Create dataframe of node and aggregated edge embeddings for high dimensional feature networks

Aggregates edge strain and tension to node level

create_node_edge_df_hd(embeddings_data, function_names = c("mean", "median"))

Arguments

embeddings_data	A list. The output of any of the setse embedding functions
function_names	A string vector. the names of the aggregation methods to be used

Value

A dataframe with node names, node force, node elevation and strain and tension aggregated using the named functions. The strain and tension columns are returned with names in the form "strain_x" where "x" is the name of the function used to aggregate. The total number of columns is dependent on the number of aggregation functions.

Details

Often if can be useful to have edge data at node level, an example of this would be plotting the node and tension or strain. To do this requires that the edge embeddings are aggregated somehow to node level and joined to the appropriate node. This function takes as an argument the output of the setse embedding functions and any number of aggregation functions to produce a dataframe that is convenient to use.

Examples

g <- biconnected_network %>%
 prepare_edges(.) %>%
 #prepare the continuous features as normal
 prepare_continuous_force(., node_names = "name", force_var = "force") %>%
 #prepare the categorical features as normal
 prepare_categorical_force(., node_names = "name", force_var = "group")
  
 #embed them using the high dimensional function
 two_dimensional_embeddings <- setse_auto_hd(g, force = c("group_A", "force"), k = "weight")

 out <- create_node_edge_df_hd(two_dimensional_embeddings , 
  function_names = c("mean", "mode", "sum"))