void main()
{
char left,right;
lcd("Press SW1");
sw1_press();
while(1)
{
left = in_d(0);
right = in_d(1);
if(left==1 && right==1)
{
forward(10);
}
else if(left==0 && right==1)
{
backward(1000);
turn_right(800);
}
else if(left==1 && right==0)
{
backward(1000);
turn_left(800);
}
else if(left==0 && right==0)
{
backward(1000);
turn_left(1500);
}
}
}
void LSH_DFE::generate_input_data(size_t features_num, size_t elements_num){
srand(unsigned(time(NULL)));
in_d = InputData(elements_num, features_num);
for(size_t i=0; i<elements_num; i++)
for(size_t j=0; j<features_num; j++)
in_d(i, j) = float(rand()) / float(RAND_MAX) * formalize_max;
}
void LSH_DFE::init_data_structure(){
input_dfe = new float[in_d.size1() * in_d.size2()];
int index = 0;
for(unsigned int i=0; i<in_d.size1(); i++)
for(unsigned int j=0; j<in_d.size2(); j++)
input_dfe[index++] = in_d(i, j);
m_new_grid_cpu.resize(in_d.size1());
m_new_grid_dfe.resize(in_d.size1());
hash_set_dimensions();
}
void LSH_DFE::rehash_data_projection(){
// locality sensitive hashing using CPU
// use int8_t to represent the result of every sub hash function
// 128 / 8 = 16, which should be equal to DOUT
int8_t temp[DOUT];
std::vector<float> mult(DOUT);
for(unsigned int i=0; i<in_d.size1(); i++){
for(unsigned int j=0; j<DOUT; j++){
float data = 0.0f;
for(unsigned int k=0; k<in_d.size2(); k++)
data += in_d(i, k) * m_hash(j, k);
mult[j] = data;
}
for(unsigned int j=0; j<DOUT; j++)
temp[j] = (int8_t)(mult[j]/ m_cell_width);
memcpy(&m_new_grid_cpu[i], temp, sizeof(DimType));
}
}
