Stats.hd15iqr() - Code Metrics - Inspection of "Add support for pygal 2.2 and test all the pygal v..." - ionelmc/pytest-benchmark - Measure and Improve Code Quality continuously with Scrutinizer

Completed

Push — master ( 7b504c...b6f606 )

by Ionel Cristian

created 2016-05-26 23:01 UTC

Stats.hd15iqr() A

↳ Parent: Stats

Complexity

Conditions

Size

Total Lines

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
cc	3
c	0
b	0
f	0
dl	0
loc	13
rs	9.4285

from __future__ import division
from __future__ import print_function

import statistics
from bisect import bisect_left
from bisect import bisect_right

from .utils import cached_property
from .utils import funcname


class Stats(object):
    fields = (
        "min", "max", "mean", "stddev", "rounds", "median", "iqr", "q1", "q3", "iqr_outliers", "stddev_outliers",
        "outliers", "ld15iqr", "hd15iqr"
    )

    def __init__(self):
        self.data = []

    def __bool__(self):
        return bool(self.data)

    def __nonzero__(self):
        return bool(self.data)

    def as_dict(self):
        return dict(
            (field, getattr(self, field))
            for field in self.fields
        )

    def update(self, duration):
        self.data.append(duration)

    @cached_property
    def sorted_data(self):
        return sorted(self.data)

    @cached_property
    def total(self):
        return sum(self.data)

    @cached_property
    def min(self):
        return min(self.data)

    @cached_property
    def max(self):
        return max(self.data)

    @cached_property
    def mean(self):
        return statistics.mean(self.data)

    @cached_property
    def stddev(self):
        if len(self.data) > 1:
            return statistics.stdev(self.data)
        else:
            return 0

    @property
    def stddev_outliers(self):
        """
        Count of StdDev outliers: what's beyond (Mean - StdDev, Mean - StdDev)
        """
        count = 0
        q0 = self.mean - self.stddev
        q4 = self.mean + self.stddev
        for val in self.data:
            if val < q0 or val > q4:
                count += 1
        return count

    @cached_property
    def rounds(self):
        return len(self.data)

    @cached_property
    def median(self):
        return statistics.median(self.data)

    @cached_property
    def ld15iqr(self):
        """
        Tukey-style Lowest Datum within 1.5 IQR under Q1.
        """
        if len(self.data) == 1:
            return self.data[0]
        else:
            return self.sorted_data[bisect_left(self.sorted_data, self.q1 - 1.5 * self.iqr)]

    @cached_property
    def hd15iqr(self):
        """
        Tukey-style Highest Datum within 1.5 IQR over Q3.
        """
        if len(self.data) == 1:
            return self.data[0]
        else:
            pos = bisect_right(self.sorted_data, self.q3 + 1.5 * self.iqr)
            if pos == len(self.data):
                return self.sorted_data[-1]
            else:
                return self.sorted_data[pos]

    @cached_property

    def q1(self):
        rounds = self.rounds
        data = self.sorted_data

        # See: https://en.wikipedia.org/wiki/Quartile#Computing_methods
        if rounds == 1:
            return data[0]
        elif rounds % 2:  # Method 3
            n, q = rounds // 4, rounds % 4
            if q == 1:
                return 0.25 * data[n - 1] + 0.75 * data[n]
            else:
                return 0.75 * data[n] + 0.25 * data[n + 1]
        else:  # Method 2
            return statistics.median(data[:rounds // 2])

    @cached_property

    def q3(self):
        rounds = self.rounds
        data = self.sorted_data

        # See: https://en.wikipedia.org/wiki/Quartile#Computing_methods
        if rounds == 1:
            return data[0]
        elif rounds % 2:  # Method 3
            n, q = rounds // 4, rounds % 4
            if q == 1:
                return 0.75 * data[3 * n] + 0.25 * data[3 * n + 1]
            else:
                return 0.25 * data[3 * n + 1] + 0.75 * data[3 * n + 2]
        else:  # Method 2
            return statistics.median(data[rounds // 2:])

    @cached_property
    def iqr(self):
        return self.q3 - self.q1

    @property
    def iqr_outliers(self):
        """
        Count of Tukey outliers: what's beyond (Q1 - 1.5IQR, Q3 + 1.5IQR)
        """
        count = 0
        q0 = self.q1 - 1.5 * self.iqr
        q4 = self.q3 + 1.5 * self.iqr
        for val in self.data:
            if val < q0 or val > q4:
                count += 1
        return count

    @cached_property
    def outliers(self):
        return "%s;%s" % (self.stddev_outliers, self.iqr_outliers)


class BenchmarkStats(object):
    def __init__(self, fixture, iterations, options):
        self.name = fixture.name
        self.fullname = fixture.fullname
        self.group = fixture.group
        self.param = fixture.param
        self.params = fixture.params

        self.iterations = iterations
        self.stats = Stats()
        self.options = options
        self.fixture = fixture

    def __bool__(self):
        return bool(self.stats)

    def __nonzero__(self):
        return bool(self.stats)

    def get(self, key, default=None):
        try:
            return getattr(self.stats, key)
        except AttributeError:
            return getattr(self, key, default)

    def __getitem__(self, key):
        try:
            return getattr(self.stats, key)
        except AttributeError:
            return getattr(self, key)

    @property
    def has_error(self):
        return self.fixture.has_error

    def as_dict(self, include_data=True, flat=False, stats=True):
        result = {
            "group": self.group,
            "name": self.name,
            "fullname": self.fullname,
            "params": self.params,
            "param": self.param,
            "options": dict(
                (k, funcname(v) if callable(v) else v) for k, v in self.options.items()
            )
        }
        if stats:
            stats = self.stats.as_dict()
            if include_data:
                stats["data"] = self.stats.data
            stats["iterations"] = self.iterations
            if flat:
                result.update(stats)
            else:
                result["stats"] = stats
        return result

    def update(self, duration):
        self.stats.update(duration / self.iterations)


1		from __future__ import division
2		from __future__ import print_function
3
4		import statistics
5		from bisect import bisect_left
6		from bisect import bisect_right
7
8		from .utils import cached_property
9		from .utils import funcname
10
11
12		class Stats(object):
13		fields = (
14		"min", "max", "mean", "stddev", "rounds", "median", "iqr", "q1", "q3", "iqr_outliers", "stddev_outliers",
15		"outliers", "ld15iqr", "hd15iqr"
16		)
17
18		def __init__(self):
19		self.data = []
20
21		def __bool__(self):
22		return bool(self.data)
23
24		def __nonzero__(self):
25		return bool(self.data)
26
27		def as_dict(self):
28		return dict(
29		(field, getattr(self, field))
30		for field in self.fields
31		)
32
33		def update(self, duration):
34		self.data.append(duration)
35
36		@cached_property
37		def sorted_data(self):
38		return sorted(self.data)
39
40		@cached_property
41		def total(self):
42		return sum(self.data)
43
44		@cached_property
45		def min(self):
46		return min(self.data)
47
48		@cached_property
49		def max(self):
50		return max(self.data)
51
52		@cached_property
53		def mean(self):
54		return statistics.mean(self.data)
55
56		@cached_property
57		def stddev(self):
58		if len(self.data) > 1:
59		return statistics.stdev(self.data)
60		else:
61		return 0
62
63		@property
64		def stddev_outliers(self):
65		"""
66		Count of StdDev outliers: what's beyond (Mean - StdDev, Mean - StdDev)
67		"""
68		count = 0
69		q0 = self.mean - self.stddev
70		q4 = self.mean + self.stddev
71		for val in self.data:
72		if val < q0 or val > q4:
73		count += 1
74		return count
75
76		@cached_property
77		def rounds(self):
78		return len(self.data)
79
80		@cached_property
81		def median(self):
82		return statistics.median(self.data)
83
84		@cached_property
85		def ld15iqr(self):
86		"""
87		Tukey-style Lowest Datum within 1.5 IQR under Q1.
88		"""
89		if len(self.data) == 1:
90		return self.data[0]
91		else:
92		return self.sorted_data[bisect_left(self.sorted_data, self.q1 - 1.5 * self.iqr)]
93
94		@cached_property
95		def hd15iqr(self):
96		"""
97		Tukey-style Highest Datum within 1.5 IQR over Q3.
98		"""
99		if len(self.data) == 1:
100		return self.data[0]
101		else:
102		pos = bisect_right(self.sorted_data, self.q3 + 1.5 * self.iqr)
103		if pos == len(self.data):
104		return self.sorted_data[-1]
105		else:
106		return self.sorted_data[pos]
107
108	View Code Duplication	@cached_property
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109		def q1(self):
110		rounds = self.rounds
111		data = self.sorted_data
112
113		# See: https://en.wikipedia.org/wiki/Quartile#Computing_methods
114		if rounds == 1:
115		return data[0]
116		elif rounds % 2: # Method 3
117		n, q = rounds // 4, rounds % 4
118		if q == 1:
119		return 0.25 * data[n - 1] + 0.75 * data[n]
120		else:
121		return 0.75 * data[n] + 0.25 * data[n + 1]
122		else: # Method 2
123		return statistics.median(data[:rounds // 2])
124
125	View Code Duplication	@cached_property
		0 ignored issues – show Duplication introduced 2016-05-26 23:02 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
126		def q3(self):
127		rounds = self.rounds
128		data = self.sorted_data
129
130		# See: https://en.wikipedia.org/wiki/Quartile#Computing_methods
131		if rounds == 1:
132		return data[0]
133		elif rounds % 2: # Method 3
134		n, q = rounds // 4, rounds % 4
135		if q == 1:
136		return 0.75 * data[3 * n] + 0.25 * data[3 * n + 1]
137		else:
138		return 0.25 * data[3 * n + 1] + 0.75 * data[3 * n + 2]
139		else: # Method 2
140		return statistics.median(data[rounds // 2:])
141
142		@cached_property
143		def iqr(self):
144		return self.q3 - self.q1
145
146		@property
147		def iqr_outliers(self):
148		"""
149		Count of Tukey outliers: what's beyond (Q1 - 1.5IQR, Q3 + 1.5IQR)
150		"""
151		count = 0
152		q0 = self.q1 - 1.5 * self.iqr
153		q4 = self.q3 + 1.5 * self.iqr
154		for val in self.data:
155		if val < q0 or val > q4:
156		count += 1
157		return count
158
159		@cached_property
160		def outliers(self):
161		return "%s;%s" % (self.stddev_outliers, self.iqr_outliers)
162
163
164		class BenchmarkStats(object):
165		def __init__(self, fixture, iterations, options):
166		self.name = fixture.name
167		self.fullname = fixture.fullname
168		self.group = fixture.group
169		self.param = fixture.param
170		self.params = fixture.params
171
172		self.iterations = iterations
173		self.stats = Stats()
174		self.options = options
175		self.fixture = fixture
176
177		def __bool__(self):
178		return bool(self.stats)
179
180		def __nonzero__(self):
181		return bool(self.stats)
182
183		def get(self, key, default=None):
184		try:
185		return getattr(self.stats, key)
186		except AttributeError:
187		return getattr(self, key, default)
188
189		def __getitem__(self, key):
190		try:
191		return getattr(self.stats, key)
192		except AttributeError:
193		return getattr(self, key)
194
195		@property
196		def has_error(self):
197		return self.fixture.has_error
198
199		def as_dict(self, include_data=True, flat=False, stats=True):
200		result = {
201		"group": self.group,
202		"name": self.name,
203		"fullname": self.fullname,
204		"params": self.params,
205		"param": self.param,
206		"options": dict(
207		(k, funcname(v) if callable(v) else v) for k, v in self.options.items()
208		)
209		}
210		if stats:
211		stats = self.stats.as_dict()
212		if include_data:
213		stats["data"] = self.stats.data
214		stats["iterations"] = self.iterations
215		if flat:
216		result.update(stats)
217		else:
218		result["stats"] = stats
219		return result
220
221		def update(self, duration):
222		self.stats.update(duration / self.iterations)
223

ionelmc / pytest-benchmark

Push — master ( 7b504c...b6f606 )

Stats.hd15iqr() A

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