_test_long_term_memory_old - Code Metrics - Inspection of "remove unused code" - SimonBlanke/Hyperactive - Measure and Improve Code Quality continuously with Scrutinizer

Passed

Push — master ( b8f359...927840 )

by Simon

created 2021-01-30 18:51 UTC

_test_long_term_memory_old A

↳ Parent: Project

Complexity

Total Complexity

Size/Duplication

Total Lines	386
Duplicated Lines	7.51 %

Importance

Changes

Metric	Value
eloc	206
dl	29
loc	386
rs	9.76
c	0
b	0
f	0
wmc	33

12 Functions

Rating	Name	Duplication	Size	Complexity
A	func3()	0	2	1
A	test_ltm_10()	0	27	1
A	test_ltm_obj()	0	24	4
A	test_ltm_list()	0	28	4
A	test_ltm_int()	14	14	1
A	func1()	0	2	1
A	objective_function()	0	3	1
A	test_ltm_float()	15	15	1
A	test_ltm_str()	0	16	1
A	func2()	0	2	1
A	test_ltm_class()	0	24	4
A	test_ltm_func()	0	24	4

3 Methods

Rating	Name	Size	Complexity
A	class2_.__init__()	2	1
A	class1_.__init__()	2	1
A	class3_.__init__()	2	1

How to fix Duplicated Code

import os
import inspect
import pytest

import numpy as np
import pandas as pd

from hyperactive import Hyperactive, LongTermMemory


def func1():
    pass


def func2():
    pass


def func3():
    pass


def objective_function(opt):
    score = -opt["x1"] * opt["x1"]
    return score


class class1:
    pass


class class2:
    pass


class class3:
    pass


class class1_:
    def __init__(self):
        pass


class class2_:
    def __init__(self):
        pass


class class3_:
    def __init__(self):
        pass


search_space_int = {
    "x1": list(range(0, 3, 1)),
}

search_space_float = {
    "x1": list(np.arange(0, 0.003, 0.001)),
}

search_space_str = {
    "x1": list(range(0, 100, 1)),
    "str1": ["0", "1", "2"],
}

search_space_func = {
    "x1": list(range(0, 100, 1)),
    "func1": [func1, func2, func3],
}


search_space_class = {
    "x1": list(range(0, 100, 1)),
    "class1": [class1, class2, class3],
}


search_space_obj = {
    "x1": list(range(0, 100, 1)),
    "class1": [class1_(), class2_(), class3_()],
}

search_space_lists = {
    "x1": list(range(0, 100, 1)),
    "list1": [[1, 1, 1], [1, 2, 1], [1, 1, 2]],
}

search_space_para = (
    "search_space",
    [
        (search_space_int),
        (search_space_float),
        (search_space_str),
        (search_space_func),
        (search_space_class),
        (search_space_obj),
        (search_space_lists),
    ],
)

path_para = (
    "path",
    [("./"), (None),],
)

"""
@pytest.mark.parametrize(*path_para)
@pytest.mark.parametrize(*search_space_para)
def test_ltm_0(search_space, path):
    model_name = "test_ltm_0"

    def objective_function(opt):
        score = -opt["x1"] * opt["x1"]
        return score

    hyper = Hyperactive()
    hyper.add_search(objective_function, search_space, n_iter=25)
    hyper.run()

    memory = LongTermMemory(model_name, path=path)
    results1 = hyper.results(objective_function)
    memory.save(results1, objective_function)

    results2 = memory.load()
    remove_file(path)

    assert results1.equals(results2)
"""


def test_ltm_10():
    path = None
    model_name = "test_ltm_0"

    def objective_function(opt):
        score = -opt["x1"] * opt["x1"]
        return score

    search_space = {
        "x1": list(range(0, 3, 1)),
    }

    memory = LongTermMemory(model_name, path=path)

    hyper = Hyperactive()
    hyper.add_search(
        objective_function, search_space, n_iter=25, long_term_memory=memory
    )
    hyper.run()

    hyper = Hyperactive()
    hyper.add_search(
        objective_function, search_space, n_iter=25, long_term_memory=memory
    )
    hyper.run()

    memory.remove_model_data()


"""
@pytest.mark.parametrize(*path_para)
@pytest.mark.parametrize(*search_space_para)
def test_ltm_1(search_space, path):
    model_name = "test_ltm_1"

    def objective_function(opt):
        score = -opt["x1"] * opt["x1"]
        return score

    memory = LongTermMemory(model_name, path=path)

    hyper0 = Hyperactive()
    hyper0.add_search(
        objective_function, search_space, n_iter=25, long_term_memory=memory
    )
    hyper0.run()

    hyper1 = Hyperactive()
    hyper1.add_search(
        objective_function, search_space, n_iter=25, long_term_memory=memory
    )
    hyper1.run()

    remove_file()
"""


def test_ltm_int():

    path = "./"
    model_name = "test_ltm_int"
    array = np.arange(3 * 10).reshape(10, 3)
    results1 = pd.DataFrame(array, columns=["x1", "x2", "x3"])

    memory = LongTermMemory(model_name, path=path)
    memory.save(results1, objective_function)

    results2 = memory.load()

    memory.remove_model_data()

    assert results1.equals(results2)


def test_ltm_float():

    path = "./"
    model_name = "test_ltm_float"
    array = np.arange(3 * 10).reshape(10, 3)
    array = array / 1000
    results1 = pd.DataFrame(array, columns=["x1", "x2", "x3"])

    memory = LongTermMemory(model_name, path=path)
    memory.save(results1, objective_function)

    results2 = memory.load()

    memory.remove_model_data()

    assert results1.equals(results2)


def test_ltm_str():
    path = "./"
    model_name = "test_ltm_str"
    array = ["str1", "str2", "str3"]
    results1 = pd.DataFrame(
        [array, array, array, array, array], columns=["x1", "x2", "x3"]
    )

    memory = LongTermMemory(model_name, path=path)
    memory.save(results1, objective_function)

    results2 = memory.load()

    memory.remove_model_data()

    assert results1.equals(results2)


def func1():
    pass


def func2():
    pass


def func3():
    pass


def test_ltm_func():
    path = "./"
    model_name = "test_ltm_func"

    array = [func1, func2, func3]
    results1 = pd.DataFrame(
        [array, array, array, array, array], columns=["x1", "x2", "x3"]
    )

    memory = LongTermMemory(model_name, path=path)
    memory.save(results1, objective_function)

    results2 = memory.load()

    memory.remove_model_data()

    func_str_list = []
    for func_ in array:
        func_str_list.append(inspect.getsource(func_))

    for func_ in list(results2.values.flatten()):
        func_str_ = inspect.getsource(func_)
        if func_str_ not in func_str_list:
            assert False


class class1:
    name = "class1"


class class2:
    name = "class2"


class class3:
    name = "class3"


def test_ltm_class():
    path = "./"
    model_name = "test_ltm_class"

    array = [class1, class2, class3]
    results1 = pd.DataFrame(
        [array, array, array, array, array], columns=["x1", "x2", "x3"]
    )

    memory = LongTermMemory(model_name, path=path)
    memory.save(results1, objective_function)

    results2 = memory.load()

    memory.remove_model_data()

    for class_1 in list(results2.values.flatten()):
        assert_ = False
        for class_2 in array:
            if class_1.name == class_2.name:
                assert_ = True
                break

        assert assert_


class class1_:
    def __init__(self):
        self.name = "class1_"


class class2_:
    def __init__(self):
        self.name = "class2_"


class class3_:
    def __init__(self):
        self.name = "class3_"


def test_ltm_obj():
    path = "./"
    model_name = "test_ltm_obj"

    array = [class1_(), class2_(), class3_()]
    results1 = pd.DataFrame(
        [array, array, array, array, array], columns=["x1", "x2", "x3"]
    )

    memory = LongTermMemory(model_name, path=path)
    memory.save(results1, objective_function)

    results2 = memory.load()

    memory.remove_model_data()

    for obj_1 in list(results2.values.flatten()):
        assert_ = False
        for obj_2 in array:
            if obj_1.name == obj_2.name:
                assert_ = True
                break

        assert assert_


def test_ltm_list():
    path = "./"
    model_name = "test_ltm_list"

    dict_ = {"x1": [[1, 1, 1], [1, 2, 1], [1, 1, 2]]}
    results1 = pd.DataFrame(dict_)
    print("\n results1 \n", results1)

    memory = LongTermMemory(model_name, path=path)
    memory.save(results1, objective_function)

    results2 = memory.load()

    memory.remove_model_data()
    print("\n results2 \n", results2)

    for list_1 in list(results2.values.flatten()):
        assert_ = False
        for list_2 in list(dict_.values())[0]:
            print("\n list_1 ", list_1)
            print("list_2 ", list_2)
            print(list_1 == list_2)

            if list_1 == list_2:
                assert_ = True
                break

        assert assert_



1		import os
2		import inspect
3		import pytest
4
5		import numpy as np
6		import pandas as pd
7
8		from hyperactive import Hyperactive, LongTermMemory
9
10
11		def func1():
12		pass
13
14
15		def func2():
16		pass
17
18
19		def func3():
20		pass
21
22
23		def objective_function(opt):
24		score = -opt["x1"] * opt["x1"]
25		return score
26
27
28		class class1:
29		pass
30
31
32		class class2:
33		pass
34
35
36		class class3:
37		pass
38
39
40		class class1_:
41		def __init__(self):
42		pass
43
44
45		class class2_:
46		def __init__(self):
47		pass
48
49
50		class class3_:
51		def __init__(self):
52		pass
53
54
55		search_space_int = {
56		"x1": list(range(0, 3, 1)),
57		}
58
59		search_space_float = {
60		"x1": list(np.arange(0, 0.003, 0.001)),
61		}
62
63		search_space_str = {
64		"x1": list(range(0, 100, 1)),
65		"str1": ["0", "1", "2"],
66		}
67
68		search_space_func = {
69		"x1": list(range(0, 100, 1)),
70		"func1": [func1, func2, func3],
71		}
72
73
74		search_space_class = {
75		"x1": list(range(0, 100, 1)),
76		"class1": [class1, class2, class3],
77		}
78
79
80		search_space_obj = {
81		"x1": list(range(0, 100, 1)),
82		"class1": [class1_(), class2_(), class3_()],
83		}
84
85		search_space_lists = {
86		"x1": list(range(0, 100, 1)),
87		"list1": [[1, 1, 1], [1, 2, 1], [1, 1, 2]],
88		}
89
90		search_space_para = (
91		"search_space",
92		[
93		(search_space_int),
94		(search_space_float),
95		(search_space_str),
96		(search_space_func),
97		(search_space_class),
98		(search_space_obj),
99		(search_space_lists),
100		],
101		)
102
103		path_para = (
104		"path",
105		[("./"), (None),],
106		)
107
108		"""
109		@pytest.mark.parametrize(*path_para)
110		@pytest.mark.parametrize(*search_space_para)
111		def test_ltm_0(search_space, path):
112		model_name = "test_ltm_0"
113
114		def objective_function(opt):
115		score = -opt["x1"] * opt["x1"]
116		return score
117
118		hyper = Hyperactive()
119		hyper.add_search(objective_function, search_space, n_iter=25)
120		hyper.run()
121
122		memory = LongTermMemory(model_name, path=path)
123		results1 = hyper.results(objective_function)
124		memory.save(results1, objective_function)
125
126		results2 = memory.load()
127		remove_file(path)
128
129		assert results1.equals(results2)
130		"""
131
132
133		def test_ltm_10():
134		path = None
135		model_name = "test_ltm_0"
136
137		def objective_function(opt):
138		score = -opt["x1"] * opt["x1"]
139		return score
140
141		search_space = {
142		"x1": list(range(0, 3, 1)),
143		}
144
145		memory = LongTermMemory(model_name, path=path)
146
147		hyper = Hyperactive()
148		hyper.add_search(
149		objective_function, search_space, n_iter=25, long_term_memory=memory
150		)
151		hyper.run()
152
153		hyper = Hyperactive()
154		hyper.add_search(
155		objective_function, search_space, n_iter=25, long_term_memory=memory
156		)
157		hyper.run()
158
159		memory.remove_model_data()
160
161
162		"""
163		@pytest.mark.parametrize(*path_para)
164		@pytest.mark.parametrize(*search_space_para)
165		def test_ltm_1(search_space, path):
166		model_name = "test_ltm_1"
167
168		def objective_function(opt):
169		score = -opt["x1"] * opt["x1"]
170		return score
171
172		memory = LongTermMemory(model_name, path=path)
173
174		hyper0 = Hyperactive()
175		hyper0.add_search(
176		objective_function, search_space, n_iter=25, long_term_memory=memory
177		)
178		hyper0.run()
179
180		hyper1 = Hyperactive()
181		hyper1.add_search(
182		objective_function, search_space, n_iter=25, long_term_memory=memory
183		)
184		hyper1.run()
185
186		remove_file()
187		"""
188
189
190	View Code Duplication	def test_ltm_int():
		0 ignored issues – show Duplication introduced 2021-01-30 18:54 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
191		path = "./"
192		model_name = "test_ltm_int"
193		array = np.arange(3 * 10).reshape(10, 3)
194		results1 = pd.DataFrame(array, columns=["x1", "x2", "x3"])
195
196		memory = LongTermMemory(model_name, path=path)
197		memory.save(results1, objective_function)
198
199		results2 = memory.load()
200
201		memory.remove_model_data()
202
203		assert results1.equals(results2)
204
205
206	View Code Duplication	def test_ltm_float():
		0 ignored issues – show Duplication introduced 2021-01-30 18:54 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
207		path = "./"
208		model_name = "test_ltm_float"
209		array = np.arange(3 * 10).reshape(10, 3)
210		array = array / 1000
211		results1 = pd.DataFrame(array, columns=["x1", "x2", "x3"])
212
213		memory = LongTermMemory(model_name, path=path)
214		memory.save(results1, objective_function)
215
216		results2 = memory.load()
217
218		memory.remove_model_data()
219
220		assert results1.equals(results2)
221
222
223		def test_ltm_str():
224		path = "./"
225		model_name = "test_ltm_str"
226		array = ["str1", "str2", "str3"]
227		results1 = pd.DataFrame(
228		[array, array, array, array, array], columns=["x1", "x2", "x3"]
229		)
230
231		memory = LongTermMemory(model_name, path=path)
232		memory.save(results1, objective_function)
233
234		results2 = memory.load()
235
236		memory.remove_model_data()
237
238		assert results1.equals(results2)
239
240
241		def func1():
242		pass
243
244
245		def func2():
246		pass
247
248
249		def func3():
250		pass
251
252
253		def test_ltm_func():
254		path = "./"
255		model_name = "test_ltm_func"
256
257		array = [func1, func2, func3]
258		results1 = pd.DataFrame(
259		[array, array, array, array, array], columns=["x1", "x2", "x3"]
260		)
261
262		memory = LongTermMemory(model_name, path=path)
263		memory.save(results1, objective_function)
264
265		results2 = memory.load()
266
267		memory.remove_model_data()
268
269		func_str_list = []
270		for func_ in array:
271		func_str_list.append(inspect.getsource(func_))
272
273		for func_ in list(results2.values.flatten()):
274		func_str_ = inspect.getsource(func_)
275		if func_str_ not in func_str_list:
276		assert False
277
278
279		class class1:
280		name = "class1"
281
282
283		class class2:
284		name = "class2"
285
286
287		class class3:
288		name = "class3"
289
290
291		def test_ltm_class():
292		path = "./"
293		model_name = "test_ltm_class"
294
295		array = [class1, class2, class3]
296		results1 = pd.DataFrame(
297		[array, array, array, array, array], columns=["x1", "x2", "x3"]
298		)
299
300		memory = LongTermMemory(model_name, path=path)
301		memory.save(results1, objective_function)
302
303		results2 = memory.load()
304
305		memory.remove_model_data()
306
307		for class_1 in list(results2.values.flatten()):
308		assert_ = False
309		for class_2 in array:
310		if class_1.name == class_2.name:
311		assert_ = True
312		break
313
314		assert assert_
315
316
317		class class1_:
318		def __init__(self):
319		self.name = "class1_"
320
321
322		class class2_:
323		def __init__(self):
324		self.name = "class2_"
325
326
327		class class3_:
328		def __init__(self):
329		self.name = "class3_"
330
331
332		def test_ltm_obj():
333		path = "./"
334		model_name = "test_ltm_obj"
335
336		array = [class1_(), class2_(), class3_()]
337		results1 = pd.DataFrame(
338		[array, array, array, array, array], columns=["x1", "x2", "x3"]
339		)
340
341		memory = LongTermMemory(model_name, path=path)
342		memory.save(results1, objective_function)
343
344		results2 = memory.load()
345
346		memory.remove_model_data()
347
348		for obj_1 in list(results2.values.flatten()):
349		assert_ = False
350		for obj_2 in array:
351		if obj_1.name == obj_2.name:
352		assert_ = True
353		break
354
355		assert assert_
356
357
358		def test_ltm_list():
359		path = "./"
360		model_name = "test_ltm_list"
361
362		dict_ = {"x1": [[1, 1, 1], [1, 2, 1], [1, 1, 2]]}
363		results1 = pd.DataFrame(dict_)
364		print("\n results1 \n", results1)
365
366		memory = LongTermMemory(model_name, path=path)
367		memory.save(results1, objective_function)
368
369		results2 = memory.load()
370
371		memory.remove_model_data()
372		print("\n results2 \n", results2)
373
374		for list_1 in list(results2.values.flatten()):
375		assert_ = False
376		for list_2 in list(dict_.values())[0]:
377		print("\n list_1 ", list_1)
378		print("list_2 ", list_2)
379		print(list_1 == list_2)
380
381		if list_1 == list_2:
382		assert_ = True
383		break
384
385		assert assert_
386
387

SimonBlanke / Hyperactive

Push — master ( b8f359...927840 )

_test_long_term_memory_old A

Complexity

Size/Duplication

Importance

12 Functions

3 Methods

How to fix Duplicated Code

Duplicated Code

Duplication Side-by-Side

Filter issues like