87 lines
2.3 KiB
Go
87 lines
2.3 KiB
Go
/*
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Copyright © 2025 filifa
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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package markov
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import (
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"gonum.org/v1/gonum/graph"
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"gonum.org/v1/gonum/graph/multi"
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"gonum.org/v1/gonum/graph/simple"
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"gonum.org/v1/gonum/mat"
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)
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// AbsorbingMarkovChain is a graph representing an absorbing Markov chain. This
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// embeds a multi.WeightedDirectedGraph (as opposed to
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// simple.WeightedDirectedGraph) to handle self loops.
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type AbsorbingMarkovChain struct {
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*multi.WeightedDirectedGraph
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}
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// NewAbsorbingMarkovChain returns an absorbing Markov chain with no nodes or
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// edges.
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func NewAbsorbingMarkovChain() *AbsorbingMarkovChain {
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return &AbsorbingMarkovChain{WeightedDirectedGraph: multi.NewWeightedDirectedGraph()}
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}
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// AbsorbingNodes returns all the nodes in the Markov chain identified as
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// absorbing nodes.
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func (g *AbsorbingMarkovChain) AbsorbingNodes() []graph.Node {
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absorbingNodes := make([]graph.Node, 0)
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for nodes := g.Nodes(); nodes.Next(); {
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u := nodes.Node()
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successors := g.From(u.ID())
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if successors.Len() != 1 {
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continue
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}
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successors.Next()
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v := successors.Node()
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if u == v {
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absorbingNodes = append(absorbingNodes, u)
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}
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}
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return absorbingNodes
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}
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// AdjacencyMatrix returns the graph's adjacency matrix.
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func (g *AbsorbingMarkovChain) AdjacencyMatrix() *mat.Dense {
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adj := simple.NewDirectedMatrix(g.Nodes().Len(), 0, 0, 0)
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for edges := g.WeightedEdges(); edges.Next(); {
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e := edges.WeightedEdge()
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if e.From() == e.To() {
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continue
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}
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adj.SetWeightedEdge(e)
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}
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a := mat.DenseCopyOf(adj.Matrix())
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nodes := adj.Nodes()
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for i := 0; nodes.Next(); i++ {
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id := nodes.Node().ID()
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u := g.Node(id)
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e := g.WeightedEdge(u.ID(), u.ID())
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if e != nil {
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a.Set(i, i, e.Weight())
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}
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}
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return a
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}
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