| Safe Haskell | None |
|---|---|
| Language | Haskell2010 |
Data.Graph.Generators.Random.ErdosRenyi
Description
Implementations of binomially random graphs, as described by Erdős and Rényi.
Graphs generated using this method have a constant edge probability between two nodes.
See Erdős and A. Rényi, On Random Graphs, Publ. Math. 6, 290 (1959).
graph-generators copyright: Copyright (C) 2014 Uli Köhler
NetworkX copyright: Copyright (C) 2004-2010 by Aric Hagberg hagberg@lanl.gov Dan Schult dschult@colgate.edu Pieter Swart swart@lanl.gov All rights reserved. BSD license.
- erdosRenyiGraph :: GenIO -> Int -> Double -> IO GraphInfo
- erdosRenyiGraph' :: Int -> Double -> IO GraphInfo
- erdosRenyiContext :: GenIO -> Int -> [Int] -> Double -> IO GraphContext
- selectWithProbability :: GenIO -> Double -> [a] -> IO [a]
Graph generators
Arguments
| :: GenIO | The random number generator to use |
| -> Int | The number of nodes |
| -> Double | The probability for any pair of nodes to be connected |
| -> IO GraphInfo | The resulting graph (IO required for randomness) |
Generate a unlabelled directed random graph using the Algorithm introduced by Erdős and Rényi, also called a binomial random graph generator.
Note that self-loops with also be generated with probability p.
This algorithm runs in O(n²) and is best suited for non-sparse networks.
The generated nodes are identified by [0..n-1].
Example usage, using a truly random generator:
import System.Random.MWC gen <- withSystemRandom . asGenIO $ return erdosRenyiGraph 10 0.1
...
Modelled after NetworkX 1.8.1 erdos_renyi_graph().
Arguments
| :: Int | The number of nodes |
| -> Double | The probability for any pair of nodes to be connected |
| -> IO GraphInfo | The resulting graph (IO required for randomness) |
Like erdosRenyiGraph, but uses a newly initialized random number generator.
See withSystemRandom for details on how the generator is
initialized.
By using this function, you don't have to initialize the generator by yourself, however generator initialization is slow, so reusing the generator is recommended.
Usage example:
erdosRenyiGraph' 10 0.1
Graph component generators
Arguments
| :: GenIO | The random number generator to use |
| -> Int | Identifier of the context's central node |
| -> [Int] | The algorithm will generate random edges to those nodes from or to the given node |
| -> Double | The probability for any pair of nodes to be connected |
| -> IO GraphContext | The resulting graph (IO required for randomness) |
Generate a unlabelled context using the Erdős and Rényi method.
See erdosRenyiGraph for a detailed algorithm description.
Example usage, using a truly random generator:
import System.Random.MWC gen <- withSystemRandom . asGenIO $ return
Utility functions
Arguments
| :: GenIO | The random generator state |
| -> Double | The probability to select each list element |
| -> [a] | The list to filter |
| -> IO [a] | The filtered list |
Filter a list by selecting each list element uniformly with a given probability p
Although this is mainly used internally, it can be used as general utility function