@fluxgraph/knowledge/dist/algorithms/index.mjs.map

A flexible, database-agnostic knowledge graph implementation for TypeScript

{"version":3,"sources":["../../src/algorithms/index.ts"],"sourcesContent":["import { KnowledgeGraph } from '../core/KnowledgeGraph';\nimport { KnowledgeNode, KnowledgeEdge } from '../types';\n\n/**\n * Graph algorithms for analyzing and working with knowledge graphs\n */\nexport class GraphAlgorithms {\n  private graph: KnowledgeGraph;\n  \n  constructor(graph: KnowledgeGraph) {\n    this.graph = graph;\n  }\n  \n  /**\n   * Calculate degree centrality for a node\n   * Degree centrality is the number of edges connected to a node\n   */\n  async degreeCentrality(nodeId: string): Promise<number> {\n    const result = await this.graph.queryRelated(nodeId, { depth: 1 });\n    return result.edges.length;\n  }\n  \n  /**\n   * Calculate degree centrality for all nodes\n   */\n  async allDegreeCentrality(): Promise<Map<string, number>> {\n    const centrality = new Map<string, number>();\n    \n    // This is a simplified implementation\n    // In production, you'd want to batch this operation\n    const nodes = await this.graph.queryByType('CUSTOM', { limit: 1000 });\n    \n    for (const node of nodes.nodes) {\n      const degree = await this.degreeCentrality(node.id);\n      centrality.set(node.id, degree);\n    }\n    \n    return centrality;\n  }\n  \n  /**\n   * Find all paths between two nodes up to a maximum length\n   */\n  async findAllPaths(\n    fromNodeId: string,\n    toNodeId: string,\n    maxLength = 5\n  ): Promise<Array<{ nodes: KnowledgeNode[]; edges: KnowledgeEdge[]; length: number }>> {\n    const paths: Array<{ nodes: KnowledgeNode[]; edges: KnowledgeEdge[]; length: number }> = [];\n    \n    // Use DFS to find all paths\n    const visited = new Set<string>();\n    const currentPath: string[] = [];\n    const currentEdges: KnowledgeEdge[] = [];\n    \n    const dfs = async (currentNodeId: string, depth: number) => {\n      if (depth > maxLength) return;\n      \n      if (currentNodeId === toNodeId) {\n        // Found a path\n        const nodeObjects = await Promise.all(\n          [...currentPath, currentNodeId].map(id => this.graph.getNode(id))\n        );\n        \n        paths.push({\n          nodes: nodeObjects.filter(n => n !== null) as KnowledgeNode[],\n          edges: [...currentEdges],\n          length: currentPath.length,\n        });\n        return;\n      }\n      \n      if (visited.has(currentNodeId)) return;\n      \n      visited.add(currentNodeId);\n      currentPath.push(currentNodeId);\n      \n      // Get all outgoing edges\n      const result = await this.graph.queryRelated(currentNodeId, { \n        depth: 1, \n        direction: 'out' \n      });\n      \n      for (const edge of result.edges) {\n        if (edge.fromNodeId === currentNodeId) {\n          currentEdges.push(edge);\n          await dfs(edge.toNodeId, depth + 1);\n          currentEdges.pop();\n        }\n      }\n      \n      currentPath.pop();\n      visited.delete(currentNodeId);\n    };\n    \n    await dfs(fromNodeId, 0);\n    return paths;\n  }\n  \n  /**\n   * Detect cycles in the graph\n   */\n  async detectCycles(): Promise<Array<{ nodes: string[]; edges: KnowledgeEdge[] }>> {\n    const cycles: Array<{ nodes: string[]; edges: KnowledgeEdge[] }> = [];\n    const visited = new Set<string>();\n    const recursionStack = new Set<string>();\n    const path: string[] = [];\n    const pathEdges: KnowledgeEdge[] = [];\n    \n    const dfs = async (nodeId: string): Promise<boolean> => {\n      visited.add(nodeId);\n      recursionStack.add(nodeId);\n      path.push(nodeId);\n      \n      const result = await this.graph.queryRelated(nodeId, { \n        depth: 1, \n        direction: 'out' \n      });\n      \n      for (const edge of result.edges) {\n        if (edge.fromNodeId === nodeId) {\n          pathEdges.push(edge);\n          \n          if (!visited.has(edge.toNodeId)) {\n            if (await dfs(edge.toNodeId)) {\n              return true;\n            }\n          } else if (recursionStack.has(edge.toNodeId)) {\n            // Found a cycle\n            const cycleStartIndex = path.indexOf(edge.toNodeId);\n            cycles.push({\n              nodes: path.slice(cycleStartIndex),\n              edges: pathEdges.slice(cycleStartIndex),\n            });\n          }\n          \n          pathEdges.pop();\n        }\n      }\n      \n      path.pop();\n      recursionStack.delete(nodeId);\n      return false;\n    };\n    \n    // Check all nodes for cycles\n    const nodes = await this.graph.queryByType('CUSTOM', { limit: 1000 });\n    \n    for (const node of nodes.nodes) {\n      if (!visited.has(node.id)) {\n        await dfs(node.id);\n      }\n    }\n    \n    return cycles;\n  }\n  \n  /**\n   * Find connected components in the graph\n   */\n  async findConnectedComponents(): Promise<Array<Set<string>>> {\n    const components: Array<Set<string>> = [];\n    const visited = new Set<string>();\n    \n    const dfs = async (nodeId: string, component: Set<string>) => {\n      if (visited.has(nodeId)) return;\n      \n      visited.add(nodeId);\n      component.add(nodeId);\n      \n      const result = await this.graph.queryRelated(nodeId, { \n        depth: 1, \n        direction: 'both' \n      });\n      \n      for (const node of result.nodes) {\n        if (node.id !== nodeId && !visited.has(node.id)) {\n          await dfs(node.id, component);\n        }\n      }\n    };\n    \n    // Get all nodes\n    const nodes = await this.graph.queryByType('CUSTOM', { limit: 10000 });\n    \n    for (const node of nodes.nodes) {\n      if (!visited.has(node.id)) {\n        const component = new Set<string>();\n        await dfs(node.id, component);\n        components.push(component);\n      }\n    }\n    \n    return components;\n  }\n  \n  /**\n   * Calculate PageRank for all nodes\n   * Simplified implementation - real PageRank would need iterative computation\n   */\n  async pageRank(\n    damping = 0.85,\n    iterations = 10\n  ): Promise<Map<string, number>> {\n    const pageRank = new Map<string, number>();\n    const nodes = await this.graph.queryByType('CUSTOM', { limit: 10000 });\n    const nodeIds = nodes.nodes.map(n => n.id);\n    const N = nodeIds.length;\n    \n    // Initialize PageRank values\n    for (const nodeId of nodeIds) {\n      pageRank.set(nodeId, 1 / N);\n    }\n    \n    // Iterative computation\n    for (let iter = 0; iter < iterations; iter++) {\n      const newPageRank = new Map<string, number>();\n      \n      for (const nodeId of nodeIds) {\n        let rank = (1 - damping) / N;\n        \n        // Get incoming edges\n        const result = await this.graph.queryRelated(nodeId, { \n          depth: 1, \n          direction: 'in' \n        });\n        \n        for (const edge of result.edges) {\n          if (edge.toNodeId === nodeId) {\n            const sourceRank = pageRank.get(edge.fromNodeId) || 0;\n            const sourceOutDegree = await this.degreeCentrality(edge.fromNodeId);\n            rank += damping * (sourceRank / Math.max(sourceOutDegree, 1));\n          }\n        }\n        \n        newPageRank.set(nodeId, rank);\n      }\n      \n      // Update PageRank values\n      for (const [nodeId, rank] of newPageRank) {\n        pageRank.set(nodeId, rank || 0);\n      }\n    }\n    \n    return pageRank;\n  }\n  \n  /**\n   * Find nodes that form a clique (fully connected subgraph)\n   */\n  async findCliques(minSize = 3): Promise<Array<Set<string>>> {\n    const cliques: Array<Set<string>> = [];\n    const nodes = await this.graph.queryByType('CUSTOM', { limit: 1000 });\n    const nodeIds = nodes.nodes.map(n => n.id);\n    \n    // Bron-Kerbosch algorithm (simplified)\n    const bronKerbosch = async (\n      R: Set<string>,\n      P: Set<string>,\n      X: Set<string>\n    ) => {\n      if (P.size === 0 && X.size === 0) {\n        if (R.size >= minSize) {\n          cliques.push(new Set(R));\n        }\n        return;\n      }\n      \n      for (const v of P) {\n        const neighbors = new Set<string>();\n        const result = await this.graph.queryRelated(v, { depth: 1 });\n        \n        for (const node of result.nodes) {\n          if (node.id !== v) {\n            neighbors.add(node.id);\n          }\n        }\n        \n        const newR = new Set(R);\n        newR.add(v);\n        \n        const newP = new Set<string>();\n        for (const p of P) {\n          if (neighbors.has(p)) newP.add(p);\n        }\n        \n        const newX = new Set<string>();\n        for (const x of X) {\n          if (neighbors.has(x)) newX.add(x);\n        }\n        \n        await bronKerbosch(newR, newP, newX);\n        \n        P.delete(v);\n        X.add(v);\n      }\n    };\n    \n    await bronKerbosch(new Set(), new Set(nodeIds), new Set());\n    return cliques;\n  }\n  \n  /**\n   * Calculate clustering coefficient for a node\n   */\n  async clusteringCoefficient(nodeId: string): Promise<number> {\n    const result = await this.graph.queryRelated(nodeId, { depth: 1 });\n    const neighbors = result.nodes.filter(n => n.id !== nodeId);\n    \n    if (neighbors.length < 2) return 0;\n    \n    let triangles = 0;\n    const possibleTriangles = (neighbors.length * (neighbors.length - 1)) / 2;\n    \n    // Check how many neighbors are connected to each other\n    for (let i = 0; i < neighbors.length; i++) {\n      for (let j = i + 1; j < neighbors.length; j++) {\n        const neighborI = neighbors[i];\n        const neighborJ = neighbors[j];\n        if (!neighborI || !neighborJ) continue;\n        \n        const edges = await this.graph.getEdgesBetween(\n          neighborI.id,\n          neighborJ.id\n        );\n        \n        if (edges.length > 0) {\n          triangles++;\n        }\n      }\n    }\n    \n    return triangles / possibleTriangles;\n  }\n  \n  /**\n   * Find communities using label propagation\n   */\n  async detectCommunities(): Promise<Map<string, number>> {\n    const communities = new Map<string, number>();\n    const nodes = await this.graph.queryByType('CUSTOM', { limit: 1000 });\n    \n    // Initialize each node with its own community\n    let communityId = 0;\n    for (const node of nodes.nodes) {\n      communities.set(node.id, communityId++);\n    }\n    \n    // Iterate until convergence\n    let changed = true;\n    let iterations = 0;\n    const maxIterations = 10;\n    \n    while (changed && iterations < maxIterations) {\n      changed = false;\n      iterations++;\n      \n      for (const node of nodes.nodes) {\n        const result = await this.graph.queryRelated(node.id, { depth: 1 });\n        \n        // Count community labels of neighbors\n        const labelCounts = new Map<number, number>();\n        \n        for (const neighbor of result.nodes) {\n          if (neighbor.id !== node.id) {\n            const label = communities.get(neighbor.id);\n            if (label !== undefined) {\n              labelCounts.set(label, (labelCounts.get(label) || 0) + 1);\n            }\n          }\n        }\n        \n        // Adopt the most common label\n        if (labelCounts.size > 0) {\n          const maxLabel = Array.from(labelCounts.entries())\n            .reduce((a, b) => a[1] > b[1] ? a : b)[0];\n          \n          if (communities.get(node.id) !== maxLabel) {\n            communities.set(node.id, maxLabel);\n            changed = true;\n          }\n        }\n      }\n    }\n    \n    return communities;\n  }\n}\n\n// Export convenience functions\nexport async function degreeCentrality(graph: KnowledgeGraph, nodeId: string): Promise<number> {\n  const algorithms = new GraphAlgorithms(graph);\n  return algorithms.degreeCentrality(nodeId);\n}\n\nexport async function findShortestPath(\n  graph: KnowledgeGraph,\n  fromNodeId: string,\n  toNodeId: string\n): Promise<any> {\n  return graph.findShortestPath(fromNodeId, toNodeId);\n}\n\nexport async function detectCycles(graph: KnowledgeGraph): Promise<any> {\n  const algorithms = new GraphAlgorithms(graph);\n  return algorithms.detectCycles();\n}\n\nexport async function pageRank(graph: KnowledgeGraph): Promise<Map<string, number>> {\n  const algorithms = new GraphAlgorithms(graph);\n  return 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