Function astar

packages/effect/src/Graph.ts:2699–2848

(
  graph: Graph<N, E, T> | MutableGraph<N, E, T>,
  config: AstarConfig<E, N>
)

 * @category algorithms
 */
export const astar = <N, E, T extends Kind = "directed">(
  graph: Graph<N, E, T> | MutableGraph<N, E, T>,
  config: AstarConfig<E, N>
): Option.Option<PathResult<E>> => {
  const { cost, heuristic, source, target } = config
  // Validate that source and target nodes exist
  if (!graph.nodes.has(source)) {
    throw missingNode(source)
  }
  if (!graph.nodes.has(target)) {
    throw missingNode(target)
  }

  // Early return if source equals target
  if (source === target) {
    return Option.some({
      path: [source],
      distance: 0,
      costs: []
    })
  }

  // Get target node data for heuristic calculations
  const targetNodeData = graph.nodes.get(target)
  if (targetNodeData === undefined) {
    throw new Error(`Target node ${target} data not found`)
  }

  // Distance tracking (g-score) and f-score (g + h)
  const gScore = new Map<NodeIndex, number>()
  const fScore = new Map<NodeIndex, number>()
  const previous = new Map<NodeIndex, { node: NodeIndex; edgeData: E } | null>()
  const visited = new Set<NodeIndex>()

  // Initialize scores
  // Iterate directly over node keys
  for (const node of graph.nodes.keys()) {
    gScore.set(node, node === source ? 0 : Infinity)
    fScore.set(node, Infinity)
    previous.set(node, null)
  }

  // Calculate initial f-score for source
  const sourceNodeData = graph.nodes.get(source)
  if (sourceNodeData !== undefined) {
    const h = heuristic(sourceNodeData, targetNodeData)
    fScore.set(source, h)
  }

  // Priority queue using f-score (total estimated cost)
  const openSet: Array<{ node: NodeIndex; fScore: number }> = [
    { node: source, fScore: fScore.get(source)! }
  ]

  while (openSet.length > 0) {
    // Find node with lowest f-score
    let minIndex = 0
    for (let i = 1; i < openSet.length; i++) {