Justin Visser
a0635544d9
Forwarding was a single global ForwardProb; make it a per-student composite (Config.ForwardChance): baseline propensity raised by the fake's Novelty, lowered by ambient HarmAwareness, and scaled down for an educated student by ProgramEffect (1 = today's hard block). RunCascade now takes a precomputed per-student []float64 chance and has no education special case. Defaults are behaviour-neutral, so the 82/58/6 golden tests are unchanged; the model is tuned in a later slice.
113 lines
3.5 KiB
Go
113 lines
3.5 KiB
Go
package engine
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import (
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"slices"
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"testing"
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)
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// The cascade is deterministic once thresholds are fixed, so these tests
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// hand-craft a tiny line graph (0-1-2-3) and exact thresholds: no
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// randomness, every expectation is exact.
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func lineGraph(numNodes int) *Graph {
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graph := NewGraph(numNodes)
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for node := 0; node < numNodes-1; node++ {
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graph.AddEdge(node, node+1)
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}
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return graph
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}
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// uniformThresholds gives every directed edge the same threshold.
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func uniformThresholds(graph *Graph, value float64) EdgeThresholds {
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thresholds := make(EdgeThresholds)
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for node := range graph.NumNodes() {
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for _, neighbor := range graph.Neighbors(node) {
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thresholds[[2]int{node, neighbor}] = value
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}
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}
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return thresholds
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}
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// uniformChance gives every student the same forwarding chance.
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func uniformChance(numNodes int, value float64) []float64 {
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chances := make([]float64, numNodes)
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for node := range chances {
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chances[node] = value
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}
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return chances
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}
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func TestRunCascadeSpreadsAlongOpenEdges(t *testing.T) {
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graph := lineGraph(4)
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thresholds := uniformThresholds(graph, 0.1) // 0.1 < 0.5: every edge forwards
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result := RunCascade(graph, 0, uniformChance(4, 0.5), thresholds)
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wantRounds := []int{0, 1, 2, 3} // one hop further each round
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if !slices.Equal(result.ReachedAtRound, wantRounds) {
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t.Errorf("ReachedAtRound = %v, want %v", result.ReachedAtRound, wantRounds)
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}
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if result.NumReached != 4 {
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t.Errorf("NumReached = %d, want 4", result.NumReached)
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}
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if result.NumRounds != 4 {
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t.Errorf("NumRounds = %d, want 4", result.NumRounds)
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}
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}
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func TestRunCascadeThresholdBlocksOneDirection(t *testing.T) {
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graph := lineGraph(4)
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thresholds := uniformThresholds(graph, 0.1)
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// Close the 1 -> 2 direction only. The open 2 -> 1 direction must not
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// matter: student 2 never gets the fake, so never forwards anything.
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thresholds[[2]int{1, 2}] = 0.9
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result := RunCascade(graph, 0, uniformChance(4, 0.5), thresholds)
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wantRounds := []int{0, 1, NeverReached, NeverReached}
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if !slices.Equal(result.ReachedAtRound, wantRounds) {
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t.Errorf("ReachedAtRound = %v, want %v", result.ReachedAtRound, wantRounds)
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}
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if result.NumReached != 2 {
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t.Errorf("NumReached = %d, want 2", result.NumReached)
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}
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}
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func TestRunCascadeEducatedReceivesButDoesNotForward(t *testing.T) {
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graph := lineGraph(4)
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thresholds := uniformThresholds(graph, 0.1)
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// Student 1 is educated by a full-strength program: forwarding chance 0.
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chance := uniformChance(4, 0.5)
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chance[1] = 0
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result := RunCascade(graph, 0, chance, thresholds)
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// Student 1 still receives the fake in round 1, but the chain stops there.
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wantRounds := []int{0, 1, NeverReached, NeverReached}
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if !slices.Equal(result.ReachedAtRound, wantRounds) {
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t.Errorf("ReachedAtRound = %v, want %v", result.ReachedAtRound, wantRounds)
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}
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}
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func TestNewEdgeThresholdsDeterministicAndComplete(t *testing.T) {
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graph, err := HolmeKim(30, 3, 0.45, newRand(17))
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if err != nil {
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t.Fatal(err)
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}
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first := NewEdgeThresholds(graph, newRand(2))
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second := NewEdgeThresholds(graph, newRand(2))
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if wantSize := 2 * graph.NumEdges(); len(first) != wantSize {
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t.Errorf("len(thresholds) = %d, want %d (two directions per edge)", len(first), wantSize)
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}
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for directedEdge, firstDraw := range first {
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if firstDraw < 0 || firstDraw >= 1 {
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t.Errorf("threshold %v = %v, want in [0, 1)", directedEdge, firstDraw)
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}
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if secondDraw := second[directedEdge]; firstDraw != secondDraw {
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t.Errorf("threshold %v differs across identical seeds: %v != %v",
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directedEdge, firstDraw, secondDraw)
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}
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}
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}
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