsl_matrix_set(ptv, i, 1, sqrt(gsl_vector_get(&dv.vector, i)));
*pp = ptv;
ptv = NULL;
ret = 0;
done:
gsl_matrix_free(mat);
gsl_matrix_free(ptv);
gsl_matrix_free(km1);
gsl_matrix_free(km2);
gsl_matrix_free(res);
gsl_matrix_free(stm);
return ret;
}
int model::train(const dataset &ds)
{
int ret = -1;
gsl_matrix *km = NULL;
gsl_matrix *ikm = NULL;
gsl_permutation *perm = NULL;
gsl_vector_view dv;
gsl_matrix_free(_ikm);
if (load_training_data(ds)) {
ULIB_FATAL("couldn't load training data");
goto done;
}
dbg_print_mat(_fm, "Feature Matrix:");
if (get_col_mean()) {
ULIB_FATAL("couldn't get feature column means");
goto done;
}
zero_out_mat(_fm);
if (get_col_sd()) {
ULIB_FATAL("couldn't get feature column standard deviations");
goto done;
}
norm_mat(_fm);
dbg_print_mat(_fm, "Normalized Feature Matrix:");
km = comp_kern_mat(_fm, _kern);
dbg_print_mat(km, "Kernel Matrix:");
if (km == NULL) {
ULIB_FATAL("couldn't compute kernel matrix");
goto done;
}
dv = gsl_matrix_diagonal(km);
gsl_vector_add_constant(&dv.vector, _noise_var);
ikm = gsl_matrix_alloc(km->size1, km->size2);
if (ikm == NULL) {
ULIB_FATAL("couldn't allocate cost model");
goto done;
}
int signum;
perm = gsl_permutation_alloc(ikm->size1);
if (perm == NULL) {
ULIB_FATAL("couldn't allocate cost model");
goto done;
}
gsl_linalg_LU_decomp(km, perm, &signum);
gsl_linalg_LU_invert(km, perm, ikm);
gsl_vector_add_constant(_tv, -_t_avg);
_ikm = ikm;
ikm = NULL;
ret = 0;
done:
gsl_permutation_free(perm);
gsl_matrix_free(km);
gsl_matrix_free(ikm);
return ret;
}
