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NCBI C++ ToolKit: src/algo/cobalt/clusterer.cpp Source File

);

);

);

(dmat(elem, *elem_it) >

) {

= dmat(elem, *elem_it);

+= dmat(elem, *elem_it);

(vector<double>, it, vals) {

/= (double)vals.size();

= dist > current_dist ? dist : current_dist;

);

(num_elements == 1) {

(num_elements == 2) {

dist = (*m_DistMatrix)(0, 1) / 2.0;

max_dist = 0.0;

(

=0;

< num_elements - 1;

++) {

(

j=

+1;j < num_elements;j++) {

max_dist = (*m_DistMatrix)(

, j);

(max_dist <= max_diam) {

(

=0;

< (

)num_elements;

++) {

vector<bool> used_entry(num_elements,

);

(

=0;

< num_elements;

++) {

clusters[

].AddElement((

)

);

vector<TPhyTreeNode*> nodes(num_elements);

(

=0;

< nodes.size();

++) {

vector< vector<double> > dists_to_root(num_elements);

num_clusters = num_elements;

(num_clusters > 1) {

(!used_entry[min_i] && min_i < num_elements) {

(!used_entry[min_j] && min_j < num_elements) {

(min_j >= num_elements) {

}

(min_j >= num_elements && min_i < num_elements);

(do_trees || (min_i < num_elements && min_j < num_elements));

(

=0;

< num_elements - 1;

++) {

(

j=

+1;j < num_elements;j++) {

(!used_entry[

] || !used_entry[j]) {

(dmat(

, j) < dmat(min_i, min_j)) {

(used_entry[min_i] && used_entry[min_j]);

(dmat(min_i, min_j) > max_diam) {

&& clusters[min_i].

() == 1 && clusters[min_j].

() == 1) {

new_min_j = 0;

((!used_entry[new_min_j] || new_min_j == min_j

|| new_min_j == min_i

|| clusters[new_min_j].

() == 1)

&& new_min_j < num_elements) {

(new_min_j < num_elements) {

(

j=new_min_j+1;j < num_elements;j++) {

(!used_entry[j] || clusters[j].

() == 1

|| j == min_j || j == min_i) {

(dmat(min_i, j) < dmat(min_i, new_min_j)) {

(new_min_j < num_elements) {

(clusters[min_i].

() > 0 && clusters[min_j].

() > 0);

(min_i < num_elements && min_j < num_elements);

left = min_i;

right = min_j;

new_root->

(nodes[left]);

new_root->

(nodes[right]);

mean_dist_to_root_left =

(dists_to_root[left]);

mean_dist_to_root_right =

(dists_to_root[right]);

left_edge_length = dist - mean_dist_to_root_left;

right_edge_length = dist - mean_dist_to_root_right;

left_edge_length = left_edge_length > 0.0 ? left_edge_length : 0.0;

= right_edge_length > 0.0 ? right_edge_length : 0.0;

nodes[left]->GetValue().SetDist(left_edge_length);

nodes[right]->GetValue().SetDist(right_edge_length);

(dists_to_root[left].

()) {

dists_to_root[left].push_back(dist);

*it += left_edge_length;

(dists_to_root[right].

()) {

dists_to_root[right].push_back(dist);

*it += right_edge_length;

nodes[min_i] = new_root;

nodes[min_j] =

;

(vector<double>, it, dists_to_root[min_j]) {

dists_to_root[min_i].push_back(*it);

dists_to_root[min_j].clear();

used_entry[min_j] =

;

(!do_trees || !nodes[min_j]);

(

=0;i < min_i && min_i > 0;

++) {

(!used_entry[

]) {

dmat(

, min_i) =

(clusters[

], included_cluster,

dmat(

, min_i), dist_method);

dmat(min_i,

) = dmat(

, min_i);

(

j=min_i+1;j < num_elements;j++) {

(!used_entry[j]) {

dmat(min_i, j) =

(clusters[j], included_cluster,

dmat(min_i, j), dist_method);

dmat(j, min_i) = dmat(min_i, j);

clusters[min_j].clear();

(

=0;

< num_elements;

++) {

(used_entry[

]) {

it->AddElement(*elem);

);

(it->first != it->second);

(

[cluster_id].GetMaxDistance() < it->weight) {

[cluster_id].SetMaxDistance(it->weight);

(vector<int>, it, cluster) {

.push_back(it->m_Tree);

dist = link.

/ 2.0;

[cluster_id].m_DistToRoot.push_back(dist);

[cluster_id].m_DistToRoot.push_back(dist);

sum_dist = 0.0;

ave_dist_to_root

= sum_dist / (double)

[cluster_id].m_DistToRoot.size();

d = (distance - ave_dist_to_root) / 2.0;

old_root->

().SetDist(d > 0.0 ? d : 0.0);

node->

().SetDist(d > 0.0 ? d : 0.0);

[cluster_id].m_DistToRoot.push_back(d);

vector<int> el(1, elem);

left_dist_to_root, right_dist_to_root;

left_dist_to_root = sum / (double)cluster1.

();

right_dist_to_root = sum / (double)cluster2.

();

left_dist = dist - left_dist_to_root;

right_dist = dist - right_dist_to_root;

left->

().SetDist(left_dist > 0.0 ? left_dist : 0.0);

right->

().SetDist(right_dist > 0.0 ? right_dist : 0.0);

(cluster1.

.capacity() < num_elements) {

+ (

)(0.3 * num_elements));

(vector<int>, it, cluster2) {

& dist)

trees.push_back(*it);

trees.push_back(*it);

= "__1cEncbiGcobaltKCClustererMReleaseTrees6MrnDstdGvector4Cpn0AJCTreeNode4n0AMCPhyNodeData_n0AVCDefaultNodeKeyGetter4n0E_____n0DJallocator4C5_____v_"

(index < 0 || index >= (

)

.size()) {

);

(index < 0 || index >= (

)

.size()) {

);

cluster->SetPrototype(cluster->FindCenterElement(*

));

);

(

=0;

< cluster.

() - 1;

++) {

(

j=

+1;j < cluster.

();j++) {

mat(

, j) = mat(j,

) = (*m_DistMatrix)(cluster[

], cluster[j]);

);

);

(m_Elements.empty()) {

(m_Elements.size() == 1) {

m_Elements[0];

vector<double> sum_distance;

sum_distance.resize(m_Elements.size());

(

=0;

< m_Elements.size();

++) {

(

j=0;j < m_Elements.size();j++) {

dist += dmatrix(m_Elements[

], m_Elements[j]);

sum_distance[

] = dist;

min_index = 0;

(

=1;

< sum_distance.size();

++) {

(sum_distance[

] < sum_distance[min_index]) {

m_Elements[min_index];

Exceptions for CClusterer class.

int FindCenterElement(const TDistMatrix &dmatrix) const

Find element that is closest to the center of the cluster.

void clear(void)

Removes all elements from the cluster.

size_t size(void) const

Get cluster size.

TPhyTreeNode * m_Tree

Cluster tree root.

void AddElement(int el)

Add element to the cluster.

vector< int > m_Elements

List of indeces of cluster elements.

int operator[](size_t index) const

Get element.

vector< double > m_DistToRoot

Distances between cluster elements and tree root.

void SetMaxDistance(double dist)

Set maximum distance in cluster.

vector< TPhyTreeNode * > & GetTrees(void)

Get list of trees for clusters.

list< int > m_UnusedEntries

void ComputeClustersFromLinks(void)

Compute clusters using graph of distances between elements.

int GetClusterId(int elem) const

Find id of cluster to which given element belongs.

bool x_CanAddElem(int cluster_id, int elem, double &dist) const

Check whether element can be added to the cluster.

void ReleaseTrees(vector< TPhyTreeNode * > &trees)

Get list of trees for clusters and release ownership to caller.

@ eDist

Clusters can be joined if there is a link between at least one pair of elements.

@ eClique

Clusters can be joined if there is a link between all pairs of their elements.

EDistMethod

Method for computing distance between clusters.

@ eCompleteLinkage

Maximum distance between elements.

@ eAverageLinkage

Avegrae distance between elements.

TPhyTreeNode * ReleaseTree(int index=0)

Get cluster tree and release ownership to caller.

shared_ptr< TDistMatrix > m_DistMatrix

void Reset(void)

Clear clusters and distance matrix.

const TSingleCluster & GetSingleCluster(size_t index) const

Get list of elements of a specified cluster.

CNcbiMatrix< double > TDistMatrix

CSingleCluster TSingleCluster

const TPhyTreeNode * GetTree(int index=0) const

Get tree for specific cluster.

void x_JoinElements(const CLinks::SLink &link)

Join two elements and form a cluster.

vector< int > m_ClusterId

void SetDistMatrix(const TDistMatrix &dmat)

Set new distance matrix.

const TDistMatrix & GetDistMatrix(void) const

Get distance matrix.

void SetLinks(CRef< CLinks > links)

Set distance links.

void x_JoinClustElem(int cluster_id, int elem, double dist)

Add element to a cluster.

void Run(void)

Cluster elements.

~CClusterer()

Destructor.

void x_JoinClusters(int cluster1_id, int cluster2_id, double dist)

Join two clusters.

void ComputeClusters(double max_diam, EDistMethod dist_method=eCompleteLinkage, bool do_trees=true, double infinity=-1.0)

Compute clusters.

void x_Init(void)

Initialize parameters.

vector< TSingleCluster > TClusters

bool x_CanJoinClusters(int cluster1_id, int cluster2_id, double &dist) const

Check whether two clusters can be joined.

void x_CreateCluster(int elem)

Create one-element cluster.

vector< TPhyTreeNode * > m_Trees

EClustMethod m_LinkMethod

void SetPrototypes(void)

Set prototypes for all clusters as center elements.

void PurgeDistMatrix(void)

Delete distance matrix.

CClusterer(void)

Create empty clusterer.

void GetClusterDistMatrix(int index, TDistMatrix &mat) const

Get distance matrix for elements of a selected cluster.

bool IsLink(int first, int second) const

Check if link exists between given two nodes.

void Sort(void)

Sort links according to weights in ascending order.

Uint4 GetNumElements(void) const

Get number of nodes.

list< SLink >::const_iterator SLink_CI

SLink_CI begin(void) const

Get iterator pointing to the first link.

SLink_CI end(void) const

Get iterator pointing behind the last link.

bool IsSorted(void) const

Check whether the links are sorted according to weights.

void Resize(size_t i, size_t j, T val=T())

resize this matrix, filling the empty cells with a known value

size_t GetRows() const

get the number of rows in this matrix

size_t GetCols() const

get the number of columns in this matrix

iterator begin()

iterators

definition of a Culling tree

static void s_CheckDistMatrix(const CClusterer::TDistMatrix &dmat)

static void s_PurgeTrees(vector< TPhyTreeNode * > &trees)

TPhyTreeNode * s_CreateTreeLeaf(int id)

static double s_FindDistAsMax(const CClusterer::TSingleCluster &cluster1, const CClusterer::TSingleCluster &cluster2, const CClusterer::TDistMatrix &dmat)

static double s_FindMean(const vector< double > &vals)

Find mean.

static double s_FindDistAsMean(const CClusterer::TSingleCluster &cluster1, const CClusterer::TSingleCluster &cluster2, const CClusterer::TDistMatrix &dmat)

Find mean distance between cluster elements.

static double s_FindDist(const CClusterer::CSingleCluster &cluster, const CClusterer::CSingleCluster &included_cluster, const CClusterer::CSingleCluster &extended_cluster, const CClusterer::TDistMatrix &dmat, double current_dist, CClusterer::EDistMethod dist_method)

Find distance between two clusters (cluster and included_cluster + extended_cluster) using given dist...

static double s_FindSumDistFromElem(int elem, const CClusterer::TSingleCluster &cluster, const CClusterer::TDistMatrix &dmat)

Find sum of distances between given element and cluster elements.

static double s_FindMaxDistFromElem(int elem, const CClusterer::TSingleCluster &cluster, const CClusterer::TDistMatrix &dmat)

#define ITERATE(Type, Var, Cont)

ITERATE macro to sequence through container elements.

#define NON_CONST_ITERATE(Type, Var, Cont)

Non constant version of ITERATE macro.

void swap(NCBI_NS_NCBI::pair_base_member< T1, T2 > &pair1, NCBI_NS_NCBI::pair_base_member< T1, T2 > &pair2)

#define NCBI_THROW(exception_class, err_code, message)

Generic macro to throw an exception, given the exception class, error code and message string.

void Reset(void)

Reset reference object.

bool Empty(void) const THROWS_NONE

Check if CRef is empty – not pointing to any object, which means having a null value.

static string IntToString(int value, TNumToStringFlags flags=0, int base=10)

Convert int to string.

void AddNode(TTreeType *subnode)

Add new subnode.

const TValue & GetValue(void) const

Return node's value.

unsigned int

A callback function used to compare two keys in a database.

constexpr bool empty(list< Ts... >) noexcept

const struct ncbi::grid::netcache::search::fields::SIZE size

void copy(Njn::Matrix< S > *matrix_, const Njn::Matrix< T > &matrix0_)

CTreeNode< CPhyNodeData > TPhyTreeNode

double weight

Edge weight.

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