Dijkstra's algorithm is a popular graph search algorithm used to find the shortest path between nodes in a weighted graph. Here is a simple implementation of Dijkstra's algorithm in Go.
package main
import (
"container/heap"
"fmt"
)
// Item represents a node in the graph
type Item struct {
value string // The value of the item
priority int // The priority (distance from source)
index int // The index of the item in the heap
}
// PriorityQueue implements heap.Interface and holds Items
type PriorityQueue []*Item
func (pq PriorityQueue) Len() int { return len(pq) }
func (pq PriorityQueue) Less(i, j int) bool {
return pq[i].priority < pq[j].priority
}
func (pq PriorityQueue) Swap(i, j int) {
pq[i], pq[j] = pq[j], pq[i]
pq[i].index = i
pq[j].index = j
}
// Push and Pop methods for the priority queue
func (pq *PriorityQueue) Push(x interface{}) {
n := len(*pq)
item := x.(*Item)
item.index = n
*pq = append(*pq, item)
}
func (pq *PriorityQueue) Pop() interface{} {
old := *pq
n := len(old)
item := old[n-1]
*pq = old[0 : n-1]
return item
}
// Dijkstra's function to find the shortest path from a source node
func Dijkstra(graph map[string]map[string]int, start string) map[string]int {
distances := make(map[string]int)
for k := range graph {
distances[k] = int(^uint(0) >> 1) // Set to infinity
}
distances[start] = 0
pq := &PriorityQueue{}
heap.Init(pq)
heap.Push(pq, &Item{
value: start,
priority: 0,
})
for pq.Len() > 0 {
current := heap.Pop(pq).(*Item)
for neighbor, weight := range graph[current.value] {
distance := distances[current.value] + weight
if distance < distances[neighbor] {
distances[neighbor] = distance
heap.Push(pq, &Item{
value: neighbor,
priority: distance,
})
}
}
}
return distances
}
func main() {
graph := map[string]map[string]int{
"A": {"B": 1, "C": 4},
"B": {"A": 1, "C": 2, "D": 5},
"C": {"A": 4, "B": 2, "D": 1},
"D": {"B": 5, "C": 1},
}
distances := Dijkstra(graph, "A")
fmt.Println("Shortest distances from A:", distances)
}
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