/* compute the mean, the covariance matrix, and the eigenvectors.
They are stored in the structure itself */
void pca_online_complete (struct pca_online_s * pca)
{
int d = pca->d;
int n = pca->n;
fvec_div_by (pca->mu, d, n);
fvec_div_by (pca->cov, d * d, n);
float * mumut = fvec_new (d*d);
fmat_mul_tr (pca->mu, pca->mu, d, d, 1, mumut);
fvec_sub (pca->cov, mumut, d*d);
free (mumut);
assert(fvec_all_finite(pca->cov,d*d));
pca->eigvec = fmat_new_pca_from_covariance (d, pca->cov, pca->eigval);
}
/* compute the mean and covariance matrix */
void pca_online_cov (struct pca_online_s * pca)
{
int d = pca->d;
int n = pca->n;
fvec_div_by (pca->mu, d, n);
fvec_div_by (pca->cov, d * (long)d, n);
float * mumut = fvec_new (d*(long)d);
fmat_mul_tr (pca->mu, pca->mu, d, d, 1, mumut);
fvec_sub (pca->cov, mumut, d*(long)d);
free (mumut);
fvec_mul_by (pca->cov, d * (long)d, n / (double) (n-1));
assert(fvec_all_finite(pca->cov,d*(long)d));
pca->n = -pca->n;
}
float *fmat_new_pca(int d,int n,const float *v, float *singvals) {
float *cov=fmat_new_covariance(d,n,v,NULL,1);
assert(fvec_all_finite(cov,d*d));
float *evals=singvals;
if(!singvals) evals=fvec_new(d);
float *ret=fmat_new_pca_from_covariance(d,cov,evals);
if(!singvals) free(evals);
free(cov);
return ret;
}