From b01c97b0ccc0ce8b8383efffca9d432ea96bed0e Mon Sep 17 00:00:00 2001 From: balasan Date: Wed, 4 Nov 2020 17:17:52 -0800 Subject: [PATCH] deterministic pagerank --- .DS_Store | Bin 0 -> 6148 bytes deterministic/graph.go | 283 ++++++ deterministic/pagerank.go | 153 ++++ deterministic/pagerank_test.go | 398 +++++++++ deterministic/processResults.go | 36 + deterministic/test_utils.go | 26 + go.mod | 8 + go.sum | 837 ++++++++++++++++++ non-deterministic/.DS_Store | Bin 0 -> 6148 bytes graph.go => non-deterministic/graph.go | 36 +- pagerank.go => non-deterministic/pagerank.go | 3 +- .../pagerank_test.go | 62 +- .../processResults.go | 0 13 files changed, 1831 insertions(+), 11 deletions(-) create mode 100644 .DS_Store create mode 100644 deterministic/graph.go create mode 100644 deterministic/pagerank.go create mode 100644 deterministic/pagerank_test.go create mode 100644 deterministic/processResults.go create mode 100644 deterministic/test_utils.go create mode 100644 go.mod create mode 100644 go.sum create mode 100644 non-deterministic/.DS_Store rename graph.go => non-deterministic/graph.go (87%) rename pagerank.go => non-deterministic/pagerank.go (98%) rename pagerank_test.go => non-deterministic/pagerank_test.go (81%) rename processResults.go => non-deterministic/processResults.go (100%) diff --git a/.DS_Store b/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..b224374d9b2a96144faafc8d70955f6c5d1cb5e4 GIT binary patch literal 6148 zcmeHKOK;Oa5Z-MA*bN|8>Y^7F1-N@cFhbWT8 zi4!MIaOr`E_#1^E!LQ&35;tZalvHU$$^jy@Bh7x}-I?+3msxKXA%tt)$VJFO2w9*4 zOLNeiB4S+Vh|K7o%Yazs$WR+4h=S%L-loGaU>KM-2E^XIf+7?n4m!MlIqc$QlsD6m zu@tuVIJb1)^_#5S8Cu<#q-|EOhbare+j{Wr%gf~tN4Ll4Z?ou}5uMh^jOO9P#6WMJ zz1*;ucl6A@hMhFYdA0f(&&-xCT)br2b7i}HwQN83Tde2vfOqp+kTslTKZ)Wn$aa&6 zw{~K>nZ^e(y_0PRJkA~p=N(`W9F!e|_mjBSa27TgyoU|ZJGjjel6y3by` zdj00@yZ1*QWfa2V=M*xp;JE!H`+iH)a8*pe>M7MRLDX=ST-*EpTvy3Nk-w_te35@v zH3xo1Q%3iJyr0A#Gdj(No~%`#=1H2l83qgk|AYbYeITF$J&lDz`RRa0UI740&@BaQ zahDJ=M5Cv%PzWO+ScL+rP^_;QScOAB(SDxBLZJ#rSYJM{elylL6fEBk`H6H#*i&d) z!+>GnBm=YR(GlnW=GpiElR@UmFkl$?uNc6kx?iuslJwa+vN&4KOk)`Ms|@@ApXJzX literal 0 HcmV?d00001 diff --git a/deterministic/graph.go b/deterministic/graph.go new file mode 100644 index 0000000..15ec6f8 --- /dev/null +++ b/deterministic/graph.go @@ -0,0 +1,283 @@ +// Package reputation is an implementation of the Relevant Reputaiton protocol: +// a personalized pagerank algorithm that supports negative links +// personalized version offers sybil resistance +// can be used for voting, governance, ranking +// references: +// https://github.com/alixaxel/pagerank +// https://github.com/dcadenas/pagerank +// notes: +// Optimization - using int-indexed maps? +// TODO: edge case (only impacts display) - if a node has no inputs we should set its score to 0 to avoid +// a stale score if all of nodes inputs are cancelled out +// would need to keep track of node inputs... +package reputation_det + +import ( + "strconv" + + sdk "github.com/cosmos/cosmos-sdk/types" +) + +// NodeType is positive or negative +// each node in the graph can be represented by two nodes, +// a positive and a negative one +type NodeType int + +// Positive nodes are consumers of positive links +// Negative nodes are consumers of neg links +const ( + Positive NodeType = iota + Negative +) + +const Decimals = 18 + +// this is defines the cutoff for when a node will have it's outging links counted +// if previously NegativeRank / PositiveRank > MaxNegOffset / (MaxNegOffset + 1) we will not consider +// any outgoing links +// otherwise, we counter the outgoing lings with one 'heavy' link proportional to the MaxNegOffset ratio +const MaxNegOffset = 10 + +type NodeInput struct { + Id string + PRank sdk.Uint + NRank sdk.Uint +} + +type Node struct { + id string + rank sdk.Uint // pos page rank of the node + rankNeg sdk.Uint // only used when combining results + degree sdk.Uint // sum of all outgoing links + nodeType NodeType +} + +// Graph holds node and edge data. +type Graph struct { + nodes map[string]*Node + negNodes map[string]*Node + edges map[string](map[string]sdk.Uint) + params RankParams + negConsumer NodeInput + Precision sdk.Uint + MaxNegOffset sdk.Uint +} + +type RankParams struct { + α, ε sdk.Uint + personalization []string +} + +// NewGraph initializes and returns a new graph. +func NewGraph(α sdk.Uint, ε sdk.Uint, negConsumerRank sdk.Uint) *Graph { + return &Graph{ + nodes: make(map[string]*Node), + negNodes: make(map[string]*Node), + edges: make(map[string](map[string]sdk.Uint)), + params: RankParams{ + α: α, + ε: ε, + personalization: make([]string, 0), + }, + negConsumer: NodeInput{Id: "negConsumer", PRank: negConsumerRank, NRank: sdk.ZeroUint()}, + Precision: sdk.NewUintFromBigInt(sdk.NewIntWithDecimal(1, Decimals).BigInt()), + MaxNegOffset: sdk.NewUintFromBigInt(sdk.NewIntWithDecimal(MaxNegOffset, Decimals).BigInt()), + } +} + +// helper method to create a node input struct +func NewNodeInput(id string, pRank sdk.Uint, nRank sdk.Uint) NodeInput { + return NodeInput{Id: id, PRank: pRank, NRank: nRank} +} + +// AddPersonalizationNode adds a node to the pagerank personlization vector +// these nodes will have high rank by default and all other rank will stem from them +// this makes non-personalaziation nodes sybil resistant (they cannot increase their own rank) +func (graph *Graph) AddPersonalizationNode(pNode NodeInput) { + graph.params.personalization = append(graph.params.personalization, pNode.Id) + // this to ensures source nodes exist + graph.InitPosNode(pNode) +} + +// Link creates a weighted edge between a source-target node pair. +// If the edge already exists, the weight is incremented. +func (graph *Graph) Link(source, target NodeInput, weight sdk.Int) { + + // if a node's neg/pos rank is > MaxNegOffset / (MaxNegOffset + 1) we don't process it + if source.PRank.GT(sdk.ZeroUint()) { + negPosRatio := source.NRank.Mul(graph.Precision).Quo(source.PRank) + one := graph.Precision + if negPosRatio.GT(graph.MaxNegOffset.Mul(graph.Precision).Quo(graph.MaxNegOffset.Add(one))) { + return + } + } + + sourceKey := getKey(source.Id, Positive) + sourceNode := graph.initNode(sourceKey, source, Positive) + + // if weight is negative we use negative receiving node + var nodeType NodeType + var weightUint sdk.Uint + if weight.LT(sdk.ZeroInt()) { + nodeType = Negative + weightUint = sdk.NewUintFromBigInt(weight.Neg().BigInt()) + } else { + nodeType = Positive + weightUint = sdk.NewUintFromBigInt(weight.BigInt()) + } + targetKey := getKey(target.Id, nodeType) + + graph.initNode(targetKey, target, nodeType) + + sourceNode.degree = sourceNode.degree.Add(weightUint) + + if _, ok := graph.edges[sourceKey]; ok == false { + graph.edges[sourceKey] = map[string]sdk.Uint{} + } + + if _, ok := graph.edges[sourceKey][targetKey]; ok == false { + graph.edges[sourceKey][targetKey] = sdk.ZeroUint() + } + + graph.edges[sourceKey][targetKey] = graph.edges[sourceKey][targetKey].Add(weightUint) + + // note: use target.id here to make sure we reference the original id + graph.cancelOpposites(*sourceNode, target.Id, nodeType) +} + +func (graph *Graph) Finalize() { + graph.processNegatives() +} + +// processNegatives creates an extra outgoing link from positive nodes +// if they have a negative counterpart +// this reduces the weight of the outgoing links from low-ranking nodes +func (graph *Graph) processNegatives() { + negConsumerInput := graph.negConsumer + + for _, negNode := range graph.negNodes { + // positive node doesn't exist + if _, ok := graph.nodes[negNode.id]; ok == false { + return + } + + // node has no outgpoing links + if graph.nodes[negNode.id].degree.IsZero() { + return + } + + posNode := graph.nodes[negNode.id] + if posNode.rank.IsZero() || negNode.rank.IsZero() { + return + } + negConsumer := graph.initNode(negConsumerInput.Id, negConsumerInput, Positive) + + one := graph.Precision + + // posNode.rank is not 0 check above + negPosRatio := negNode.rank.Mul(graph.Precision).Quo(posNode.rank) + + var negMultiple sdk.Uint + + // if negPosRatio > MaxNegOffset / (MaxNegOffset + 1) we use the MaxNegOffset + // this first case should not happen because we ignore these links + if negPosRatio.GT(graph.MaxNegOffset.Mul(graph.Precision).Quo(graph.MaxNegOffset.Add(one))) { + negMultiple = graph.MaxNegOffset + } else { + denom := one.Sub(negPosRatio) + negMultiple = one.Mul(graph.Precision).Quo(denom).Sub(one) + } + // cap the vote decrease at 10x + negWeight := negMultiple.Mul(graph.nodes[negNode.id].degree).Quo(graph.Precision) + + // this should actually never happen if degree is > 0 + if _, ok := graph.edges[negNode.id]; ok == false { + graph.edges[negNode.id] = map[string]sdk.Uint{} + } + + if _, ok := graph.edges[negNode.id][negConsumer.id]; ok == false { + graph.edges[negNode.id][negConsumer.id] = sdk.ZeroUint() + } + + graph.edges[negNode.id][negConsumer.id] = graph.edges[negNode.id][negConsumer.id].Add(negWeight) + graph.nodes[negNode.id].degree = graph.nodes[negNode.id].degree.Add(negWeight) + } +} + +// if there is both a positive and a negative link from A to B we cancel them out +func (graph *Graph) cancelOpposites(sourceNode Node, target string, nodeType NodeType) { + key := getKey(target, nodeType) + var oppositeKey string + if oppositeKey = getKey(target, Positive); nodeType == Positive { + oppositeKey = getKey(target, Negative) + } + + if _, ok := graph.edges[sourceNode.id][oppositeKey]; ok == false { + return + } + + edge := graph.edges[sourceNode.id][key] + opositeEdge := graph.edges[sourceNode.id][oppositeKey] + + switch { + case opositeEdge.GT(edge): + graph.removeEdge(sourceNode.id, key) + graph.edges[sourceNode.id][oppositeKey] = opositeEdge.Sub(edge) + // remove degree from both delete node and the adjustment + sourceNode.degree = sourceNode.degree.Sub(edge.Mul(sdk.NewUint(2))) + + case edge.GT(opositeEdge): + graph.removeEdge(sourceNode.id, oppositeKey) + graph.edges[sourceNode.id][key] = edge.Sub(opositeEdge) + // remove degree from both delete node and the adjustment + sourceNode.degree = sourceNode.degree.Sub(opositeEdge.Mul(sdk.NewUint(2))) + + case edge.Equal(opositeEdge): + graph.removeEdge(sourceNode.id, oppositeKey) + graph.removeEdge(sourceNode.id, key) + + sourceNode.degree = sourceNode.degree.Sub(opositeEdge.Mul(sdk.NewUint(2))) + } +} + +func (graph *Graph) InitPosNode(inputNode NodeInput) *Node { + return graph.initNode(inputNode.Id, inputNode, Positive) +} + +func (graph *Graph) initNode(key string, inputNode NodeInput, nodeType NodeType) *Node { + if _, ok := graph.nodes[key]; ok == false { + graph.nodes[key] = &Node{ + id: inputNode.Id, // id is independent of pos/neg keys + degree: sdk.ZeroUint(), + rank: sdk.ZeroUint(), + rankNeg: sdk.ZeroUint(), + nodeType: nodeType, + } + // store negative nodes so we can easily merge them later + if nodeType == Negative { + graph.negNodes[key] = graph.nodes[key] + } + } + // update rank here in case we initilized with 0 early on + var prevRank sdk.Uint + if prevRank = inputNode.PRank; nodeType == Negative { + prevRank = inputNode.NRank + } + graph.nodes[key].rank = prevRank + return graph.nodes[key] +} + +func (graph *Graph) removeEdge(source string, target string) { + delete(graph.edges[source], target) + if len(graph.edges[source]) == 0 { + delete(graph.edges, source) + } +} + +func getKey(key string, nodeType NodeType) string { + if nodeType == Positive { + return key + } + // TODO whats the best way to do this if we use int indexes? odd & even? + return key + "_" + strconv.FormatInt(int64(nodeType), 10) +} diff --git a/deterministic/pagerank.go b/deterministic/pagerank.go new file mode 100644 index 0000000..2b466b8 --- /dev/null +++ b/deterministic/pagerank.go @@ -0,0 +1,153 @@ +package reputation_det + +import ( + sdk "github.com/cosmos/cosmos-sdk/types" +) + +// Rank computes the PageRank of every node in the directed graph. +// α (alpha) is the damping factor, usually set to 0.85. +// ε (epsilon) is the convergence criteria, usually set to a tiny value. +// +// This method will run as many iterations as needed, until the graph converges. +func (graph Graph) Rank(callback func(key string, pRank sdk.Uint, nRank sdk.Uint)) { + graph.Finalize() + + one := graph.Precision + + Δ := one + N := sdk.NewUint(uint64(len(graph.nodes))) + pVector := graph.params.personalization + ε := graph.params.ε + α := graph.params.α + + personalized := len(pVector) > 0 + + // these are personlaization node weights + // we adjust them so that all p nodes have the same outgoing link weight + pWeights := graph.initPersonalizationNodes() + + // Normalize all the edge weights so that their sum amounts to 1. + for source := range graph.nodes { + if graph.nodes[source].degree.GT(sdk.ZeroUint()) { + for target := range graph.edges[source] { + graph.edges[source][target] = graph.edges[source][target].Mul(graph.Precision).Quo(graph.nodes[source].degree) + } + } + } + + graph.initScores(N, pWeights) + + iter := 0 + for Δ.GT(ε) { + danglingWeight := sdk.ZeroUint() + nodes := map[string]sdk.Uint{} + + for key, value := range graph.nodes { + nodes[key] = value.rank + + if value.degree.IsZero() { + danglingWeight = danglingWeight.Add(value.rank) + } + + graph.nodes[key].rank = sdk.ZeroUint() + } + + danglingWeight = danglingWeight.Mul(α).Quo(graph.Precision) + + for source := range graph.nodes { + for target, weight := range graph.edges[source] { + addWeight := α.Mul(nodes[source]).Quo(graph.Precision).Mul(weight).Quo(graph.Precision) + graph.nodes[target].rank = graph.nodes[target].rank.Add(addWeight) + } + + if !personalized { + graph.nodes[source].rank = graph.nodes[source].rank.Add(one.Sub(α).Quo(N).Add(danglingWeight.Quo(N))) + } + } + + // random jump + dangling weights are transferred to admins + // this makes pagerank sybil resistant + if personalized { + for i, root := range pVector { + graph.nodes[root].rank = graph.nodes[root].rank.Add((one.Sub(α).Add(danglingWeight)).Mul(pWeights[i])).Quo(graph.Precision) + } + } + + Δ = sdk.ZeroUint() + + for key, value := range graph.nodes { + var diff sdk.Uint + // if _, ok := nodes[key]; ok == false { + // nodes[key] = sdk.ZeroUint() + // } + if value.rank.LT(nodes[key]) { + diff = nodes[key].Sub(value.rank) + } else { + diff = value.rank.Sub(nodes[key]) + } + Δ = Δ.Add(diff) + } + iter++ + } + + // fmt.Println("iterations:", iter, "Δ", Δ) + graph.processResults(callback) +} + +// make sure the total start sum of all scores is 1 +// we initialze the start scores to optimize the computation +func (graph Graph) initScores(N sdk.Uint, pWeights []sdk.Uint) { + // get sum of all node scores + personalization := graph.params.personalization + totalScore := sdk.ZeroUint() + for _, node := range graph.nodes { + totalScore = totalScore.Add(node.rank) + } + + // if start sum is close to 1 we are done + if totalScore.GT(graph.Precision.MulUint64(9).QuoUint64(10)) { + return + } + + // TODO use prev scores for initialization + if len(pWeights) == 0 { + // initialize all nodes if there is no personalizeation vector + for key := range graph.nodes { + graph.nodes[key].rank = graph.nodes[key].rank.Add(graph.Precision.Sub(totalScore).Quo(N)) + } + return + } + // initialize personalization vector + for i, root := range personalization { + graph.nodes[root].rank = graph.nodes[root].rank.Add(graph.Precision.Sub(totalScore).Mul(graph.Precision).Quo(pWeights[i])) + } +} + +// compute personalization weights based on degree +// this ensures source nodes will have the same weight +// we also update start scores here +func (graph Graph) initPersonalizationNodes() []sdk.Uint { + pVector := graph.params.personalization + pWeights := make([]sdk.Uint, len(pVector)) + + pWeightsSum := sdk.ZeroUint() + scoreSum := sdk.ZeroUint() + for i, key := range pVector { + var d sdk.Uint + // root node score and weight should not be 0 + if d = graph.Precision; graph.nodes[key].degree.GT(sdk.ZeroUint()) { + d = graph.nodes[key].degree + } + pWeights[i] = d + pWeightsSum = pWeightsSum.Add(d) + scoreSum = scoreSum.Add(graph.nodes[key].rank) + } + + // normalize personalization weights + for i, key := range pVector { + pWeights[i] = pWeights[i].Mul(graph.Precision).Quo(pWeightsSum) + graph.nodes[key].rank = scoreSum.Mul(pWeights[i]).Quo(graph.Precision) + } + + return pWeights +} diff --git a/deterministic/pagerank_test.go b/deterministic/pagerank_test.go new file mode 100644 index 0000000..7d05d90 --- /dev/null +++ b/deterministic/pagerank_test.go @@ -0,0 +1,398 @@ +package reputation_det + +import ( + "reflect" + "testing" + + sdk "github.com/cosmos/cosmos-sdk/types" +) + +type Result struct { + pRank sdk.Uint + nRank sdk.Uint +} + +var zero = sdk.ZeroUint() + +func TestEmpty(t *testing.T) { + graph := NewGraphHelper(0.85, 0.000001, zero) + + actual := map[string]Result{} + expected := map[string]Result{} + + graph.Rank(func(id string, pRank sdk.Uint, nRank sdk.Uint) { + actual[id] = Result{ + pRank: pRank, + nRank: nRank, + } + }) + + if reflect.DeepEqual(actual, expected) != true { + t.Error("Expected", expected, "but got", actual) + } +} + +func TestSimple(t *testing.T) { + graph := NewGraphHelper(0.85, 0.000001, zero) + + a := NewNodeInputHelper("a", 0, 0) + b := NewNodeInputHelper("b", 0, 0) + c := NewNodeInputHelper("c", 0, 0) + d := NewNodeInputHelper("d", 0, 0) + + // circle + graph.LinkHelper(a, b, 1.0) + graph.LinkHelper(b, c, 1.0) + graph.LinkHelper(c, d, 1.0) + graph.LinkHelper(d, a, 1.0) + + actual := map[string]Result{} + expected := map[string]Result{ + "a": {pRank: FtoBD(0.25), nRank: FtoBD(0)}, + "b": {pRank: FtoBD(0.25), nRank: FtoBD(0)}, + "c": {pRank: FtoBD(0.25), nRank: FtoBD(0)}, + "d": {pRank: FtoBD(0.25), nRank: FtoBD(0)}, + } + + graph.Rank(func(id string, pRank sdk.Uint, nRank sdk.Uint) { + actual[id] = Result{ + pRank: pRank, + nRank: nRank, + } + }) + + for key, value := range actual { + expVal := expected[key] + if !value.pRank.Equal(expVal.pRank) { + t.Error("Expected", expVal.pRank.String(), "but got", value.pRank.String()) + } + if !value.nRank.Equal(expVal.nRank) { + t.Error("Expected", expVal.nRank.String(), "but got", value.nRank.String()) + } + } +} + +func TestWeighted(t *testing.T) { + graph := NewGraphHelper(0.85, 0.000001, zero) + + a := NewNodeInputHelper("a", 0, 0) + b := NewNodeInputHelper("b", 0, 0) + c := NewNodeInputHelper("c", 0, 0) + + graph.LinkHelper(a, b, 1.0) + graph.LinkHelper(a, c, 2.0) + + actual := map[string]Result{} + + graph.Rank(func(id string, pRank sdk.Uint, nRank sdk.Uint) { + actual[id] = Result{ + pRank: pRank, + nRank: nRank, + } + }) + + if actual["b"].pRank.GTE(actual["c"].pRank) { + t.Errorf("rank of b %s is not > c %s", actual["b"].pRank.String(), actual["c"].pRank.String()) + } +} + +func TestPersonalized(t *testing.T) { + graph := NewGraphHelper(0.85, 0.000001, zero) + + a := NewNodeInputHelper("a", 0, 0) + b := NewNodeInputHelper("b", 0, 0) + c := NewNodeInputHelper("c", 0, 0) + d := NewNodeInputHelper("d", 0, 0) + + graph.AddPersonalizationNode(a) + + graph.LinkHelper(a, b, 1.0) + graph.LinkHelper(d, c, 2.0) + + actual := map[string]Result{} + expected := map[string]Result{ + "a": {pRank: FtoBD(0.25), nRank: FtoBD(0)}, + "b": {pRank: FtoBD(0.25), nRank: FtoBD(0)}, + "c": {pRank: FtoBD(0), nRank: FtoBD(0)}, + "d": {pRank: FtoBD(0), nRank: FtoBD(0)}, + } + + graph.Rank(func(id string, pRank sdk.Uint, nRank sdk.Uint) { + actual[id] = Result{ + pRank: pRank, + nRank: nRank, + } + }) + + if reflect.DeepEqual(actual["c"], expected["c"]) != true { + t.Error("Expected", expected["c"], "but got", actual["c"]) + } + if reflect.DeepEqual(actual["d"], expected["d"]) != true { + t.Error("Expected", expected["d"], "but got", actual["d"]) + } +} + +func TestPersonalizedNoLinkHelper(t *testing.T) { + graph := NewGraphHelper(0.85, 0.000001, zero) + + a := NewNodeInputHelper("a", 0, 0) + b := NewNodeInputHelper("b", 0, 0) + c := NewNodeInputHelper("c", 0, 0) + d := NewNodeInputHelper("d", 0, 0) + + graph.AddPersonalizationNode(a) + + graph.LinkHelper(b, c, 1.0) + graph.LinkHelper(d, c, 1.0) + + actual := map[string]Result{} + + expected := map[string]Result{ + "a": {pRank: FtoBD(1.0), nRank: FtoBD(0)}, + "b": {pRank: FtoBD(0), nRank: FtoBD(0)}, + "c": {pRank: FtoBD(0), nRank: FtoBD(0)}, + "d": {pRank: FtoBD(0), nRank: FtoBD(0)}, + } + + graph.Rank(func(id string, pRank sdk.Uint, nRank sdk.Uint) { + actual[id] = Result{ + pRank: pRank, + nRank: nRank, + } + }) + + if reflect.DeepEqual(actual, expected) != true { + t.Error("Expected", expected, "but got", actual) + } +} + +func TestCancelOpposites(t *testing.T) { + graph := NewGraphHelper(0.85, 0.000001, zero) + + a := NewNodeInputHelper("a", 0, 0) + b := NewNodeInputHelper("b", 0, 0) + c := NewNodeInputHelper("c", 0, 0) + d := NewNodeInputHelper("d", 0, 0) + + graph.AddPersonalizationNode(a) + + graph.LinkHelper(a, b, 1.0) + graph.LinkHelper(a, b, -1.0) + graph.LinkHelper(a, c, 2.0) + graph.LinkHelper(a, c, -1.0) + graph.LinkHelper(a, d, 1.0) + graph.LinkHelper(a, d, -2.0) + + actual := map[string]Result{} + + graph.Rank(func(id string, pRank sdk.Uint, nRank sdk.Uint) { + actual[id] = Result{ + pRank: pRank, + nRank: nRank, + } + }) + + if !actual["b"].pRank.Add(actual["b"].nRank).Equal(sdk.ZeroUint()) { + t.Errorf("rank of b should be 0 but its %s", actual["b"].pRank.String()) + } + + if !actual["c"].nRank.Equal(sdk.ZeroUint()) { + t.Errorf("c rank should be positive") + } + + if !actual["d"].pRank.Equal(sdk.ZeroUint()) { + t.Errorf("d rank should be negative") + } +} + +func TestNegativeLink(t *testing.T) { + graph := NewGraphHelper(0.85, 0.000001, zero) + + a := NewNodeInputHelper("a", 0, 0) + b := NewNodeInputHelper("b", 0, 0) + c := NewNodeInputHelper("c", 0, 0) + d := NewNodeInputHelper("d", 0, 0) + e := NewNodeInputHelper("e", 0, 0) + + graph.AddPersonalizationNode(a) + + graph.LinkHelper(a, b, 2.0) + graph.LinkHelper(a, c, 1.0) + graph.LinkHelper(c, d, 1.0) + graph.LinkHelper(b, d, -1.0) + graph.LinkHelper(a, e, -1.0) + + actual := map[string]Result{} + + graph.Rank(func(id string, pRank sdk.Uint, nRank sdk.Uint) { + actual[id] = Result{ + pRank: pRank, + nRank: nRank, + } + }) + + if actual["d"].nRank.Sub(actual["d"].pRank).LTE(sdk.ZeroUint()) { + t.Errorf("rank of d should be neagative") + } + + if !actual["e"].pRank.Equal(sdk.ZeroUint()) || actual["e"].nRank.Equal(sdk.ZeroUint()) { + t.Errorf("pure neagative node has incorrect results") + } + + // use prev computation as input for the next iteration + initNegativeConsumer := actual["negConsumer"].pRank + if _, ok := actual["negConsumer"]; ok == false { + initNegativeConsumer = zero + } + + graph = NewGraphHelper(0.85, 0.000001, initNegativeConsumer) + + a = NewNodeInput("a", actual["a"].pRank, actual["a"].nRank) + b = NewNodeInput("b", actual["b"].pRank, actual["b"].nRank) + c = NewNodeInput("c", actual["c"].pRank, actual["c"].nRank) + d = NewNodeInput("d", actual["d"].pRank, actual["d"].nRank) + e = NewNodeInput("e", actual["e"].pRank, actual["e"].nRank) + + graph.AddPersonalizationNode(a) + + graph.LinkHelper(a, b, 2.0) + graph.LinkHelper(a, c, 1.0) + graph.LinkHelper(c, d, 1.0) + graph.LinkHelper(b, d, -1.0) + graph.LinkHelper(d, e, 1.0) + + graph.Rank(func(id string, pRank sdk.Uint, nRank sdk.Uint) { + actual[id] = Result{ + pRank: pRank, + nRank: nRank, + } + }) + + if !actual["e"].pRank.Equal(sdk.ZeroUint()) { + t.Errorf("weight of neg node should be 0") + } +} + +func TestNegativeConsumer(t *testing.T) { + graph := NewGraphHelper(0.85, 0.000001, zero) + + a := NewNodeInputHelper("a", 0, 0) + b := NewNodeInputHelper("b", 0, 0) + c := NewNodeInputHelper("c", 0, 0) + d := NewNodeInputHelper("d", 0, 0) + e := NewNodeInputHelper("e", 0, 0) + + graph.AddPersonalizationNode(a) + + graph.LinkHelper(a, b, 1.0) + graph.LinkHelper(a, c, 2.0) + graph.LinkHelper(c, d, 1.0) + graph.LinkHelper(b, d, -1.0) + graph.LinkHelper(d, e, 1.0) + + actual := map[string]Result{} + + graph.Rank(func(id string, pRank sdk.Uint, nRank sdk.Uint) { + actual[id] = Result{ + pRank: pRank, + nRank: nRank, + } + }) + + // use prev computation as input for the next iteration + initNegativeConsumer := actual["negConsumer"].pRank + if _, ok := actual["negConsumer"]; ok == false { + initNegativeConsumer = zero + } + + graph = NewGraphHelper(0.85, 0.000001, initNegativeConsumer) + + eRank := actual["e"].pRank + + a = NewNodeInput("a", actual["a"].pRank, actual["a"].nRank) + b = NewNodeInput("b", actual["b"].pRank, actual["b"].nRank) + c = NewNodeInput("c", actual["c"].pRank, actual["c"].nRank) + d = NewNodeInput("d", actual["d"].pRank, actual["d"].nRank) + e = NewNodeInput("e", actual["e"].pRank, actual["e"].nRank) + + graph.AddPersonalizationNode(a) + + graph.LinkHelper(a, b, 1.0) + graph.LinkHelper(a, c, 2.0) + graph.LinkHelper(c, d, 1.0) + graph.LinkHelper(b, d, -1.0) + graph.LinkHelper(d, e, 1.0) + + graph.Rank(func(id string, pRank sdk.Uint, nRank sdk.Uint) { + actual[id] = Result{ + pRank: pRank, + nRank: nRank, + } + }) + + if eRank.LT(actual["e"].pRank) { + t.Errorf("weight of neg node should decrease") + } +} + +func TestMaxNeg(t *testing.T) { + graph := NewGraphHelper(0.85, 0.000001, zero) + + a := NewNodeInputHelper("a", 0, 0) + b := NewNodeInputHelper("b", 0, 0) + c := NewNodeInputHelper("c", 0, 0) + d := NewNodeInputHelper("d", 0, 0) + e := NewNodeInputHelper("e", 0, 0) + + graph.AddPersonalizationNode(a) + + graph.LinkHelper(a, b, 11.0) + graph.LinkHelper(a, c, 12.0) + graph.LinkHelper(c, d, 1.0) + graph.LinkHelper(b, d, -1.0) + graph.LinkHelper(d, e, 1.0) + + actual := map[string]Result{} + + graph.Rank(func(id string, pRank sdk.Uint, nRank sdk.Uint) { + actual[id] = Result{ + pRank: pRank, + nRank: nRank, + } + }) + + // use prev computation as input for the next iteration + initNegativeConsumer := actual["negConsumer"].pRank + if _, ok := actual["negConsumer"]; ok == false { + initNegativeConsumer = zero + } + + graph = NewGraphHelper(0.85, 0.000001, initNegativeConsumer) + + eRank := actual["e"].pRank + + a = NewNodeInput("a", actual["a"].pRank, actual["a"].nRank) + b = NewNodeInput("b", actual["b"].pRank, actual["b"].nRank) + c = NewNodeInput("c", actual["c"].pRank, actual["c"].nRank) + d = NewNodeInput("d", actual["d"].pRank, actual["d"].nRank) + e = NewNodeInput("e", actual["e"].pRank, actual["e"].nRank) + + graph.AddPersonalizationNode(a) + + graph.LinkHelper(a, b, 11.0) + graph.LinkHelper(a, c, 12.0) + graph.LinkHelper(c, d, 1.0) + graph.LinkHelper(b, d, -1.0) + graph.LinkHelper(d, e, 1.0) + + graph.Rank(func(id string, pRank sdk.Uint, nRank sdk.Uint) { + actual[id] = Result{ + pRank: pRank, + nRank: nRank, + } + }) + + if eRank.LT(actual["e"].pRank) { + t.Errorf("weight of neg node should decrease") + } +} diff --git a/deterministic/processResults.go b/deterministic/processResults.go new file mode 100644 index 0000000..79f8bf9 --- /dev/null +++ b/deterministic/processResults.go @@ -0,0 +1,36 @@ +package reputation_det + +import ( + sdk "github.com/cosmos/cosmos-sdk/types" +) + +type Results struct { + rankPos float64 + rankNeg float64 + id string +} + +func (graph Graph) processResults(callback func(id string, pRank sdk.Uint, nRank sdk.Uint)) { + graph.mergeNegatives() + for key, node := range graph.nodes { + callback(key, node.rank, node.rankNeg) + } +} + +func (graph Graph) mergeNegatives() { + for key, node := range graph.negNodes { + // create the positive node if it doesn't exist + if _, ok := graph.nodes[node.id]; ok == false { + graph.nodes[node.id] = &Node{ + id: key, + rank: sdk.ZeroUint(), + degree: sdk.ZeroUint(), + nodeType: Positive, + } + } + // write the neg rank value to the positive node + graph.nodes[node.id].rankNeg = node.rank + // we don't want negative nodes around after they are merged + delete(graph.nodes, key) + } +} diff --git a/deterministic/test_utils.go b/deterministic/test_utils.go new file mode 100644 index 0000000..8fad082 --- /dev/null +++ b/deterministic/test_utils.go @@ -0,0 +1,26 @@ +package reputation_det + +import ( + "math" + + sdk "github.com/cosmos/cosmos-sdk/types" +) + +// FtoBD converts a float64 to a Uint with decimals (i * 10^decimals) +func FtoBD(n float64) sdk.Uint { + return sdk.NewUint(uint64(n * math.Pow(10, float64(Decimals)))) +} + +func NewGraphHelper(α, ε float64, negConsumerRank sdk.Uint) *Graph { + return NewGraph(FtoBD(α), FtoBD(ε), negConsumerRank) +} + +func NewNodeInputHelper(id string, pRank float64, nRank float64) NodeInput { + return NewNodeInput(id, FtoBD(pRank), FtoBD(nRank)) +} + +func (graph Graph) LinkHelper(source, target NodeInput, weight float64) { + weightInt := sdk.NewInt(int64(weight * math.Pow(10, float64(Decimals/2)))) + weightInt = weightInt.Mul(sdk.NewInt(int64(math.Pow(10, float64(Decimals/2))))) + graph.Link(source, target, weightInt) +} diff --git a/go.mod b/go.mod new file mode 100644 index 0000000..15e881c --- /dev/null +++ b/go.mod @@ -0,0 +1,8 @@ +module github.com/relevant-community/reputation + +go 1.15 + +require ( + github.com/cosmos/cosmos-sdk v0.40.0-rc0 + github.com/google/go-cmp v0.5.0 +) diff --git a/go.sum b/go.sum new file mode 100644 index 0000000..afb419c --- /dev/null +++ b/go.sum @@ -0,0 +1,837 @@ +cloud.google.com/go v0.26.0/go.mod h1:aQUYkXzVsufM+DwF1aE+0xfcU+56JwCaLick0ClmMTw= +cloud.google.com/go v0.34.0/go.mod h1:aQUYkXzVsufM+DwF1aE+0xfcU+56JwCaLick0ClmMTw= +cloud.google.com/go v0.38.0/go.mod h1:990N+gfupTy94rShfmMCWGDn0LpTmnzTp2qbd1dvSRU= +cloud.google.com/go v0.44.1/go.mod h1:iSa0KzasP4Uvy3f1mN/7PiObzGgflwredwwASm/v6AU= +cloud.google.com/go v0.44.2/go.mod h1:60680Gw3Yr4ikxnPRS/oxxkBccT6SA1yMk63TGekxKY= +cloud.google.com/go v0.45.1/go.mod h1:RpBamKRgapWJb87xiFSdk4g1CME7QZg3uwTez+TSTjc= +cloud.google.com/go v0.46.3/go.mod h1:a6bKKbmY7er1mI7TEI4lsAkts/mkhTSZK8w33B4RAg0= 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== 0 { + return + } + posNode := graph.nodes[negNode.id] if posNode.rank == 0 { return } + + if negNode.rank >= posNode.rank { + panic("negative ranking nodes should not have any degree") // this should never happen + } + negConsumer := graph.initNode(negConsumerInput.Id, negConsumerInput, Positive) + var negMultiple float64 + + // this first case should not happen because we ignore these links + if negNode.rank/posNode.rank > MAX_NEG_OFFSET/(MAX_NEG_OFFSET+1) { + // cap the degree multiple at MAX_NEG_OFFSET + negMultiple = MAX_NEG_OFFSET + } else { + negMultiple = 1/(1-negNode.rank/posNode.rank) - 1 + } + // this is the weight we add to the outgoing node - negWeight := math.Max(0, 1/(1-negNode.rank/posNode.rank)-1) - // cap the vote decrease at 10x - negWeight = math.Min(10, negWeight) * graph.nodes[negNode.id].degree + negWeight := negMultiple * graph.nodes[negNode.id].degree if _, ok := graph.edges[negNode.id]; ok == false { graph.edges[negNode.id] = map[string]float64{} @@ -170,13 +190,13 @@ func (graph *Graph) cancelOpposites(sourceNode Node, target string, nodeType Nod switch { case opositeEdge > edge: graph.removeEdge(sourceNode.id, key) - graph.edges[sourceNode.id][oppositeKey] = -edge + graph.edges[sourceNode.id][oppositeKey] -= edge // remove degree from both delete node and the adjustment sourceNode.degree -= 2 * edge case edge > opositeEdge: graph.removeEdge(sourceNode.id, oppositeKey) - graph.edges[sourceNode.id][key] = -opositeEdge + graph.edges[sourceNode.id][key] -= opositeEdge // remove degree from both delete node and the adjustment sourceNode.degree -= 2 * opositeEdge diff --git a/pagerank.go b/non-deterministic/pagerank.go similarity index 98% rename from pagerank.go rename to non-deterministic/pagerank.go index 8e49e7e..9c16326 100644 --- a/pagerank.go +++ b/non-deterministic/pagerank.go @@ -1,7 +1,6 @@ package reputation import ( - "fmt" "math" ) @@ -79,7 +78,7 @@ func (graph Graph) Rank(callback func(key string, pRank float64, nRank float64)) iter++ } - fmt.Println("iterations:", iter, "Δ", Δ) + // fmt.Println("iterations:", iter, "Δ", Δ) graph.processResults(callback) } diff --git a/pagerank_test.go b/non-deterministic/pagerank_test.go similarity index 81% rename from pagerank_test.go rename to non-deterministic/pagerank_test.go index 2d67669..8ecefba 100644 --- a/pagerank_test.go +++ b/non-deterministic/pagerank_test.go @@ -313,6 +313,66 @@ func TestNegativeConsumer(t *testing.T) { }) if eRank <= actual["e"].pRank { - t.Errorf("weight of neg node should decrease") + t.Errorf("weight of neg node should decrease %f, %f", eRank, actual["e"].pRank) + } +} + +func TestMaxNeg(t *testing.T) { + graph := NewGraph(0.85, 0.000001, 0) + + a := NewNodeInput("a", 0, 0) + b := NewNodeInput("b", 0, 0) + c := NewNodeInput("c", 0, 0) + d := NewNodeInput("d", 0, 0) + e := NewNodeInput("e", 0, 0) + + graph.AddPersonalizationNode(a) + + graph.Link(a, b, MAX_NEG_OFFSET+1) + graph.Link(a, c, MAX_NEG_OFFSET+2) + graph.Link(c, d, 1.0) + graph.Link(b, d, -1.0) + graph.Link(d, e, 1.0) + + actual := map[string]Result{} + + graph.Rank(func(id string, pRank float64, nRank float64) { + actual[id] = Result{ + pRank: pRank, + nRank: nRank, + } + }) + + // use prev computation as input for the next iteration + + graph = NewGraph(0.85, 0.000001, actual["negConsumer"].pRank) + + eRank := actual["e"].pRank + + a = NewNodeInput("a", actual["a"].pRank, actual["a"].nRank) + b = NewNodeInput("b", actual["b"].pRank, actual["b"].nRank) + c = NewNodeInput("c", actual["c"].pRank, actual["c"].nRank) + d = NewNodeInput("d", actual["d"].pRank, actual["d"].nRank) + e = NewNodeInput("e", 0, 0) + + graph.AddPersonalizationNode(a) + + graph.Link(a, b, MAX_NEG_OFFSET+1) + graph.Link(a, c, MAX_NEG_OFFSET+2) + graph.Link(c, d, 1.0) + graph.Link(b, d, -1.0) + graph.Link(d, e, 1.0) + + actual = map[string]Result{} + + graph.Rank(func(id string, pRank float64, nRank float64) { + actual[id] = Result{ + pRank: pRank, + nRank: nRank, + } + }) + + if eRank <= actual["e"].pRank { + t.Errorf("weight of neg node should decrease %f, %f", eRank, actual["e"].pRank) } } diff --git a/processResults.go b/non-deterministic/processResults.go similarity index 100% rename from processResults.go rename to non-deterministic/processResults.go