Source code for equisolve.numpy.sample_selection

# -*- Mode: python; tab-width: 4; indent-tabs-mode:nil; coding:utf-8 -*-
#
# Copyright (c) 2023 Authors and contributors
# (see the AUTHORS.rst file for the full list of names)
#
# Released under the BSD 3-Clause "New" or "Revised" License
# SPDX-License-Identifier: BSD-3-Clause
"""Wrappers for the sample selectors of `scikit-matter`_.

.. _`scikit-matter`: https://scikit-matter.readthedocs.io/en/latest/selection.html
"""

from skmatter._selection import _CUR, _FPS

from ._selection import GreedySelector


[docs] class FPS(GreedySelector): """ Transformer that performs Greedy Sample Selection using Farthest Point Sampling. Refer to :py:class:`skmatter.sample_selection.FPS` for full documentation. """ def __init__( self, initialize=0, n_to_select=None, score_threshold=None, score_threshold_type="absolute", progress_bar=False, full=False, random_state=0, ): super().__init__( selector_class=_FPS, selection_type="sample", initialize=initialize, n_to_select=n_to_select, score_threshold=score_threshold, score_threshold_type=score_threshold_type, progress_bar=progress_bar, full=full, random_state=random_state, )
[docs] class CUR(GreedySelector): """Transformer that performs Greedy Sample Selection using CUR. Refer to :py:class:`skmatter.sample_selection.CUR` for full documentation. """ def __init__( self, recompute_every=1, k=1, tolerance=1e-12, n_to_select=None, score_threshold=None, score_threshold_type="absolute", progress_bar=False, full=False, random_state=0, ): super().__init__( selector_class=_CUR, selection_type="sample", recompute_every=recompute_every, k=k, tolerance=tolerance, n_to_select=n_to_select, score_threshold=score_threshold, score_threshold_type=score_threshold_type, progress_bar=progress_bar, full=full, random_state=random_state, )