Class RandomWalk
- All Implemented Interfaces:
Algorithm
,DynamicAlgorithm
,org.graphstream.stream.AttributeSink
,org.graphstream.stream.ElementSink
,org.graphstream.stream.Sink
public class RandomWalk extends org.graphstream.stream.SinkAdapter implements DynamicAlgorithm
Idea
This algorithm create a given number of entities first associated with random nodes in the graph. Then by turns, each entity chooses an edge at random and crosses it. This is iterated a given number of turns. Each time an entity crosses an edge, a count is incremented on it and each time it arrives on a node a count is counted on it.
You can override the entity class to provide your own behaviour for entity movement.
Counts on edges and nodes
If the algorithm was run for an infinite number of turns, each counter would have the same value. However we can choose to stop the algorithm when needed. Furthermore the algorithm can be biased by providing each entity with a memory of the already crossed edges. It can avoid these edges when choosing at random its next edge.
When an entity has no edge to choose (either because of its memory or because it reached a node that is only reachable via a one directed edge), the entity will jump randomly on another node.
When the number of turns awaited is reached, one can observe the counts on each edge and node. Edges and nodes that are very attractive in terms of topology should have a more important count than others.
This algorithm does not cope well with dynamic graphs. You can however improve this by using evaporation. When evaporation is activated, at each turn, the node and edge counts are multiplied by a number between 0 and 1. Therefore each edge or node count must be constantly updated by entities leading to a value that stabilizes in time.
The basic tabu entity
At each step, the default entities move from their current node to another via
an edge randomly chosen. This is done in the Entity.step()
method.
This method makes a list of all leaving edges of the current node. If the node has no leaving edge, the entity jumps to another randomly chosen node. Then an edge is chosen at random in the list of leaving edges. The edge is chosen uniformly if there are no weights on the edges, else, an edge with an higher weight has more chances to be chosen than an edge with a lower weight.
When crossed, if the memory is larger than 0, the edge crossed is remembered so that the entity will not choose it anew until it crosses as many edges as the memory size.
Usage
With the default entities, you can make a node entirely tabu by putting the ``tabu`` attribute on it. No entity will traverse an edge that leads to such a node.
You can change the default entity class either by overriding the
createEntity()
method or by changing the entity class name
using setEntityClass(String)
.
If the edges have weights, the entities can use them to favour edges
with higher weights when randomly choosing them. By default the
weights are searched on edges using the ``weight`` attribute. However
you can override this using setWeightAttribute(String)
method.
If you choose to have evaporation on edge counts at each turn, you can
set it using setEvaporation(double)
. The evaporation is a number
between 0 and 1. If set to 1 (the default), the counts are not modified,
else the counts are multiplied by the evaporation at each turn.
To compute a turn, use the compute()
method. This will move each
entity from one node to another.
Once computed each edge and node will have an attribute ``passes`` stored
on it containing the number of passage of an entity. You can change the
name of this attribute using setPassesAttribute(String)
. After
each computation of a turn, you can obtain the edge and nodes counts using
either the passes attribute, or the utility methods getPasses(Node)
and getPasses(Edge)
.
You can count only the passes on the nodes or edges using the two methods
computeEdgesPasses(boolean)
and computeNodePasses(boolean)
.
As some entities may have jumped from their node to another one chosen
randomly, you can obtain the number of entities that jumped using
getJumpCount()
.
Complexity
The complexity, at each turn is O(n) with n the number of entities.Example
Here is how to compute a simple pass count for 1000 steps:Graph graph = new MultiGraph("random walk"); RandomWalk rwalk = new RandomWalk(); // Populate the graph. rwalk.setEntityCount(graph.getNodeCount()/2); rwalk.init(graph); for(int i=0; i<1000; i++) { rwalk.compute(); } rwalk.terminate(); for(Edge edge: graph.getEachEdge()) { System.out.println("Edge %s counts %f%n", edge.getId(), rwalk.getPasses(edge)); }
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Nested Class Summary
Nested Classes Modifier and Type Class Description class
RandomWalk.Context
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Constructor Summary
Constructors Constructor Description RandomWalk()
New random walk with a new random seed (based on time), with an entity memory set to 10 nodes (tabu list), with an attributes to store passes named "passes" and no weight attribute.RandomWalk(long randomSeed)
New random walk with a given random seed, with an entity memory set to 10 nodes (tabu list), with an attributes to store passes named "passes" and no weight attribute. -
Method Summary
Modifier and Type Method Description void
compute()
Execute one step of the algorithm.void
computeEdgesPasses(boolean on)
Activate or not the counts on edges when entities cross thems.void
computeNodePasses(boolean on)
Activate or not the counts on nodes when entities cross thems.Entity
createEntity()
Create an entity.String
defaultResult()
void
edgeAdded(String graphId, long timeId, String edgeId, String fromNodeId, String toNodeId, boolean directed)
ArrayList<org.graphstream.graph.Edge>
findTheMostUsedEdges()
Sort all edges by their "passes" attribute and return the array of sorted edges.ArrayList<org.graphstream.graph.Node>
findTheMostUsedNodes()
Sort all nodes by their "passes" attribute and return the array of sorted nodes.int
getEntityCount()
Number of entities.double
getEvaporation()
The evaporation value.int
getGoCount()
int
getJumpCount()
Number of entities that jumped instead of traversing an edge at last step.double
getJumpRatio()
Ratio of entities that executed a jump instead of traversing an edge at last step.double
getPasses(org.graphstream.graph.Edge edge)
The number of entity passage on the given edge.double
getPasses(org.graphstream.graph.Node node)
The number of entity passage on the given node.String
getPassesAttribute()
The name of the attribute where the number of entities passes are stored (for edges and nodes).long
getRandomSeed()
The random seed used.int
getWaitCount()
void
init(org.graphstream.graph.Graph graph)
Initialize the algorithm for a given graph with a given entity count.void
nodeAdded(String graphId, long timeId, String nodeId)
void
setEntityClass(String name)
Set the name of the entity class to use.void
setEntityCount(int entityCount)
Set the number of entities which will be created at the algorithm initialization.void
setEntityMemory(int size)
Set the entity memory in number of nodes remembered.void
setEvaporation(double evaporation)
Set the evaporation of edge counts.void
setPassesAttribute(String name)
Set the name of the attribute used to store the number of passes of each entity on each edge or node.void
setWeightAttribute(String name)
The name of the attribute used to fetch edges importance.void
terminate()
End the algorithm by removing any listener on the graph and releasing memory.Methods inherited from class org.graphstream.stream.SinkAdapter
edgeAttributeAdded, edgeAttributeChanged, edgeAttributeRemoved, edgeRemoved, graphAttributeAdded, graphAttributeChanged, graphAttributeRemoved, graphCleared, nodeAttributeAdded, nodeAttributeChanged, nodeAttributeRemoved, nodeRemoved, stepBegins
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Constructor Details
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RandomWalk
public RandomWalk()New random walk with a new random seed (based on time), with an entity memory set to 10 nodes (tabu list), with an attributes to store passes named "passes" and no weight attribute. -
RandomWalk
public RandomWalk(long randomSeed)New random walk with a given random seed, with an entity memory set to 10 nodes (tabu list), with an attributes to store passes named "passes" and no weight attribute.- Parameters:
randomSeed
- The random seed.
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Method Details
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getPassesAttribute
The name of the attribute where the number of entities passes are stored (for edges and nodes).- Returns:
- A string representing the attribute name for entity passes.
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setEntityClass
Set the name of the entity class to use. If set to null, the default entity class will be used (RandomWalk.TabuEntity).- Parameters:
name
- The name of the entity class to use.
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setEntityMemory
public void setEntityMemory(int size)Set the entity memory in number of nodes remembered. This memory is used as a tabu list, that is a set of nodes not to cross.- Parameters:
size
- The memory size, 0 is a valid size to disable the tabu list.
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setEvaporation
public void setEvaporation(double evaporation)Set the evaporation of edge counts. This is a number between 0 and 1. If less than 1, at each turn, each edge count is multiplied by this factor. The use of evaporation allows to stabilize the counts.- Parameters:
evaporation
- A number between 0 and 1.
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getEvaporation
public double getEvaporation()The evaporation value.- Returns:
- The evaporation.
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getRandomSeed
public long getRandomSeed()The random seed used.- Returns:
- A long integer containing the random seed.
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getEntityCount
public int getEntityCount()Number of entities.- Returns:
- The number of entities.
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getJumpCount
public int getJumpCount()Number of entities that jumped instead of traversing an edge at last step. An entity executes a jump when it is blocked in a dead end (either a real one, or because of its tabu list).- Returns:
- The jump count.
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getWaitCount
public int getWaitCount() -
getGoCount
public int getGoCount() -
getJumpRatio
public double getJumpRatio()Ratio of entities that executed a jump instead of traversing an edge at last step. An entity executes a jump when it is blocked in a dead end (either a real one, or because of its tabu list).- Returns:
- The jump ratio (in [0-1]).
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setWeightAttribute
The name of the attribute used to fetch edges importance.- Parameters:
name
- A string giving the weight name.
-
setPassesAttribute
Set the name of the attribute used to store the number of passes of each entity on each edge or node.- Parameters:
name
- A string giving the passes name.
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getPasses
public double getPasses(org.graphstream.graph.Edge edge)The number of entity passage on the given edge.- Parameters:
edge
- The edge to look at.- Returns:
- The number of passes on the edge.
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getPasses
public double getPasses(org.graphstream.graph.Node node)The number of entity passage on the given node.- Parameters:
node
- The node to look at.- Returns:
- The number of passes on the node.
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setEntityCount
public void setEntityCount(int entityCount)Set the number of entities which will be created at the algorithm initialization.- Parameters:
entityCount
- number of entities
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computeEdgesPasses
public void computeEdgesPasses(boolean on)Activate or not the counts on edges when entities cross thems.- Parameters:
on
- If true (the default) the edges passes are counted.
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computeNodePasses
public void computeNodePasses(boolean on)Activate or not the counts on nodes when entities cross thems.- Parameters:
on
- If true (the default) the nodes passes are counted.
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createEntity
Create an entity. Override this method to create different kinds of entities or change the entity class name. The default one is the "TabuEntity".- Returns:
- The new entity.
- See Also:
setEntityClass(String)
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init
public void init(org.graphstream.graph.Graph graph)Initialize the algorithm for a given graph with a given entity count. The entities are created at random locations on the graph. -
compute
public void compute()Execute one step of the algorithm. During one step, each entity choose a next edge to cross, toward a new node. The passes attribute of these edge and node are updated.- Specified by:
compute
in interfaceAlgorithm
- See Also:
Algorithm.init(Graph)
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terminate
public void terminate()End the algorithm by removing any listener on the graph and releasing memory.- Specified by:
terminate
in interfaceDynamicAlgorithm
- See Also:
Algorithm.init(org.graphstream.graph.Graph)
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findTheMostUsedEdges
Sort all edges by their "passes" attribute and return the array of sorted edges.- Returns:
- An array with all edges of the graph sorted by their number of entity pass.
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findTheMostUsedNodes
Sort all nodes by their "passes" attribute and return the array of sorted nodes.- Returns:
- An array with all nodes of the graph sorted by their number of entity pass.
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edgeAdded
public void edgeAdded(String graphId, long timeId, String edgeId, String fromNodeId, String toNodeId, boolean directed)- Specified by:
edgeAdded
in interfaceorg.graphstream.stream.ElementSink
- Overrides:
edgeAdded
in classorg.graphstream.stream.SinkAdapter
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nodeAdded
- Specified by:
nodeAdded
in interfaceorg.graphstream.stream.ElementSink
- Overrides:
nodeAdded
in classorg.graphstream.stream.SinkAdapter
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defaultResult
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