static void ann_predict_meanstd(uint16_t *pixels, float mean, float std)
{
int i, j;
float ah[6];
float x, x_val, y_val;
for (i = 0; i < num_hidden; i++) {
ah[i] = BH(i);
}
uint16_t subsample;
for (i = 0; i < num_subsample; i++) {
subsample = pixels[i];
x = (float)(subsample - mean) / std;
for (j = 0; j < num_hidden; j++) {
float wih_tmp = WIH(i, j);
ah[j] += x * wih_tmp;
}
}
x_val = BO(0);
y_val = BO(1);
for (i = 0; i < num_hidden; i++) {
x_val += WHO(i, 0) * tanh_approx(ah[i]);
y_val += WHO(i, 1) * tanh_approx(ah[i]);
}
// pred = global for storing prediction values
pred[PRED_X] = (unsigned short)((x_val * 112) + 0.5);
pred[PRED_Y] = (unsigned short)((y_val * 111) + 0.5);
return;
}
///////////////////////////////////////////////////////////////////
// CLOSEST IN
///////////////////////////////////////////////////////////////////
Vec3f ClosestIn(Simplex& P){
assert(P.GetSize() > 0);
if(P.GetSize() == 1) return P.at(0);
else if(P.GetSize() == 2){ //We have a line.
Vector3f AO(-P.at(1)[0], -P.at(1)[1], -P.at(1)[2]);
Vector3f AB(P.at(0)[0] - P.at(1)[0], P.at(0)[1] - P.at(1)[1], P.at(0)[2] - P.at(1)[2]);
Vector3f BO(-P.at(0)[0], -P.at(0)[1], -P.at(0)[2]);
float v = (AB.dot(AO))/(AB.dot(AO) + (-AB).dot(BO));
return (P.at(1)*(1-v) + (P.at(0))*v);
}else{//We have a triangle
Vector3f A(P.at(2)[0], P.at(2)[1], P.at(2)[2]);
Vector3f B(P.at(1)[0], P.at(1)[1], P.at(1)[2]);
Vector3f C (P.at(0)[0], P.at(0)[1], P.at(0)[2]);
Vector3f AB = B-A;
Vector3f AC = C-A;
Vector3f N = AB.cross(AC);
Vector3f Nab = N.cross(AB);
Vector3f Nac = N.cross(AC);
float v = (-A).dot(Nac)/((AB).dot(Nac));
float w = (-A).dot(Nab)/((AC).dot(Nab));
float u = 1-v-w;
return (P.at(2)*u + P.at(1)*v + P.at(0)*w);
}
}
void test_oid_and_interpolation() {
char *oid_s = "010203040506070809101112";
bcon oid_bc[] = { "_id", BO(""), "user_id", BO("010203040506070809101112"), "admin_id", BPO(&oid_s), BEND };
if ( verbose ) { putchar('\t'); bcon_print( oid_bc ); putchar('\n'); }
test_bson_from_bcon( oid_bc, BCON_OK, BSON_VALID );;
}
