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Utils

This file is part of the TPOT library.

The current version of TPOT was developed at Cedars-Sinai by: - Pedro Henrique Ribeiro (https://github.com/perib, https://www.linkedin.com/in/pedro-ribeiro/) - Anil Saini (anil.saini@cshs.org) - Jose Hernandez (jgh9094@gmail.com) - Jay Moran (jay.moran@cshs.org) - Nicholas Matsumoto (nicholas.matsumoto@cshs.org) - Hyunjun Choi (hyunjun.choi@cshs.org) - Miguel E. Hernandez (miguel.e.hernandez@cshs.org) - Jason Moore (moorejh28@gmail.com)

The original version of TPOT was primarily developed at the University of Pennsylvania by: - Randal S. Olson (rso@randalolson.com) - Weixuan Fu (weixuanf@upenn.edu) - Daniel Angell (dpa34@drexel.edu) - Jason Moore (moorejh28@gmail.com) - and many more generous open-source contributors

TPOT is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

TPOT is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public License along with TPOT. If not, see http://www.gnu.org/licenses/.

is_pareto_efficient(scores, return_mask=True)

Find the pareto-efficient points :param scores: An (n_points, n_scores) array :param return_mask: True to return a mask :return: An array of indices of pareto-efficient points. If return_mask is True, this will be an (n_points, ) boolean array Otherwise it will be a (n_efficient_points, ) integer array of indices.

Source code in tpot2/utils/utils.py 
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def is_pareto_efficient(scores, return_mask = True):
    """
    Find the pareto-efficient points
    :param scores: An (n_points, n_scores) array
    :param return_mask: True to return a mask
    :return: An array of indices of pareto-efficient points.
        If return_mask is True, this will be an (n_points, ) boolean array
        Otherwise it will be a (n_efficient_points, ) integer array of indices.
    """
    is_efficient = np.arange(scores.shape[0])
    n_points = scores.shape[0]
    next_point_index = 0  # Next index in the is_efficient array to search for
    while next_point_index<len(scores):
        nondominated_point_mask = np.any(scores>scores[next_point_index], axis=1)
        nondominated_point_mask[next_point_index] = True
        is_efficient = is_efficient[nondominated_point_mask]  # Remove dominated points
        scores = scores[nondominated_point_mask]
        next_point_index = np.sum(nondominated_point_mask[:next_point_index])+1
    if return_mask:
        is_efficient_mask = np.zeros(n_points, dtype = bool)
        is_efficient_mask[is_efficient] = True
        return is_efficient_mask
    else:
        return is_efficient