public void prepareLevel0() {
m_instance_data.begin(Buffer.READ_WRITE);
Buffer attributes = m_instance_data.attributes();
// init min max
for (int i = 0; i < m_leaf_node_ids.length; ++i) m_leaf_node_ids[i] = 0;
for (int i = 0; i < m_min_temp.length; ++i) m_min_temp[i] = Double.MAX_VALUE;
for (int i = 0; i < m_max_temp.length; ++i) m_max_temp[i] = -Double.MAX_VALUE;
/* for (int i = 0; i < m_instance_data.rows(); ++i)
{
for (int att = 0; att < m_num_attributes; ++att)
{
int node_offset = (int)( att );
double value = attributes.read( (att + i * m_num_attributes) * DirectMemory.DOUBLE_SIZE);
System.out.println("Att " + att + " value "+ value);
double min =m_min_temp[node_offset];
double max =m_max_temp[node_offset];
if (value > max)
m_max_temp[node_offset]= value;
if (value < min)
m_min_temp[node_offset]= value;
}
}
*/
m_instance_data.commit();
}
public KDTreeBufferCPU(
Instances dataset, Context ctx, int tree_depth, DenseInstanceBuffer buffer) {
m_instance_data = buffer;
m_tree_depth = tree_depth;
m_leaf_node_ids = new int[buffer.rows()];
m_branch_nodes = (int) (Math.pow(2, tree_depth + 1) - 1) - (int) Math.pow(2, tree_depth);
m_dataset = dataset;
m_num_attributes = dataset.numAttributes();
m_max_temp = new double[m_dataset.numAttributes() * m_branch_nodes];
m_min_temp = new double[m_dataset.numAttributes() * m_branch_nodes];
m_node_split_dim = new int[m_branch_nodes];
m_node_split_value = new double[m_branch_nodes];
}
/**
* CPU build implementation
*
* @param level
*/
public void buildCPU(int level) {
int prev_level = level - 1;
long start_node = 0;
long end_node = 0;
if (level > 1) {
start_node = max_level_id(level - 2) + 1;
end_node = max_level_id(level - 1);
}
m_instance_data.begin(Buffer.READ_WRITE);
// find min_max
for (int i = 0; i < m_instance_data.rows(); ++i) {
int node_id = m_leaf_node_ids[i];
if (!(node_id >= start_node && node_id <= end_node))
throw new RuntimeException("All instances should be in the leaves");
for (int att = 0; att < m_num_attributes; ++att) {
int node_offset = node_id * m_num_attributes + att;
Buffer attributes = m_instance_data.attributes();
double value = attributes.read((att + i * m_num_attributes) * DirectMemory.DOUBLE_SIZE);
double min = m_min_temp[node_offset];
double max = m_max_temp[node_offset];
if (value > max) m_max_temp[node_offset] = value;
if (value < min) m_min_temp[node_offset] = value;
}
}
// split by mean of widest dim
int split_candidate = -1;
double max_range = -1;
for (int node = (int) start_node; node <= end_node; ++node) {
// 1 thread
for (int att = 0; att < m_num_attributes; ++att) {
double min_val = m_min_temp[(node * m_num_attributes + att)];
double max_val = m_max_temp[(node * m_num_attributes + att)];
double abs_min_val = m_min_temp[att];
double abs_max_val = m_max_temp[att];
double range = (abs_max_val - abs_min_val);
if (range > 0) {
double node_range = (max_val - min_val) / range;
if (node_range > max_range) {
split_candidate = att;
max_range = node_range;
}
}
}
m_node_split_dim[node] = split_candidate;
m_node_split_value[node] =
m_min_temp[(node * m_num_attributes + split_candidate)] + max_range / 2;
}
for (int i = 0; i < m_instance_data.rows(); ++i) {
int node_id = m_leaf_node_ids[i];
int split_dim = m_node_split_dim[node_id];
double split_value = m_node_split_value[node_id];
double att_value =
m_instance_data
.attributes()
.read((split_dim + i * m_num_attributes) * DirectMemory.DOUBLE_SIZE);
if (att_value > split_value) m_leaf_node_ids[i] = (int) child(node_id) + 1;
else m_leaf_node_ids[i] = (int) child(node_id);
}
m_instance_data.commit();
}
