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"""2D parabola function, common benchmark for optimization algorithms.""" |
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# copyright: hyperactive developers, MIT License (see LICENSE file) |
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from hyperactive.base import BaseExperiment |
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class Parabola(BaseExperiment): |
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r"""2D parabola, common benchmark for optimization algorithms. |
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Parabola parameterized by the formula: |
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.. math:: |
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f(x, y) = a * (x^2 + y^2) + b * x + c * y |
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where :math:`a`, :math:`b`, and :math:`c` are coefficients which can |
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be set as parameters. |
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The function arguments :math:`x` and :math:`y` |
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are the input variables of the `score` method, |
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and are set as `x` and `y` respectively. |
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Parameters |
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---------- |
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a : float, default=1.0 |
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Coefficient of the parabola. |
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b : float, default=0.0 |
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Coefficient of the parabola. |
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c : float, default=0.0 |
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Coefficient of the parabola. |
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Example |
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------- |
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>>> from hyperactive.experiment.toy import Parabola |
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>>> parabola = Parabola(a=1.0, b=0.0, c=0.0) |
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>>> params = {"x": 1, "y": 2} |
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>>> score, add_info = parabola.score(params) |
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Quick call without metadata return or dictionary: |
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>>> score = parabola(x=1, y=2) |
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""" |
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_tags = { |
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"property:randomness": "deterministic", # random or deterministic |
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# if deterministic, two calls of score will result in the same value |
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# random = two calls may result in different values; same as "stochastic" |
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} |
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def __init__(self, a=1.0, b=0.0, c=0.0): |
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self.a = a |
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self.b = b |
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self.c = c |
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super().__init__() |
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def _paramnames(self): |
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return ["x", "y"] |
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def _score(self, params): |
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x = params["x"] |
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y = params["y"] |
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return self.a * (x**2 + y**2) + self.b * x + self.c * y, {} |
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@classmethod |
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def _get_score_params(self): |
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"""Return settings for testing the score function. Used in tests only. |
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Returns a list, the i-th element corresponds to self.get_test_params()[i]. |
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It should be a valid call for self.score. |
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Returns |
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------- |
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list of dict |
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The parameters to be used for scoring. |
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""" |
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params0 = {"x": 0, "y": 0} |
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params1 = {"x": 1, "y": 1} |
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return [params0, params1] |
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SimonBlanke /
Hyperactive
