tracktable.applications.cluster module¶
Module contents¶
tracktable.applications.cluster - Determine if trajectories are clustered together.
cluster_trajectories(), cluster_trajectories_rendezvous() and cluster_trajectories_shape() are the main driver functions for clustering.
- tracktable.applications.cluster.cluster_name(cluster_id)[source]¶
Retrieve the cluster name for the given cluster ID.
- Parameters
cluster_id (int) – Cluster ID to retrieve the name for.
- Returns
The name of the cluser ID.
- tracktable.applications.cluster.cluster_trajectories(trajectories, feature_vector_function, search_box_span, *args, min_cluster_size=2, **kwargs)[source]¶
Create a cotravel feature vector for each trajectory and use box-DBSCAN to cluster the trajectories.
- Parameters
- Keyword Arguments
min_cluster_size (int) – The minimum number of points that you’re willing to call a cluster. (Default: 2)
- Returns
list of ordered pairs. The first value of each ordered pair corresponds to trajectory index (matching the ordering of the given list of trajectories), and the second number is the number of the cluster that the trajectory belongs to.
- tracktable.applications.cluster.cluster_trajectories_rendezvous(trajectories, start_fraction=0, end_fraction=1, num_control_points=10, epsilon_longitude=0.02, epsilon_latitude=0.02, epsilon_timestamp=3000, min_cluster_size=2)[source]¶
Create a cotravel feature vector for each trajectory and use box-DBSCAN to cluster the trajectories.
- Parameters
trajectories (list) – Trajectories to cluster.
- Keyword Arguments
start_fraction (float) – The fraction along the trajectory where you want to start sampling control points when looking for passersby. (Default: 0)
end_fraction (float) – The fraction along the trajectory where you want to stop sampling control points when looking for passersby. (Default: 1)
num_control_points (int) – The number of equally-spaced points to sample along each trajectory when clustering. (Default: 10)
epsilon_longitude (float) – The longitude in degrees to bound the DBSCAN clsutering (Default: 0.02)
epsilon_latitude (float) – The latitude in degrees to bound the DBSCAN clsutering (Default: 0.02)
epsilon_timestamp (int) – The timestamp in seconds to bound the DBSCAN clsutering (Default: 3000)
min_cluster_size (int) – The minimum number of points that you’re willing to call a cluster. (Default: 2)
- Returns
list of ordered pairs. The first value of each ordered pair corresponds to trajectory index (matching the ordering of the given list of trajectories), and the second number is the number of the cluster that the trajectory belongs to.
- tracktable.applications.cluster.cluster_trajectories_shape(trajectories, depth=4, epsilon=0.05, min_cluster_size=2)[source]¶
Create a cotravel feature vector for each trajectory and use box-DBSCAN to cluster the trajectories.
- Parameters
trajectories (list) – Trajectories to cluster.
- Keyword Arguments
- Returns
list of ordered pairs. The first value of each ordered pair corresponds to trajectory index (matching the ordering of the given list of trajectories), and the second number is the number of the cluster that the trajectory belongs to.