openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for over 200 supported car makes and models.
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//
// Excerpt from fastcluster_R.cpp
//
// Copyright: Daniel Müllner, 2011 <http://danifold.net>
//
struct pos_node {
t_index pos;
int node;
};
void order_nodes(const int N, const int * const merge, const t_index * const node_size, int * const order) {
/* Parameters:
N : number of data points
merge : (N-1)×2 array which specifies the node indices which are
merged in each step of the clustering procedure.
Negative entries -1...-N point to singleton nodes, while
positive entries 1...(N-1) point to nodes which are themselves
parents of other nodes.
node_size : array of node sizes - makes it easier
order : output array of size N
Runtime: Θ(N)
*/
auto_array_ptr<pos_node> queue(N/2);
int parent;
int child;
t_index pos = 0;
queue[0].pos = 0;
queue[0].node = N-2;
t_index idx = 1;
do {
--idx;
pos = queue[idx].pos;
parent = queue[idx].node;
// First child
child = merge[parent];
if (child<0) { // singleton node, write this into the 'order' array.
order[pos] = -child;
++pos;
}
else { /* compound node: put it on top of the queue and decompose it
in a later iteration. */
queue[idx].pos = pos;
queue[idx].node = child-1; // convert index-1 based to index-0 based
++idx;
pos += node_size[child-1];
}
// Second child
child = merge[parent+N-1];
if (child<0) {
order[pos] = -child;
}
else {
queue[idx].pos = pos;
queue[idx].node = child-1;
++idx;
}
} while (idx>0);
}
#define size_(r_) ( ((r_<N) ? 1 : node_size[r_-N]) )
template <const bool sorted>
void generate_R_dendrogram(int * const merge, double * const height, int * const order, cluster_result & Z2, const int N) {
// The array "nodes" is a union-find data structure for the cluster
// identites (only needed for unsorted cluster_result input).
union_find nodes(sorted ? 0 : N);
if (!sorted) {
std::stable_sort(Z2[0], Z2[N-1]);
}
t_index node1, node2;
auto_array_ptr<t_index> node_size(N-1);
for (t_index i=0; i<N-1; ++i) {
// Get two data points whose clusters are merged in step i.
// Find the cluster identifiers for these points.
if (sorted) {
node1 = Z2[i]->node1;
node2 = Z2[i]->node2;
}
else {
node1 = nodes.Find(Z2[i]->node1);
node2 = nodes.Find(Z2[i]->node2);
// Merge the nodes in the union-find data structure by making them
// children of a new node.
nodes.Union(node1, node2);
}
// Sort the nodes in the output array.
if (node1>node2) {
t_index tmp = node1;
node1 = node2;
node2 = tmp;
}
/* Conversion between labeling conventions.
Input: singleton nodes 0,...,N-1
compound nodes N,...,2N-2
Output: singleton nodes -1,...,-N
compound nodes 1,...,N
*/
merge[i] = (node1<N) ? -static_cast<int>(node1)-1
: static_cast<int>(node1)-N+1;
merge[i+N-1] = (node2<N) ? -static_cast<int>(node2)-1
: static_cast<int>(node2)-N+1;
height[i] = Z2[i]->dist;
node_size[i] = size_(node1) + size_(node2);
}
order_nodes(N, merge, node_size, order);
}