Griewank.function() - Code Metrics - Inspection of "Merge pull request #31 from lucijabrezocnik/featur..." - NiaOrg/NiaPy - Measure and Improve Code Quality continuously with Scrutinizer

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created 2018-02-14 19:16 UTC

Griewank.function() A

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Complexity

Conditions

Size

Total Lines

Duplication

Lines	0
Ratio	0 %

Importance

Changes	1
Bugs	0	Features	1

Metric	Value
dl	0
loc	18
rs	9.4285
c	1
b	0
f	1
cc	3

"""Implementation of Griewank function.


Date: February 2018

Authors: Iztok Fister Jr. and Lucija Brezočnik

License: MIT

Function: Griewank function

Input domain:
    The function can be defined on any input domain but it is usually
    evaluated on the hypercube x_i ∈ [-100, 100], for all i = 1, 2,..., D.

Global minimum:
    f(x*) = 0, at x* = (0,...,0)

LaTeX formats:
    Inline: $f(x) = \sum_{i=1}^D \frac{x_i^2}{4000} -
            \prod_{i=1}^D cos(\frac{x_i}{\sqrt{i}}) + 1$
    Equation: \begin{equation} f(x) = \sum_{i=1}^D \frac{x_i^2}{4000} -
              \prod_{i=1}^D cos(\frac{x_i}{\sqrt{i}}) + 1 \end{equation}
    Domain: $-100 \leq x_i \leq 100$

Reference paper:
    Jamil, M., and Yang, X. S. (2013).
    A literature survey of benchmark functions for global optimisation problems.
    International Journal of Mathematical Modelling and Numerical Optimisation,
    4(2), 150-194.
"""

import math

__all__ = ['Griewank']


class Griewank(object):

    def __init__(self, Lower=-100, Upper=100):
        self.Lower = Lower
        self.Upper = Upper

    @classmethod
    def function(cls):
        def evaluate(D, sol):

            val1 = 0.0
            val2 = 1.0

            for i in range(D):
                val1 += (math.pow(sol[i], 2) / 4000)
                val2 *= (math.cos(sol[i] / math.sqrt(i + 1)))

            return val1 - val2 + 1

        return evaluate


1			"""Implementation of Griewank function.
			0 ignored issues – show Bug introduced 2018-02-14 19:17 UTC by Report Bug Copy Issue Report A suspicious escape sequence `\s` was found. Did you maybe forget to add an `r` prefix? Escape sequences in Python are generally interpreted according to rules similar to standard C. Only if strings are prefixed with `r` or `R` are they interpreted as regular expressions. The escape sequence that was used indicates that you might have intended to write a regular expression. Learn more about the available escape sequences. in the Python documentation. Loading history... Bug introduced 2018-02-14 19:17 UTC by Report Bug Copy Issue Report A suspicious escape sequence `\p` was found. Did you maybe forget to add an `r` prefix? Escape sequences in Python are generally interpreted according to rules similar to standard C. Only if strings are prefixed with `r` or `R` are they interpreted as regular expressions. The escape sequence that was used indicates that you might have intended to write a regular expression. Learn more about the available escape sequences. in the Python documentation. Loading history... Bug introduced 2018-02-14 19:17 UTC by Report Bug Copy Issue Report A suspicious escape sequence `\e` was found. Did you maybe forget to add an `r` prefix? Escape sequences in Python are generally interpreted according to rules similar to standard C. Only if strings are prefixed with `r` or `R` are they interpreted as regular expressions. The escape sequence that was used indicates that you might have intended to write a regular expression. Learn more about the available escape sequences. in the Python documentation. Loading history... Bug introduced 2018-02-14 19:17 UTC by Report Bug Copy Issue Report A suspicious escape sequence `\l` was found. Did you maybe forget to add an `r` prefix? Escape sequences in Python are generally interpreted according to rules similar to standard C. Only if strings are prefixed with `r` or `R` are they interpreted as regular expressions. The escape sequence that was used indicates that you might have intended to write a regular expression. Learn more about the available escape sequences. in the Python documentation. Loading history...
2
3			Date: February 2018
4
5			Authors: Iztok Fister Jr. and Lucija Brezočnik
6
7			License: MIT
8
9			Function: Griewank function
10
11			Input domain:
12			The function can be defined on any input domain but it is usually
13			evaluated on the hypercube x_i ∈ [-100, 100], for all i = 1, 2,..., D.
14
15			Global minimum:
16			f(x) = 0, at x = (0,...,0)
17
18			LaTeX formats:
19			Inline: $f(x) = \sum_{i=1}^D \frac{x_i^2}{4000} -
20			\prod_{i=1}^D cos(\frac{x_i}{\sqrt{i}}) + 1$
21			Equation: \begin{equation} f(x) = \sum_{i=1}^D \frac{x_i^2}{4000} -
22			\prod_{i=1}^D cos(\frac{x_i}{\sqrt{i}}) + 1 \end{equation}
23			Domain: $-100 \leq x_i \leq 100$
24
25			Reference paper:
26			Jamil, M., and Yang, X. S. (2013).
27			A literature survey of benchmark functions for global optimisation problems.
28			International Journal of Mathematical Modelling and Numerical Optimisation,
29			4(2), 150-194.
30			"""
31
32			import math
33
34			__all__ = ['Griewank']
35
36
37			class Griewank(object):
38
39			def __init__(self, Lower=-100, Upper=100):
40			self.Lower = Lower
41			self.Upper = Upper
42
43			@classmethod
44			def function(cls):
45			def evaluate(D, sol):
46
47			val1 = 0.0
48			val2 = 1.0
49
50			for i in range(D):
51			val1 += (math.pow(sol[i], 2) / 4000)
52			val2 *= (math.cos(sol[i] / math.sqrt(i + 1)))
53
54			return val1 - val2 + 1
55
56			return evaluate
57

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