# Source code for abydos.distance._cole

# Copyright 2018-2020 by Christopher C. Little.
# This file is part of Abydos.
#
# Abydos is free software: you can redistribute it and/or modify
# 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._cole.

Cole correlation
"""

from ._token_distance import _TokenDistance

__all__ = ['Cole']

[docs]class Cole(_TokenDistance):
r"""Cole correlation.

For two sets X and Y and a population N, the Cole correlation
:cite:Cole:1949 has three formulae:

- If :math:|X \cap Y| \cdot |(N \setminus X) \setminus Y| \geq
|X \setminus Y| \cdot |Y \setminus Y| then

.. math::

corr_{Cole}(X, Y) =
\frac{|X \cap Y| \cdot |(N \setminus X) \setminus Y| -
|X \setminus Y| \cdot |Y \setminus X|}
{(|X \cap Y| + |X \setminus Y|) \cdot
(|X \setminus Y| + |(N \setminus X) \setminus Y|)}

- If :math:|(N \setminus X) \setminus Y| \geq |X \cap Y| then

.. math::

corr_{Cole}(X, Y) =
\frac{|X \cap Y| \cdot |(N \setminus X) \setminus Y| -
|X \setminus Y| \cdot |Y \setminus X|}
{(|X \cap Y| + |X \setminus Y|) \cdot
(|X \cap Y| + |Y \setminus X|)}

- Otherwise

.. math::

corr_{Cole}(X, Y) =
\frac{|X \cap Y| \cdot |(N \setminus X) \setminus Y| -
|X \setminus Y| \cdot |Y \setminus X|}
{(|X \setminus Y| + |(N \setminus X) \setminus Y|) \cdot
(|Y \setminus X| + |(N \setminus X) \setminus Y|)}

Cole terms this measurement the Coefficient of Interspecific Association.

In :ref:2x2 confusion table terms <confusion_table>, where a+b+c+d=n,
this is

.. math::

corr_{Cole} =
\left\{
\begin{array}{ll}
\\
\frac{ad-bc}{(a+b)(a+c)} & \textup{if} ~d \geq a \\
\\
\end{array}
\right.

"""

def __init__(
self,
alphabet=None,
tokenizer=None,
intersection_type='crisp',
**kwargs
):
"""Initialize Cole instance.

Parameters
----------
alphabet : Counter, collection, int, or None
This represents the alphabet of possible tokens.
See :ref:alphabet <alphabet> description in
:py:class:_TokenDistance for details.
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.

"""
super(Cole, self).__init__(
alphabet=alphabet,
tokenizer=tokenizer,
intersection_type=intersection_type,
**kwargs
)

[docs]    def corr(self, src, tar):
"""Return the Cole correlation of two strings.

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

Returns
-------
float
Cole correlation

Examples
--------
>>> cmp = Cole()
>>> cmp.corr('cat', 'hat')
0.49743589743589745
>>> cmp.corr('Niall', 'Neil')
0.3290543431750107
>>> cmp.corr('aluminum', 'Catalan')
0.10195910195910196
>>> cmp.corr('ATCG', 'TAGC')
-1.0

"""
if src == tar:
return 1.0

self._tokenize(src, tar)

a = self._intersection_card()
b = self._src_only_card()
c = self._tar_only_card()
d = self._total_complement_card()

admbc = a * d - b * c

return 0.0

if a * d >= b * c:
return admbc / ((a + b) * (b + d))
if d >= a:
return admbc / ((a + b) * (a + c))
return admbc / ((b + d) * (c + d))

[docs]    def sim(self, src, tar):
"""Return the Cole similarity of two strings.

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

Returns
-------
float
Cole similarity

Examples
--------
>>> cmp = Cole()
>>> cmp.sim('cat', 'hat')
0.7487179487179487
>>> cmp.sim('Niall', 'Neil')
0.6645271715875054
>>> cmp.sim('aluminum', 'Catalan')
0.550979550979551
>>> cmp.sim('ATCG', 'TAGC')
0.0