flownet 0.1.1

Documentation Improvements

Restructured run_assignment() @details section using \subsection{} for better organization:
- Separate sections for AoN method, PSL method, route enumeration algorithm, and coordinate-based filtering
Added return.extra parameter documentation as a clear table showing which options are available for each method
Clarified that paths returns edge indices, not node indices
Added comprehensive examples including:
- PSL method usage with nthreads parameter
- Trade flow disaggregation workflow (country-to-city level)
Added academic references for the Path-Sized Logit model (Ben-Akiva & Bierlaire, 1999)
Added link to AequilibriaeE (Python) documentation for additional PSL resources
Improved error messages to be more informative (show which columns are missing, what class was received)
Increased vignette table of contents depth for better navigation
Added citation for the PSL model in vignette

Better penalization strategy for multimodal networks in simplify_network() shortest-paths method
Enforced numeric type conversion for cost columns
Various minor fixes and improvements

run_assignment(): Core function for traffic assignment using the path-sized logit (PSL) model
- Efficient route enumeration algorithm that generates sensible alternative routes between origin-destination pairs
- Accounts for route overlap using path-sized logit probabilities
- Supports both directed and undirected graphs
- Configurable detour factors and angle constraints for route selection
- Optional return of detailed path information, edge counts, costs, and weights
- High-performance C implementation for critical path operations
- Multithreading (asynchronous parallelism) using mirai.

linestrings_to_graph(): Convert LINESTRING geometries (sf objects) to graph data frames
- Extracts node coordinates and creates edge representations
- Optional coordinate rounding for precision handling
- Preserves additional columns from input data
- Automatic computation of edge lengths
create_undirected_graph(): Convert directed graphs to undirected graphs
- Normalizes edge directions and aggregates duplicate connections
- Flexible aggregation using collapse::collap() with customizable functions
- Preserves spatial coordinates and line identifiers
consolidate_graph(): Simplify network topology by removing intermediate nodes
- Removes nodes that occur exactly twice, merging connecting edges
- Optional removal of loops, duplicate edges, and singleton edges
- Recursive consolidation for complete simplification
- Weighted aggregation of edge attributes
- Preserves coordinate information when present
simplify_network(): Simplify networks using shortest-paths or spatial clustering methods
- Method “shortest-paths”: Filters network to edges used in shortest paths between specified nodes
- Method “cluster”: Spatially clusters nodes using leaderCluster algorithm and contracts the graph

normalize_graph(): Normalize node IDs to consecutive integers starting from 1
- Essential for graph algorithms requiring sequential node IDs
- Preserves graph structure while remapping identifiers
nodes_from_graph(): Extract unique nodes with coordinates from graph
- Returns data frame or sf POINT object with node locations
- Useful for mapping zones to network nodes
linestrings_from_graph(): Convert graph data frames back to LINESTRING geometries
- Inverse operation of linestrings_to_graph()
- Preserves all graph attributes in output sf object
distances_from_graph(): Compute distance matrices for all node pairs
- Uses igraph for efficient shortest path distance computation
- Supports both directed and undirected graphs

melt_od_matrix(): Convert origin-destination matrices to long format
- Transforms matrix format to edge list suitable for traffic assignment
- Handles missing values and zero flows

africa_network: A road transport network with 2,825 LINESTRING features representing existing roads (2,344 edges) and proposed new links (481 edges). Each edge includes attributes such as distance, travel duration, border crossing costs, terrain ruggedness, and road upgrade costs.
africa_cities_ports: 453 African cities with population > 100,000 and international ports. Includes population data, capital status, and port cargo outflows.
africa_segments: 14,358 raw network segments representing intersected road routes. Useful for demonstrating network consolidation and simplification functions.
africa_trade: Bilateral trade flows between 47 African countries aggregated by HS section (21 product categories). Values represent annual averages over 2012-2022.

The africa_network, africa_cities_ports, and africa_segments datasets are from Krantz, S. (2024). Optimal Investments in Africa’s Road Network. Policy Research Working Paper 10893. World Bank. Replication materials are available at github.com/SebKrantz/OptimalAfricanRoads.

R (>= 4.1)
collapse (>= 2.1.5) - Fast data transformations and memory efficient programming
kit (>= 0.0.5) - Fast tabulation and vectorized switches
igraph (>= 2.1.4) - Graph operations and shortest path algorithms
sf (>= 1.0.0) - Spatial data handling
geodist (>= 0.1.1) - Fast geodesic distance computations
leaderCluster (>= 1.5.0) - Efficient spatial clustering algorithms
mirai (>= 2.5.2) - Asynchronous parallelism for R
progress (>= 1.2.3) - Progress bars for long-running operations

GPL-3