## Content#

`nngt.analysis.adjacency_matrix` (graph[, …]) |
Adjacency matrix of the graph. |

`nngt.analysis.all_shortest_paths` (g, source, …) |
Yields all shortest paths from source to target. |

`nngt.analysis.assortativity` (g, degree[, weights]) |
Returns the assortativity of the graph. |

`nngt.analysis.average_path_length` (g[, …]) |
Returns the average shortest path length between sources and targets. |

`nngt.analysis.bayesian_blocks` (t[, x, sigma, …]) |
Bayesian Blocks Implementation |

`nngt.analysis.betweenness` (g[, btype, weights]) |
Returns the normalized betweenness centrality of the nodes and edges. |

`nngt.analysis.betweenness_distrib` (graph[, …]) |
Betweenness distribution of a graph. |

`nngt.analysis.binning` (x[, bins, log]) |
Binning function providing automatic binning using Bayesian blocks in addition to standard linear and logarithmic uniform bins. |

`nngt.analysis.closeness` (g[, weights, nodes, …]) |
Returns the closeness centrality of some nodes. |

`nngt.analysis.connected_components` (g[, ctype]) |
Returns the connected component to which each node belongs. |

`nngt.analysis.degree_distrib` (graph[, …]) |
Degree distribution of a graph. |

`nngt.analysis.diameter` (g[, directed, …]) |
Returns the diameter of the graph. |

`nngt.analysis.get_b2` ([network, …]) |
Return the B2 coefficient for the neurons. |

`nngt.analysis.get_firing_rate` ([network, …]) |
Return the average firing rate for the neurons. |

`nngt.analysis.get_spikes` ([recorder, …]) |
Return a 2D sparse matrix, where: |

`nngt.analysis.global_clustering` (g[, …]) |
Returns the global clustering coefficient. |

`nngt.analysis.global_clustering_binary_undirected` (g) |
Returns the undirected global clustering coefficient. |

`nngt.analysis.local_closure` (g[, directed, …]) |
Compute the local closure for each node, as defined in [Yin2019] as the fraction of 2-walks that are closed. |

`nngt.analysis.local_clustering` (g[, nodes, …]) |
Local (weighted directed) clustering coefficient of the nodes, ignoring self-loops. |

`nngt.analysis.local_clustering_binary_undirected` (g) |
Returns the undirected local clustering coefficient of some nodes. |

`nngt.analysis.node_attributes` (network, …) |
Return node attributes for a set of nodes. |

`nngt.analysis.num_iedges` (graph) |
Returns the number of inhibitory connections. |

`nngt.analysis.reciprocity` (g) |
Calculate the edge reciprocity of the graph. |

`nngt.analysis.shortest_distance` (g[, …]) |
Returns the length of the shortest paths between sources`and `targets. |

`nngt.analysis.shortest_path` (g, source, target) |
Returns a shortest path between source`and `target. |

`nngt.analysis.small_world_propensity` (g[, …]) |
Returns the small-world propensity of the graph as first defined in [Muldoon2016]. |

`nngt.analysis.spectral_radius` (graph[, …]) |
Spectral radius of the graph, defined as the eigenvalue of greatest module. |

`nngt.analysis.subgraph_centrality` (graph[, …]) |
Returns the subgraph centrality for each node in the graph. |

`nngt.analysis.total_firing_rate` ([network, …]) |
Computes the total firing rate of the network from the spike times. |

`nngt.analysis.transitivity` (g[, directed, …]) |
Same as `global_clustering()` . |

`nngt.analysis.triangle_count` (g[, nodes, …]) |
Returns the number or the strength (also called intensity) of triangles for each node. |

`nngt.analysis.triplet_count` (g[, nodes, …]) |
Returns the number or the strength (also called intensity) of triplets for each node. |