abydos.distance._eudex.Eudex.dist_abs() - Code Metrics - Inspection of "Merge pull request #149 from chrislit/0.3.6" - chrislit/abydos - Measure and Improve Code Quality continuously with Scrutinizer

Completed

Push — master ( f43547...71985b )

by Chris

created 2018-11-17 08:52 UTC

abydos.distance._eudex.Eudex.dist_abs() C

↳ Parent: abydos.distance._eudex

Complexity

Conditions

Size

Total Lines	114
Code Lines	27

Duplication

Lines	0
Ratio	0 %

Code Coverage

Tests	25
CRAP Score	11

Importance

Changes

Metric	Value
cc	11
eloc	27
nop	6
dl	0
loc	114
ccs	25
cts	25
cp	1
crap	11
rs	5.4
c	0
b	0
f	0

How to fix Long Method Complexity

# -*- coding: utf-8 -*-

# Copyright 2018 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._eudex.

eudex distance functions
"""

from __future__ import (
    absolute_import,
    division,
    print_function,
    unicode_literals,
)

from types import GeneratorType

from six.moves import range

from ._distance import _Distance
from ..phonetic import eudex

__all__ = ['Eudex', 'dist_eudex', 'eudex_hamming', 'sim_eudex']


class Eudex(_Distance):

    """Distance between the Eudex hashes of two terms.

    Cf. :cite:`Ticki:2016`.
    """

    @staticmethod
    def gen_fibonacci():
        """Yield the next Fibonacci number.

        Based on https://www.python-course.eu/generators.php
        Starts at Fibonacci number 3 (the second 1)

        Yields
        ------
        int
            The next Fibonacci number

        """
        num_a, num_b = 1, 2
        while True:
            yield num_a
            num_a, num_b = num_b, num_a + num_b

    @staticmethod
    def gen_exponential(base=2):
        """Yield the next value in an exponential series of the base.

        Starts at base**0

        Parameters
        ----------
        base : int
            The base to exponentiate

        Yields
        ------
        int
            The next power of `base`

        """
        exp = 0
        while True:
            yield base ** exp
            exp += 1

    def dist_abs(

        self, src, tar, weights='exponential', max_length=8, normalized=False

    ):
        """Calculate the distance between the Eudex hashes of two terms.

        Parameters
        ----------
        src : str
            Source string for comparison
        tar : str
            Target string for comparison
        weights : str, iterable, or generator function
            The weights or weights generator function

                - If set to ``None``, a simple Hamming distance is calculated.
                - If set to ``exponential``, weight decays by powers of 2, as
                  proposed in the eudex specification:
                  https://github.com/ticki/eudex.
                - If set to ``fibonacci``, weight decays through the Fibonacci
                  series, as in the eudex reference implementation.
                - If set to a callable function, this assumes it creates a
                  generator and the generator is used to populate a series of
                  weights.
                - If set to an iterable, the iterable's values should be
                  integers and will be used as the weights.

        max_length : int
            The number of characters to encode as a eudex hash
        normalized : bool
            Normalizes to [0, 1] if True

        Returns
        -------
        int
            The Eudex Hamming distance

        Examples
        --------
        >>> cmp = Eudex()
        >>> cmp.dist_abs('cat', 'hat')
        128
        >>> cmp.dist_abs('Niall', 'Neil')
        2
        >>> cmp.dist_abs('Colin', 'Cuilen')
        10
        >>> cmp.dist_abs('ATCG', 'TAGC')
        403

        >>> cmp.dist_abs('cat', 'hat', weights='fibonacci')
        34
        >>> cmp.dist_abs('Niall', 'Neil', weights='fibonacci')
        2
        >>> cmp.dist_abs('Colin', 'Cuilen', weights='fibonacci')
        7
        >>> cmp.dist_abs('ATCG', 'TAGC', weights='fibonacci')
        117

        >>> cmp.dist_abs('cat', 'hat', weights=None)
        1
        >>> cmp.dist_abs('Niall', 'Neil', weights=None)
        1
        >>> cmp.dist_abs('Colin', 'Cuilen', weights=None)
        2
        >>> cmp.dist_abs('ATCG', 'TAGC', weights=None)
        9

        >>> # Using the OEIS A000142:
        >>> cmp.dist_abs('cat', 'hat', [1, 1, 2, 6, 24, 120, 720, 5040])
        1
        >>> cmp.dist_abs('Niall', 'Neil', [1, 1, 2, 6, 24, 120, 720, 5040])
        720
        >>> cmp.dist_abs('Colin', 'Cuilen',
        ... [1, 1, 2, 6, 24, 120, 720, 5040])
        744
        >>> cmp.dist_abs('ATCG', 'TAGC', [1, 1, 2, 6, 24, 120, 720, 5040])
        6243

        """
        # Calculate the eudex hashes and XOR them
        xored = eudex(src, max_length=max_length) ^ eudex(
            tar, max_length=max_length
        )

        # Simple hamming distance (all bits are equal)
        if not weights:
            binary = bin(xored)
            distance = binary.count('1')
            if normalized:
                return distance / (len(binary) - 2)
            return distance

        # If weights is a function, it should create a generator,
        # which we now use to populate a list
        if callable(weights):
            weights = weights()
        elif weights == 'exponential':
            weights = Eudex.gen_exponential()
        elif weights == 'fibonacci':
            weights = Eudex.gen_fibonacci()
        if isinstance(weights, GeneratorType):
            weights = [next(weights) for _ in range(max_length)][::-1]

        # Sum the weighted hamming distance
        distance = 0
        max_distance = 0
        while (xored or normalized) and weights:
            max_distance += 8 * weights[-1]
            distance += bin(xored & 0xFF).count('1') * weights.pop()
            xored >>= 8

        if normalized:
            distance /= max_distance

        return distance

    def dist(self, src, tar, weights='exponential', max_length=8):

        """Return normalized distance between the Eudex hashes of two terms.

        This is Eudex distance normalized to [0, 1].

        Parameters
        ----------
        src : str
            Source string for comparison
        tar : str
            Target string for comparison
        weights : str, iterable, or generator function
            The weights or weights generator function
        max_length : int
            The number of characters to encode as a eudex hash

        Returns
        -------
        int
            The normalized Eudex Hamming distance

        Examples
        --------
        >>> cmp = Eudex()
        >>> round(cmp.dist('cat', 'hat'), 12)
        0.062745098039
        >>> round(cmp.dist('Niall', 'Neil'), 12)
        0.000980392157
        >>> round(cmp.dist('Colin', 'Cuilen'), 12)
        0.004901960784
        >>> round(cmp.dist('ATCG', 'TAGC'), 12)
        0.197549019608

        """
        return self.dist_abs(src, tar, weights, max_length, True)


def eudex_hamming(
    src, tar, weights='exponential', max_length=8, normalized=False

):
    """Calculate the Hamming distance between the Eudex hashes of two terms.

    This is a wrapper for :py:meth:`Eudex.eudex_hamming`.

    Parameters
    ----------
    src : str
        Source string for comparison
    tar : str
        Target string for comparison
    weights : str, iterable, or generator function
        The weights or weights generator function
    max_length : int
        The number of characters to encode as a eudex hash
    normalized : bool
        Normalizes to [0, 1] if True

    Returns
    -------
    int
        The Eudex Hamming distance

    Examples
    --------
    >>> eudex_hamming('cat', 'hat')
    128
    >>> eudex_hamming('Niall', 'Neil')
    2
    >>> eudex_hamming('Colin', 'Cuilen')
    10
    >>> eudex_hamming('ATCG', 'TAGC')
    403

    >>> eudex_hamming('cat', 'hat', weights='fibonacci')
    34
    >>> eudex_hamming('Niall', 'Neil', weights='fibonacci')
    2
    >>> eudex_hamming('Colin', 'Cuilen', weights='fibonacci')
    7
    >>> eudex_hamming('ATCG', 'TAGC', weights='fibonacci')
    117

    >>> eudex_hamming('cat', 'hat', weights=None)
    1
    >>> eudex_hamming('Niall', 'Neil', weights=None)
    1
    >>> eudex_hamming('Colin', 'Cuilen', weights=None)
    2
    >>> eudex_hamming('ATCG', 'TAGC', weights=None)
    9

    >>> # Using the OEIS A000142:
    >>> eudex_hamming('cat', 'hat', [1, 1, 2, 6, 24, 120, 720, 5040])
    1
    >>> eudex_hamming('Niall', 'Neil', [1, 1, 2, 6, 24, 120, 720, 5040])
    720
    >>> eudex_hamming('Colin', 'Cuilen', [1, 1, 2, 6, 24, 120, 720, 5040])
    744
    >>> eudex_hamming('ATCG', 'TAGC', [1, 1, 2, 6, 24, 120, 720, 5040])
    6243

    """
    return Eudex().dist_abs(src, tar, weights, max_length, normalized)


def dist_eudex(src, tar, weights='exponential', max_length=8):
    """Return normalized Hamming distance between Eudex hashes of two terms.

    This is a wrapper for :py:meth:`Eudex.dist`.

    Parameters
    ----------
    src : str
        Source string for comparison
    tar : str
        Target string for comparison
    weights : str, iterable, or generator function
        The weights or weights generator function
    max_length : int
        The number of characters to encode as a eudex hash

    Returns
    -------
    int
        The normalized Eudex Hamming distance

    Examples
    --------
    >>> round(dist_eudex('cat', 'hat'), 12)
    0.062745098039
    >>> round(dist_eudex('Niall', 'Neil'), 12)
    0.000980392157
    >>> round(dist_eudex('Colin', 'Cuilen'), 12)
    0.004901960784
    >>> round(dist_eudex('ATCG', 'TAGC'), 12)
    0.197549019608

    """
    return Eudex().dist(src, tar, weights, max_length)


def sim_eudex(src, tar, weights='exponential', max_length=8):
    """Return normalized Hamming similarity between Eudex hashes of two terms.

    This is a wrapper for :py:meth:`Eudex.sim`.

    Parameters
    ----------
    src : str
        Source string for comparison
    tar : str
        Target string for comparison
    weights : str, iterable, or generator function
        The weights or weights generator function
    max_length : int
        The number of characters to encode as a eudex hash

    Returns
    -------
    int
        The normalized Eudex Hamming similarity

    Examples
    --------
    >>> round(sim_eudex('cat', 'hat'), 12)
    0.937254901961
    >>> round(sim_eudex('Niall', 'Neil'), 12)
    0.999019607843
    >>> round(sim_eudex('Colin', 'Cuilen'), 12)
    0.995098039216
    >>> round(sim_eudex('ATCG', 'TAGC'), 12)
    0.802450980392

    """
    return Eudex().sim(src, tar, weights, max_length)


if __name__ == '__main__':
    import doctest

    doctest.testmod()


1		# -- coding: utf-8 --
2
3		# Copyright 2018 by Christopher C. Little.
4		# This file is part of Abydos.
5		#
6		# Abydos is free software: you can redistribute it and/or modify
7		# it under the terms of the GNU General Public License as published by
8		# the Free Software Foundation, either version 3 of the License, or
9		# (at your option) any later version.
10		#
11		# Abydos is distributed in the hope that it will be useful,
12		# but WITHOUT ANY WARRANTY; without even the implied warranty of
13		# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
14		# GNU General Public License for more details.
15		#
16		# You should have received a copy of the GNU General Public License
17		# along with Abydos. If not, see <http://www.gnu.org/licenses/>.
18
19	1	"""abydos.distance._eudex.
20
21		eudex distance functions
22		"""
23
24	1	from __future__ import (
25		absolute_import,
26		division,
27		print_function,
28		unicode_literals,
29		)
30
31	1	from types import GeneratorType
32
33	1	from six.moves import range
34
35	1	from ._distance import _Distance
36	1	from ..phonetic import eudex
37
38	1	__all__ = ['Eudex', 'dist_eudex', 'eudex_hamming', 'sim_eudex']
39
40
41	1	class Eudex(_Distance):
		0 ignored issues – show Unused Code introduced 2018-11-04 08:02 UTC by Report Bug Copy Issue Report The variable `__class__` seems to be unused. Loading history...
42		"""Distance between the Eudex hashes of two terms.
43
44		Cf. :cite:`Ticki:2016`.
45		"""
46
47	1	@staticmethod
48		def gen_fibonacci():
49		"""Yield the next Fibonacci number.
50
51		Based on https://www.python-course.eu/generators.php
52		Starts at Fibonacci number 3 (the second 1)
53
54		Yields
55		------
56		int
57		The next Fibonacci number
58
59		"""
60	1	num_a, num_b = 1, 2
61	1	while True:
62	1	yield num_a
63	1	num_a, num_b = num_b, num_a + num_b
64
65	1	@staticmethod
66	1	def gen_exponential(base=2):
67		"""Yield the next value in an exponential series of the base.
68
69		Starts at base**0
70
71		Parameters
72		----------
73		base : int
74		The base to exponentiate
75
76		Yields
77		------
78		int
79		The next power of `base`
80
81		"""
82	1	exp = 0
83	1	while True:
84	1	yield base ** exp
85	1	exp += 1
86
87	1	def dist_abs(
		0 ignored issues – show best-practice introduced 2018-11-04 08:02 UTC by Report Bug Copy Issue Report Too many arguments (6/5) Loading history... Bug introduced 2018-11-04 08:02 UTC by Report Bug Copy Issue Report Parameters differ from overridden 'dist_abs' method Loading history...
88		self, src, tar, weights='exponential', max_length=8, normalized=False
		0 ignored issues – show Coding Style introduced 2018-10-24 06:00 UTC by Report Bug Copy Issue Report Wrong hanging indentation before block (add 4 spaces). Loading history...
89		):
90		"""Calculate the distance between the Eudex hashes of two terms.
91
92		Parameters
93		----------
94		src : str
95		Source string for comparison
96		tar : str
97		Target string for comparison
98		weights : str, iterable, or generator function
99		The weights or weights generator function
100
101		- If set to ``None``, a simple Hamming distance is calculated.
102		- If set to ``exponential``, weight decays by powers of 2, as
103		proposed in the eudex specification:
104		https://github.com/ticki/eudex.
105		- If set to ``fibonacci``, weight decays through the Fibonacci
106		series, as in the eudex reference implementation.
107		- If set to a callable function, this assumes it creates a
108		generator and the generator is used to populate a series of
109		weights.
110		- If set to an iterable, the iterable's values should be
111		integers and will be used as the weights.
112
113		max_length : int
114		The number of characters to encode as a eudex hash
115		normalized : bool
116		Normalizes to [0, 1] if True
117
118		Returns
119		-------
120		int
121		The Eudex Hamming distance
122
123		Examples
124		--------
125		>>> cmp = Eudex()
126		>>> cmp.dist_abs('cat', 'hat')
127		128
128		>>> cmp.dist_abs('Niall', 'Neil')
129		2
130		>>> cmp.dist_abs('Colin', 'Cuilen')
131		10
132		>>> cmp.dist_abs('ATCG', 'TAGC')
133		403
134
135		>>> cmp.dist_abs('cat', 'hat', weights='fibonacci')
136		34
137		>>> cmp.dist_abs('Niall', 'Neil', weights='fibonacci')
138		2
139		>>> cmp.dist_abs('Colin', 'Cuilen', weights='fibonacci')
140		7
141		>>> cmp.dist_abs('ATCG', 'TAGC', weights='fibonacci')
142		117
143
144		>>> cmp.dist_abs('cat', 'hat', weights=None)
145		1
146		>>> cmp.dist_abs('Niall', 'Neil', weights=None)
147		1
148		>>> cmp.dist_abs('Colin', 'Cuilen', weights=None)
149		2
150		>>> cmp.dist_abs('ATCG', 'TAGC', weights=None)
151		9
152
153		>>> # Using the OEIS A000142:
154		>>> cmp.dist_abs('cat', 'hat', [1, 1, 2, 6, 24, 120, 720, 5040])
155		1
156		>>> cmp.dist_abs('Niall', 'Neil', [1, 1, 2, 6, 24, 120, 720, 5040])
157		720
158		>>> cmp.dist_abs('Colin', 'Cuilen',
159		... [1, 1, 2, 6, 24, 120, 720, 5040])
160		744
161		>>> cmp.dist_abs('ATCG', 'TAGC', [1, 1, 2, 6, 24, 120, 720, 5040])
162		6243
163
164		"""
165		# Calculate the eudex hashes and XOR them
166	1	xored = eudex(src, max_length=max_length) ^ eudex(
167		tar, max_length=max_length
168		)
169
170		# Simple hamming distance (all bits are equal)
171	1	if not weights:
172	1	binary = bin(xored)
173	1	distance = binary.count('1')
174	1	if normalized:
175	1	return distance / (len(binary) - 2)
176	1	return distance
177
178		# If weights is a function, it should create a generator,
179		# which we now use to populate a list
180	1	if callable(weights):
181	1	weights = weights()
182	1	elif weights == 'exponential':
183	1	weights = Eudex.gen_exponential()
184	1	elif weights == 'fibonacci':
185	1	weights = Eudex.gen_fibonacci()
186	1	if isinstance(weights, GeneratorType):
187	1	weights = [next(weights) for _ in range(max_length)][::-1]
188
189		# Sum the weighted hamming distance
190	1	distance = 0
191	1	max_distance = 0
192	1	while (xored or normalized) and weights:
193	1	max_distance += 8 * weights[-1]
194	1	distance += bin(xored & 0xFF).count('1') * weights.pop()
195	1	xored >>= 8
196
197	1	if normalized:
198	1	distance /= max_distance
199
200	1	return distance
201
202	1	def dist(self, src, tar, weights='exponential', max_length=8):
		0 ignored issues – show Bug introduced 2018-11-04 08:02 UTC by Report Bug Copy Issue Report Parameters differ from overridden 'dist' method Loading history...
203		"""Return normalized distance between the Eudex hashes of two terms.
204
205		This is Eudex distance normalized to [0, 1].
206
207		Parameters
208		----------
209		src : str
210		Source string for comparison
211		tar : str
212		Target string for comparison
213		weights : str, iterable, or generator function
214		The weights or weights generator function
215		max_length : int
216		The number of characters to encode as a eudex hash
217
218		Returns
219		-------
220		int
221		The normalized Eudex Hamming distance
222
223		Examples
224		--------
225		>>> cmp = Eudex()
226		>>> round(cmp.dist('cat', 'hat'), 12)
227		0.062745098039
228		>>> round(cmp.dist('Niall', 'Neil'), 12)
229		0.000980392157
230		>>> round(cmp.dist('Colin', 'Cuilen'), 12)
231		0.004901960784
232		>>> round(cmp.dist('ATCG', 'TAGC'), 12)
233		0.197549019608
234
235		"""
236	1	return self.dist_abs(src, tar, weights, max_length, True)
237
238
239	1	def eudex_hamming(
240		src, tar, weights='exponential', max_length=8, normalized=False
		0 ignored issues – show Coding Style introduced 2018-11-04 08:02 UTC by Report Bug Copy Issue Report Wrong hanging indentation before block (add 4 spaces). Loading history...
241		):
242		"""Calculate the Hamming distance between the Eudex hashes of two terms.
243
244		This is a wrapper for :py:meth:`Eudex.eudex_hamming`.
245
246		Parameters
247		----------
248		src : str
249		Source string for comparison
250		tar : str
251		Target string for comparison
252		weights : str, iterable, or generator function
253		The weights or weights generator function
254		max_length : int
255		The number of characters to encode as a eudex hash
256		normalized : bool
257		Normalizes to [0, 1] if True
258
259		Returns
260		-------
261		int
262		The Eudex Hamming distance
263
264		Examples
265		--------
266		>>> eudex_hamming('cat', 'hat')
267		128
268		>>> eudex_hamming('Niall', 'Neil')
269		2
270		>>> eudex_hamming('Colin', 'Cuilen')
271		10
272		>>> eudex_hamming('ATCG', 'TAGC')
273		403
274
275		>>> eudex_hamming('cat', 'hat', weights='fibonacci')
276		34
277		>>> eudex_hamming('Niall', 'Neil', weights='fibonacci')
278		2
279		>>> eudex_hamming('Colin', 'Cuilen', weights='fibonacci')
280		7
281		>>> eudex_hamming('ATCG', 'TAGC', weights='fibonacci')
282		117
283
284		>>> eudex_hamming('cat', 'hat', weights=None)
285		1
286		>>> eudex_hamming('Niall', 'Neil', weights=None)
287		1
288		>>> eudex_hamming('Colin', 'Cuilen', weights=None)
289		2
290		>>> eudex_hamming('ATCG', 'TAGC', weights=None)
291		9
292
293		>>> # Using the OEIS A000142:
294		>>> eudex_hamming('cat', 'hat', [1, 1, 2, 6, 24, 120, 720, 5040])
295		1
296		>>> eudex_hamming('Niall', 'Neil', [1, 1, 2, 6, 24, 120, 720, 5040])
297		720
298		>>> eudex_hamming('Colin', 'Cuilen', [1, 1, 2, 6, 24, 120, 720, 5040])
299		744
300		>>> eudex_hamming('ATCG', 'TAGC', [1, 1, 2, 6, 24, 120, 720, 5040])
301		6243
302
303		"""
304	1	return Eudex().dist_abs(src, tar, weights, max_length, normalized)
305
306
307	1	def dist_eudex(src, tar, weights='exponential', max_length=8):
308		"""Return normalized Hamming distance between Eudex hashes of two terms.
309
310		This is a wrapper for :py:meth:`Eudex.dist`.
311
312		Parameters
313		----------
314		src : str
315		Source string for comparison
316		tar : str
317		Target string for comparison
318		weights : str, iterable, or generator function
319		The weights or weights generator function
320		max_length : int
321		The number of characters to encode as a eudex hash
322
323		Returns
324		-------
325		int
326		The normalized Eudex Hamming distance
327
328		Examples
329		--------
330		>>> round(dist_eudex('cat', 'hat'), 12)
331		0.062745098039
332		>>> round(dist_eudex('Niall', 'Neil'), 12)
333		0.000980392157
334		>>> round(dist_eudex('Colin', 'Cuilen'), 12)
335		0.004901960784
336		>>> round(dist_eudex('ATCG', 'TAGC'), 12)
337		0.197549019608
338
339		"""
340	1	return Eudex().dist(src, tar, weights, max_length)
341
342
343	1	def sim_eudex(src, tar, weights='exponential', max_length=8):
344		"""Return normalized Hamming similarity between Eudex hashes of two terms.
345
346		This is a wrapper for :py:meth:`Eudex.sim`.
347
348		Parameters
349		----------
350		src : str
351		Source string for comparison
352		tar : str
353		Target string for comparison
354		weights : str, iterable, or generator function
355		The weights or weights generator function
356		max_length : int
357		The number of characters to encode as a eudex hash
358
359		Returns
360		-------
361		int
362		The normalized Eudex Hamming similarity
363
364		Examples
365		--------
366		>>> round(sim_eudex('cat', 'hat'), 12)
367		0.937254901961
368		>>> round(sim_eudex('Niall', 'Neil'), 12)
369		0.999019607843
370		>>> round(sim_eudex('Colin', 'Cuilen'), 12)
371		0.995098039216
372		>>> round(sim_eudex('ATCG', 'TAGC'), 12)
373		0.802450980392
374
375		"""
376	1	return Eudex().sim(src, tar, weights, max_length)
377
378
379		if __name__ == '__main__':
380		import doctest
381
382		doctest.testmod()
383

chrislit / abydos

Push — master ( f43547...71985b )

abydos.distance._eudex.Eudex.dist_abs() C

Complexity

Size

Duplication

Code Coverage

Importance

How to fix Long Method Complexity

Long Method

Complexity

Duplication Side-by-Side

Filter issues like