GraphTheory[RandomGraphs]
RandomBipartiteGraph
generate a random bipartite graph
Calling Sequence
Parameters
Options
Description
Examples
Compatibility
RandomBipartiteGraph(n,p,options)
RandomBipartiteGraph(n,m,options)
RandomBipartiteGraph([a,b],p,options)
RandomBipartiteGraph([a,b],m,options)
n, a, b
-
positive integers
p
numeric value between 0.0 and 1.0
m
non-negative integer
options
(optional) equation(s) of the form option=value where option is one of seed or weights
directed = truefalse
Specifies whether the graph should be directed. The default is false.
seed = integer or none
Seed for the random number generator. When an integer is specified, this is equivalent to calling randomize(seed).
weights = range or procedure
If the option weights=m..n is specified, where m≤n are integers, the graph is a weighted graph with edge weights chosen from [m,n] uniformly at random. The weight matrix W in the graph has datatype=integer, and if the edge from vertex i to j is not in the graph then W[i,j] = 0.
If the option weights=x..y where x≤y are decimals is specified, the graph is a weighted graph with numerical edge weights chosen from [x,y] uniformly at random. The weight matrix W in the graph has datatype=float[8], that is, double precision floats (16 decimal digits), and if the edge from vertex i to j is not in the graph then W[i,j] = 0.0.
If the option weights=f where f is a function (a Maple procedure) that returns a number (integer, rational, or decimal number), then f is used to generate the edge weights. The weight matrix W in the graph has datatype=anything, and if the edge from vertex i to j is not in the graph then W[i,j] = 0.
RandomBipartiteGraph(n, p) creates an unweighted bipartite graph on n vertices where each possible edge is present with probability p.
RandomBipartiteGraph(n, m) creates an unweighted bipartite graph on n vertices and m edges where the m edges are chosen uniformly at random.
RandomBipartiteGraph([a,b], p) creates an unweighted bipartite graph on a+b vertices with partite sets of sizes a and b, where each possible edge is present with probability p.
RandomBipartiteGraph([a,b], m) creates an unweighted bipartite graph on a+b vertices with partite sets of sizes a and b, and with m edges chosen uniformly at random.
By default, the created bipartite graph is undirected. If the option directed or directed=true is given, the resulting graph is directed.
The random number generator used can be seeded using the seed option or the randomize function.
with⁡GraphTheory:
with⁡RandomGraphs:
G≔RandomBipartiteGraph⁡10,0.5
G≔Graph 1: an undirected graph with 10 vertices and 8 edge(s)
IsBipartite⁡G,p
true
1,2,3,4,5,6,7,8,9,10
G≔RandomBipartiteGraph⁡2,3,1.0
G≔Graph 2: an undirected graph with 5 vertices and 6 edge(s)
Neighbors⁡G
3,4,5,3,4,5,1,2,1,2,1,2
G≔RandomBipartiteGraph⁡2,2,4,weights=1..10
G≔Graph 3: an undirected weighted graph with 4 vertices and 4 edge(s)
WeightMatrix⁡G
0067007967007900
H≔RandomBipartiteGraph⁡7,11,45
H≔Graph 4: an undirected graph with 18 vertices and 46 edge(s)
ChromaticIndex⁡H
8
The GraphTheory[RandomGraphs][RandomBipartiteGraph] command was updated in Maple 2021.
The directed option was introduced in Maple 2021.
For more information on Maple 2021 changes, see Updates in Maple 2021.
See Also
AssignEdgeWeights
GraphTheory:-ChromaticIndex
GraphTheory:-IsBipartite
GraphTheory:-Neighbors
GraphTheory:-WeightMatrix
RandomDigraph
RandomGraph
RandomNetwork
RandomTournament
RandomTree
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