Synthetic Connection Networks

• makerandCIJ_dir.m. (BD networks)
  Generates a random, directed network with a specified number of nodes and links.
  Contributor: OS.
  .
• makerandCIJ_und.m. (BU networks)
  Generates a random, undirected network with a specified number of nodes and links.
  Contributor: OS.
  .
• makerandCIJdegreesfixed.m. (BD networks)
  Generates a random, directed network with a specified in-degree and out-degree sequence. Returns a flag, denoting whether the algorithm succeeded or failed. Also compare to network randomization algorithms (see below).
  Contributor: OS.
  .
• makeevenCIJ.m. (BD networks)
  Generates a random, directed network with a specified number of clusters (modules), linked together by evenly distributed random connections.
  Contributor: OS.
  .
• makefractalCIJ.m. (BD networks)
  Generates a directed network with a hierarchical (fractal) cluster organization.
  Contributor: OS.
  .
• makelatticeCIJ.m. (BD networks)
  Generates a lattice, directed network of a specified number of nodes and links without toroidal boundary counditions (no ring-like "wrapping around").
  Contributor: OS.
  .
• makeringlatticeCIJ.m. (BD networks)
  'makelatticeCIJ.m' with toroidal boundary conditions (ring-like "wrapping around").
  Contributor: OS.
  .
• maketoeplitzCIJ.m. (BD networks)
  Generates a directed network with a specified number of nodes and links, and with links arranged such that their density exhibits a Gaussian drop-off with increasing distance from the main diagonal.
  Contributor: OS.

Graph randomization algorithms

All network metrics should be compared to metrics extracted from corresponding reference (null model) networks. The most commonly used null model is that of a random network of the same size and degree distribution as the original network.

• randmio_dir.m; randmio_dir_connected.m. (BD, WD networks)
  An alternative randomization algorithm, that preserves in and out degree distribution, as well as out strength (but not in strength) distribution in weighted directed networks. In addition, 'randmio_dir_connected.m' ensures that the randomized network maintains connectedness -- the input network for this function must be connected, and the randomization effect may decrease.
  Reference: Maslov and Sneppen (2002). Contributor: MR.
  .
• randmio_und.m; randmio_und_connected.m. (BD, WD networks)
  A version of 'randmio_dir.m' and 'randmio_dir_connected.m' for undirected networks. The strength distributions are not preserved for weighted networks.
  Reference: Maslov and Sneppen (2002). Contributor: MR.
  .
• latmio_dir.m; latmio_dir_connected.m. (BD, WD networks)
  An algorithm that latticizes a weighted directed network, with preservation of in- and out-degree distributions, as well as of out-strength (but not in-strength) distribution. In addition, 'latmio_dir_connected.m' ensures that the randomized network maintains connectedness -- the input network for this function must be connected. Surrogate lattice networks may be useful, for example, for comparison of motif frequency distributions.
  References: Maslov and Sneppen (2002), Sporns and Zwi (2004). Contributor: MR.
  .
• latmio_und.m; latmio_und_connected.m. (BD, WD networks)
  A version of 'latmio_dir.m' and 'latmio_dir_connected.m' for undirected networks. The strength distributions are not preserved for weighted networks.
  Reference: Maslov and Sneppen (2002). Contributor: MR.

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