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The impact on the current implementation is negligible. name old time/op new time/op delta BellmanFordFrom/500_tenth-8 4.14ms ± 1% 4.11ms ± 1% -0.73% (p=0.001 n=10+9) BellmanFordFrom/1000_tenth-8 16.3ms ± 1% 16.1ms ± 1% -0.82% (p=0.000 n=10+10) BellmanFordFrom/2000_tenth-8 66.2ms ± 1% 60.9ms ± 0% -8.08% (p=0.000 n=10+9) BellmanFordFrom/500_half-8 18.0ms ± 5% 16.9ms ± 1% -6.28% (p=0.000 n=10+9) BellmanFordFrom/1000_half-8 68.5ms ± 2% 67.4ms ± 1% -1.50% (p=0.000 n=9+8) BellmanFordFrom/2000_half-8 281ms ± 1% 276ms ± 1% -1.45% (p=0.000 n=9+10) BellmanFordFrom/500_full-8 33.4ms ± 0% 33.0ms ± 1% -1.29% (p=0.000 n=9+9) BellmanFordFrom/1000_full-8 137ms ± 1% 133ms ± 0% -3.11% (p=0.000 n=8+9) BellmanFordFrom/2000_full-8 549ms ± 1% 546ms ± 1% ~ (p=0.065 n=10+9) name old alloc/op new alloc/op delta BellmanFordFrom/500_tenth-8 142kB ± 0% 142kB ± 0% ~ (p=0.110 n=10+9) BellmanFordFrom/1000_tenth-8 284kB ± 0% 284kB ± 0% ~ (p=0.382 n=10+10) BellmanFordFrom/2000_tenth-8 624kB ± 0% 624kB ± 0% ~ (p=0.956 n=10+10) BellmanFordFrom/500_half-8 142kB ± 0% 142kB ± 0% ~ (p=0.666 n=10+10) BellmanFordFrom/1000_half-8 284kB ± 0% 284kB ± 0% ~ (p=0.070 n=10+8) BellmanFordFrom/2000_half-8 624kB ± 0% 624kB ± 0% ~ (p=0.290 n=10+10) BellmanFordFrom/500_full-8 142kB ± 0% 142kB ± 0% ~ (p=0.234 n=9+10) BellmanFordFrom/1000_full-8 284kB ± 0% 284kB ± 0% ~ (p=0.051 n=10+9) BellmanFordFrom/2000_full-8 624kB ± 0% 624kB ± 0% ~ (p=0.790 n=9+10) name old allocs/op new allocs/op delta BellmanFordFrom/500_tenth-8 2.03k ± 0% 2.03k ± 0% ~ (all equal) BellmanFordFrom/1000_tenth-8 4.03k ± 0% 4.03k ± 0% ~ (all equal) BellmanFordFrom/2000_tenth-8 8.03k ± 0% 8.03k ± 0% ~ (all equal) BellmanFordFrom/500_half-8 2.03k ± 0% 2.03k ± 0% ~ (p=0.294 n=10+8) BellmanFordFrom/1000_half-8 4.03k ± 0% 4.03k ± 0% ~ (all equal) BellmanFordFrom/2000_half-8 8.03k ± 0% 8.03k ± 0% ~ (all equal) BellmanFordFrom/500_full-8 2.03k ± 0% 2.03k ± 0% ~ (p=1.000 n=10+10) BellmanFordFrom/1000_full-8 4.03k ± 0% 4.03k ± 0% ~ (all equal) BellmanFordFrom/2000_full-8 8.03k ± 0% 8.03k ± 0% ~ (p=1.000 n=10+10) The performance of the lazy implementation is a little worse and allocations are a lot worse than the eager implementation. This reflects that the benchmark is performed on a graph with a single connected component which gains no benefit from the incremental approach but suffers the cost of repeated reallocation for appends. name new time/op inc time/op delta BellmanFordFrom/500_tenth-8 4.11ms ± 1% 4.28ms ± 1% +4.05% (p=0.000 n=9+10) BellmanFordFrom/1000_tenth-8 16.1ms ± 1% 16.0ms ± 6% ~ (p=0.143 n=10+10) BellmanFordFrom/2000_tenth-8 60.9ms ± 0% 62.8ms ± 0% +3.13% (p=0.000 n=9+10) BellmanFordFrom/500_half-8 16.9ms ± 1% 17.5ms ± 1% +3.97% (p=0.000 n=9+10) BellmanFordFrom/1000_half-8 67.4ms ± 1% 70.0ms ± 2% +3.76% (p=0.000 n=8+9) BellmanFordFrom/2000_half-8 276ms ± 1% 285ms ± 0% +2.91% (p=0.000 n=10+10) BellmanFordFrom/500_full-8 33.0ms ± 1% 35.5ms ± 5% +7.40% (p=0.000 n=9+10) BellmanFordFrom/1000_full-8 133ms ± 0% 137ms ± 2% +3.48% (p=0.000 n=9+9) BellmanFordFrom/2000_full-8 546ms ± 1% 592ms ± 6% +8.42% (p=0.000 n=9+10) name new alloc/op inc alloc/op delta BellmanFordFrom/500_tenth-8 142kB ± 0% 182kB ± 0% +27.84% (p=0.000 n=9+10) BellmanFordFrom/1000_tenth-8 284kB ± 0% 363kB ± 0% +27.94% (p=0.000 n=10+10) BellmanFordFrom/2000_tenth-8 624kB ± 0% 893kB ± 0% +43.26% (p=0.000 n=10+10) BellmanFordFrom/500_half-8 142kB ± 0% 182kB ± 0% +27.83% (p=0.000 n=10+10) BellmanFordFrom/1000_half-8 284kB ± 0% 363kB ± 0% +27.90% (p=0.000 n=8+10) BellmanFordFrom/2000_half-8 624kB ± 0% 893kB ± 0% +43.25% (p=0.000 n=10+10) BellmanFordFrom/500_full-8 142kB ± 0% 182kB ± 0% +27.82% (p=0.000 n=10+10) BellmanFordFrom/1000_full-8 284kB ± 0% 363kB ± 0% +27.89% (p=0.000 n=9+10) BellmanFordFrom/2000_full-8 624kB ± 0% 893kB ± 0% +43.23% (p=0.000 n=10+10) name new allocs/op inc allocs/op delta BellmanFordFrom/500_tenth-8 2.03k ± 0% 2.10k ± 0% +3.50% (p=0.000 n=8+8) BellmanFordFrom/1000_tenth-8 4.03k ± 0% 4.12k ± 0% +2.39% (p=0.000 n=10+10) BellmanFordFrom/2000_tenth-8 8.03k ± 0% 8.17k ± 0% +1.77% (p=0.000 n=10+10) BellmanFordFrom/500_half-8 2.03k ± 0% 2.10k ± 0% +3.49% (p=0.000 n=8+10) BellmanFordFrom/1000_half-8 4.03k ± 0% 4.12k ± 0% +2.36% (p=0.000 n=9+10) BellmanFordFrom/2000_half-8 8.03k ± 0% 8.17k ± 0% +1.77% (p=0.000 n=8+10) BellmanFordFrom/500_full-8 2.03k ± 0% 2.10k ± 0% +3.50% (p=0.000 n=10+10) BellmanFordFrom/1000_full-8 4.03k ± 0% 4.12k ± 0% +2.36% (p=0.000 n=9+10) BellmanFordFrom/2000_full-8 8.03k ± 0% 8.17k ± 0% +1.76% (p=0.000 n=10+10)
193 lines
5.2 KiB
Go
193 lines
5.2 KiB
Go
// Copyright ©2015 The Gonum Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style
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// license that can be found in the LICENSE file.
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package path
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import (
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"fmt"
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"sync"
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"testing"
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"gonum.org/v1/gonum/graph"
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"gonum.org/v1/gonum/graph/graphs/gen"
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"gonum.org/v1/gonum/graph/simple"
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"gonum.org/v1/gonum/graph/traverse"
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)
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var (
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gnpUndirected_10_tenth = gnpUndirected(10, 0.1)
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gnpUndirected_100_tenth = gnpUndirected(100, 0.1)
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gnpUndirected_1000_tenth = gnpUndirected(1000, 0.1)
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gnpUndirected_10_half = gnpUndirected(10, 0.5)
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gnpUndirected_100_half = gnpUndirected(100, 0.5)
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gnpUndirected_1000_half = gnpUndirected(1000, 0.5)
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nswUndirected_10_2_2_2 = navigableSmallWorldUndirected(10, 2, 2, 2)
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nswUndirected_10_2_5_2 = navigableSmallWorldUndirected(10, 2, 5, 2)
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nswUndirected_100_5_10_2 = navigableSmallWorldUndirected(100, 5, 10, 2)
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nswUndirected_100_5_20_2 = navigableSmallWorldUndirected(100, 5, 20, 2)
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)
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func gnpUndirected(n int, p float64) func() graph.Undirected {
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var once sync.Once
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var cache graph.Undirected
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return func() graph.Undirected {
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once.Do(func() {
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g := simple.NewUndirectedGraph()
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err := gen.Gnp(g, n, p, nil)
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if err != nil {
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panic(fmt.Sprintf("path: bad test: %v", err))
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}
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cache = g
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})
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return cache
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}
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}
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func navigableSmallWorldUndirected(n, p, q int, r float64) func() graph.Undirected {
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var once sync.Once
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var cache graph.Undirected
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return func() graph.Undirected {
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once.Do(func() {
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g := simple.NewUndirectedGraph()
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err := gen.NavigableSmallWorld(g, []int{n, n}, p, q, r, nil)
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if err != nil {
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panic(fmt.Sprintf("path: bad test: %v", err))
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}
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cache = g
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})
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return cache
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}
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}
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func manhattan(size int) func(x, y graph.Node) float64 {
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return func(x, y graph.Node) float64 {
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return manhattanBetween(coordinatesForID(x, size, size), coordinatesForID(y, size, size))
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}
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}
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func coordinatesForID(n graph.Node, c, r int) [2]int {
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id := n.ID()
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if id >= int64(c*r) {
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panic("out of range")
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}
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return [2]int{int(id) / r, int(id) % r}
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}
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// manhattanBetween returns the Manhattan distance between a and b.
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func manhattanBetween(a, b [2]int) float64 {
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var d int
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for i, v := range a {
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d += abs(v - b[i])
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}
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return float64(d)
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}
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func abs(a int) int {
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if a < 0 {
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return -a
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}
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return a
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}
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func BenchmarkAStarUndirected(b *testing.B) {
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benchmarks := []struct {
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name string
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graph graph.Undirected
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h Heuristic
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}{
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{"GNP Undirected 10 tenth", gnpUndirected_10_tenth(), nil},
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{"GNP Undirected 100 tenth", gnpUndirected_100_tenth(), nil},
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{"GNP Undirected 1000 tenth", gnpUndirected_1000_tenth(), nil},
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{"GNP Undirected 10 half", gnpUndirected_10_half(), nil},
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{"GNP Undirected 100 half", gnpUndirected_100_half(), nil},
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{"GNP Undirected 1000 half", gnpUndirected_1000_half(), nil},
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{"NSW Undirected 10 2 2 2", nswUndirected_10_2_2_2(), nil},
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{"NSW Undirected 10 2 2 2 heuristic", nswUndirected_10_2_2_2(), manhattan(10)},
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{"NSW Undirected 10 2 5 2", nswUndirected_10_2_5_2(), nil},
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{"NSW Undirected 10 2 5 2 heuristic", nswUndirected_10_2_5_2(), manhattan(10)},
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{"NSW Undirected 100 5 10 2", nswUndirected_100_5_10_2(), nil},
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{"NSW Undirected 100 5 10 2 heuristic", nswUndirected_100_5_10_2(), manhattan(100)},
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{"NSW Undirected 100 5 20 2", nswUndirected_100_5_20_2(), nil},
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{"NSW Undirected 100 5 20 2 heuristic", nswUndirected_100_5_20_2(), manhattan(100)},
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}
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for _, bm := range benchmarks {
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b.Run(bm.name, func(b *testing.B) {
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var expanded int
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for i := 0; i < b.N; i++ {
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_, expanded = AStar(simple.Node(0), simple.Node(1), bm.graph, bm.h)
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}
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if expanded == 0 {
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b.Fatal("unexpected number of expanded nodes")
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}
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})
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}
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}
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var (
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gnpDirected_500_tenth = gnpDirected(500, 0.1)
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gnpDirected_1000_tenth = gnpDirected(1000, 0.1)
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gnpDirected_2000_tenth = gnpDirected(2000, 0.1)
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gnpDirected_500_half = gnpDirected(500, 0.5)
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gnpDirected_1000_half = gnpDirected(1000, 0.5)
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gnpDirected_2000_half = gnpDirected(2000, 0.5)
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gnpDirected_500_full = gnpDirected(500, 1)
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gnpDirected_1000_full = gnpDirected(1000, 1)
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gnpDirected_2000_full = gnpDirected(2000, 1)
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)
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func gnpDirected(n int, p float64) func() graph.Directed {
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var once sync.Once
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var cache graph.Directed
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return func() graph.Directed {
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once.Do(func() {
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g := simple.NewDirectedGraph()
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err := gen.Gnp(g, n, p, nil)
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if err != nil {
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panic(fmt.Sprintf("path: bad test: %v", err))
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}
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cache = g
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})
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return cache
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}
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}
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func BenchmarkBellmanFordFrom(b *testing.B) {
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benchmarks := []struct {
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name string
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graph graph.Directed
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}{
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{"500 tenth", gnpDirected_500_tenth()},
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{"1000 tenth", gnpDirected_1000_tenth()},
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{"2000 tenth", gnpDirected_2000_tenth()},
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{"500 half", gnpDirected_500_half()},
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{"1000 half", gnpDirected_1000_half()},
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{"2000 half", gnpDirected_2000_half()},
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{"500 full", gnpDirected_500_full()},
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{"1000 full", gnpDirected_1000_full()},
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{"2000 full", gnpDirected_2000_full()},
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}
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type incremental struct {
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traverse.Graph
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}
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for _, bm := range benchmarks {
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for _, tg := range []struct {
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typ string
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g traverse.Graph
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}{
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{g: bm.graph},
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{typ: " incremental", g: incremental{bm.graph}},
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} {
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b.Run(bm.name+tg.typ, func(b *testing.B) {
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for i := 0; i < b.N; i++ {
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BellmanFordFrom(bm.graph.Node(0), tg.g)
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}
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})
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}
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}
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}
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