Code Duplication - SimonBlanke/Gradient-Free-Optimizers - Measure and Improve Code Quality continuously with Scrutinizer

Code Duplication Length = 55-56 lines in 4 locations

tests/test_optimizers/test_early_stop.py 2 locations


    assert n_performed_iter == (n_iter_no_change + 1)


@pytest.mark.parametrize(*optimizers)
def test_early_stop_6(Optimizer):
    def objective_function(para):
        return para["x1"]

    search_space = {
        "x1": np.arange(0, 100, 0.01),
    }

    n_iter_no_change = 5
    early_stopping = {
        "n_iter_no_change": 5,
        "tol_abs": None,
        "tol_rel": 10,
    }

    start1 = {"x1": 1}
    start2 = {"x1": 1.1}
    start3 = {"x1": 1.22}
    start4 = {"x1": 1.35}
    start5 = {"x1": 1.48}

    warm_start_l = [
        start1,
        start1,
        start1,
        start1,
        start1,
        start2,
        start2,
        start2,
        start3,
        start3,
        start3,
        start4,
        start4,
        start4,
        start5,
        start5,
        start5,
    ]
    n_iter = len(warm_start_l)

    opt = Optimizer(search_space, initialize={"warm_start": warm_start_l})
    opt.search(
        objective_function,
        n_iter=n_iter,
        early_stopping=early_stopping,
    )
    search_data = opt.results
    n_performed_iter = len(search_data)

    print("\n n_performed_iter \n", n_performed_iter)
    print("\n n_iter_no_change \n", n_iter_no_change)

    assert n_performed_iter == n_iter


@pytest.mark.parametrize(*optimizers)

    assert n_performed_iter == (n_iter_no_change + 1)


@pytest.mark.parametrize(*optimizers)
def test_early_stop_4(Optimizer):
    def objective_function(para):
        return para["x1"]

    search_space = {
        "x1": np.arange(0, 100, 0.1),
    }

    n_iter_no_change = 5
    early_stopping = {
        "n_iter_no_change": 5,
        "tol_abs": 0.1,
        "tol_rel": None,
    }

    start1 = {"x1": 0}
    start2 = {"x1": 0.1}
    start3 = {"x1": 0.2}
    start4 = {"x1": 0.3}
    start5 = {"x1": 0.4}

    warm_start_l = [
        start1,
        start1,
        start1,
        start1,
        start1,
        start2,
        start2,
        start2,
        start3,
        start3,
        start3,
        start4,
        start4,
        start4,
        start5,
        start5,
        start5,
    ]
    n_iter = len(warm_start_l)

    opt = Optimizer(search_space, initialize={"warm_start": warm_start_l})
    opt.search(
        objective_function,
        n_iter=n_iter,
        early_stopping=early_stopping,
    )
    search_data = opt.results
    n_performed_iter = len(search_data)

    print("\n n_performed_iter \n", n_performed_iter)
    print("\n n_iter_no_change \n", n_iter_no_change)

    assert n_performed_iter == n_iter


@pytest.mark.parametrize(*optimizers)

tests/test_early_stop.py 2 locations


    assert n_performed_iter == (n_iter_no_change + 1)


def test_early_stop_6():
    def objective_function(para):
        return para["x1"]

    search_space = {
        "x1": np.arange(0, 100, 0.01),
    }

    n_iter_no_change = 5
    early_stopping = {
        "n_iter_no_change": 5,
        "tol_abs": None,
        "tol_rel": 10,
    }

    start1 = {"x1": 1}
    start2 = {"x1": 1.1}
    start3 = {"x1": 1.22}
    start4 = {"x1": 1.35}
    start5 = {"x1": 1.48}

    warm_start_l = [
        start1,
        start1,
        start1,
        start1,
        start1,
        start2,
        start2,
        start2,
        start3,
        start3,
        start3,
        start4,
        start4,
        start4,
        start5,
        start5,
        start5,
    ]
    n_iter = len(warm_start_l)

    opt = HillClimbingOptimizer(search_space, initialize={"warm_start": warm_start_l})
    opt.search(
        objective_function,
        n_iter=n_iter,
        early_stopping=early_stopping,
    )
    search_data = opt.results
    n_performed_iter = len(search_data)

    print("\n n_performed_iter \n", n_performed_iter)
    print("\n n_iter_no_change \n", n_iter_no_change)

    assert n_performed_iter == n_iter


def test_early_stop_7():

    assert n_performed_iter == (n_iter_no_change + 1)


def test_early_stop_4():
    def objective_function(para):
        return para["x1"]

    search_space = {
        "x1": np.arange(0, 100, 0.1),
    }

    n_iter_no_change = 5
    early_stopping = {
        "n_iter_no_change": 5,
        "tol_abs": 0.1,
        "tol_rel": None,
    }

    start1 = {"x1": 0}
    start2 = {"x1": 0.1}
    start3 = {"x1": 0.2}
    start4 = {"x1": 0.3}
    start5 = {"x1": 0.4}

    warm_start_l = [
        start1,
        start1,
        start1,
        start1,
        start1,
        start2,
        start2,
        start2,
        start3,
        start3,
        start3,
        start4,
        start4,
        start4,
        start5,
        start5,
        start5,
    ]
    n_iter = len(warm_start_l)

    opt = HillClimbingOptimizer(search_space, initialize={"warm_start": warm_start_l})
    opt.search(
        objective_function,
        n_iter=n_iter,
        early_stopping=early_stopping,
    )
    search_data = opt.results
    n_performed_iter = len(search_data)

    print("\n n_performed_iter \n", n_performed_iter)
    print("\n n_iter_no_change \n", n_iter_no_change)

    assert n_performed_iter == n_iter


def test_early_stop_5():

		@@ 207-262 (lines=56) @@
204		assert n_performed_iter == (n_iter_no_change + 1)
205
206
207		@pytest.mark.parametrize(*optimizers)
208		def test_early_stop_6(Optimizer):
209		def objective_function(para):
210		return para["x1"]
211
212		search_space = {
213		"x1": np.arange(0, 100, 0.01),
214		}
215
216		n_iter_no_change = 5
217		early_stopping = {
218		"n_iter_no_change": 5,
219		"tol_abs": None,
220		"tol_rel": 10,
221		}
222
223		start1 = {"x1": 1}
224		start2 = {"x1": 1.1}
225		start3 = {"x1": 1.22}
226		start4 = {"x1": 1.35}
227		start5 = {"x1": 1.48}
228
229		warm_start_l = [
230		start1,
231		start1,
232		start1,
233		start1,
234		start1,
235		start2,
236		start2,
237		start2,
238		start3,
239		start3,
240		start3,
241		start4,
242		start4,
243		start4,
244		start5,
245		start5,
246		start5,
247		]
248		n_iter = len(warm_start_l)
249
250		opt = Optimizer(search_space, initialize={"warm_start": warm_start_l})
251		opt.search(
252		objective_function,
253		n_iter=n_iter,
254		early_stopping=early_stopping,
255		)
256		search_data = opt.results
257		n_performed_iter = len(search_data)
258
259		print("\n n_performed_iter \n", n_performed_iter)
260		print("\n n_iter_no_change \n", n_iter_no_change)
261
262		assert n_performed_iter == n_iter
263
264
265		@pytest.mark.parametrize(*optimizers)
		@@ 99-154 (lines=56) @@
96		assert n_performed_iter == (n_iter_no_change + 1)
97
98
99		@pytest.mark.parametrize(*optimizers)
100		def test_early_stop_4(Optimizer):
101		def objective_function(para):
102		return para["x1"]
103
104		search_space = {
105		"x1": np.arange(0, 100, 0.1),
106		}
107
108		n_iter_no_change = 5
109		early_stopping = {
110		"n_iter_no_change": 5,
111		"tol_abs": 0.1,
112		"tol_rel": None,
113		}
114
115		start1 = {"x1": 0}
116		start2 = {"x1": 0.1}
117		start3 = {"x1": 0.2}
118		start4 = {"x1": 0.3}
119		start5 = {"x1": 0.4}
120
121		warm_start_l = [
122		start1,
123		start1,
124		start1,
125		start1,
126		start1,
127		start2,
128		start2,
129		start2,
130		start3,
131		start3,
132		start3,
133		start4,
134		start4,
135		start4,
136		start5,
137		start5,
138		start5,
139		]
140		n_iter = len(warm_start_l)
141
142		opt = Optimizer(search_space, initialize={"warm_start": warm_start_l})
143		opt.search(
144		objective_function,
145		n_iter=n_iter,
146		early_stopping=early_stopping,
147		)
148		search_data = opt.results
149		n_performed_iter = len(search_data)
150
151		print("\n n_performed_iter \n", n_performed_iter)
152		print("\n n_iter_no_change \n", n_iter_no_change)
153
154		assert n_performed_iter == n_iter
155
156
157		@pytest.mark.parametrize(*optimizers)

		@@ 203-257 (lines=55) @@
200		assert n_performed_iter == (n_iter_no_change + 1)
201
202
203		def test_early_stop_6():
204		def objective_function(para):
205		return para["x1"]
206
207		search_space = {
208		"x1": np.arange(0, 100, 0.01),
209		}
210
211		n_iter_no_change = 5
212		early_stopping = {
213		"n_iter_no_change": 5,
214		"tol_abs": None,
215		"tol_rel": 10,
216		}
217
218		start1 = {"x1": 1}
219		start2 = {"x1": 1.1}
220		start3 = {"x1": 1.22}
221		start4 = {"x1": 1.35}
222		start5 = {"x1": 1.48}
223
224		warm_start_l = [
225		start1,
226		start1,
227		start1,
228		start1,
229		start1,
230		start2,
231		start2,
232		start2,
233		start3,
234		start3,
235		start3,
236		start4,
237		start4,
238		start4,
239		start5,
240		start5,
241		start5,
242		]
243		n_iter = len(warm_start_l)
244
245		opt = HillClimbingOptimizer(search_space, initialize={"warm_start": warm_start_l})
246		opt.search(
247		objective_function,
248		n_iter=n_iter,
249		early_stopping=early_stopping,
250		)
251		search_data = opt.results
252		n_performed_iter = len(search_data)
253
254		print("\n n_performed_iter \n", n_performed_iter)
255		print("\n n_iter_no_change \n", n_iter_no_change)
256
257		assert n_performed_iter == n_iter
258
259
260		def test_early_stop_7():
		@@ 97-151 (lines=55) @@
94		assert n_performed_iter == (n_iter_no_change + 1)
95
96
97		def test_early_stop_4():
98		def objective_function(para):
99		return para["x1"]
100
101		search_space = {
102		"x1": np.arange(0, 100, 0.1),
103		}
104
105		n_iter_no_change = 5
106		early_stopping = {
107		"n_iter_no_change": 5,
108		"tol_abs": 0.1,
109		"tol_rel": None,
110		}
111
112		start1 = {"x1": 0}
113		start2 = {"x1": 0.1}
114		start3 = {"x1": 0.2}
115		start4 = {"x1": 0.3}
116		start5 = {"x1": 0.4}
117
118		warm_start_l = [
119		start1,
120		start1,
121		start1,
122		start1,
123		start1,
124		start2,
125		start2,
126		start2,
127		start3,
128		start3,
129		start3,
130		start4,
131		start4,
132		start4,
133		start5,
134		start5,
135		start5,
136		]
137		n_iter = len(warm_start_l)
138
139		opt = HillClimbingOptimizer(search_space, initialize={"warm_start": warm_start_l})
140		opt.search(
141		objective_function,
142		n_iter=n_iter,
143		early_stopping=early_stopping,
144		)
145		search_data = opt.results
146		n_performed_iter = len(search_data)
147
148		print("\n n_performed_iter \n", n_performed_iter)
149		print("\n n_iter_no_change \n", n_iter_no_change)
150
151		assert n_performed_iter == n_iter
152
153
154		def test_early_stop_5():

SimonBlanke / Gradient-Free-Optimizers

Code Duplication Length = 55-56 lines in 4 locations

tests/test_optimizers/test_early_stop.py 2 locations

tests/test_early_stop.py 2 locations