Use of assert detected. The enclosed code will be removed when compiling to optimised byte code.

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    assert (
        len(X) > n_samples
    ), "The numbers of points that shall be selected (n_samples),\
         needs to be smaller than the length of the feature matrix (X)"

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Use of assert detected. The enclosed code will be removed when compiling to optimised byte code.

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    assert n_samples > 0 and isinstance(
        n_samples, int
    ), "The number of points that shall be selected (n_samples)\
             needs to be an integer greater than 0"

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Use of assert detected. The enclosed code will be removed when compiling to optimised byte code.

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    assert palinstance.number_design_points == len(
        y
    ), "The number of points in the design space must equal the number of measurements"

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Use of assert detected. The enclosed code will be removed when compiling to optimised byte code.

Open

    assert (
        len(X) > n_samples
    ), "The numbers of points that shall be selected (n_samples),\
         needs to be smaller than the length of the feature matrix (X)"

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Use of assert detected. The enclosed code will be removed when compiling to optimised byte code.

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    assert n_samples > 0 and isinstance(
        n_samples, int
    ), "The number of points that shall be selected (n_samples)\
         needs to be an integer greater than 0"

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File utils.py has 257 lines of code (exceeds 250 allowed). Consider refactoring.

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# -*- coding: utf-8 -*-
# Copyright 2020 PyePAL authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.

Function get_maxmin_samples has 7 arguments (exceeds 4 allowed). Consider refactoring.

Open

def get_maxmin_samples(  # pylint:disable=invalid-name

Function dominance_check_jitted_3 has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

def dominance_check_jitted_3(array: np.array, point: np.array, ignore_me: int) -> bool:
    """Check if any point in array dominates point. ignore_me
    since numba does not understand masked arrays"""
    sorted_idx = array[:, 0].argsort()[::-1]
    ignore_me = np.where(sorted_idx == ignore_me)[0][0]

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Function get_nondimensional_pareto_error has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

def get_nondimensional_pareto_error(
    y_true: np.ndarray, y_pred: np.ndarray, ranges: np.ndarray
) -> float:
    """Calculates a non-dimensional error metric,
    the scaled minimum maximum average distance of a Pareto-optimal

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Function get_maxmin_samples has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

def get_maxmin_samples(  # pylint:disable=invalid-name
    X: np.array,
    n_samples: int,
    metric: str = "euclidean",
    init: str = "mean",

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