tests.test_optimizer_parameter.test_DecisionTree.test_warm_start_smbo() - Code Metrics - Inspection of "update formating + renaming" - SimonBlanke/Gradient-Free-Optimizers - Measure and Improve Code Quality continuously with Scrutinizer

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by Simon

created 2020-10-07 11:55 UTC

test_warm_start_smbo() A

↳ Parent: tests.test_optimizer_parameter.test_DecisionTree

Complexity

Conditions

Size

Total Lines	15
Code Lines	12

Duplication

Lines	15
Ratio	100 %

Importance

Changes

Metric	Value
cc	3
eloc	12
nop	0
dl	15
loc	15
rs	9.8
c	0
b	0
f	0

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

import numpy as np

from gradient_free_optimizers import DecisionTreeOptimizer
from ._base_test import _base_test

n_iter = 33
opt = DecisionTreeOptimizer


def get_score(para):
    return -(para["x1"] * para["x1"])


def test_warm_start_smbo():

    gpr_X, gpr_y = [], []
    for _ in range(10):
        pos_ = np.random.randint(0, high=9)
        pos = np.array([pos_])

        para = {
            "x1": pos_,
        }
        gpr_X.append(pos)
        gpr_y.append(get_score(para))

    for warm_start_smbo in [None, (gpr_X, gpr_y)]:
        opt_para = {"warm_start_smbo": warm_start_smbo}
        _base_test(opt, n_iter, opt_para=opt_para)


def test_max_sample_size():
    for max_sample_size in [10, 100, 10000, 10000000000]:
        opt_para = {"max_sample_size": max_sample_size}
        _base_test(opt, n_iter, opt_para=opt_para)


"""
def test_gpr():
    opt = Hyperactive(X, y, memory=memory)
    opt.search(
        search_config,
        n_iter=n_iter,
        optimizer={"DecisionTree": {"tree_regressor": "random_forest"}},
    )
"""


1		# Author: Simon Blanke
2		# Email: [email protected]
3		# License: MIT License
4
5		import numpy as np
6
7		from gradient_free_optimizers import DecisionTreeOptimizer
8		from ._base_test import _base_test
9
10		n_iter = 33
11		opt = DecisionTreeOptimizer
12
13
14		def get_score(para):
15		return -(para["x1"] * para["x1"])
16
17
18	View Code Duplication	def test_warm_start_smbo():
		0 ignored issues – show Duplication introduced 2020-10-07 11:59 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
19		gpr_X, gpr_y = [], []
20		for _ in range(10):
21		pos_ = np.random.randint(0, high=9)
22		pos = np.array([pos_])
23
24		para = {
25		"x1": pos_,
26		}
27		gpr_X.append(pos)
28		gpr_y.append(get_score(para))
29
30		for warm_start_smbo in [None, (gpr_X, gpr_y)]:
31		opt_para = {"warm_start_smbo": warm_start_smbo}
32		_base_test(opt, n_iter, opt_para=opt_para)
33
34
35		def test_max_sample_size():
36		for max_sample_size in [10, 100, 10000, 10000000000]:
37		opt_para = {"max_sample_size": max_sample_size}
38		_base_test(opt, n_iter, opt_para=opt_para)
39
40
41		"""
42		def test_gpr():
43		opt = Hyperactive(X, y, memory=memory)
44		opt.search(
45		search_config,
46		n_iter=n_iter,
47		optimizer={"DecisionTree": {"tree_regressor": "random_forest"}},
48		)
49		"""
50

SimonBlanke / Gradient-Free-Optimizers

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test_warm_start_smbo() A

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