hyperactive.optimizers.sequence_model.sbom.SBOM._init_iteration() - Code Metrics - Inspection of "restructuring of all optimizer classes" - SimonBlanke/Hyperactive - Measure and Improve Code Quality continuously with Scrutinizer

Completed

Push — master ( ce1e03...f67568 )

by Simon

created 2020-02-29 10:25 UTC

SBOM._init_iteration() A

↳ Parent: hyperactive.optimizers.sequence_model.sbom

Complexity

Conditions

Size

Total Lines	17
Code Lines	12

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
cc	2
eloc	12
nop	2
dl	0
loc	17
rs	9.8
c	0
b	0
f	0

# Author: Simon Blanke
# Email: [email protected]
# License: MIT License


import numpy as np


from ...base_optimizer import BaseOptimizer
from ...base_positioner import BasePositioner


class SBOM(BaseOptimizer):
    def __init__(self, _opt_args_):
        super().__init__(_opt_args_)
        self.n_positioners = 1

    def _all_possible_pos(self, cand):
        pos_space = []
        for dim_ in cand._space_.dim:
            pos_space.append(np.arange(dim_ + 1))

        self.n_dim = len(pos_space)
        self.all_pos_comb = np.array(np.meshgrid(*pos_space)).T.reshape(-1, self.n_dim)

    def _init_iteration(self, _cand_):
        p = SbomPositioner()
        p.move_random(_cand_)

        self._optimizer_eval(_cand_, p)
        self._update_pos(_cand_, p)

        self._all_possible_pos(_cand_)

        if self._opt_args_.warm_start_smbo:
            self.X_sample = _cand_.mem._get_para()
            self.Y_sample = _cand_.mem._get_score()
        else:
            self.X_sample = _cand_.pos_best.reshape(1, -1)
            self.Y_sample = np.array(_cand_.score_best).reshape(1, -1)

        return p


class SbomPositioner(BasePositioner):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)


1			# Author: Simon Blanke
2			# Email: [email protected]
3			# License: MIT License
4
5
6			import numpy as np
7
8
9			from ...base_optimizer import BaseOptimizer
10			from ...base_positioner import BasePositioner
11
12
13			class SBOM(BaseOptimizer):
14			def __init__(self, _opt_args_):
15			super().__init__(_opt_args_)
16			self.n_positioners = 1
17
18			def _all_possible_pos(self, cand):
19			pos_space = []
20			for dim_ in cand._space_.dim:
21			pos_space.append(np.arange(dim_ + 1))
22
23			self.n_dim = len(pos_space)
24			self.all_pos_comb = np.array(np.meshgrid(*pos_space)).T.reshape(-1, self.n_dim)
25
26			def _init_iteration(self, _cand_):
27			p = SbomPositioner()
28			p.move_random(_cand_)
29
30			self._optimizer_eval(_cand_, p)
31			self._update_pos(_cand_, p)
32
33			self._all_possible_pos(_cand_)
34
35			if self._opt_args_.warm_start_smbo:
36			self.X_sample = _cand_.mem._get_para()
37			self.Y_sample = _cand_.mem._get_score()
38			else:
39			self.X_sample = _cand_.pos_best.reshape(1, -1)
40			self.Y_sample = np.array(_cand_.score_best).reshape(1, -1)
41
42			return p
43
44
45			class SbomPositioner(BasePositioner):
46			def __init__(self, args, *kwargs):
47			super().__init__(args, *kwargs)
48

SimonBlanke / Hyperactive

Push — master ( ce1e03...f67568 )

SBOM._init_iteration() A

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