elpigraph.findPaths

elpigraph.findPaths(X, PG, min_path_len=None, nnodes=None, max_inner_fraction=0.1, min_node_n_points=2, max_n_points=None, min_compactness=0.5, radius=None, allow_same_branch=True, fit_loops=True, Lambda=None, Mu=None, cycle_Lambda=None, cycle_Mu=None, weights=None, ignore_equivalent=False, plot=False, verbose=False)

This function tries to add extra paths to the graph by computing a series of principal curves connecting two nodes and retaining plausible ones using heuristic parameters

min_path_len: int, default=None

Minimum distance along the graph (in number of nodes) that separates the two nodes to connect with a principal curve

n_nodes: int, default=None

Number of nodes in the candidate principal curves

max_inner_fraction: float in [0,1], default=0.1

Maximum fraction of points inside vs outside the loop Controls how empty the loop formed with the added path should be.

min_node_n_points: int, default=1

Minimum number of points associated to nodes of the principal curve (prevents creating paths through empty space)

max_n_points: int, default=5% of the number of points

Maximum number of points inside the loop

min_compactness: float in [0,1], default=0.5

Minimum ‘roundness’ of the loop (1=more round) (if very narrow loops are not desired)

radius: float, default=None

Max distance in space that separates the two nodes to connect with a principal curve

allow_same_branch: bool, default=True

Whether to allow new paths to connect two nodes from the same branch

fit_loops: bool, default=True

Whether to refit the graph to data after adding the new paths

plot: bool, default=False

Whether to plot selected candidate paths

verbose: bool, default=False weights: bool, default=False

Whether to use point weights