Documentation

SpaceNet is a Python package for spatial network analysis. It is structured into several subpackages, each of which contains functions and classes for specific types of spatial network analysis. The subpackages are listed below, along with a brief description of each one.

Subpackage	Description
utils	A collection of utility functions for spatial network analysis.
global_metrics	Global metrics for spatial networks.
node_metrics	Node-based metrics for spatial networks.
centrality	Centralities for spatial networks.
point_patterns	Point pattern analysis for spatial networks.
partition	Methods for partitioning spatial networks.
datasets	Datasets for testing and demonstration of spatial network analysis methods.
helpers	Helper functions for spatial network analysis.

SpaceNet reference list

All of the modules are listed below, and each module has its own documentation page that provides a detailed description of the functions and classes that are available in that module.

• spacenet.utils
  • Creating and modifying spatial networks
    • spacenet.utils.spatial_network_from_points
      • spatial_network_from_points()
    • spacenet.utils.spatial_network_from_edgelist
      • spatial_network_from_edgelist()
    • spacenet.utils.spatial_network_from_adjacency
      • spatial_network_from_adjacency()
    • spacenet.utils.add_node_labels
      • add_node_labels()
    • spacenet.utils.delete_node_labels
      • delete_node_labels()
  • Querying spatial networks
    • spacenet.utils.query_nodes
      • query_nodes()
  • Viewing data
    • spacenet.utils.plot_spatial_network
      • plot_spatial_network()
    • spacenet.utils.print_network_properties
      • print_network_properties()
  • Exporting data
    • spacenet.utils.nodes_to_dataframe
      • nodes_to_dataframe()
• spacenet.global_metrics
  • Global metrics for spatial networks
    • spacenet.global_metrics.volume
      • volume()
    • spacenet.global_metrics.diameter
      • diameter()
    • spacenet.global_metrics.alpha_index
      • alpha_index()
    • spacenet.global_metrics.beta_index
      • beta_index()
    • spacenet.global_metrics.gamma_index
      • gamma_index()
    • spacenet.global_metrics.cyclomatic_number
      • cyclomatic_number()
    • spacenet.global_metrics.mean_detour_index
      • mean_detour_index()
    • spacenet.global_metrics.mean_clustering_coefficient
      • mean_clustering_coefficient()
• spacenet.node_metrics
  • Node metrics for spatial networks
    • spacenet.node_metrics.degree
      • degree()
    • spacenet.node_metrics.eccentricity
      • eccentricity()
    • spacenet.node_metrics.clustering_coefficient
      • clustering_coefficient()
• spacenet.centrality
  • Centralities for spatial networks
    • spacenet.centrality.closeness
      • closeness()
    • spacenet.centrality.degree_centrality
      • degree_centrality()
    • spacenet.centrality.laplacian
      • laplacian()
    • spacenet.centrality.node_reach
      • node_reach()
• spacenet.point_patterns
  • Pair correlation functions
    • spacenet.point_patterns.cross_pair_correlation_function
      • cross_pair_correlation_function()
    • spacenet.point_patterns.weighted_pair_correlation_function
      • weighted_pair_correlation_function()
    • spacenet.point_patterns.cross_weighted_pair_correlation_function
      • cross_weighted_pair_correlation_function()
  • Correlation helper functions
    • spacenet.point_patterns.helpers.spatial_bootstrap
      • spatial_bootstrap()
    • spacenet.point_patterns.helpers.polynomial_kernel
      • polynomial_kernel()
    • spacenet.point_patterns.helpers.integrated_poly_finite_kernel
      • integrated_poly_finite_kernel()
    • spacenet.point_patterns.helpers.is_connected_filter
      • is_connected_filter()
    • spacenet.point_patterns.helpers.compute_contributions
      • compute_contributions()
    • spacenet.point_patterns.helpers.compute_weighted_contributions
      • compute_weighted_contributions()
    • spacenet.point_patterns.helpers.compute_contributions_parallel
      • compute_contributions_parallel()
    • spacenet.point_patterns.helpers.compute_weighted_contributions_parallel
      • compute_weighted_contributions_parallel()
• spacenet.partition
  • Spatial network partitioning
    • spacenet.partition.compact_volume_partition
      • compact_volume_partition()
    • spacenet.partition.modularity_partition
      • modularity_partition()
• spacenet.datasets
  • spacenet.datasets.load_dataset
    • load_dataset()
• spacenet.helpers
  • Helper functions for spatial networks
    • spacenet.helpers.get_edge_weights
      • get_edge_weights()
    • spacenet.helpers.get_nodes_and_labels
      • get_nodes_and_labels()
    • spacenet.helpers.get_node_node_distance
      • get_node_node_distance()
    • spacenet.helpers.node_node_distance
      • node_node_distance()
    • spacenet.helpers.update_node_node_distance_cache
      • update_node_node_distance_cache()
    • spacenet.helpers.remove_nodes_from_distance_cache
      • remove_nodes_from_distance_cache()
    • spacenet.helpers.shortest_path_length_node_a_to_node_b
      • shortest_path_length_node_a_to_node_b()
    • spacenet.helpers.clear_distance_cache
      • clear_distance_cache()
    • spacenet.helpers.batched_dijkstra
      • batched_dijkstra()