apply_penalization: Applies penalization to edges in a graph based on a specific weight update criteria.

path_penalization: This function applies penalization to edge weights specifically for shortest paths in a graph. It uses a specified function to update edge weights iteratively.

graph_randomization: Randomizes weights for all edges in a graph to find k paths with updated costs. It extract the penalization values froma a random distribution function.

path_randomization: Performs randomization on edge weights specifically for shortest paths in a graph, like before extracting penalization values from a random distribution.

duarouter: Applies edge weight adjustments using a specified disturbance factor.

k_disjointed: Penalizes edges to infinity to get to the results of quasi-disjointed paths.

no_randomization: Applies no randomization to edge weights.

k_mdnsp: This function applies a specified function to update edge weights for finding k paths with cost under a certain threshold while ensuring the maximum possible level of dissimilarity.

next_ssvp_by_length: This function generates the next simple single-via path based on edge lengths in a graph.

kspml: This function provides k-shortest paths with minimum collective length, by using the SSVP.

kspmo: This function is similar to ‘kspml’ but employs a different dissimilarity metric to evaluate the similarity between paths.

plateau_algorithm: This function runs the plateau-based algorithm to find k plateaus and build paths from it. It ensures that that the plateaus are disjointed, a maximum distance threshold must be specified.

k_shortest_paths: This function implements the Yen algorithm for finding k shortest paths in a graph.

distinct_edges_traveled: Computes the set of distinct edges traveled in a list of paths.

redundancy: Computes the redundancy score of a set of paths.

normalized_jaccard_coefficient: Computes the normalized Jaccard coefficient between two sets of edges.

compute_edge_load: Computes the load on each edge in a list of paths.

compute_edge_load_normalized: Computes the load normalized by path cardinality on each edge in a list of paths.

get_load_balance_entropy: Computes the entropy of the set of paths on the road network.

compute_edge_capacity: Computes the capacity of each edge in a road network.

compute_voc: Computes the volume-over-capacity ratio for each edge in a road network.

dis: Computes the dissimilarity between two paths.

div: Computes the diversity between a list of paths.

compute_driver_sources: Provide a list of paths with an edge to tile mapping and get the traffic source tiles for each edge

compute_MDS: Get the Major Driver Sources by filtering according to a threshold

compute_k_road: Get the kroad values for each edge based on the MDS.

split_interval_sliding: Get specified window intervals

compute_temp_redundancy_sliding: Compute the Temp Redundancy of a certain traffic assignment result according to a specified time interval

from_sumo_to_igraph_network: Converts a SUMO road network to an igraph network.

get_shortest_path: Finds the shortest path between two edges in a igraph graph and translates it to SUMO format.

compute_path_cost: Computes the cost of a path in a graph.

test_sumo_ig_shortest_paths: Tests the conversion of sumo to iGraph with the shortest path algorithm with randomly selected edges.

visualize_paths: Visualizes paths on a map using folium.

edge_list_to_gps_list: Converts a list of edges to a list of GPS points.

compute_ellipse: Computes an ellipse representing the region around an edge pair.

ellipse_subgraph: Extracts a subgraph within the region defined by an ellipse.