FPS

class PAsampling.wrappers.FPS(precomputed_distances=False)

Implements the Farthest Point Sampling (FPS) algorithm.

This class provides a wrapper around the fps_np function, allowing for the selection of a subset of samples from a dataset based on the FPS strategy. The selection can be performed using different distance functions and can handle precomputed distance matrices.

Attributes:

precomputed_distancesbool, optional (default=False)

If True, the fit function expects a precomputed distance matrix as input.

fit(X, initial_subset, b_samples, distance_func=None, verbose=False)

Fits the model to the data X and returns the indices of the selected samples.

Parameters:

Xnumpy.ndarray

Input data matrix with shape (n_samples, n_features), representing a set of data points. If “precomputed_distances” is True, X is expected to be the matrix of precomputed pairwise distances with shape (n_samples, n_samples).

initial_subsetlist

List of indices (rows of the input points matrix) representing the initial set of selected elements.

b_samplesint

The desired number of points to select.

distance_funccallable, optional (default=None)

A function to compute pairwise distances. If None, Euclidean distance is used.

verbosebool, optional (default=False)

If True, progress messages are printed.

Returns:

sampleslist

List of indices representing the selected points using the FPS algorithm.