Reference

Embedding

Perform the embedding using one of the SETSe function

setse()

Basic SETSe embedding

setse_auto()

SETSe embedding with automatic drag and timestep selection

setse_auto_hd()

SETSe embedding with automatic drag and timestep selection for high-dimensional feature vectors

setse_bicomp()

SETSe embedding on each bi-connected component using setse_auto

setse_expanded()

SETSe embedding showing full convergence history

setse_shift()

setse algorithm with automatic timestep adjustment

Pre-embedding

Functions used before the network has been embedded

prepare_categorical_force()

Prepare categorical features for embedding

prepare_continuous_force()

Prepare continuous features for embedding

prepare_edges()

Prepare network edges

remove_small_components()

Remove small components

calc_spring_area()

Calculate the cross sectional area of the edge

calc_spring_constant()

Calculate the spring constant

create_balanced_blocks()

Create balanced blocks

mass_adjuster()

Mass adjuster

Post-embedding

Functions used after the network has been embedded

create_node_edge_df()

Create dataframe of node and aggregated edge embeddings

create_node_edge_df_hd()

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

calc_tension_strain()

Calculate line tension and strain from the topology and node embeddings

calc_tension_strain_hd()

Calculate line tension and strain from the topology and node embeddings for high dimensional feature networks

Networks

Data to use for embedding

generate_peels_network()

Create a random Peel network

biconnected_network

A simple network made of three bi-connected components