represents a spatial distribution for graphs with n vertices uniformly distributed over the unit square and edges between vertices that are at distance at most r.
represents a spatial distribution for graphs with vertices uniformly distributed over the d-dimensional unit square.
represents a spatial distribution for graphs with vertices distributed according to the probability distribution dist.
Details and Options
- SpatialGraphDistribution[n,r] is equivalent to SpatialGraphDistribution[n,r,2].
- The probability distribution dist can be any symbolic probability distribution specification.
- SpatialGraphDistribution by default effectively uses the Euclidean distance function EuclideanDistance.
- The following option can be given:
DistanceFunction Automatic the distance metric to use
- SpatialGraphDistribution can be used with such functions as RandomGraph.
Examplesopen allclose all
Basic Examples (2)
Probability density functions of the EdgeCount:
By default, distance is measured using EuclideanDistance:
A wireless ad hoc network can be modeled with a SpatialGraphDistribution:
A frog in a lily pond is able to jump 1.5 feet to get from one of the 25 lily pads to another. Model the frog jumping network from the lily pad density and SpatialGraphDistribution:
Properties & Relations (6)
Wolfram Research (2012), SpatialGraphDistribution, Wolfram Language function, https://reference.wolfram.com/language/ref/SpatialGraphDistribution.html.
Wolfram Language. 2012. "SpatialGraphDistribution." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/SpatialGraphDistribution.html.
Wolfram Language. (2012). SpatialGraphDistribution. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/SpatialGraphDistribution.html