nuget
图对象的操作API，并不包括有I/O操作函数，这个模块仅仅是提供对象的逻辑操作的方法集合
Microsoft.VisualBasic.Data.GraphTheory 1.0.9753.4776.
01 Namespaces
Microsoft.VisualBasic.Data.GraphTheory
| Type | Summary | Members |
|---|---|---|
| AbstractTree | An abstract tree data model | 11 |
| BipartiteEdge | 4 | |
| BipartiteMatching | 15 | |
| CharacterNode | 在字典树之中，一个字母构成一个节点 | 4 |
| Edge | Direction: Edge.U -> Edge.V. | 6 |
| Extensions | 10 | |
| Graph | A graph G = (V, E) consists of a set V of vertices and a set E edges, that is, unordered pairs Of vertices. | 1 |
| Graph | A graph G = (V, E) consists of a set V of vertices and a set E edges, that is, unordered pairs Of vertices. | 23 |
| PQTree | @author santi | 37 |
| SequenceGraphTransform | Sequence Graph Transform (SGT) — Sequence Embedding for Clustering, Classification, and Search Sequence Graph Transform (SGT) is a sequence embedding function. | 13 |
| SparseGraph | 4 | |
| TermTree | A tree with string term as key | 4 |
| Tree | 使用字符串String作为键名的树节点 | 5 |
| Tree | Tree node with data. | 1 |
| Trie | 朴素字典树（Trie） | 6 |
| Utils | 10 | |
| Vertex | Vertex in a graph | 4 |
Microsoft.VisualBasic.Data.GraphTheory.Analysis
| Type | Summary | Members |
|---|---|---|
| GraphAnalysis | 2 | |
| Ullmann | Ullmann算法是子图同构 问题的经典回溯算法，由J.R. | 5 |
Microsoft.VisualBasic.Data.GraphTheory.Analysis.Dijkstra
| Type | Summary | Members |
|---|---|---|
| Calculator | calculates all-pairs shortest paths or shortest paths from a single node | 7 |
| DijkstraAlgoritm | 8 | |
| DijkstraRouter | Dijkstra:Shortest Route Calculation - Object Oriented > Michael Demeersseman, 4 Jan 2008 > http://www.codeproject.com/Articles/22647/Dijkstra-Shortest-Route-Calculation-Object-… | 9 |
| Route | 从出发点到终点所经过的路径 | 9 |
| RoutePathway | 3 |
Microsoft.VisualBasic.Data.GraphTheory.Analysis.Dijkstra.DijkstraAlgoritm
| Type | Summary | Members |
|---|---|---|
| Node | Holds all the details of a node in the graph. | 7 |
Microsoft.VisualBasic.Data.GraphTheory.Analysis.FastUnfolding
| Type | Summary | Members |
|---|---|---|
| FastUnfolding | Fast unfolding of communities in large networks. | 4 |
| Utils | 1 |
Microsoft.VisualBasic.Data.GraphTheory.Analysis.Louvain
| Type | Summary | Members |
|---|---|---|
| Builder | 2 | |
| Edge | 2 | |
| LeidenCommunity | Leiden算法 - Louvain算法的改进版，保证社区连通性 核心改进： 1. | 24 |
| LouvainCommunity | A fast algorithm To find communities In large network | 22 |
Microsoft.VisualBasic.Data.GraphTheory.Analysis.LPA
| Type | Summary | Members |
|---|---|---|
| Builder | 将NetworkGraph网络图对象构建为LPA标签传播算法 所需要的链式前向星邻接表数据结构 | 2 |
| Edge | LPA邻接表之中所使用的边的数据结构（链式前向星） | 2 |
| LabelPropagation | Label Propagation Algorithm, LPA community detection | 13 |
Microsoft.VisualBasic.Data.GraphTheory.Analysis.MorganFingerprint
| Type | Summary | Members |
|---|---|---|
| GraphMorganFingerprint | Morgan fingerprints, also known as circular fingerprints, are a type of molecular fingerprint used in cheminformatics to represent the structure of chemical compounds. | 4 |
| IMorganAtom | 3 | |
| MorganGraph | 2 |
Microsoft.VisualBasic.Data.GraphTheory.Analysis.PageRank
| Type | Summary | Members |
|---|---|---|
| GraphMatrix | 可以用来构建PageRank计算所需要的index矩阵 | 5 |
| PageRank | 无权重的pagerank计算模块.(https://github.com/jeffersonhwang/pagerank) | 4 |
| WeightedPageRank | Package pagerank implements the weighted PageRank algorithm. | 1 |
| WeightedPRGraph | 2 | |
| WeightedPRNode | Weighted pagerank node | 3 |
Microsoft.VisualBasic.Data.GraphTheory.Dijkstra.PQDijkstra
| Type | Summary | Members |
|---|---|---|
| DijkstraFast | Implements a generalized Dijkstra's algorithm to calculate both minimum distance and minimum path. | 4 |
| Finder | 1 | |
| PQDijkstraProvider | 4 |
Microsoft.VisualBasic.Data.GraphTheory.Dijkstra.PQDijkstra.DijkstraFast
| Type | Summary | Members |
|---|---|---|
| InternodeTraversalCost | Determines the cost of moving from a given node to another given node. | 3 |
| NearbyNodesHint | An optional delegate that can help optimize the algorithm by showing it a subset of nodes to consider. | 3 |
| Results | 5 |
Microsoft.VisualBasic.Data.GraphTheory.EMD
| Type | Summary | Members |
|---|---|---|
| Edge | @author Telmo Menezes (telmo@telmomenezes.com) | 0 |
| Feature2D | @author Telmo Menezes (telmo@telmomenezes.com) | 2 |
| JFastEMD | Earth Mover's Distance @author Telmo Menezes (telmo@telmomenezes.com) @author Ofir Pele | 1 |
| Run | 1 | |
| Signature | Signatures can be used to represent sparse n-dimensional matrices. | 4 |
Microsoft.VisualBasic.Data.GraphTheory.GridGraph
Microsoft.VisualBasic.Data.GraphTheory.HuffmanTree
| Type | Summary | Members |
|---|---|---|
| HuffmanNeuron | Created by fangy on 13-12-20. | 7 |
| HuffmanNode | Created by fangy on 13-12-17. | 4 |
| HuffmanTreeTools | Created by fangy on 13-12-17. | 2 |
Microsoft.VisualBasic.Data.GraphTheory.KdTree
| Type | Summary | Members |
|---|---|---|
| KdNodeAccessor | Helper class for access the node data by different dimensions | 7 |
| KdNodeHeapItem | A KD-tree node bind with the distance with the target query point. | 3 |
| KdTree | KDTree is a class supporting KD-tree insertion, deletion, equality search, range search, and nearest neighbor(s) using double-precision floating-point keys. | 11 |
| KdTreeNode | K-D Tree node class | 9 |
| KdUtils | 2 |
Microsoft.VisualBasic.Data.GraphTheory.KdTree.ApproximateNearNeighbor
| Type | Summary | Members |
|---|---|---|
| ApproximateNearNeighbor | K Nearest Neighbour Search Uses a kd-tree to find the p number of near neighbours for each point in an input/output dataset. | 2 |
| KNeighbors | k neighbors of a item row | 4 |
| TagVector | a matrix row data is a vector | 5 |
| VectorAccessor | 1 |
Microsoft.VisualBasic.Data.GraphTheory.KNearNeighbors
| Type | Summary | Members |
|---|---|---|
| KNN | KNN search handler for phenograph | 2 |
| ScoreMetric | 3 |
Microsoft.VisualBasic.Data.GraphTheory.KNearNeighbors.HNSW
| Type | Summary | Members |
|---|---|---|
| BinaryHeap | Binary heap wrapper around the IList It's a max-heap implementation i.e. | 11 |
| CosineDistance | Calculates cosine similarity. | 4 |
| Graph | The layered graph implementation. | 10 |
| KNNSearchResult | Representation of knn search result. | 3 |
| NeighbourSelectionHeuristic | Type of heuristic to select best neighbours for a node. | 4 |
| Node | The abstract node implementation. | 11 |
| NodeAlg3 | The implementation of the SELECT-NEIGHBORS-SIMPLE(q, C, M) algorithm. | 2 |
| NodeAlg4 | The implementation of the SELECT-NEIGHBORS-HEURISTIC(q, C, M, lc, extendCandidates, keepPrunedConnections) algorithm. | 2 |
| Parameters | Parameters of the algorithm. | 7 |
| ReverseComparer | Reverses the order of the nested comparer. | 4 |
| ReverseComparerExtensions | Extension methods to shortcut ReverseComparer usage. | 2 |
| SmallWorld | Hierarchical Navigable Small World Graphs. | 12 |
| TravelingCosts | Implementation of distance calculation from an arbitrary point to the given destination. | 7 |
| VectorUtils | Utilities to work with vectors. | 4 |
Microsoft.VisualBasic.Data.GraphTheory.MinimumSpanningTree
| Type | Summary | Members |
|---|---|---|
| Kruskal | Minimum spanning tree via Kruskal algorithm | 2 |
Microsoft.VisualBasic.Data.GraphTheory.Network
在这个命名空间之中包含有网络的数据模型API，网络布局，I/O和可视化模块都保留在gr模块之中
| Type | Summary | Members |
|---|---|---|
| Edge | interaction edge is a tuple of two node vertex object | 0 |
| Extensions | Graph network api module extensions | 6 |
| ExtensionsAPI | 5 | |
| IndexEdge | an edge link: [u, v] | 2 |
| INode | Node model in the network | 2 |
| NetworkGraph | The base type of the network graph | 3 |
| Node | A network node model | 1 |
| SubNetworkComponents | 2 |
Microsoft.VisualBasic.Data.GraphTheory.SparseGraph
| Type | Summary | Members |
|---|---|---|
| IInteraction | interaction edge tuple of vertex reference id | 2 |