# Copyright 2018-2020 by Christopher C. Little.
# This file is part of Abydos.
#
# Abydos is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Abydos 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 General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Abydos. If not, see <http://www.gnu.org/licenses/>.

"""abydos.distance._euclidean.

Euclidean distance & similarity
"""

from typing import Any, Counter as TCounter, Optional, Sequence, Set, Union

from abydos.distance._minkowski import Minkowski
from abydos.tokenizer import _Tokenizer

__all__ = ['Euclidean']


class Euclidean(Minkowski):
    """Euclidean distance.

    Euclidean distance is the straigh-line or as-the-crow-flies distance,
    equivalent to Minkowski distance in :math:`L^2`-space.

    .. versionadded:: 0.3.6
    """

    def __init__(
        self,
        alphabet: Optional[
            Union[TCounter[str], Sequence[str], Set[str], int]
        ] = 0,
        tokenizer: Optional[_Tokenizer] = None,
        intersection_type: str = 'crisp',
        **kwargs: Any
    ) -> None:
        """Initialize Euclidean instance.

        Parameters
        ----------
        alphabet : collection or int
            The values or size of the alphabet
        tokenizer : _Tokenizer
            A tokenizer instance from the :py:mod:`abydos.tokenizer` package
        intersection_type : str
            Specifies the intersection type, and set type as a result:
            See :ref:`intersection_type <intersection_type>` description in
            :py:class:`_TokenDistance` for details.
        **kwargs
            Arbitrary keyword arguments

        Other Parameters
        ----------------
        qval : int
            The length of each q-gram. Using this parameter and tokenizer=None
            will cause the instance to use the QGram tokenizer with this
            q value.
        metric : _Distance
            A string distance measure class for use in the ``soft`` and
            ``fuzzy`` variants.
        threshold : float
            A threshold value, similarities above which are counted as
            members of the intersection for the ``fuzzy`` variant.


        .. versionadded:: 0.4.0

        """
        super(Euclidean, self).__init__(
            pval=2,
            alphabet=alphabet,
            tokenizer=tokenizer,
            intersection_type=intersection_type,
            **kwargs
        )

    def dist_abs(self, src: str, tar: str, normalized: bool = False) -> float:
        """Return the Euclidean distance between two strings.

        Parameters
        ----------
        src : str
            Source string (or QGrams/Counter objects) for comparison
        tar : str
            Target string (or QGrams/Counter objects) for comparison
        normalized : bool
            Normalizes to [0, 1] if True


        Returns
        -------
        float
            The Euclidean distance

        Examples
        --------
        >>> cmp = Euclidean()
        >>> cmp.dist_abs('cat', 'hat')
        2.0
        >>> round(cmp.dist_abs('Niall', 'Neil'), 12)
        2.645751311065
        >>> cmp.dist_abs('Colin', 'Cuilen')
        3.0
        >>> round(cmp.dist_abs('ATCG', 'TAGC'), 12)
        3.162277660168


        .. versionadded:: 0.3.0
        .. versionchanged:: 0.3.6
            Encapsulated in class

        """
        return super(Euclidean, self).dist_abs(src, tar, normalized=normalized)

    def dist(self, src: str, tar: str) -> float:
        """Return the normalized Euclidean distance between two strings.

        The normalized Euclidean distance is a distance
        metric in :math:`L^2`-space, normalized to [0, 1].

        Parameters
        ----------
        src : str
            Source string (or QGrams/Counter objects) for comparison
        tar : str
            Target string (or QGrams/Counter objects) for comparison

        Returns
        -------
        float
            The normalized Euclidean distance

        Examples
        --------
        >>> cmp = Euclidean()
        >>> round(cmp.dist('cat', 'hat'), 12)
        0.57735026919
        >>> round(cmp.dist('Niall', 'Neil'), 12)
        0.683130051064
        >>> round(cmp.dist('Colin', 'Cuilen'), 12)
        0.727606875109
        >>> cmp.dist('ATCG', 'TAGC')
        1.0


        .. versionadded:: 0.3.0
        .. versionchanged:: 0.3.6
            Encapsulated in class

        """
        return self.dist_abs(src, tar, normalized=True)


if __name__ == '__main__':
    import doctest

    doctest.testmod()
