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Create Undirected Graph

Source: R/utils.R
create_undirected_graph.Rd

Convert a directed graph to an undirected graph by normalizing edges and aggregating duplicate connections.

Usage

create_undirected_graph(graph_df, by = NULL, ...)

Arguments

graph_df

A data frame representing a directed graph including columns: from, to, and (optionally) edge, FX, FY, TX, TY.

by

Link characteristics to preserve/not aggregate across, passed as a one-sided formula or character vector of column names. Typically this includes attributes like mode, type, or capacity to ensure that only edges with the same characteristics are aggregated.

...

Arguments passed to collap() for aggregation across duplicated (diretional) edges. The defaults are FUN = fmean for numeric columns and catFUN = fmode for categorical columns. Select columns using cols or use argument custom = list(fmean = cols1, fsum = cols2, fmode = cols3) to map different columns to specific aggregation functions. You can weight the aggregation (using w = ~ weight_col).

Value

A data frame representing an undirected graph with:

  • edge - Edge identifier (first value from duplicates)

  • from - Starting node ID (normalized to be < to)

  • to - Ending node ID (normalized to be > from)

  • FX - Starting node X-coordinate (first value from duplicates)

  • FY - Starting node Y-coordinate (first value from duplicates)

  • TX - Ending node X-coordinate (first value from duplicates)

  • TY - Ending node Y-coordinate (first value from duplicates)

  • Aggregated columns

Details

This function converts a directed graph to an undirected graph by:

  • Normalizing edge directions so that from < to for all edges

  • Collapsing duplicate edges (same from and to nodes)

  • For spatial/identifier columns (edge, FX, FY, TX, TY), taking the first value from duplicates

  • For aggregation columns, collap() will be applied.

Examples

library(flownet)

# Convert segments to graph and make undirected
graph <- africa_segments |>
  linestrings_from_graph() |>
  linestrings_to_graph()
graph_undir <- create_undirected_graph(graph, FUN = "fsum")

# Fewer edges after removing directional duplicates
c(directed = nrow(graph), undirected = nrow(graph_undir))
#>   directed undirected 
#>      14358      11385